subject:(Autonomous driving)

Georgia Tech

1. Williams, Grady Robert. Model predictive path integral control: Theoretical foundations and applications to autonomous driving.

Degree: PhD, Computer Science, 2019, Georgia Tech

URL: http://hdl.handle.net/1853/62666

► This thesis presents a new approach for stochastic model predictive (optimal) control: model predictive path integral control, which is based on massive parallel sampling of… (more)

Subjects/Keywords: Stochastic optimal control; Autonomous driving

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APA (6^th Edition):

Williams, G. R. (2019). Model predictive path integral control: Theoretical foundations and applications to autonomous driving. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62666

Chicago Manual of Style (16^th Edition):

Williams, Grady Robert. “Model predictive path integral control: Theoretical foundations and applications to autonomous driving.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 21, 2021. http://hdl.handle.net/1853/62666.

MLA Handbook (7^th Edition):

Williams, Grady Robert. “Model predictive path integral control: Theoretical foundations and applications to autonomous driving.” 2019. Web. 21 Jan 2021.

Vancouver:

Williams GR. Model predictive path integral control: Theoretical foundations and applications to autonomous driving. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1853/62666.

Council of Science Editors:

Williams GR. Model predictive path integral control: Theoretical foundations and applications to autonomous driving. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62666

Delft University of Technology

2. Krishnakumar, Ajinkya (author). Path Planning in Heterogenous Environments: A Combined Approach.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:ad17bc2e-3745-4bb2-8f34-fca58d8c69c3

►

Autonomous vehicles are the inevitable future of the industry as theoretically they guarantee higher road throughput and a much safer means of transport compared to… (more)

▼

Autonomous vehicles are the inevitable future of the industry as theoretically they guarantee higher road throughput and a much safer means of transport compared to today’s ground vehicle. This has attracted the industries and universities making it a very important topic of research. The basic function of the autonomous vehicle boils down to transporting its passenger safety from door to door. This requires planning of a path that is obstacle free. Currently, sampling-based methods are widely used for path planning. Although these methods are proving to be successful in open environments, they are inefficient in heterogeneous environments. Planning in urban environments would be successful if this obstacle is tackled. In the current literature, it was found that there are many methods which focus on solving the path planning problem while planning around the obstruction, while there are other methods that focus on converging to optimal solutions. Hence, there is a need for methods that would plan optimal paths in heterogeneous environments. This thesis introduced a combined approach that shares elements of planning paths around obstacles and optimal path planning which are provided by the algorithms Adaptive RRT and Informed RRT* respectively. These methods are combined along with a Dubin’s motion model to simulate basic vehicle’s constraints. The proposed approach was compared with state of the art methods like RRT* to evaluate its performance via simulation. The simulation was carried out in three different scenarios with variable complexity depending upon the available free configuration space. The ability to find a solution and converge it were evaluated, an improvement of 50% was noticed in finding the initial solution and around 25% improvement was seen in convergence. This concluded that such a hybrid approach could be an important contribution to urban path planning.

Mechanical Engineering

Advisors/Committee Members: Alonso Mora, Javier (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: Motion Planning; Autonomous driving; Algorithm

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APA (6^th Edition):

Krishnakumar, A. (. (2019). Path Planning in Heterogenous Environments: A Combined Approach. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:ad17bc2e-3745-4bb2-8f34-fca58d8c69c3

Chicago Manual of Style (16^th Edition):

Krishnakumar, Ajinkya (author). “Path Planning in Heterogenous Environments: A Combined Approach.” 2019. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:ad17bc2e-3745-4bb2-8f34-fca58d8c69c3.

MLA Handbook (7^th Edition):

Krishnakumar, Ajinkya (author). “Path Planning in Heterogenous Environments: A Combined Approach.” 2019. Web. 21 Jan 2021.

Vancouver:

Krishnakumar A(. Path Planning in Heterogenous Environments: A Combined Approach. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:ad17bc2e-3745-4bb2-8f34-fca58d8c69c3.

Council of Science Editors:

Krishnakumar A(. Path Planning in Heterogenous Environments: A Combined Approach. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:ad17bc2e-3745-4bb2-8f34-fca58d8c69c3

University of Florida

3. Brinkley, Julian L. Autonomous Vehicles and Visually Impaired Operators.

Degree: PhD, Human-Centered Computing - Computer and Information Science and Engineering, 2018, University of Florida

URL: https://ufdc.ufl.edu/UFE0051989

► The emergence of fully autonomous or self-driving vehicles may prove to be the biggest change in personal mobility in more than a century. Recent reports… (more)

Subjects/Keywords: atlas – autonomous – self-driving – vehicle

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APA (6^th Edition):

Brinkley, J. L. (2018). Autonomous Vehicles and Visually Impaired Operators. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0051989

Chicago Manual of Style (16^th Edition):

Brinkley, Julian L. “Autonomous Vehicles and Visually Impaired Operators.” 2018. Doctoral Dissertation, University of Florida. Accessed January 21, 2021. https://ufdc.ufl.edu/UFE0051989.

MLA Handbook (7^th Edition):

Brinkley, Julian L. “Autonomous Vehicles and Visually Impaired Operators.” 2018. Web. 21 Jan 2021.

Vancouver:

Brinkley JL. Autonomous Vehicles and Visually Impaired Operators. [Internet] [Doctoral dissertation]. University of Florida; 2018. [cited 2021 Jan 21]. Available from: https://ufdc.ufl.edu/UFE0051989.

Council of Science Editors:

Brinkley JL. Autonomous Vehicles and Visually Impaired Operators. [Doctoral Dissertation]. University of Florida; 2018. Available from: https://ufdc.ufl.edu/UFE0051989

4. Rylén, Emil. Future challenges in development and deployment of autonomous vehicles .

Degree: Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper, 2019, Chalmers University of Technology

URL: http://hdl.handle.net/20.500.12380/301408

► The race towards autonomously driving vehicles has already, and will continue to, have large effect on the automotive industry. This Master's thesis is a study… (more)

▼ The race towards autonomously driving vehicles has already, and will continue to, have large effect on the automotive industry. This Master's thesis is a study that aims to identify the challenges that the automotive industry faces in the transformation towards producing and deploying autonomous vehicles. It also aims to identify similarities and differences between the stakeholder in the industry. The insights gained can be used as input to stakeholders in the industry for strategic decision making regarding what focus areas to consider in this transition towards autonomous transport solutions. Interviews were conducted with a wide range of stakeholder in the industry to get a larger scope on the result and possibility to compare relevant information. Literatures studies was conducted prior to the interviews to build a foundation of knowledge and identify research questions. Topics that were addressed during the interviews were: (1) General information and future thoughts, (2) testing methods, (3) data collection and storage, (4) safety, and (5) communication possibilities. The stakeholders that participated in the interviews were: one university research laboratory, one research organisation, one strategic innovation program, one consultancy company, two OEMs and two testing service providers. From the interviews conducted, it can be argued that the challenges are many and it is uncertain what challenges will be the hardest to overcome. The two government organisations claim that the biggest hindrance will be the safety of the technology and the testing service organisations claim that the regulations and laws will be the biggest hindrance. Multiple interviewees brought up the problems of having different regulations and road infrastructure in different countries. All stakeholder agrees that more collaboration, increased transparency and new mythologies for testing and verification will be needed in the future for the technology of autonomous vehicles to be successfully developed and deployed. The OEMs will have a hard task in finding the balance between; sharing information and technology to increase the speed and reduce the cost of the development; and finding unique solutions that creates great customer value in their products compared to competitors. Another challenge for autonomous vehicles is the one related to responsibility. This will in the end be a problem that the government or international regulators will have to address, just as the one with data ownership. It can be argued governments will play a major role in the future that will shape the way the development of autonomous vehicles will continue.

