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Delft University of Technology
1.
Blauw, Mathieu (author).
Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8 
► The Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of…
(more)
▼ The Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of money each day. Roads are designed for the current traffic composition. Due to the promotion of Adaptive Cruise Control (ACC) systems, utilisation of these systems is expected to increase. Society benefits from insights into the effects these systems have on traffic flow, as they can help to reduce traffic jams and accidents. ACC systems are designed to increase driving comfort by taking over throttling and braking from the human driver. For optimal driver acceptance, these systems show similar driving behaviour to that of human drivers. However, this is not entirely possible due to limited anticipation. To predict how differences in driving behaviour affect traffic flows, researchers usually perform simulations using parametric car-following models. However, research shows contradictory findings. The goal of this research was to gain insights into the performance of commonly applied parametric car-following models on representing the driving behaviour of ACC systems. Optimal model calibration was obtained by investigating the sensitivity of the model calibration to synthetic data. Investigated were the calibration methodology and the quality and quantity of calibration data. Models are calibrated to real-world driving data from an Audi A4 from 2017. These models were used to assess the capability of representing typical highway scenarios: steady-state car-following, cut-in, cut-out, hard-braking and stop-and-go scenarios. The considered models were the Intelligent Driver Model (IDM) model, which has previously been applied to model the driving behaviour of human drivers, the newly developed simplified ACC (sACC) model and a variant on this model. Insights in the sensitivity of the model calibration were obtained by performing a sensitivity analysis on synthetic data. Essential factors in achieving an optimal model calibration are: 1) the model closely matches the driving behaviour in the data, 2) noise levels are as low as possible and 3) the data should contain as many situations as possible that are also included in the model. The dataset must be sufficiently long to include all these situations and to allow the model to develop its dynamics entirely. Using these insights, a calibration was performed on real-world ACC driving data from an Audi A4 (2017). For the ACC system, it was found: 1) the ACC system exhibits non-linear driving behaviour, 2) the acceleration depends on the current velocity and distance to the desired velocity, 3) the system does not consider an intelligent braking strategy and is thus not able of handling safety-critical driving situations and 4) the model includes a sub-controller which ensures comfortable driving behaviour. Except for the comfortable sub-controller, the non-linear IDM model considers all of these factors and thus best represents the driving behaviour. The linear sACC model cannot represent standing…
Advisors/Committee Members: Happee, Riender (mentor), Knoop, Victor (mentor), Wang, Meng (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: ACC; Adaptive Cruise Control; Car-Following Models; Model Calibration; Calibration; Parametric; Rijkswaterstaat; IDM; Intelligent Driver Model
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APA (6th Edition):
Blauw, M. (. (2019). Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8
Chicago Manual of Style (16th Edition):
Blauw, Mathieu (author). “Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.” 2019. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8.
MLA Handbook (7th Edition):
Blauw, Mathieu (author). “Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.” 2019. Web. 14 Apr 2021.
Vancouver:
Blauw M(. Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8.
Council of Science Editors:
Blauw M(. Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8
Delft University of Technology
2.
Bhoraskar, Akshay (author).
Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:acf934e3-ceeb-49ba-b98e-11f384324aea
► This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul…
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▼ This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul operations using various machine learning techniques. It intends to provide a possible alternative to simulation or physics based models, which often are very complicated. The stringent laws on emission control set by the Paris Agreement and the fact that heavy duty trucks contribute to almost 27% of CO2 emissions from road transport and their dependence on diesel for operations (in long haul) makes it the need of the hour to first, have an estimate on the emissions being produced and second, to develop technologies to reduce those emissions. This study focuses specifically on the first part i.e., estimating the amount of fuel consumed by heavy duty trucks in the European Union and thereby determine the emissions being produced. The main objective is to examine whether an approach of machine learning could be a viable option to predict fuel consumption. This thesis is part of the AEROFLEX project and was done in collaboration with TNO, which provided all the data-sets required for the study. The idea was to explore the regime of machine learning for one time step ahead prediction of fuel consumption. Furthermore, this study also focused on the development of another model by not using any variables affected by the driver as input into the training model. This exclusion was necessary to make sure the model remained adaptive to new routes and new trucks, especially because large scale on-road testing of the newly developed trucks is impossible and also because this way would help predict the fuel consumed by a truck without the necessity of it driving on a road. The study concludes with a comparison with an existing simulation model at TNO and provide an alternative machine learning solution. It also provides a comparison between different machine learning techniques and suggest the most accurate one. It was found that machine learning could potentially be used to predict the amount of fuel consumed by a long haul heavy duty truck driving on a motorway. It was also found that engine torque was the variable that affected the fuel consumption of the truck the most. Furthermore, Neural Network was the most potent algorithm among all the other learning techniques for both the models developed in this study with it performing better than the simulation tool by a factor of approximately 3.8 in the model where the driver/drive influenced inputs were not considered in the training data-set. The results obtained from this work at a sampling frequency of 10 Hz. (i.e., 0.1 seconds) are comparable to the ones reported by other sources at a sampling rate of 0.016 Hz. (i.e., 1 minute) or 0.0016 Hz. (i.e., 10 minutes). This goes on to say that the machine learning algorithms are also potent at much higher sampling frequencies.
