Multi-lane Changing Model with Coupling Driving Intention and Inclination

  • Jiangfeng Wang Beijing Jiaotong University
  • Chang Gao Beijing Jiaotong University
  • Zhouyuan Zhu Beijing Jiaotong University
  • Xuedong Yan Beijing Jiaotong University
Keywords: lane changing model, driver intention, driving inclination, cellular automaton,

Abstract

Considering the impact of drivers’ psychology and behaviour, a multi-lane changing model coupling driving intention and inclination is proposed by introducing two quantitative indices of intention: strength of lane changing and risk factor. According to the psychological and behavioural characteristics of aggressive drivers and conservative drivers, the safety conditions for lane changing are designed respectively. The numerical simulations show that the proposed model is suitable for describing the traffic flow with frequent lane changing, which is more consistent with the driving behaviour of drivers in China. Compared with symmetric two-lane cellular automata (STCA) model, the proposed model can improve the average speed of vehicles by 1.04% under different traffic demands when aggressive drivers are in a higher proportion (the threshold of risk factor is 0.4). When the risk factor increases, the average speed shows the polarization phenomenon with the average speed slowing down in big traffic demand. The proposed model can reflect the relationship among density, flow, and speed, and the risk factor has a significant impact on density and flow.

Author Biographiesaaa replica rolex repwatches replica rolex watches for men replica iwc watch

Jiangfeng Wang, Beijing Jiaotong University
Beijing Jiaotong Univesity
Associate Professor
16/10/2009~Present

University of Washington
Visiting Scholar
03/11/2013~03/12/2014

Beijing Jiaotong Univesity
Associate Professor
16/10/2009~06/01/2012

BeijingUniversity of Aeronautics and Astronautics
PostDoc
01/07/2007~16/10/2009

BeijingUniversity of Aeronautics and Astronautics
01/09/2004~01/07/2007
Doctor´s Degree

Jilin University
01/09/2001~01/07/2004
Master´s Degree

Jilin University
01/09/1997~01/07/2001
Bachelor´s degree
Chang Gao, Beijing Jiaotong University

Beijing Jiaotong University
01/09/2014~present


Beijing Jiaotong University
01/09/2010~01/07/2014
Bachelor´s degree

Zhouyuan Zhu, Beijing Jiaotong University

Beijing Jiaotong University
01/09/2014~present


Changsha university of science & technology
01/09/2010~01/07/2014
Bachelor´s degree

Xuedong Yan, Beijing Jiaotong University
Beijing Jiaotong Univesity
Professor
16/12/2009~Present

References

Tang TQ, Wang YP, Yang XB. A multilane traffic flow model accounting for lane width, lane-changing and the number of lanes. Networks and Spatial Economics. 2014 Dec;14(3):465-483.

Wei LY, Wang ZL, Wu RH. Research and modeling of the lane-changing behaviour on the approach. Acta Physica Sinica. 2014 Oct;63(4):1-5.

Jetto K, Ez ZH, Benyoussef A. Investigation of merging and diverging cars on a multi-lane road using cellular automation model. Chinese Physics B. 2012 Jan;21(11):1-8.

Veljanovska K, Bombol KM, Maher T. Reinforcement learning technique in multiple motorway access control strategy design. Promet – Traffic & Transportation. 2010 Mar;22(2):117-123.

Pei YL, Wang YG, Zhang Y. Microscopic model of automobile lane-changing virtual desire trajectory by spline curve. Promet – Traffic & Transportation. 2010 Aug;22(3):203-208.

Hoseini SMS, Vaziri M. Modelling drivers' behaviour as a crash risk reduction process. Promet – Traffic & Transportation. 2008 Aug;20(3):139-146.

Hoseini SMS. Comparison of microscopic drivers' probabilistic lane-changing models with real traffic microscopic data. Promet – Traffic & Transportation. 2011 Mar;23(4):241-251.