Subjects/Keywords: Autonomous; Automotive; Self-driving

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APA (6^th Edition):

Rylén, E. (2019). Future challenges in development and deployment of autonomous vehicles . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/301408

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rylén, Emil. “Future challenges in development and deployment of autonomous vehicles .” 2019. Thesis, Chalmers University of Technology. Accessed January 21, 2021. http://hdl.handle.net/20.500.12380/301408.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rylén, Emil. “Future challenges in development and deployment of autonomous vehicles .” 2019. Web. 21 Jan 2021.

Vancouver:

Rylén E. Future challenges in development and deployment of autonomous vehicles . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/20.500.12380/301408.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rylén E. Future challenges in development and deployment of autonomous vehicles . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/301408

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

5. Daoud, Mohamed Ashraf Gameleldin. Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving.

Degree: 2020, University of Waterloo

URL: http://hdl.handle.net/10012/16436

► The evolving autonomous driving technology has been attracting significant research efforts in both academia and industry because of its promising potentials. Eliminating the human intervention… (more)

▼ The evolving autonomous driving technology has been attracting significant research efforts in both academia and industry because of its promising potentials. Eliminating the human intervention in driving will drastically improve the road safety and will create more mobility freedom for the humankind. Decision-making system in autonomy pipeline is the last module that interacts directly with the surrounding environment. Typical decision-making systems perform a variety of tasks including local motion planning, obstacle avoidance, and path-following in a sequential manner. An alternative approach is to perform these tasks simultaneously to obtain faster decision-making actions. This thesis focuses on designing an optimization-based simultaneous controller that performs obstacle avoidance, local motion planning, and vehicle control on roads regardless of their orientation while following a target path, and also incorporates adjustable driving behavior. Firstly, a decision-making scheme that enables autonomous driving for long trips while expanding the usage of the available computational resources and ensuring obstacle avoidance functionality is proposed. The proposed scheme utilizes a parallel architecture for local motion planning and control layers to increase time efficiency. In addition, a novel feasibility-guaranteed lane change and double lane change planners are introduced for path planning and obstacle avoidance. Finally, an online parameterized curve generator is proposed and integrated with a recently developed path-following controller. Next, a nonlinear model predictive control (NMPC) scheme is developed for the path-following control of autonomous vehicles. In addition, a dual-objective cost function which is composed of a regulation part and an economic part is introduced. By tuning the weights of this cost, a driving behavior can be implemented; two different driving behaviors are designed, namely, energy-efficient and sport driving modes. Finally, a kinematic bicycle model is used for predicting the vehicle motion while a longitudinal motion dynamic model is used for estimating the energy consumption. Finally, a novel representation framework for static maps and obstacles based on Fourier Series is proposed. The framework relies on Complex Fourier Series analysis to reduce the computation time and outputs mathematical equations to describe the shape of the considered object. Furthermore, two methods were proposed, namely; offline method and online method. The offline method is used to create accurate representations for static maps and most common obstacles an ego vehicle may encounter. The online method is used to model the free space around the vehicle when dealing with uncertain environments. The proposed contributions fill significant gaps in the autonomous driving problem. All the proposed work is tested and validated using numerical simulations and some experiments. The results show the effectiveness of the proposed contributions.

Subjects/Keywords: autonomous driving; model predictive control

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APA (6^th Edition):

Daoud, M. A. G. (2020). Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16436

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Daoud, Mohamed Ashraf Gameleldin. “Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving.” 2020. Thesis, University of Waterloo. Accessed January 21, 2021. http://hdl.handle.net/10012/16436.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Daoud, Mohamed Ashraf Gameleldin. “Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving.” 2020. Web. 21 Jan 2021.

Vancouver:

Daoud MAG. Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10012/16436.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Daoud MAG. Simultaneous Local Motion Planning and Control, Adjustable Driving Behavior, and Obstacle Representation for Autonomous Driving. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/16436

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

6. Barad, Hrishikesh. System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles.

Degree: MS, Industrial and Systems Engineering, 2019, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/10493

► One of the main reasons for increasing carbon emissions by the transportation sector is the frequent congestion caused in a traffic network. Congestion in… (more)

▼ One of the main reasons for increasing carbon emissions by the transportation sector is the frequent congestion caused in a traffic network. Congestion in transportation occurs when demand for commuting resources exceeds their capacity and with the increasing use of road vehicles, congestion and thereby emissions will continue to rise if proper actions are not taken. Adoption of intelligent transportation systems like autonomous vehicle technology can help in increasing the efficiency of transportation in terms of time, fuel and carbon footprint. This research proposes a System Level Eco-Driving (SLED) algorithm and compares the results, produced by performing microscopic simulations, with conventional driving and the coordination heuristic (COORD) algorithm. The SLED algorithm is designed based on shortcomings and observations of the COORD algorithm to improve the traffic network efficiency. In the SLED strategy, a trailing autonomous vehicle would only request coordination if it is within a set distance from the preceding autonomous vehicle and coordination requests will be evaluated based on their estimated system level emissions impact. Additionally, the human-driven vehicles will not be allowed to change lanes. Average CO2 emissions per vehicle for SLED showed improvements ranging from 0% to 5% compared to COORD. Additionally, the threshold limit to surpass the conventional driving behavior CO2 emissions at 900 vehicles per hour density reduced to 30% using SLED as compared to 40% using the COORD algorithm. Average wait time per vehicle for the SLED algorithm at 1200 vehicles per hour density increased by one to six seconds as compared to the COORD strategy although reduced up to thirty seconds of wait time compared to the conventional driving behavior. This finding can be helpful for policy makers to switch the algorithms based on the requirement i.e. opt for the SLED algorithm if reducing emissions has a higher priority compared to wait and travel time while opt for the COORD algorithm if reducing wait and travel time has a higher priority compared to emissions. Advisors/Committee Members: Katie McConky.

Subjects/Keywords: Autonomous; Eco-driving; Emissions; Simulation; Sustainability; v2x

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APA (6^th Edition):

Barad, H. (2019). System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10493

Chicago Manual of Style (16^th Edition):

Barad, Hrishikesh. “System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed January 21, 2021. https://scholarworks.rit.edu/theses/10493.

MLA Handbook (7^th Edition):

Barad, Hrishikesh. “System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles.” 2019. Web. 21 Jan 2021.

Vancouver:

Barad H. System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2021 Jan 21]. Available from: https://scholarworks.rit.edu/theses/10493.

Council of Science Editors:

Barad H. System-level Eco-driving (SLED): Algorithms for Connected and Autonomous Vehicles. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10493

Cornell University

7. Hardy, Jason. Contingency Planning And Obstacle Anticipation For Autonomous Driving.

Degree: PhD, Aerospace Engineering, 2013, Cornell University

URL: http://hdl.handle.net/1813/34277

► This thesis explores the challenge of robustly handling dynamic obstacle uncertainty in autonomous driving systems. The path planning performance of Cornell's autonomous vehicle platform Skynet… (more)

Subjects/Keywords: Contingency Planning; Collision Avoidance; Autonomous Driving

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APA (6^th Edition):

Hardy, J. (2013). Contingency Planning And Obstacle Anticipation For Autonomous Driving. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/34277

Chicago Manual of Style (16^th Edition):

Hardy, Jason. “Contingency Planning And Obstacle Anticipation For Autonomous Driving.” 2013. Doctoral Dissertation, Cornell University. Accessed January 21, 2021. http://hdl.handle.net/1813/34277.

MLA Handbook (7^th Edition):

Hardy, Jason. “Contingency Planning And Obstacle Anticipation For Autonomous Driving.” 2013. Web. 21 Jan 2021.

Vancouver:

Hardy J. Contingency Planning And Obstacle Anticipation For Autonomous Driving. [Internet] [Doctoral dissertation]. Cornell University; 2013. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1813/34277.