Advisors/Committee Members: Pan, Wei (mentor), Wisse, Martijn (graduation committee), Knoop, Victor (graduation committee), van Eijk, Emiel (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Fuel Prediction; Machine Learning; Heavy duty vehicles
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APA (6th Edition):
Bhoraskar, A. (. (2019). Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:acf934e3-ceeb-49ba-b98e-11f384324aea
Chicago Manual of Style (16th Edition):
Bhoraskar, Akshay (author). “Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques.” 2019. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:acf934e3-ceeb-49ba-b98e-11f384324aea.
MLA Handbook (7th Edition):
Bhoraskar, Akshay (author). “Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques.” 2019. Web. 14 Apr 2021.
Vancouver:
Bhoraskar A(. Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:acf934e3-ceeb-49ba-b98e-11f384324aea.
Council of Science Editors:
Bhoraskar A(. Prediction of Fuel Consumption of Long Haul Heavy Duty Vehicles using Machine Learning and Comparison of the Performance of Various Learning Techniques. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:acf934e3-ceeb-49ba-b98e-11f384324aea
Delft University of Technology
3.
Brouwer, Dorus (author).
Flow Capacity of Bottlenecks in a Cycle Storage.
Degree: 2018, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:3da97731-76cd-4df7-aa96-0ff16a2145f3
► There is a need to know flow capacities of common bottlenecks of cycle storages because an increasing number of large cycle storages are being designed.…
(more)
▼ There is a need to know flow capacities of common bottlenecks of cycle storages because an increasing number of large cycle storages are being designed. Flow capacity values are not available from literature nor is a suitable method to determine those values. This research contributes to filling these research gaps, by developing a method to measure capacity, and applying it to case studies. The method also offers a way to calculate the standard deviation of the flow, as well as a confidence interval for the capacity. This is possible because the flow is normally distributed. Knowing the variation of the flow, predictions can be made on how often a queue will emerge. The essence of the method is to measure in an event-based manner, discard the time at which there was no queue before the bottleneck, and then divide the remaining measurements into intervals of equal duration and treat those intervals as individual capacity measurements. The method has shown to yield a capacity value that is independent of the averaging interval. The standard deviation however, does not always vary as independent data from a normal distribution would. It is hypothesised that the autocorrelation could be used to correct for that. 95% confidence intervals for capacity were found as follows; check-in: 21.2 ± 1.2 (σ=3.5), stairs: 24.78 ±0.60 (σ=1.02).
Transport, Infrastructure and Logistics
Advisors/Committee Members: Hoogendoorn, Serge (mentor), Knoop, Victor (mentor), Duinkerken, Mark (mentor), Schakenbos, Rik (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: Bicycle storage; Stairs; Check-in; Gate; Capacity; flow variation; Railway stations
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APA (6th Edition):
Brouwer, D. (. (2018). Flow Capacity of Bottlenecks in a Cycle Storage. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3da97731-76cd-4df7-aa96-0ff16a2145f3
Chicago Manual of Style (16th Edition):
Brouwer, Dorus (author). “Flow Capacity of Bottlenecks in a Cycle Storage.” 2018. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:3da97731-76cd-4df7-aa96-0ff16a2145f3.
