+publisher:"Delft University of Technology" +contributor:("Wang, Meng")

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

Record Details Similar Records Cite « Share

❌

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

APA (6^th 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 (16^th 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 March 05, 2021. http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8.

MLA Handbook (7^th Edition):

Blauw, Mathieu (author). “Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.” 2019. Web. 05 Mar 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 Mar 05]. 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. Pizzigoni, Edoardo (author). ACC target performance setting via NDS big data analysis.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:da09fb40-8142-4545-8440-2c91ef7434ff

► Advanced Driving Assistance Systems (ADAS) technologies like Adaptive Cruise Control (ACC) are becoming the normality for many users, and many major car manufacturers are introducing… (more)

▼ Advanced Driving Assistance Systems (ADAS) technologies like Adaptive Cruise Control (ACC) are becoming the normality for many users, and many major car manufacturers are introducing SAE level 2 and 3 automation systems into the market. The main advantage of Automated Vehicles (AV) will be the significant decrease in road accidents and casualties. However, a significant shift from conventional to automated vehicles must occur before it can have a positive impact on society. If the behaviour of the vehicle is not perceived as natural, the user will most likely not activate the ADAS features again. During this study a naturalistic dataset is used to investigate the driver behaviour, in the hope of bringing the current ACC logic to a more human-like behaviour that will feel more natural to the driver. The research question summarizes the final objective of this study: How can Naturalistic Driving Study (NDS) datasets be used in target performance setting for ACC systems? This study will answer the research question by studying human behaviour in the scene of following an accelerating vehicle. The main body of this thesis is divided in three chapters, one for each step of the research. First the information about the used datasets are provided together with the methodologies used to extract the relevant time-series data. Secondly driver behaviour models are created in order to mathematically characterize human behaviour. The strength of the created models is their ability to represent the full range of driver behaviour in terms of driving style. The aggressiveness parameter of the model can be easily adjusted to represent different percentiles of driver behaviour. This allows for a quick and effective tuning process: by changing a single parameter the driving style of the model can be fully modified. Finally, the driver behaviour models are implemented into a simulation environment. The models are simulated against an existing ACC logic in order to assess the difference in behaviour. The comparison highlighted two conclusions: first, the ACC logic behaves in a very conservative way compared to driver behaviour, especially when starting from standstill. Secondly, the kept by the ACC logic was not consistent throughout the speed range. This variation of the logic's driving style could result even more bothersome to the customer than its general conservative behaviour. The string stability of the driver behaviour models was also assessed. Although the proposed logic proved more stable than the regular ACC logic, it still cannot reach full string stability. Hopefully, with the method developed in this study, the process of getting accustomed to this new technology will become easier for the customer. Thanks to the driver behaviour models the motion of the vehicle can feel familiar and predictable, with the controller becoming part of the Human Machine Interface (HMI). As the customer gets more familiar with this technology his expectation will also increase and change, especially as the levels of automation start to… Advisors/Committee Members: Happee, Riender (mentor), Wang, Meng (graduation committee), Stapel, Jork (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: ACC; ADAS; driver modeling; driver behaviour; Automated vehicles; car following; naturalistic driving study

Record Details Similar Records Cite « Share

❌

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

APA (6^th Edition):

Pizzigoni, E. (. (2019). ACC target performance setting via NDS big data analysis. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:da09fb40-8142-4545-8440-2c91ef7434ff

Chicago Manual of Style (16^th Edition):

Pizzigoni, Edoardo (author). “ACC target performance setting via NDS big data analysis.” 2019. Masters Thesis, Delft University of Technology. Accessed March 05, 2021. http://resolver.tudelft.nl/uuid:da09fb40-8142-4545-8440-2c91ef7434ff.

MLA Handbook (7^th Edition):

Pizzigoni, Edoardo (author). “ACC target performance setting via NDS big data analysis.” 2019. Web. 05 Mar 2021.

Vancouver:

Pizzigoni E(. ACC target performance setting via NDS big data analysis. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 05]. Available from: http://resolver.tudelft.nl/uuid:da09fb40-8142-4545-8440-2c91ef7434ff.