Council of Science Editors:

Hardy J. Contingency Planning And Obstacle Anticipation For Autonomous Driving. [Doctoral Dissertation]. Cornell University; 2013. Available from: http://hdl.handle.net/1813/34277

Cornell University

8. Havlak, Francis. Probabilistic Anticipation For Autonomous Urban Robots.

Degree: PhD, Mechanical Engineering, 2015, Cornell University

URL: http://hdl.handle.net/1813/40632

► The ability to anticipate the behavior of other vehicles on the road is a key part of how humans drive safely in complex environments. This… (more)

Subjects/Keywords: Autonomous Driving; Bayesian Estimation; Machine Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Havlak, F. (2015). Probabilistic Anticipation For Autonomous Urban Robots. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/40632

Chicago Manual of Style (16^th Edition):

Havlak, Francis. “Probabilistic Anticipation For Autonomous Urban Robots.” 2015. Doctoral Dissertation, Cornell University. Accessed January 21, 2021. http://hdl.handle.net/1813/40632.

MLA Handbook (7^th Edition):

Havlak, Francis. “Probabilistic Anticipation For Autonomous Urban Robots.” 2015. Web. 21 Jan 2021.

Vancouver:

Havlak F. Probabilistic Anticipation For Autonomous Urban Robots. [Internet] [Doctoral dissertation]. Cornell University; 2015. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1813/40632.

Council of Science Editors:

Havlak F. Probabilistic Anticipation For Autonomous Urban Robots. [Doctoral Dissertation]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/40632

Cornell University

9. Zhou, Yichen. A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving.

Degree: M.S., Mechanical Engineering, Mechanical Engineering, 2019, Cornell University

URL: http://hdl.handle.net/1813/67255

► In the field of autonomous driving, anticipation of the dynamic environment is of great importance for the ego vehicle to make decisions and plan future… (more)

Subjects/Keywords: anticipation; autonomous driving; Robotics; Mechanical engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhou, Y. (2019). A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving. (Masters Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/67255

Chicago Manual of Style (16^th Edition):

Zhou, Yichen. “A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving.” 2019. Masters Thesis, Cornell University. Accessed January 21, 2021. http://hdl.handle.net/1813/67255.

MLA Handbook (7^th Edition):

Zhou, Yichen. “A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving.” 2019. Web. 21 Jan 2021.

Vancouver:

Zhou Y. A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving. [Internet] [Masters thesis]. Cornell University; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1813/67255.

Council of Science Editors:

Zhou Y. A General Goal Point Model for Anticipation of Vehicle Motions for Autonomous Driving. [Masters Thesis]. Cornell University; 2019. Available from: http://hdl.handle.net/1813/67255

McMaster University

10. Luo, Zhongzhen. LiDAR Based Perception System: Pioneer Technology for Safety Driving.

Degree: PhD, 2017, McMaster University

URL: http://hdl.handle.net/11375/22056

►

Perceiving the surrounding multiple vehicles robustly and effectively is a very important step in building Advanced Driving Assistant System (ADAS) or autonomous vehicles. This thesis… (more)

Subjects/Keywords: LiDAR; Autonomous Driving; Perception; Artificial Intelligence; Tracking

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APA (6^th Edition):

Luo, Z. (2017). LiDAR Based Perception System: Pioneer Technology for Safety Driving. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/22056

Chicago Manual of Style (16^th Edition):

Luo, Zhongzhen. “LiDAR Based Perception System: Pioneer Technology for Safety Driving.” 2017. Doctoral Dissertation, McMaster University. Accessed January 21, 2021. http://hdl.handle.net/11375/22056.

MLA Handbook (7^th Edition):

Luo, Zhongzhen. “LiDAR Based Perception System: Pioneer Technology for Safety Driving.” 2017. Web. 21 Jan 2021.

Vancouver:

Luo Z. LiDAR Based Perception System: Pioneer Technology for Safety Driving. [Internet] [Doctoral dissertation]. McMaster University; 2017. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/11375/22056.

Council of Science Editors:

Luo Z. LiDAR Based Perception System: Pioneer Technology for Safety Driving. [Doctoral Dissertation]. McMaster University; 2017. Available from: http://hdl.handle.net/11375/22056

University of Waterloo

11. Masud, Zarif. Switching GAN-based Image Filters to Improve Perception for Autonomous Driving.

Degree: 2019, University of Waterloo

URL: http://hdl.handle.net/10012/15228

► Autonomous driving holds the potential to increase human productivity, reduce accidents caused by human errors, allow better utilization of roads, reduce traffic accidents and congestion,… (more)

▼ Autonomous driving holds the potential to increase human productivity, reduce accidents caused by human errors, allow better utilization of roads, reduce traffic accidents and congestion, free up parking space and provide many other advantages. Perception of Autonomous Vehicles (AV) refers to the use of sensors to perceive the world, e.g. using cameras to detect and classify objects. Traffic scene understanding is a key research problem in perception in autonomous driving, and semantic segmentation is a useful method to address this problem. Adverse weather conditions are a reality that AV must contend with. Conditions like rain, snow, haze, etc. can drastically reduce visibility and thus affect computer vision models. Models for perception for AVs are currently designed for and tested on predominantly ideal weather conditions under good illumination. The most complete solution may be to have the segmentation networks be trained on all possible adverse conditions. Thus a dataset to train a segmentation network to make it robust to rain would need to have adequate data that cover these conditions well. Moreover, labeling is an expensive task. It is particularly expensive for semantic segmentation, as each object in a scene needs to be identified and each pixel annotated in the right class. Thus, the adverse weather is a challenging problem for perception models in AVs. This thesis explores the use of Generative Adversarial Networks (GAN) in order to improve semantic segmentation. We design a framework and a methodology to evaluate the proposed approach. The framework consists of an Adversity Detector, and a series of denoising filters. The Adversity Detector is an image classifier that takes as input clear weather or adverse weather scenes, and attempts to predict whether the given image contains rain, or puddles, or other conditions that can adversely affect semantic segmentation. The filters are denoising generative adversarial networks that are trained to remove the adverse conditions from images in order to translate the image to a domain the segmentation network has been trained on, i.e. clear weather images. We use the prediction from the Adversity Detector to choose which GAN filter to use. The methodology we devise for evaluating our approach uses the trained filters to output sets of images that we can then run segmentation tasks on. This, we argue, is a better metric for evaluating the GANs than similarity measures such as SSIM. We also use synthetic data so we can perform systematic evaluation of our technique. We train two kinds of GANs, one that uses paired data (CycleGAN), and one that does not (Pix2Pix). We have concluded that GAN architectures that use unpaired data are not sufficiently good models for denoising. We train the denoising filters using the other architecture and we found them easy to train, and they show good results. While these filters do not show better performance than when we train our segmentation network with adverse weather data, we refer back to the point that training the…

Subjects/Keywords: machine learning; autonomous driving; computer vision

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APA (6^th Edition):

Masud, Z. (2019). Switching GAN-based Image Filters to Improve Perception for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15228

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Masud, Zarif. “Switching GAN-based Image Filters to Improve Perception for Autonomous Driving.” 2019. Thesis, University of Waterloo. Accessed January 21, 2021. http://hdl.handle.net/10012/15228.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Masud, Zarif. “Switching GAN-based Image Filters to Improve Perception for Autonomous Driving.” 2019. Web. 21 Jan 2021.

Vancouver:

Masud Z. Switching GAN-based Image Filters to Improve Perception for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10012/15228.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Masud Z. Switching GAN-based Image Filters to Improve Perception for Autonomous Driving. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/15228

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

12. Arora, Prashant. DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/pv63g024f

► The objective of this thesis is to develop an open-source highway driving simulator setup that allows different levels of autonomy in traffic, exposure to different… (more)

Subjects/Keywords: Driving Simulator; Autonomous Environments; Scenario Authoring

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APA (6^th Edition):

Arora, P. (2016). DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/pv63g024f

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Arora, Prashant. “DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS.” 2016. Thesis, Penn State University. Accessed January 21, 2021. https://submit-etda.libraries.psu.edu/catalog/pv63g024f.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Arora, Prashant. “DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS.” 2016. Web. 21 Jan 2021.