MLA Handbook (7th Edition):
Brouwer, Dorus (author). “Flow Capacity of Bottlenecks in a Cycle Storage.” 2018. Web. 14 Apr 2021.
Vancouver:
Brouwer D(. Flow Capacity of Bottlenecks in a Cycle Storage. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:3da97731-76cd-4df7-aa96-0ff16a2145f3.
Council of Science Editors:
Brouwer D(. Flow Capacity of Bottlenecks in a Cycle Storage. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:3da97731-76cd-4df7-aa96-0ff16a2145f3
Delft University of Technology
4.
Sloot, Mark (author).
Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc
► The aim of this master thesis is to develop a dynamic zone-based traffic model for large areas, using the concept of the Network Fundamental Diagram…
(more)
▼ The aim of this master thesis is to develop a dynamic zone-based traffic model for large areas, using the concept of the Network Fundamental Diagram (NFD), which relates the average internal flow (production) and speed in a zone to the number of vehicles in the same zone (accumulation). The model that has been developed is then applied to the Randstad area, and it is analyzed whether the model is able to reproduce the observed congestion patterns and travel times between the zones.
Civil Engineering | Transport and Planning
Advisors/Committee Members: van Lint, Hans (graduation committee), Knoop, Victor (mentor), Yuan, Kai (mentor), Verbraeck, Alexander (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Network Fundamental Diagram
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APA ·
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APA (6th Edition):
Sloot, M. (. (2019). Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc
Chicago Manual of Style (16th Edition):
Sloot, Mark (author). “Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.” 2019. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc.
MLA Handbook (7th Edition):
Sloot, Mark (author). “Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.” 2019. Web. 14 Apr 2021.
Vancouver:
Sloot M(. Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc.
Council of Science Editors:
Sloot M(. Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc
Delft University of Technology
5.
Sparnaaij, Martijn (author).
How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:a0ce4bfc-ea40-43c5-a592-4e830ab62319
► This research investigates the question how the choice of scenarios and metrics influences the calibration of pedestrian simulation models. By calibrating a pedestrian model using…
(more)
▼ This research investigates the question how the choice of scenarios and metrics influences the calibration of pedestrian simulation models. By calibrating a pedestrian model using different combinations of scenarios and metrics and comparing the results it was concluded that it matters what scenarios and metrics are included during the calibration. The implication of this is that one should calibrate a pedestrian model based on its intended usage and that this should be leading in the choice of which scenarios and metrics to use.
Advisors/Committee Members: Duives, Dorine (mentor), Hoogendoorn, Serge (graduation committee), Knoop, Victor (graduation committee), Vuik, Kees (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Pedestrian simulation models; Calibration; Pedestrian; Multi-objective calibration
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APA ·
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MLA ·
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APA (6th Edition):
Sparnaaij, M. (. (2017). How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a0ce4bfc-ea40-43c5-a592-4e830ab62319
Chicago Manual of Style (16th Edition):
Sparnaaij, Martijn (author). “How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration.” 2017. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:a0ce4bfc-ea40-43c5-a592-4e830ab62319.
MLA Handbook (7th Edition):
Sparnaaij, Martijn (author). “How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration.” 2017. Web. 14 Apr 2021.
Vancouver:
Sparnaaij M(. How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:a0ce4bfc-ea40-43c5-a592-4e830ab62319.
Council of Science Editors:
Sparnaaij M(. How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:a0ce4bfc-ea40-43c5-a592-4e830ab62319
Delft University of Technology
6.
Echaniz Soldevila, Ignasi (author).
Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
► This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model…
(more)
▼ This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine learning techniques such as Gaussian process regression (GPR) to make predictions when there exist correlation between new input and the training dataset. On the other hand, it uses existent traditional parametric CF models to predict acceleration when no similar situations are found in the training dataset. This formulation guarantees a complete and continues model and deals with the challenges of new available types of dataset in the transport field: noisy and incomplete yet with large amount of data. Multiple models have been trained using the Optimal Velocity Model (OVM) as a basis parametric model and a dataset collected in the PPA project in Amsterdam by traffic radar detection in stop and go traffic conditions. The other main innovation of this thesis is that variables rarely included in any CF model such as the status and the distance of drivers to the traffic light are also analyzed. Results show that the GPR model formulation is robust as the model performs better than OVM alone according to the main KPI, but still collisions occasionally occur. Moreover, results depict that traffic light status actively influences driver behavior. Overall, this thesis gives insights into new powerful mathematical techniques that can be applied to describe longitudinal driving behavior or any modeled process.