Council of Science Editors:

Pizzigoni E(. ACC target performance setting via NDS big data analysis. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:da09fb40-8142-4545-8440-2c91ef7434ff

Delft University of Technology

3. Glastra, Thom (author). Enabling GLOSA for on-street operating traffic light controllers.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2

► The bottleneck of the maximum road volume in urban areas is the maximum capacity of the traffic flow on the intersection, which is coordinated with… (more)

▼ The bottleneck of the maximum road volume in urban areas is the maximum capacity of the traffic flow on the intersection, which is coordinated with Traffic Light Controllers (TLCs). A promising method to decrease the number of stops are Green Light Optimal Speed Advice (GLOSA) systems. These systems will give a speed advice to arriving vehicles based on the schedule of TLCs, which needs to be known and fixed. However, most on-street controllers change their schedule until the last moment to maximize the performance. In this thesis a predictive controller is developed that is suitable for real-world application based on DIRECTOR; a state-of-the-art predictive controller. A prediction model is used to predict future arrivals based on available measurements to optimize and fix the schedule in advance. The proposed controller can enable GLOSA systems to improve performance. Appropriate pre-processing steps are implemented and the optimal input features are selected to improve the performance of a Long Short-Term Memory (LSTM) network to predict future arrivals. All detection data is stationary over time by using the differenced series. The time data is divided into workdays and weekend days to create a binary input and undesirable jumps during midnight are removed. The combination of stop line detectors, queue detectors, arrival detectors and signal states of the controlled and preceding intersections as input maximized the performance. The prediction horizon of the proposed prediction model could be extended. The Normalized Root Mean Square Error (NRMSE) decreased with 17% compared to DIRECTOR. The proposed controller extends the control horizon and uses multiple prediction models to predict the arrivals for the entire control horizon. The proposed controller outperforms DIRECTOR with 14 - 38% reduction in terms of vehicle delay and 5 - 32% reduction in terms of numbers of stops based on the scheduling mode. The GLOSA system is an add-on of the controller and is able to operate without the GLOSA system. The control horizon of the proposed controller always has a fixed length which is needed to determine the time until green. The implemented GLOSA system will determine the optimal speed based on the time until green and the expected delay due to the surrounding vehicles. The proposed controller is a cloud controlled application. Therefore, it is possible to adjust the setup (i.e. scheduling modes) during the day. Enabling GLOSA all day except during rush hours will lead to 3 - 4% reduction in terms of vehicle delay and 29 - 32% reduction in terms of numbers of stops based on the scheduling mode. This setup of the proposed controller is also competitive with the hand-crafted non-predictive on-street controller. Compared with this controller, the proposed controller will reduce the number of stops with 26% at the cost of 16% increase in vehicle delay. The proposed controller is designed conform the safety standards used on-street. Permission is received from the provincial government to do on-street pilots with the… Advisors/Committee Members: Gavrila, Dariu (graduation committee), Kooij, Julian (mentor), Wang, Meng (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Traffic flow; Traffic light controller; TLC; Predictive controller; Prediction model; Decentralized control; Model predictive control; green light optimal speed advise; GLOSA

Record Details Similar Records Cite « Share

❌

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

APA (6^th Edition):

Glastra, T. (. (2020). Enabling GLOSA for on-street operating traffic light controllers. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2

Chicago Manual of Style (16^th Edition):

Glastra, Thom (author). “Enabling GLOSA for on-street operating traffic light controllers.” 2020. Masters Thesis, Delft University of Technology. Accessed March 05, 2021. http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2.

MLA Handbook (7^th Edition):

Glastra, Thom (author). “Enabling GLOSA for on-street operating traffic light controllers.” 2020. Web. 05 Mar 2021.

Vancouver:

Glastra T(. Enabling GLOSA for on-street operating traffic light controllers. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 05]. Available from: http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2.

Council of Science Editors:

Glastra T(. Enabling GLOSA for on-street operating traffic light controllers. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:63a21739-a200-4375-8f19-641352e504b2

Delft University of Technology

4. Staiger, Julian (author). Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:37bf4dde-36e7-4d28-8dcd-6f15f6289523

► Significant developments in the field of Advanced Driver Assistance Systems (A prove traffic management and prediction, driver comfort, and vehicle safety. However, a detailed knowledge… (more)

Record Details Similar Records Cite « Share

❌

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

APA (6^th Edition):

Staiger, J. (. (2020). Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:37bf4dde-36e7-4d28-8dcd-6f15f6289523

Chicago Manual of Style (16^th Edition):

Staiger, Julian (author). “Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data.” 2020. Masters Thesis, Delft University of Technology. Accessed March 05, 2021. http://resolver.tudelft.nl/uuid:37bf4dde-36e7-4d28-8dcd-6f15f6289523.

MLA Handbook (7^th Edition):

Staiger, Julian (author). “Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data.” 2020. Web. 05 Mar 2021.

Vancouver:

Staiger J(. Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 05]. Available from: http://resolver.tudelft.nl/uuid:37bf4dde-36e7-4d28-8dcd-6f15f6289523.

Council of Science Editors:

Staiger J(. Vehicle dynamics in automated traffic: Evaluation of the vehicle dynamics for longitudinal and lateral movement using real driving test data. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:37bf4dde-36e7-4d28-8dcd-6f15f6289523

		in
And / Or
		in
And / Or
		in
And / Or
		in

Open Access Theses and Dissertations