Vancouver:

Arora P. DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Jan 21]. Available from: https://submit-etda.libraries.psu.edu/catalog/pv63g024f.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Arora P. DEVELOPMENT OF AN OPEN-SOURCE DRIVING SIMULATOR TO EVALUATE DRIVER BEHAVIOR IN AUTONOMOUS ENVIRONMENTS. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/pv63g024f

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

13. Shu, Keqi. Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making.

Degree: 2020, University of Waterloo

URL: http://hdl.handle.net/10012/16190

► Left-turning at unsignalized intersection is one of the most challenging tasks for urban automated driving, due to the various shapes of different intersections, and rapidly… (more)

▼ Left-turning at unsignalized intersection is one of the most challenging tasks for urban automated driving, due to the various shapes of different intersections, and rapidly changing nature of the driving scenarios. Many algorithms including rule-based approach, graph-based approach, optimization-based approach, etc. have been developed to overcome the problems. However, most algorithms implemented were difficult to guarantee the safety at intersection scenarios in real time due to the large uncertainty of the intersections. Other algorithms that aim to always keep a safe distance in all cases often become overly conservative, which might also be dangerous and inefficient. This thesis addresses this challenge by proposing a generalized critical turning point (CTP) based hierarchical decision making and planning method, which enables safe and efficient planning and decision making of autonomous vehicles. The high-level candidate-paths planner takes the road map information and generates CTPs using a parameterized CTP extraction model which is proposed and verified by naturalistic driving data. CTP is a novel concept and the corresponding CTP model is used to generate behavior-oriented paths that adapt to various intersections. These modifications help to assure the high searching efficiency of the planning process, and in the meanwhile, enable human-like driving behavior of the autonomous vehicle. The low-level planner formulates the decision-making task to a POMDP problem which considers the uncertainties of the agent in the intersections. The POMDP problem is then solved with a Monte Carlo tree search (MCTS)-based framework to select proper candidate paths and decide the actions on that path. The proposed framework that uses CTPs is tested in several critical scenarios and has out-performed the methods of not using CTPs. The framework has shown the ability to adapt to various shapes of intersections with different numbers of road lanes and different width of median strips, and finishes the left turns while keeping proper safety distances. The uses of the CTP concept which is proposed through human-driving left-turning behaviors, enables the framework to perform human-like behaviors that is easier to be speculated by the other agents of the intersection, which improves the safety of the ego vehicle too. The framework is also capable of personalized modification of the desired real-time performance and the corresponding stability. The use of the POMDP model which considers the unknown intentions of the surrounding vehicles has also enabled the framework to provide commute-efficient two-dimensional planning and decision-making. In all, the proposed framework enables the ego vehicle to perform less conservative and human-like actions while considering the potential of crashes in real-time, which not only improves the commute-efficiency, but also enables urban driving autonomous vehicles to naturally integrate into scenarios with human-driven vehicles in a friendly manner

Subjects/Keywords: autonomous driving; decision making; POMDP; path planning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Shu, K. (2020). Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16190

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shu, Keqi. “Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making.” 2020. Thesis, University of Waterloo. Accessed January 21, 2021. http://hdl.handle.net/10012/16190.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shu, Keqi. “Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making.” 2020. Web. 21 Jan 2021.

Vancouver:

Shu K. Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10012/16190.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shu K. Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Planning and Decision Making. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/16190

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Chicago

14. Calvi, Michele G. Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models.

Degree: 2019, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/23753

► In recent years we have seen a rise in the complexity of physical systems that humans build. As these systems become more complex also their… (more)

▼ In recent years we have seen a rise in the complexity of physical systems that humans build. As these systems become more complex also their correct functioning becomes more challenging. Furthermore, it is often difficult to obtain an accurate model of the system making formal verification of such systems even more complicated. The goal of the thesis is to investigate a frameworks whereby the model of the cyber-physical system (in this case a self-driving car) is developed through a black-box modeling approach, a long short term memory neural network. A recurrent neural network which stores information over arbitrary time intervals. This network will learn the behavior of the system from training data and can be subsequently used to guarantee safety of the system. This approach could be significant for many applications and in particular for autonomous systems which are currently a focus of intense development. In these systems, deep learning is often used to process data and make decisions on what the system should do. First, data from a simulator was used to train a neural network to generate the control of the vehicle (steering angle and acceleration).This module was used as an example of soft computing that is used in many autonomous cars. Once the control module was developed it was necessary to verify the safety of the vehicle. This was achieved by using the runtime monitoring framework. A particle filter which computes the probability distribution of the states at each time step (belief) is the integral part of the monitor. By computing the belief of the system combined with the desired safety property, we can make a decision on whether the operation of the vehicle is safe. Finally, once we obtained a monitor with good accuracies we show that it is possible to also use a data driven model of the vehicle to monitor safety. Advisors/Committee Members: Zefran, Milos (advisor), Risso, Fulvio (committee member), Han, Shuo (committee member), Zefran, Milos (chair).

Subjects/Keywords: Cyber Physical Systems; Autonomous Driving; Montior

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Calvi, M. G. (2019). Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/23753

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Calvi, Michele G. “Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models.” 2019. Thesis, University of Illinois – Chicago. Accessed January 21, 2021. http://hdl.handle.net/10027/23753.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Calvi, Michele G. “Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models.” 2019. Web. 21 Jan 2021.

Vancouver:

Calvi MG. Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models. [Internet] [Thesis]. University of Illinois – Chicago; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10027/23753.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Calvi MG. Runtime Monitoring of Cyber-Physical Systems Using Data-driven Models. [Thesis]. University of Illinois – Chicago; 2019. Available from: http://hdl.handle.net/10027/23753

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

15. Resink, Tim (author). Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b

► To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving… (more)

▼ To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that influence driving behavior comprise many factors, such as general driving physics, infrastructure geometry, traffic rules, weather and so on. Models that are used today are incapable of including many of these aspects. These deep learning models often rely heavily on the past driven trajectory as an information source for future prediction. Sparsely, some work has been done to include interaction between vehicles or some infrastructural features to the model. The lack of information regarding the driving scene can be seen as a missed opportunity, because it is a use- ful feature source to predict the motion of a vehicle. Especially when a map of the driving scene is available, reliable information regarding the road layout can be extracted. In this thesis, a model architecture is sought that is aware of the interaction between vehicles, and that un- derstands the geometry of the roads in the scene. Importantly, map information regarding the driving scene should be used as the primary source of information regarding the road geometry. First, a baseline deep learning model is constructed, that can generate predictions based on the past observed trajectory. To add interaction features to the model, a social pooling module is introduced. The social pooling method allows to efficiently include the driving behavior of other vehicles in the scene. To introduce reliable, map-based road information to the model, two novel methods are proposed. In the first, the predictions from a model are used to extract features in a map. These features describe the road scene around the predicted location, and are used to update these predictions. In the second method, the semantic map is only used to extract a road segment ahead of the vehicle. A road-RNN is introduced to con- struct features regarding the road segment, and an attention mechanism to determine what part of the road segment is relevant for the predictions. These modules are referred to as road-refinement and road-attention respectively. The importance of including both road geometry and interaction methods in the model is shown by con- structing 5 different models that vary in their road-geometric and interaction awareness. A baseline deep learning model is used and extended with a road-geometry module, an interaction module, a combination of the two, or none. To test the prediction capabilities of the models, they are trained on two different datasets. The first dataset, called i80, consists of trajectory recordings from a straight highway with dense traffic. The other dataset is a curved version of the i80, called i80c, where the trajectories and road are transformed to introduce road-geometric variations in the data. The… Advisors/Committee Members: Jonker, Pieter (mentor), Gaisser, F. (mentor), Kooij, Julian (graduation committee), Alonso Mora, Javier (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Autonomous driving; Motion prediction; Deep learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Resink, T. (. (2019). Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b

Chicago Manual of Style (16^th Edition):

Resink, Tim (author). “Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.” 2019. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b.