Advisors/Committee Members: Hoogendoorn, Serge (mentor), Knoop, Victor (graduation committee), Steenbakkers, Jeroen (graduation committee), Alonso Mora, Javier (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Car-Following models; Longitudinal driver behavior; Machine Learning; Gausssian Process Regression; Non-parametric models; Urban signalized intersections; Traffic light
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APA (6th Edition):
Echaniz Soldevila, I. (. (2017). Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
Chicago Manual of Style (16th Edition):
Echaniz Soldevila, Ignasi (author). “Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.” 2017. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0.
MLA Handbook (7th Edition):
Echaniz Soldevila, Ignasi (author). “Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.” 2017. Web. 14 Apr 2021.
Vancouver:
Echaniz Soldevila I(. Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0.
Council of Science Editors:
Echaniz Soldevila I(. Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
Delft University of Technology
7.
Perez Lazaro, Cristino (author).
A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:0488b995-46eb-402d-9767-4e33410c7f87
► Flooding events not only cause physical damage to the road infrastructure and roadside systems, yet they potentially lead to significant traffic disruptions over the network…
(more)
▼ Flooding events not only cause physical damage to the road infrastructure and roadside systems, yet they potentially lead to significant traffic disruptions over the network which have a large impact on the sustainability of urban cities. According to several climate change scenarios, flooding events as a result of intense precipitation are expected to continue into the future becoming more frequent and severe. Therefore, it is essential that engineers design and manage transport networks as efficiently as possible under adverse weather conditions in order to build more resilient transport systems. To do so, professionals need to understand and analyse the impacts of flooding on transport networks. Modelling the impacts of flooding events on the road network is nowadays possible by the use of integrated simulation techniques that combine a flood simulation model with a microscopic traffic model. With these modelling techniques, the geographic location, severity and other impacts of flooding on the road network can be predicted and studied. Nevertheless, in order to perform a consistent traffic simulation under flooding conditions, a thorough analysis of driving behaviour under such conditions needs first to be accomplished, which is a research field that has been scarcely investigated thus far. Therefore, the main contribution of this thesis is to provide a systematic methodology for studying driving adaptation effects under flooding conditions at two complementary levels, namely microscopic and macroscopic level. This consists on a multilevel approach that uses microscopic traffic data of vehicles driving through flooding to extend the study to a macroscopic level. A video analysis procedure called the `The 3-Step Video Analysis Approach´ (3SVAA) is developed by the author to extract microscopic traffic parameters from video recording of vehicles driving under different flood depths. This methodology is implemented through an empirical study that analyses two videos of vehicles crossing waterlogged stretches part of the A94 and A93 major roads in Scotland (UK). First, the 3SVAA is introduced as a suitable data collection technique to extract microscopic traffic variables (i.e. vehicle's speed, time headways and spacing) from video recording of vehicles driving through flooding. More specifically, these parameters are obtained from the vehicle's trajectories in the space (m)-time(s) diagram, which is the main outcome of this video analysis approach. Subsequently, by applying a multilevel analysis, the study can be extended to a macroscopic level by correlating macroscopic variables (i.e. average speed, flow and density) with their microscopic counterparts through the fundamental relationship of traffic flow. This allows to estimate part of the fundamental diagrams of vehicles travelling under different flood depths, and therefore to study flood impacts on free flow speed and capacity.
Civil Engineering | Transport and Planning
Advisors/Committee Members: Hoogendoorn, Serge (mentor), Pel, Adam (mentor), Knoop, Victor (graduation committee), Delft University of Technology (degree granting institution).
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APA ·
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Export
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Manager
APA (6th Edition):
Perez Lazaro, C. (. (2020). A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:0488b995-46eb-402d-9767-4e33410c7f87
Chicago Manual of Style (16th Edition):
Perez Lazaro, Cristino (author). “A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions.” 2020. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:0488b995-46eb-402d-9767-4e33410c7f87.