Tian JF, Yuan ZZ, Jia B. Cellular automaton model in the fundamental diagram approach reproducing the synchronized outflow of wide moving jams. Physics Letters A. 2012 Sep;376(44):2781-2787.

Wang J, Ding JX, Shi Q. Lane-changing behaviour and its effect on energy dissipation using full velocity difference model. International Journal of Modern Physics C. 2016 Jun;27(2):1-14.

Li X, Sun JQ. Studies of vehicle lane-changing to avoid pedestrians with cellular automata. Physica A. 2015 Nov;438(1):251-271.

Zhao HT, Li JR, Nie C. Cellular automaton models for traffic flow considering opposite driving of an emergency vehicle. International Journal of Modern Physics C. 2015 Nov;26(7):1-12.

Feng SM, Li JY, Ding N. Traffic paradox on a road segment based on a cellular automaton: impact of lane-changing behaviour. Physica A. 2015 Jun;428(1):90-102.

Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic. Journal of Physique I France. 1992 Dec;2(12):2221-2229.

Errampalli M, Okushima M, Akiyama T. Development of the microscopic traffic simulation model with the fuzzy logic technique. Simulation-Transactions of the Society for Modeling and Simulation International. 2013 Jan;89(1):87-101.

Hua XD, Wang W, Wang H. A two-lane cellular automaton traffic flow model with the influence of driving psychology. Acta Physica Sinica. 2011 Feb;60(8):1-8.

Li X, Li XG, Xiao Y. Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model. Physica A. 2016 Jun;451(1):49-62.

Zhu HB, Zhang NX, Wu WJ. A modified two-lane traffic model considering drivers' personality. Physica A. 2015 Jun;428(1):359-367.

Chai C, Wong YD. Comparison of two simulation approaches to safety assessment: cellular automata and ssam. Journal of Transportation Engineering. 2015 Jan;141(6):1-12.

Guzman HA, Larraga ME, Alvarez-Icaza L. A two lanes cellular automata model for traffic flow considering realistic driving decisions. Journal of cellular automata. 2015;10(1-2):65-93.

Zhu HB, Zhang NX, Wu WJ. A modified two-lane traffic model considering drivers’ personality. Physica A Statistical Mechanics & Its Applications. 2015 Jun;428(1):359-367.

Luo Y, Turgut D, Boeloeni L. Modeling the strategic behaviour of drivers for multi-lane highway driving. Journal of Intelligent Transportation Systems. 2015 Feb;19(1):45-62.

Wang J, Cai BG, Liu J. A lane-changing behavioural preferences learning agent with its applications. Computer science and information systems. 2015 Apr;12(2):349-374.

Ji X, Wu J, Zhao Y, et al. A new robust control method for active front steering considering the intention of the driver. Journal of Automobile Engineering. 2015 Mar;229(4):518-531.

Bi L, Wang C, Yang X, et al. Detecting driver normal and emergency lane-changing intentions with queuing network-based driver models. International Journal of Human-Computer Interaction. 2015 Feb;31(2):139-145.

Hou Y, Edara P, Sun C. Situation assessment and decision making for lane change assistance using ensemble learning methods. Expert Systems with Applications. 2015 May;42(8):3875-3882.

Golbabaei F, Nejad FM, Noory AR. A microscopic analysis of speed deviation impacts on lane-changing behaviour. Transportation Planning and Technology. 2014 Jun;37(4):391-407.

Wang YM, Zhou LS, Yong-Bo LV. Cellular automaton traffic flow model considering flexible safe space for lane-changing. China Journal of Highway and Transport. 2008 May; 20(5):1159-1162.

Published
2017-04-25
How to Cite
1.
Wang J, Gao C, Zhu Z, Yan X. Multi-lane Changing Model with Coupling Driving Intention and Inclination. Promet [Internet]. 2017Apr.25 [cited 2024Dec.27];29(2):185-92. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/2085
Section
Articles