MLA Handbook (7^th Edition):

Resink, Tim (author). “Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map.” 2019. Web. 21 Jan 2021.

Vancouver:

Resink T(. Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b.

Council of Science Editors:

Resink T(. Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:bb469461-b879-40fd-abbc-1a6e0233bf1b

Delft University of Technology

16. Trombitás, Daniel (author). Roll stability control of autonomous truck combinations.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:b719b6b2-82b5-4439-a6bd-f3173ff81a5e

►

Commercial heavy vehicles are especially prone to rolling over due to their inherent properties, such as the high centre of gravity - track width ratio… (more)

▼

Commercial heavy vehicles are especially prone to rolling over due to their inherent properties, such as the high centre of gravity - track width ratio and compliant chassis frame. Autonomous trucks cannot become widespread without eliminating this danger by guaranteeing rollover-free vehicle motion. Currently existing Roll Stability Control implementations rely on the assumption of having a responsible driver behind the steering wheel – therefore, unsupervised driving will need a higher level of roll safety than what the currently used methods can provide. Fortunately, there are two main attributes of self-driving vehicles that can be utilized to achieve this goal: Information about the reference path ahead of the truck will be available and the used algorithms may have a full control authority over the available actuators. This thesis project developed two, redundant rollover mitigation techniques to be run in parallel, for a tractor-trailer combination: The proactive and reactive Roll Stability Control methods. These vehicle motion controllers are separate, independent functional entities. While the proactive approach attempts to prevent upcoming events, the reactive Roll Stability Control is designed to mitigate imminent rollovers that could not be anticipated based on motion reference information. This controller is placed within the motion control paradigm of Control Allocation. The objective of Control Allocation is to coordinate different actuators to achieve both longitudinal and yaw accelerations as desired by the higher-level tracking controller. Roll stability is achieved by extending the set of functionalities of this framework, using both brakes and steering to realize the needed interventions. Emphasis is put on accurate wheel lift-off detection, using lateral acceleration, steering angle and accurately estimated roll angle signals. Design choices during syntheses of both controllers were made based on the conclusions of a thorough analysis of roll dynamics, carried out using a high-fidelity vehicle model, provided and validated by Volvo Group Truck Technologies. Subsequently, both controllers were implemented within Volvo's real-time framework. While the proactive method's performance was only assessed using simulations, the reactive controller was tested on Volvo's proving grounds. The thesis concludes that achieving a higher level of roll stability of (autonomous) heavy vehicles is possible, whilst having a less conservative overall behaviour compared to traditional approaches. This research contributes to making a step towards the next generation of rollover prevention for automated trucks.

Systems and Control

Advisors/Committee Members: Keviczky, Tamas (mentor), Mendel, Max (graduation committee), Shyrokau, Barys (graduation committee), Delimpaltadakis, Giannis (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Autonomous driving; Rollover prevention; Model based

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Trombitás, D. (. (2019). Roll stability control of autonomous truck combinations. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b719b6b2-82b5-4439-a6bd-f3173ff81a5e

Chicago Manual of Style (16^th Edition):

Trombitás, Daniel (author). “Roll stability control of autonomous truck combinations.” 2019. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:b719b6b2-82b5-4439-a6bd-f3173ff81a5e.

MLA Handbook (7^th Edition):

Trombitás, Daniel (author). “Roll stability control of autonomous truck combinations.” 2019. Web. 21 Jan 2021.

Vancouver:

Trombitás D(. Roll stability control of autonomous truck combinations. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:b719b6b2-82b5-4439-a6bd-f3173ff81a5e.

Council of Science Editors:

Trombitás D(. Roll stability control of autonomous truck combinations. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:b719b6b2-82b5-4439-a6bd-f3173ff81a5e

University of Waterloo

17. Chen, Xingxin. Domain Adaptation for Autonomous Driving.

Degree: 2020, University of Waterloo

URL: http://hdl.handle.net/10012/16446

► Metric based method is a promising approach to domain adaptation, which aims to align the marginal distribution of different domains with a similar conditional distribution.… (more)

Subjects/Keywords: autonomous driving; domain adaptation; computer vision

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APA (6^th Edition):

Chen, X. (2020). Domain Adaptation for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16446

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chen, Xingxin. “Domain Adaptation for Autonomous Driving.” 2020. Thesis, University of Waterloo. Accessed January 21, 2021. http://hdl.handle.net/10012/16446.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chen, Xingxin. “Domain Adaptation for Autonomous Driving.” 2020. Web. 21 Jan 2021.

Vancouver:

Chen X. Domain Adaptation for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10012/16446.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen X. Domain Adaptation for Autonomous Driving. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/16446

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

King Abdullah University of Science and Technology

18. Zarzar Torano, Jesus Alejandro. Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking.

Degree: 2019, King Abdullah University of Science and Technology

URL: http://hdl.handle.net/10754/644892

► The automation of navigation for different kinds of vehicles is a research problem of great interest. This problem has applications with unmanned aerial vehicles (UAVs)… (more)

Subjects/Keywords: Autonomous; Driving; Modular; Siamese; 3D Tracking; Vehicles

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APA (6^th Edition):

Zarzar Torano, J. A. (2019). Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/644892

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zarzar Torano, Jesus Alejandro. “Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking.” 2019. Thesis, King Abdullah University of Science and Technology. Accessed January 21, 2021. http://hdl.handle.net/10754/644892.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zarzar Torano, Jesus Alejandro. “Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking.” 2019. Web. 21 Jan 2021.

Vancouver:

Zarzar Torano JA. Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10754/644892.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zarzar Torano JA. Modular Autonomous Taxiing Simulation and 3D Siamese Vehicle Tracking. [Thesis]. King Abdullah University of Science and Technology; 2019. Available from: http://hdl.handle.net/10754/644892

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Loughborough University

19. Deligianni, Penny. Modelling drivers' braking behaviour and comfort under normal driving.

Degree: PhD, 2019, Loughborough University

URL: https://doi.org/10.26174/thesis.lboro.12035310.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.808044

► The increasing growth of population and a rising number of vehicles, connected to an individual, demand new solutions to reduce traffic delays and enhance road… (more)

▼ The increasing growth of population and a rising number of vehicles, connected to an individual, demand new solutions to reduce traffic delays and enhance road safety. Autonomous Vehicles (AVs) have been considered as an optimal solution to overcome those problems. Despite the remarkable research and development progress in the area of (semi) AVs over the last decades, there is still concern that occupants may not feel safe and comfortable due to the robot-like driving behaviour of the current technology. In order to facilitate their rapid uptake and market penetration, ride comfort in AVs must be ensured. Braking behaviour has been identified to be a crucial factor in ride comfort. There is a dearth of research on which factors affect the braking behaviour and the comfort level while braking and which braking profiles make the occupants feel safe and comfortable. Therefore, the primary aim of this thesis is to model the deceleration events of drivers under normal driving conditions to guide comfortable braking design. The aim was achieved by exploiting naturalistic driving data from three projects: (1) the Pan-European TeleFOT (Field Operational Tests of Aftermarket and Nomadic Devices in Vehicles) project, (2) the Field Operational Test (FOT) conducted by Loughborough University and Original Equipment Manufacturer (OEM), and (3) the UDRIVE Naturalistic Driving Study. A total of about 35 million observations were examined from 86 different drivers and 644 different trips resulting in almost 10,000 deceleration events for the braking features analysis and 21,600 deceleration events for the comfort level analysis. Since deceleration events are nested within trips and trips within drivers, multilevel mixed-effects linear models were employed to develop relationships between deceleration value and duration and the factors influencing them. The examined factors were kinematics, situational, driver and trip characteristics with the first two categories to affect the most the deceleration features. More specifically, the initial speed and the reason for braking play a significant role, whereas the driver's characteristics, i.e. the age and gender do not affect the deceleration features, except for driver's experience which significantly affects the deceleration duration. An algorithm was developed to calculate the braking profiles, indicating that the most used profile follows smooth braking at the beginning followed by a harder one. Moreover, comfort levels of drivers were analysed using the Mixed Multinomial Logit models to identify the effect of the explanatory factors on the comfort category of braking events. Kinematic factors and especially TTC and time headway (THW) were found to affect the most the comfort level. Particularly, when TTC or THW are increased by 1 second, the odds of the event to be “very comfortable” are respectively 1.03 and 4.5 times higher than being “very uncomfortable”. Moreover, the driver's characteristic, i.e. age and gender affect significantly the comfort level of the deceleration event.…