MLA Handbook (7th Edition):
Perez Lazaro, Cristino (author). “A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions.” 2020. Web. 14 Apr 2021.
Vancouver:
Perez Lazaro C(. A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:0488b995-46eb-402d-9767-4e33410c7f87.
Council of Science Editors:
Perez Lazaro C(. A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:0488b995-46eb-402d-9767-4e33410c7f87
Delft University of Technology
8.
van Rest, Max (author).
A decentralized traffic control strategy for various levels of vehicle technology in an urban network.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:2f047997-1aff-42e3-9e2d-c8275f42c8d2
► There is a high probability that communication between vehicles in a traffic network and between vehicles and traffic controllers will be the next major wave…
(more)
▼ There is a high probability that communication between vehicles in a traffic network and between vehicles and traffic controllers will be the next major wave of technological innovation in traffic. The collection of data of communicating vehicles in traffic offers live information about the traffic conditions, which can be used to control traffic optimally. It is expected that in the coming years a new vehicle type will take part in traffic that is able to navigate through traffic without driver and communicates with traffic controllers to share its information and receive its optimal trajectory: the automated vehicle. The automated vehicle is different from the autonomous vehicle, which does not communicate with traffic controllers or other traffic. The traffic mixture consisting of conventional, connected and automated vehicles will change gradually over time. Designing a traffic control strategy that performs well for traffic consisting of different shares of these three types of vehicles and requires only a limited amount of computational power will be a main challenge in traffic control the coming years. This report proposes a traffic control strategy and assesses the influences of this strategy on the network wide traffic conditions using a traffic simulation. In this way, the research will provide insight in the effects of vehicle connectivity and automation on the network wide traffic conditions. Based on the live traffic information from the communicating vehicles in a network, traffic can be controlled from two sides: the traffic signal control and the automated vehicle trajectory control. The traffic control method proposed in this report works as follows: first, the traffic controller collects all the information of connected and automated vehicles in the network to update the vehicle set. Locations and speeds of connected and automated vehicles can be obtained directly. Automated vehicles also provide the traffic controller of information of the non-communicating vehicles in their surroundings, detected by their sensors. Then, the virtual departure time of each vehicle will be determined, which is the time at which the vehicle would depart not hindered by other traffic or traffic signal and can be calculated using the kinematic laws. Also the corresponding virtual departure speed is determined for each vehicle. Then, starting from the first vehicle on the link, the expected departure time will be calculated, based on the virtual departure time and the traffic signal state. The expected departure times and speeds of the other vehicles on the link will be based on their virtual departure time, the expected departure time of the vehicles in front of the vehicle and the signal state. The virtual and expected departure times and speeds are used for both the signal control and the trajectory control. This report presents a decentralized signal control to limit the computational power required in large traffic networks. This signal control is based on the original back-pressure algorithm,…
Advisors/Committee Members: Knoop, Victor (mentor), Hoogendoorn, Serge (mentor), De Schutter, B (mentor), Menéndez, M (mentor), Yang, K (mentor), Delft University of Technology (degree granting institution).
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APA (6th Edition):
van Rest, M. (. (2017). A decentralized traffic control strategy for various levels of vehicle technology in an urban network. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2f047997-1aff-42e3-9e2d-c8275f42c8d2
Chicago Manual of Style (16th Edition):
van Rest, Max (author). “A decentralized traffic control strategy for various levels of vehicle technology in an urban network.” 2017. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:2f047997-1aff-42e3-9e2d-c8275f42c8d2.
MLA Handbook (7th Edition):
van Rest, Max (author). “A decentralized traffic control strategy for various levels of vehicle technology in an urban network.” 2017. Web. 14 Apr 2021.
Vancouver:
van Rest M(. A decentralized traffic control strategy for various levels of vehicle technology in an urban network. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:2f047997-1aff-42e3-9e2d-c8275f42c8d2.
Council of Science Editors:
van Rest M(. A decentralized traffic control strategy for various levels of vehicle technology in an urban network. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:2f047997-1aff-42e3-9e2d-c8275f42c8d2
Delft University of Technology
9.
Klomp, Stefan (author).
