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Modelling Driving Behaviour at Motorway Weaving Sections

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Modelling Driving Behaviour at Motorway Weaving Sections MODELLING DRIVING BEHAVIOUR AT MOTORWAY WEAVING SECTIONS Andyka Kusuma Submitted in accordance with the requirements for the degree of Philosophy of Doctoral Degree The University of Leeds Institute for Transport Studies September 2015 -ii- The candidate confirms that the work submitted is his own and that appropriate credit has been given where reference has been made to the work of others. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. © 2015. The University of Leeds and Andyka Kusuma -iii- Acknowledgement Completing a PhD is a very lonesome endeavour for the last four years, I realise this work could not be succeeding without advices, supports, and helps from copious people that I desire to say my thanks. First of all, I would like to say my special thanks to my supervisors; Dr Ronghui Liu, Dr Charisma Choudhury, and Mr Francis Montgomery for their valuable guidance, support and encouragement along this process Many thanks to The Directorate General for Higher Education, Ministry of Education and Culture, Republic of Indonesia and for the opportunity and financial support for me to pursuing this PhD degree. Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia for their assistance in this PhD research. To Dr Tzu-Chang Lee for his assistance and permission to use the trajectory extractor application. Dr Arief Gusnanto, for the discussion and sharing his experience doing a PhD. A PhD is more than doing a research and I would like to thank my fellow in ITS who the process enjoyable. Special thanks for my Indonesian fellow in ITS, Munajat Tri Nugroho, Fahmi, Probo Hardini, Aswin Siregar, and my colleague Irfan Rifai for their continuous supports, discussions and strengthens during this process. Last but not least, I would like to say my special thanks to my family, especially my lovely wife Lola Arieza for her passion, invaluable supports to continue working when everything is impossible. My parents Mr. Dede K.E Idris and Mrs. Hedijanti Joenoes, my brother and sister Fikar R. Kusuma, Nevine R. Kusuma for their inspiration and for keeping me during their doa’ for this journey. -v- Abstract This research focuses on the understanding of driving behaviour in motorway weaving sections, particularly the lane-changing and acceleration behaviours which are significant factors in characterising the operations of weaving section. Drivers’ lane-changing behaviour is a series interdependent decisions according to a particular lane-changing plan (latent). An intensive interaction with neighbouring traffic increases the lane-changing complexity in weaving section. The drivers’ choices in weaving section can be significantly affected by the actions of the neighbourhood drivers and moving as a group (i.e. platoon and weaving). Furthermore, the intensity of lane-changing has significant impact on the acceleration behaviour in weaving section traffic which may response differently from the stimulus (i.e. leave a space for pre- emptive lane-changing). An analysis of detailed trajectory data collected from moderately congested traffic flow of a typical weaving section in the M1 motorway, UK (J 42-43). The data reveals that a substantial proportion (23.4%) of the lane-changing at weaving section exhibits such group behaviour (i.e. platoon and weaving). The current study extends the state-of-the- art latent plan lane-changing model which account explicitly the various mechanisms. The model constitutes that the driver is most likely performing a pre-emptive lane- changing at the beginning of weaving section and moving toward kerbside (left direction). Moreover, the driver aggresiveness affects significantly on weaving and least on platoon lane-changing. The proposed acceleration model allows the car-following behaviour (acceleration/deceleration) corresponds with both stimulus (positive/negative relative speed). The model is conditional on gap threshold and reaction time distributions (probabilistic model) capturing the heterogeneity across drivers. most of traffic response differently from the stimulus condtions where 43.5% falls in deceleration with positive relative speed. All the parameters in each model are estimated jointly using Maximum Likelihood Estimation technique and reveal significant differences. The results show promising contribution towards improving the fidelity of microscopic traffic performance analysis. -vii- Table of Contents Acknowledgement ....................................................................................................... iii Abstract ......................................................................................................................... v Table of Contents ....................................................................................................... vii List of Figures ............................................................................................................... v List of Tables ............................................................................................................... ix Declaration ................................................................................................................... xi List of Abbreviations and Notations ....................................................................... xiii Chapter 1 Introduction .......................................................................................... 1 Background .............................................................................................................. 1 Research Objectives ................................................................................................ 4 Research Methodology ............................................................................................ 5 Thesis Outline .......................................................................................................... 7 Chapter 2 Literature Review ................................................................................ 9 Weaving Section ...................................................................................................... 9 Geometry ............................................................................................................... 9 Capacity analysis ................................................................................................. 15 Traffic characteristics .......................................................................................... 18 Lane Changing Models ......................................................................................... 22 Rule-based lane changing models ....................................................................... 22 Game theory models ........................................................................................... 28 Discrete choice models ....................................................................................... 31 Gap acceptance models ....................................................................................... 42 Car Following Models ........................................................................................... 46 Car Following Models ........................................................................................ 46 Extended car-following models .......................................................................... 54 Driver reaction time ............................................................................................ 57 Summary and Limitations of Existing Models ................................................... 59 Summary ............................................................................................................. 59 Limitations of existing models ............................................................................ 59 Chapter 3 Modelling Framework of Decision Making- Process ...................... 61 Planning Behaviour Models ................................................................................. 61 Latent Plan Models ............................................................................................... 63 Latent Plan Modelling Framework ..................................................................... 65 Probability of observed trajectory ....................................................................... 67 -viii- Latent plan modelling specification .................................................................... 69 A comparison of latent plan with other discrete choice models ........................ 70 Summary ................................................................................................................ 73 Chapter 4 Lane Changing Model ....................................................................... 75 Background ............................................................................................................ 75 Lane Changing Mechanisms in Weaving Section .............................................. 77 Solo lane changing mechanism ........................................................................... 78 Platoon lane changing mechanism ...................................................................... 78 Weaving lane changing mechanism .................................................................... 79 Lane Changing Modelling Framework ............................................................... 79 Target lane modelling ........................................................................................
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