Subjects/Keywords: Braking Behaviour; Naturalistic Driving Studies; Autonomous Vehicles

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Deligianni, P. (2019). Modelling drivers' braking behaviour and comfort under normal driving. (Doctoral Dissertation). Loughborough University. Retrieved from https://doi.org/10.26174/thesis.lboro.12035310.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.808044

Chicago Manual of Style (16^th Edition):

Deligianni, Penny. “Modelling drivers' braking behaviour and comfort under normal driving.” 2019. Doctoral Dissertation, Loughborough University. Accessed January 21, 2021. https://doi.org/10.26174/thesis.lboro.12035310.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.808044.

MLA Handbook (7^th Edition):

Deligianni, Penny. “Modelling drivers' braking behaviour and comfort under normal driving.” 2019. Web. 21 Jan 2021.

Vancouver:

Deligianni P. Modelling drivers' braking behaviour and comfort under normal driving. [Internet] [Doctoral dissertation]. Loughborough University; 2019. [cited 2021 Jan 21]. Available from: https://doi.org/10.26174/thesis.lboro.12035310.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.808044.

Council of Science Editors:

Deligianni P. Modelling drivers' braking behaviour and comfort under normal driving. [Doctoral Dissertation]. Loughborough University; 2019. Available from: https://doi.org/10.26174/thesis.lboro.12035310.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.808044

Delft University of Technology

20. Zoričić, Jasna (author). Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:91442961-2c92-4b33-96df-e92df15cef7d

►

This Master thesis was developed for Mercedes-Benz AG. The following report elaborates the steps taken in developing a holistic interior vision for ‘Sustainable Luxury’ of… (more)

▼

This Master thesis was developed for Mercedes-Benz AG. The following report elaborates the steps taken in developing a holistic interior vision for ‘Sustainable Luxury’ of Mercedes-Benz. In seek of representation for the future societal needs, and possible future challenges and opportunities in terms of holistic mobility conceptualisation, the research took place in the rural areas of Japan. Therefore, this project is aimed at ‘Self-reliant people accepting innovation raised on the traditional values’. These people are seeking the segregated life, focused on the abundant luxury of time, bonds of smaller communities, and personal fulfilment. Cherishing the community traditions, innovation is acceptable if it preserves the experiential domain of respect towards community members and the environment. To fulfil the demand for such a context, the mission was ‘to achieve a perception of an abundance of less within the experience and perception of the product while keeping the identity of the brand intact.’ As the reconciliation between sustainability and luxury indicates the change of expression of luxury in means of a form, the qualities of the premium experience are set to keeping the utmost feeling of safety and physical ease leading to comfort. Therefore, ‘encountering a moment for yourself, within a shared experience, in comfort.’ was set as the desired interaction. The ideation led to the development of three concept ideas, which were further validated and iterated leading to the conclusive vision ‘Ikigai: A reason for being’. Ikigai presents mobility solution as part of the holistic system of sustainability and manifests as a contribution to the context. The vision ‘Ikigai’ is a Level 4 shared mobility service by Mercedes-Benz, intended for the rural communities of Japan. The on-demand service, utilising the Mercedes-Benz municipal vehicle, grants community residents overcoming the dependence on the pre-scheduled, public transportation of the area. The private zones in the interior space are providing users with a possibility for individual focus and relaxation while in a shared environment. Ikigai’s minimalistic interior is enriched by the works of local craftsman. The material finishings of unique algae-based materials and bio-luminescent lights, produced in the village, are limited to the vehicle design specific to the area. Consequently, the car simultaneously represents exclusivity of the local craftsmen and uniqueness of the tradition, sharing them in rides beyond the borders of the village. The brand remains to provide unique personal experiences within innovative products. Meticulous attention to details and high build quality bring it to the class of its own in providing a sense of safety and physical ease leading to Mercedes-Benz comfort.

Design for Interaction

Advisors/Committee Members: van Grondelle, Elmer (mentor), Ruiter, Anna (mentor), Fischer, Jan (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: Mobility; Autonomous driving; Premium; Automotive; Sustainability; Biomaterials

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APA (6^th Edition):

Zoričić, J. (. (2020). Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:91442961-2c92-4b33-96df-e92df15cef7d

Chicago Manual of Style (16^th Edition):

Zoričić, Jasna (author). “Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030.” 2020. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:91442961-2c92-4b33-96df-e92df15cef7d.

MLA Handbook (7^th Edition):

Zoričić, Jasna (author). “Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030.” 2020. Web. 21 Jan 2021.

Vancouver:

Zoričić J(. Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:91442961-2c92-4b33-96df-e92df15cef7d.

Council of Science Editors:

Zoričić J(. Ikigai: A reason for Being A Holistic Vision of Mercedes-Benz 2030. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:91442961-2c92-4b33-96df-e92df15cef7d

University of Cincinnati

21. Burgei, David. Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles.

Degree: M. Arch., Design, Architecture, Art and Planning: Architecture, 2017, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504798936197976

► Edge cities, suburban commercial districts on the outskirts of larger metropolitan areas, have always been centered on the convenience of accessibility. Due to the personal… (more)

Subjects/Keywords: Architecture; Autonomous Vehicles; Self-Driving; New Urbanism

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APA (6^th Edition):

Burgei, D. (2017). Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504798936197976

Chicago Manual of Style (16^th Edition):

Burgei, David. “Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles.” 2017. Masters Thesis, University of Cincinnati. Accessed January 21, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504798936197976.

MLA Handbook (7^th Edition):

Burgei, David. “Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles.” 2017. Web. 21 Jan 2021.

Vancouver:

Burgei D. Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles. [Internet] [Masters thesis]. University of Cincinnati; 2017. [cited 2021 Jan 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504798936197976.

Council of Science Editors:

Burgei D. Autonomous Edge Cities:Revitalizing Suburban Commercial Centers with Autonomous Vehicle Technology and New (sub)Urbanist Principles. [Masters Thesis]. University of Cincinnati; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504798936197976

University of Illinois – Chicago

22. Basso, Maria. Eco Platoon Formation for Autonomous Electric Vehicles.

Degree: 2017, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/21862

► In this thesis we focused our attention on autonomous electric vehicles, developing a methodology in order to decide whether a vehicle should travel alone or… (more)

Subjects/Keywords: Eco; platoon; driving; autonomous; self-driving; energy; saving; formation; car; vehicle

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APA (6^th Edition):

Basso, M. (2017). Eco Platoon Formation for Autonomous Electric Vehicles. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21862

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Basso, Maria. “Eco Platoon Formation for Autonomous Electric Vehicles.” 2017. Thesis, University of Illinois – Chicago. Accessed January 21, 2021. http://hdl.handle.net/10027/21862.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Basso, Maria. “Eco Platoon Formation for Autonomous Electric Vehicles.” 2017. Web. 21 Jan 2021.