Ramp metering: a microscopic control approach: A case study in the Netherlands.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:d756a787-9194-410c-9e4b-899915f06fc6
► In order to reduce congestion numbers on the highways, ramp metering can be used. The currently existing ramp metering control strategies are of a macroscopic…
(more)
▼ In order to reduce congestion numbers on the highways, ramp metering can be used. The currently existing ramp metering control strategies are of a macroscopic nature. This means that the average occupancy on the main lane or average flow values on the main lane determine the temporarily fixed cycle times for the traffic light located near the on-ramp to control the inflow from the on-ramp. In this thesis, it is investigated to what extent a microscopic approach to ramp metering would lead to less travel time delays. This approach shows a green light for the on-ramp vehicles when a gap in the main lane flow on the right lane has been detected instead of using the temporarily fixed cycle times. Computations on the location of the gap measurement loop detectors is required. Therefore, an acceleration distribution has been composed by means of an experiment as well. Concludingly, it was found that the proposed microscopic algorithm leads to additional travel time savings in the base case scenario compared to the currently used Rijkswaterstaat algorithm. Furthermore, adjustments to the developed microscopic control structure, such as a combined Rijkswaterstaat and microscopic algorithm, are proposed and it is recommended for further research to implement these adjustment and investigate their effect on the travel time delays. (PS. The paper was included at the end)
Advisors/Committee Members: Hoogendoorn, Serge (mentor), Knoop, Victor (mentor), Annema, Jan Anne (mentor), Taale, Henk (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: Ramp Metering; Acceleration; microscopic simulation; Travel time
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APA (6th Edition):
Klomp, S. (. (2020). Ramp metering: a microscopic control approach: A case study in the Netherlands. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:d756a787-9194-410c-9e4b-899915f06fc6
Chicago Manual of Style (16th Edition):
Klomp, Stefan (author). “Ramp metering: a microscopic control approach: A case study in the Netherlands.” 2020. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:d756a787-9194-410c-9e4b-899915f06fc6.
MLA Handbook (7th Edition):
Klomp, Stefan (author). “Ramp metering: a microscopic control approach: A case study in the Netherlands.” 2020. Web. 14 Apr 2021.
Vancouver:
Klomp S(. Ramp metering: a microscopic control approach: A case study in the Netherlands. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:d756a787-9194-410c-9e4b-899915f06fc6.
Council of Science Editors:
Klomp S(. Ramp metering: a microscopic control approach: A case study in the Netherlands. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:d756a787-9194-410c-9e4b-899915f06fc6
Delft University of Technology
10.
van der Tuin, Marieke (author).
Time-dependent earliest arrival routes with drivers legislation and preferences.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:82a5c26e-b9ad-492a-be30-6bf6eeb4a58c
► Freight transporters use software kits to plan the routes for their trucks. Breaks required by the European drivers legislation are nowadays planned as late as…
(more)
▼ Freight transporters use software kits to plan the routes for their trucks. Breaks required by the European drivers legislation are nowadays planned as late as possible. However, in some cases it is beneficial to plan these mandatory breaks during waiting time, such as truck driving bans. In this thesis this problem is addressed by computing earliest arrival routes with optimal break planning. The problem is formulated and optimally solved as a variation of Dijkstra's algorithm. The slow Dijkstra computation times of several seconds per route are improved using time-dependent contraction hierachies, which enable a query time of several milliseconds per route while the solution quality remains good. For two days of driving with a night rest in between, 17% of the analysed routes improves with optimal break scheduling, resulting in an average improvement of 5 hours of driving time. If the taking of breaks is additionally restricted to parking lots, the influence on the arrival time is on average increased with only 3 minutes. However, 5% of the considered routes are not feasible any more due to absence of truck parking lots along the planned route. Another 15% of the routes face large changes in roads that should be taken. The planned routes are all optimized for having the earliest arrival time. However, the freight company's objective also concerns fuel optimized driving or providing reliable arrival times to the customer. This thesis analyses such preferences and combines them into a route planner that incorporates results of stated and revealed choice experiments. It is shown that generally toll avoidance and congestion avoidance have most influence on the route choice and arrival time. On average differences are small, but for some routes this leads to changes of up to 15% in travel time. This thesis analyses the problem of route planning from two perspectives: algorithmic and behavioural. Several observations are made: algorithms are not suitable for obtaining the best route instead of the fastest, and the output of behavioural research cannot be used directly in practice to compute preferred routes. Effort could be made in future to integrate both research communities such that algorithms are able to reflect what a freight transporter actually wants.
