Modelling lane changing behaviour in approaches to roadworks: Contrasting and combining driving simulator data with stated choice data

Abstract Drivers approaching lane closures due to roadworks tend to choose a target lane (plan) and seek suitable gaps to execute the plan (action). The plan is however latent or unobserved as the driver may or may not be able to move to the target lane due to the constraints imposed by the surrounding traffic. Hence, only the actions of the driver (as manifested by their final lane occupancies) are observed in the trajectory data. This paper analyses such mandatory lane changing behaviour in a roadworks environment in detail with data from a controlled driving simulator experiment and a simple stated preference survey with the same group of participants. While in the former drivers face similar constraints in implementing the plans as in the real world, in the simple stated choice survey the same drivers elicit their preferred target lanes without a need to put the plan into action. We contrast the findings from the two sources and also show correlations between the latent plan and stated target components in a latent class model. The results provide new insights into lane changing behaviour that may be useful for example for traffic management purposes. Furthermore, using stated choice data potentially reduces the cost of data collection for model development.

[1]  Stephane Hess,et al.  Modelling the effects of stress on gap-acceptance decisions combining data from driving simulator and physiological sensors , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.

[2]  J. G. Hunt,et al.  Modelling dual carriageway lane changing using neural networks , 1994 .

[3]  Praveen Edara,et al.  Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees , 2014, IEEE Transactions on Intelligent Transportation Systems.

[4]  Keqiang Li,et al.  Lane changing intention recognition based on speech recognition models , 2016 .

[5]  Charisma F. Choudhury,et al.  Transferability of Car-Following Models Between Driving Simulator and Field Traffic , 2017 .

[6]  Michael Markvan Evaluation of Interstate Highway Capacity for Short-Term Work Zone Lane Closures , 2005 .

[7]  Majid Sarvi,et al.  Lane changing models: a critical review , 2010 .

[8]  Rahul Sukthankar,et al.  Evolving an intelligent vehicle for tactical reasoning in traffic , 1997, Proceedings of International Conference on Robotics and Automation.

[9]  Dirk Helbing,et al.  General Lane-Changing Model MOBIL for Car-Following Models , 2007 .

[10]  Hesham Rakha,et al.  Game Theoretical Approach to Model Decision Making for Merging Maneuvers at Freeway On-Ramps , 2017 .

[11]  Hideyuki Kita,et al.  A merging–giveway interaction model of cars in a merging section: a game theoretic analysis , 1999 .

[12]  Ruey Long Cheu,et al.  A binary decision model for discretionary lane changing move based on fuzzy inference system , 2016 .

[13]  Xiao Qi,et al.  Simultaneous modeling of car-following and lane-changing behaviors using deep learning , 2019, Transportation Research Part C: Emerging Technologies.

[14]  Hyun Kim,et al.  Quantifying non-recurrent traffic congestion caused by freeway work zones using archived work zone and ITS traffic data , 2012 .

[15]  Zuduo Zheng,et al.  Recent developments and research needs in modeling lane changing , 2014 .

[16]  Moshe Ben-Akiva,et al.  Modelling driving decisions: a latent plan approach , 2013 .

[17]  Kerrie L. Schattler,et al.  Driving Simulator Validation for Nighttime Construction Work Zone Devices , 2007 .

[18]  Meng Wang,et al.  Game theoretic approach for predictive lane-changing and car-following control , 2015 .

[19]  Tomer Toledo,et al.  State Dependence in Lane-Changing Models , 2009 .

[20]  Hoe C Lee,et al.  The validity of driving simulator to measure on-road driving performance of older drivers , 2002 .

[21]  Alireza Talebpour,et al.  Weather and road geometry impact on longitudinal driving behavior: Exploratory analysis using an empirically supported acceleration modeling framework , 2016 .

[22]  Mazen Danaf,et al.  Modeling anger and aggressive driving behavior in a dynamic choice-latent variable model. , 2015, Accident; analysis and prevention.

[23]  Moshe Ben-Akiva,et al.  Lane-Changing Model with Explicit Target Lane Choice , 2005 .

[24]  P. G. Gipps,et al.  A MODEL FOR THE STRUCTURE OF LANE-CHANGING DECISIONS , 1986 .

[25]  Shlomo Bekhor,et al.  A passing gap acceptance model for two-lane rural highways , 2009 .

[26]  Mohamed Abdel-Aty,et al.  Validating a driving simulator using surrogate safety measures. , 2008, Accident; analysis and prevention.

[27]  Zuduo Zheng,et al.  A game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment , 2019, Transportation Research Part C: Emerging Technologies.

[28]  Haris N. Koutsopoulos,et al.  Modeling Integrated Lane-Changing Behavior , 2003 .

[29]  Francesco Bella Validation of a Driving Simulator for Work Zone Design , 2005 .

[30]  Moshe Ben-Akiva,et al.  Lane Selection Model for Urban Intersections , 2008 .

[31]  Reza Langari,et al.  A human-like game theory-based controller for automatic lane changing , 2018 .

[32]  Stephane Hess,et al.  Modelling the Effects of Stress on Gap-Acceptance Decisions in a Driving Simulator Experiment Using Physiological Sensors , 2018 .

[33]  Zuduo Zheng,et al.  Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study , 2018, Transportation Research Part C: Emerging Technologies.

[34]  Majid Sarvi,et al.  Modelling, calibrating, and validating car following and lane changing behaviour , 2016 .

[35]  Li Li,et al.  Pay to change lanes: A cooperative lane-changing strategy for connected/automated driving , 2019, Transportation Research Part C: Emerging Technologies.

[36]  Qiang Li,et al.  Observation-Based Lane-Vehicle Assignment Hierarchy: Microscopic Simulation on Urban Street Network , 2000 .

[37]  Moshe Ben-Akiva,et al.  Dynamic latent plan models , 2010 .

[38]  Keishi Tanimoto,et al.  A game theoretic analysis of merging-giveway interaction: a joint estimation model , 2002 .

[39]  Hani S. Mahmassani,et al.  Modeling Lane-Changing Behavior in a Connected Environment: A Game Theory Approach , 2015 .

[40]  Bin Jia,et al.  A data-driven lane-changing model based on deep learning , 2019, Transportation Research Part C: Emerging Technologies.

[41]  Klaus Bengler,et al.  Carrot and stick: A game-theoretic approach to motivate cooperative driving through social interaction , 2018 .