Vancouver:

Basso M. Eco Platoon Formation for Autonomous Electric Vehicles. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10027/21862.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Basso M. Eco Platoon Formation for Autonomous Electric Vehicles. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/21862

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

23. el Hassnaoui, Mounir (author). Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:94542399-7a90-4af7-b526-a785683eb8cd

► Long before humans will completely trust fully automated vehicles, partial and conditional automation where the human driver is still in the loop will dominate the… (more)

▼ Long before humans will completely trust fully automated vehicles, partial and conditional automation where the human driver is still in the loop will dominate the era of autonomous vehicles. However, more than 90% of traffic accidents are due to human errors, of which approximately half appear to be due to perceptual errors. Especially at busy and complex intersections that have a high density of visual stimuli. This poses a high demand for accurate measurement of the driver's situation awareness, for real-world driver monitoring. Eye tracking seems to be an ideal method to determine what the driver has or has not seen, since people tend to look at what they inquire information from. The main objective of this thesis assignment was therefore to develop a platform that combines the driver's gaze behaviour in combination with the vehicle's road scene perception, to set up a real-world driving experiment to gather such data on the road, and to come up with a proof of concept that gaze behaviour combined with situational knowledge can be predictive of SA. The platform developed consisted of an eye-tracker with four cameras constructed in the available Toyota Prius of the department of Intelligent Vehicles, which is equipped for self-driving. The driver's gaze was layered over the object identification data from the vehicle, to see which objects are looked at or fixated upon and which are not. A real-world driving experiment was then conducted in which participants (N = 14) performed a driving task and a recall task. The driving task consisted of 8 intersection crossings in which mostly left turns were made to manoeuvre the vehicle off a main priority road. After each crossing, the participants performed a recall task in which they had to select images of the object they encountered during the driving task. The results showed that 88.1% of all relevant objects they encountered were seen with central vision, of which 41.8% were recalled. The remainder 11.9% of all relevant objects that were not seen, have only been in peripheral view, of which 18.2% were recalled. These preliminary results indicate that at least 2.2% (18.2% of 11.9%) of relevant objects are perceived by the driver using peripheral vision. The variables seen, first saccade angle and first saccade moment contributed significantly to a prediction model that predicted whether a relevant object would be recalled by the driver. The variables fixation count, total glance duration and saccade count were not significant predictor variables. The conclusion was drawn that the results of this exploratory research confirmed that gaze behaviour combined with situational knowledge can be predictive of driver SA. However, a crucial recommendation for future research is an improved recall task procedure to obtain higher recall rates and therefore more accurate prediction of SA. This outcome could be of great value for future research and development of applications that assist or steer the driver's attention to possible threats or objects the driver is missing or not… Advisors/Committee Members: Happee, Riender (mentor), Stapel, Jork (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Eye Tracking; Autonomous driving; Situation Awareness; Real-world driving

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

el Hassnaoui, M. (. (2019). Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:94542399-7a90-4af7-b526-a785683eb8cd

Chicago Manual of Style (16^th Edition):

el Hassnaoui, Mounir (author). “Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception.” 2019. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:94542399-7a90-4af7-b526-a785683eb8cd.

MLA Handbook (7^th Edition):

el Hassnaoui, Mounir (author). “Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception.” 2019. Web. 21 Jan 2021.

Vancouver:

el Hassnaoui M(. Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:94542399-7a90-4af7-b526-a785683eb8cd.

Council of Science Editors:

el Hassnaoui M(. Measuring driver perception during on-road eye-tracking: Combining gaze behaviour and vehicle’s road scene perception. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:94542399-7a90-4af7-b526-a785683eb8cd

Delft University of Technology

24. van Dintel, Kevin (author). Highly Automated Driving: Transitions of control authority using Haptic Shared Control.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:8facf33f-2224-4418-bea9-4ffcfbca0c21

►

The arrival of highly automated vehicles introduces a new interaction between the vehicle and driver. System limitations during highly automated driving require the driver to… (more)

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The arrival of highly automated vehicles introduces a new interaction between the vehicle and driver. System limitations during highly automated driving require the driver to be ready to take back control at request. Previous studies on the take-over process concluded that the driver requires a transition period to stabilize vehicle control after resuming manual control. These studies used traded control to instantaneously transfer control back to the driver, causing an abrupt switch in control authority. Therefore, this study explores Haptic Shared Control as a different transition approach. By varying the level of haptic authority, a smooth connection between automation system and driver can be realized. The aim of this study is to investigate if Haptic Shared Control improves the take-over performance compared to the traded control approach. A total of 30 participants drove two trials in a driving simulator, one for each transition approach. Each trial consisted of 10 take-over scenarios divided into two levels of time-criticality. During autonomous driving the participants were engaged in a secondary task. The take-over performance was assessed based on safety performance, lateral vehicle control, controller performance and subjective measures. Results showed a significant decrease in the standard deviation of the lateral position evaluated over the mean trajectory per participant for the Haptic Shared Control approach compared to traded control. Haptic Shared Control also showed a significant decrease for the mean lateral obstacle clearance. The analyses on torque conflicts revealed a significant increase for critical take-over maneuver compared to non-critical take-over maneuvers. This suggests that haptic shared control can assist the driver in stabilizing lateral vehicle control after resuming manual control. On the other hand, the driver is limited in performing a sharp evasive maneuver, and this relationship is discussed. More research is needed on using an adaptable human compatible reference.

Mechanical Engineering | Vehicle Engineering

Advisors/Committee Members: Abbink, David (mentor), Petermeijer, Bastiaan (mentor), de Vries, Edwin (mentor), Plettenburg, Dick (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: autonomous driving; control transitions; Haptic shared control; driving simulator

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APA (6^th Edition):

van Dintel, K. (. (2019). Highly Automated Driving: Transitions of control authority using Haptic Shared Control. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:8facf33f-2224-4418-bea9-4ffcfbca0c21

Chicago Manual of Style (16^th Edition):

van Dintel, Kevin (author). “Highly Automated Driving: Transitions of control authority using Haptic Shared Control.” 2019. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:8facf33f-2224-4418-bea9-4ffcfbca0c21.

MLA Handbook (7^th Edition):

van Dintel, Kevin (author). “Highly Automated Driving: Transitions of control authority using Haptic Shared Control.” 2019. Web. 21 Jan 2021.

Vancouver:

van Dintel K(. Highly Automated Driving: Transitions of control authority using Haptic Shared Control. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:8facf33f-2224-4418-bea9-4ffcfbca0c21.

Council of Science Editors:

van Dintel K(. Highly Automated Driving: Transitions of control authority using Haptic Shared Control. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:8facf33f-2224-4418-bea9-4ffcfbca0c21

University of Toronto

25. Pon, Alexander. Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection.

Degree: 2019, University of Toronto

URL: http://hdl.handle.net/1807/98290

►

Safe autonomous driving requires reliable 3D object detection-the task of estimating 3D bounding boxes for objects of interest in the scene. This thesis introduces a… (more)

Subjects/Keywords: 3D Object Detection; Autonomous Driving; Autonomous Vehicles; Scene Understanding; 0771

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APA (6^th Edition):

Pon, A. (2019). Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/98290

Chicago Manual of Style (16^th Edition):

Pon, Alexander. “Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection.” 2019. Masters Thesis, University of Toronto. Accessed January 21, 2021. http://hdl.handle.net/1807/98290.

MLA Handbook (7^th Edition):

Pon, Alexander. “Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection.” 2019. Web. 21 Jan 2021.

Vancouver:

Pon A. Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection. [Internet] [Masters thesis]. University of Toronto; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1807/98290.

Council of Science Editors:

Pon A. Leveraging Proposals and Shape Reconstruction for Monocular 3D Object Detection and Object-centric Stereo Matching for 3D Object Detection. [Masters Thesis]. University of Toronto; 2019. Available from: http://hdl.handle.net/1807/98290

26. Silva, Pedro Marques Ferreira da. Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 .

Degree: 2019, Universidade de Aveiro

URL: http://hdl.handle.net/10773/29660

► Within the scope of the ATLASCAR2 project, this dissertation is based on studying and integrating the already existing autonomous driving assistance simulator named CARLA that… (more)

Subjects/Keywords: Autonomous Driving; Autonomous Vehicles; Autonomous Driving Simulators; ATLASCAR; CARLA; AD; ADAS; LIDAR; Object Detection; Image Processing

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APA (6^th Edition):

Silva, P. M. F. d. (2019). Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 . (Thesis). Universidade de Aveiro. Retrieved from http://hdl.handle.net/10773/29660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Silva, Pedro Marques Ferreira da. “Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 .” 2019. Thesis, Universidade de Aveiro. Accessed January 21, 2021. http://hdl.handle.net/10773/29660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Silva, Pedro Marques Ferreira da. “Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 .” 2019. Web. 21 Jan 2021.