Individual Double Degree: Software Technology - Transport, Infrastructure and Logistics
Advisors/Committee Members: de Weerdt, Mathijs (mentor), Chorus, Caspar (mentor), Knoop, Victor (mentor), Batz, Veit (mentor), van Cranenburgh, Sander (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: shortest path; trucks; drivers legislation; preferences; utility function; time-dependent road network; break planning
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APA (6th Edition):
van der Tuin, M. (. (2017). Time-dependent earliest arrival routes with drivers legislation and preferences. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:82a5c26e-b9ad-492a-be30-6bf6eeb4a58c
Chicago Manual of Style (16th Edition):
van der Tuin, Marieke (author). “Time-dependent earliest arrival routes with drivers legislation and preferences.” 2017. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:82a5c26e-b9ad-492a-be30-6bf6eeb4a58c.
MLA Handbook (7th Edition):
van der Tuin, Marieke (author). “Time-dependent earliest arrival routes with drivers legislation and preferences.” 2017. Web. 14 Apr 2021.
Vancouver:
van der Tuin M(. Time-dependent earliest arrival routes with drivers legislation and preferences. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:82a5c26e-b9ad-492a-be30-6bf6eeb4a58c.
Council of Science Editors:
van der Tuin M(. Time-dependent earliest arrival routes with drivers legislation and preferences. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:82a5c26e-b9ad-492a-be30-6bf6eeb4a58c
Delft University of Technology
11.
Wu, Ting Wei (author).
An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:01a09ace-7326-4b20-9c0d-3de5914c31cf
► Congestion in the landside air cargo supply chain occurs for different concurring reasons. Lack of coordination between freight forwarders, as example, might create truck congestion…
(more)
▼ Congestion in the landside air cargo supply chain occurs for different concurring reasons. Lack of coordination between freight forwarders, as example, might create truck congestion on the ground handler side. Horizontal collaboration between forwarders can be introduced and modeled via mathematical programming to mitigate congestion. Resulting models, which are generally variations of Pickup and Delivery Problem with Time Windows (PDPTW), can be solved to optimality only for small-size instances, and the computation is generally time consuming. We therefore propose a simulated annealing (SA)-embedded adaptive large neighborhood search (ALNS) heuristic to address truck route planning in the landside air cargo supply chain. In this work, we allow the search to visit infeasible time-dependent solutions. Accordingly, the objective function minimizes the feasible solution, where total travel distance cost, total travel time cost and unassigned shipments cost, and the time-dependent violation costs. Computational results are reported for 10 instances that were also solved with a mathematical programming approach. Results shows that the meta-heuristic method performs equally or better than the mathematical model given a computational limit for the latter of 2 hours. In addition, the meta-heuristic method was able to find a feasible solution for those cases where the exact model failed to identify a feasible solution.
Transport, Infrastructure and Logistics
Advisors/Committee Members: Tavasszy, Lóri (mentor), Bombelli, Alessandro (mentor), Atasoy, Bilge (mentor), Janić, Milan (graduation committee), Knoop, Victor (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Landside airport operations; Vehicle Routing; Simulated annealing; Time slack
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APA ·
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MLA ·
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Export
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Manager
APA (6th Edition):
Wu, T. W. (. (2019). An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:01a09ace-7326-4b20-9c0d-3de5914c31cf
Chicago Manual of Style (16th Edition):
Wu, Ting Wei (author). “An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo.” 2019. Masters Thesis, Delft University of Technology. Accessed April 14, 2021.
http://resolver.tudelft.nl/uuid:01a09ace-7326-4b20-9c0d-3de5914c31cf.
MLA Handbook (7th Edition):
Wu, Ting Wei (author). “An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo.” 2019. Web. 14 Apr 2021.
Vancouver:
Wu TW(. An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 14].
Available from: http://resolver.tudelft.nl/uuid:01a09ace-7326-4b20-9c0d-3de5914c31cf.
Council of Science Editors:
Wu TW(. An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:01a09ace-7326-4b20-9c0d-3de5914c31cf
. 
Open Access Theses and Dissertations