Vancouver:

Silva PMFd. Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 . [Internet] [Thesis]. Universidade de Aveiro; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10773/29660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Silva PMFd. Study and adaptation of the autonomous driving simulator CARLA for the ATLASCAR2 . [Thesis]. Universidade de Aveiro; 2019. Available from: http://hdl.handle.net/10773/29660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Guelph

27. Cortens, Benjamin. Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle.

Degree: MS, School of Computer Science, 2019, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/15935

► Future autonomous vehicles may offer systems where control authority varies between human and full automation. These vehicles are most dangerous when human intervention is required… (more)

Subjects/Keywords: Autonomous Vehicles; Driver Takeover; Human Computer Interaction; Driving Automation; Driving Safety; Situation Awareness; Driving Research; Driving Simulator; Multimodal; Warnings; Takeover Alerts

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APA (6^th Edition):

Cortens, B. (2019). Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/15935

Chicago Manual of Style (16^th Edition):

Cortens, Benjamin. “Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle.” 2019. Masters Thesis, University of Guelph. Accessed January 21, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/15935.

MLA Handbook (7^th Edition):

Cortens, Benjamin. “Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle.” 2019. Web. 21 Jan 2021.

Vancouver:

Cortens B. Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle. [Internet] [Masters thesis]. University of Guelph; 2019. [cited 2021 Jan 21]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/15935.

Council of Science Editors:

Cortens B. Impact of Alert Design and Hazard Direction on Driver Behaviour and Understanding in a Simulated Autonomous Vehicle. [Masters Thesis]. University of Guelph; 2019. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/15935

Delft University of Technology

28. Gürses, Sergin (author). How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:7ddf2758-577c-4e0f-98c6-54a20e45996d

► Human Machine Interface (HMI) is a design concept that improves the interaction between the driver and the automated vehicle, which leads to greater safety and… (more)

Subjects/Keywords: Human Machine Interface Design; Automated driving; Human Machine Interaction; Human Computer Interaction; Autonomous car; autonomous driving; Self-driving car; Automated Vehicles; automated; car; Driving; HMI

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Gürses, S. (. (2020). How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7ddf2758-577c-4e0f-98c6-54a20e45996d

Chicago Manual of Style (16^th Edition):

Gürses, Sergin (author). “How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review.” 2020. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:7ddf2758-577c-4e0f-98c6-54a20e45996d.

MLA Handbook (7^th Edition):

Gürses, Sergin (author). “How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review.” 2020. Web. 21 Jan 2021.

Vancouver:

Gürses S(. How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:7ddf2758-577c-4e0f-98c6-54a20e45996d.

Council of Science Editors:

Gürses S(. How Human-Machine Interaction keeps pace with Automated Vehicles: A systematic review. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:7ddf2758-577c-4e0f-98c6-54a20e45996d

McMaster University

29. Cudrano, Paolo. A study on lane detection methods for autonomous driving.

Degree: MSc, 2019, McMaster University

URL: http://hdl.handle.net/11375/24200

►

Machine perception is a key element for the research on autonomous driving vehicles. In particular, we focus on the problem of lane detection with a… (more)

Subjects/Keywords: lane detection; computer vision; autonomous driving; self-driving cars; perception; artificial intelligence

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cudrano, P. (2019). A study on lane detection methods for autonomous driving. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/24200

Chicago Manual of Style (16^th Edition):

Cudrano, Paolo. “A study on lane detection methods for autonomous driving.” 2019. Masters Thesis, McMaster University. Accessed January 21, 2021. http://hdl.handle.net/11375/24200.

MLA Handbook (7^th Edition):

Cudrano, Paolo. “A study on lane detection methods for autonomous driving.” 2019. Web. 21 Jan 2021.

Vancouver:

Cudrano P. A study on lane detection methods for autonomous driving. [Internet] [Masters thesis]. McMaster University; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/11375/24200.

Council of Science Editors:

Cudrano P. A study on lane detection methods for autonomous driving. [Masters Thesis]. McMaster University; 2019. Available from: http://hdl.handle.net/11375/24200

Univerzitet u Beogradu

30. Kocić, Jelena, 1982-, 57181961. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.

Degree: Elektrotehnički fakultet, 2020, Univerzitet u Beogradu

URL: https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get

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Elektrotehnika i računarstvo Uža naučna oblast: Elektronika / Electrical Engineering and Computer Science- Electronics

Cilj disertacije je ostvarivanje autonomnog održanja vozila u kolovoznoj traci analizom… (more)

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Elektrotehnika i računarstvo Uža naučna oblast: Elektronika / Electrical Engineering and Computer Science- Electronics

Cilj disertacije je ostvarivanje autonomnog održanja vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem projektovane duboke neuralne mreže, eng. deep neural network (DNN). DNN za učenje od-kraja-do-kraja na ulaz dovodi sliku sa kamere montirane na vozilu, a izlaz iz DNN je informacija o uglu okretanja upravljača vozila. Ova tehnika se još naziva i kloniranje ponašanja vozača, eng. behavior cloning. Polazna hipoteza je da je moguće ostvariti autonomnu vožnju korišćenjem duboke neuralne mreže za učenje od-kraja-do-kraja koja je računarski manje zahtevna od do sada postojećih rešenja, pri čemu korišćenjem modela nove mreže, performanse autonomne vožnje ne degradiraju značajno. Osnovna prednost novog rešenja je omogućavanje implementacije projektovanog rešenja na autonomno vozilo sa ograničenim hardverskim performansama u smislu računarske snage i memorijskog kapaciteta. Razvijena je nova arhitektura DNN za učenje od-kraja-do-kraja za autonomnu vožnju koja je nazvana J-Net. U poređenju sa drugim poznatim modelima, PilotNet i AlexNet, J-Net model ima najmanji broj trenarabilnih parametara, najmanji broj operacija nad čvorovima neuralne mreže i istrenirana J-Net mreža zauzima najmanje memorijskog prostora. Verifikacija autonomne vožnje ostvarena je u simuliranim uslovima, korišćenjem simulatora autonomne vožnje otvorenog koda, i u realnim uslovima. Za verifikaciju u realnim uslovima, projektovan je sistem za autonomnu vožnju u laboratoriji za elektroniku Elektrotehničkog fakulteta Univerziteta u Beogradu. Verifikacije u simuliranim i u realnim uslovima pokazale su da je korišćenjem J-Net modela duboke neuralne mreže za učenje od-kraja-do-kraja moguće ostvariti uspešno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora.

Advisors/Committee Members: Jovičić, Nenad, 1977-, 57183241.

Subjects/Keywords: autonomous driving; deep neural network (DNN); deep learning; camera; machine learning; robo-vehicle; simulator; autonomous driving system; end-to-end learning

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APA (6^th Edition):

Kocić, Jelena, 1982-, 5. (2020). Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kocić, Jelena, 1982-, 57181961. “Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.” 2020. Thesis, Univerzitet u Beogradu. Accessed January 21, 2021. https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kocić, Jelena, 1982-, 57181961. “Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže.” 2020. Web. 21 Jan 2021.

Vancouver:

Kocić, Jelena, 1982- 5. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. [Internet] [Thesis]. Univerzitet u Beogradu; 2020. [cited 2021 Jan 21]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kocić, Jelena, 1982- 5. Autonomno održanje vozila u kolovoznoj traci analizom informacija sa vizuelnih senzora korišćenjem neuralne mreže. [Thesis]. Univerzitet u Beogradu; 2020. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:22504/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Open Access Theses and Dissertations