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When pedestrian and vehicle are in conflict, they will pass at a certain probability after they have made a simple judgment respectively. According to the actual situation of the conflict between pedestrian and vehicle, the concept of basic payoff, conflict loss, waiting loss and mutual avoiding loss are put forward. A game matrix of the conflict between pedestrian and vehicle is consequently established. Then the evolutionary analysis paradigm is introduced, and the dynamic model of the conflict evolution between pedestrian and vehicle is established. After that, the position and stability of the equilibrium point and the evolution mechanism of the system in different traffic situations are analyzed in detail. It is found that the relative size between conflict loss and waiting loss of pedestrian and vehicle are different, corresponding to different evolution directions of the system. The possible evolutionary directions include “vehicles first”, “pedestrians first”, “neither vehicles nor pedestrians goes first”, “vehicles and pedestrians do not yield to each other”. In addition, in this paper, we define the traffic concept of opportunity loss, and analyze the sensitivity of the system to the mutual avoiding loss and the opportunity loss of pedestrian and vehicle. It is found that the increasing of the mutually avoiding loss of pedestrian or vehicle has a positive effect on improving the probability of each passing conflict zone, but it has a negative effect on reducing the probability of each passing conflict zone. On the other hand, the effect of opportunity loss is just the opposite to the mutual avoiding loss. The dynamic model established in this paper can provide a theoretical basis for the macro control of the conflict evolution direction between pedestrian and vehicle. For instance, the current conflict situation between pedestrian and vehicle in a city is “vehicles first”. For promoting the traffic civilization, the transportation officials hope to change the current conflict situation to realize the “pedestrians first”. According to the model established in this paper, some parameters of the game matrix on the conflict between pedestrian and vehicle can be changed by formulating relevant highway traffic regulations to adjust the evolution direction of the conflict between pedestrian and vehicle.
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Keywords:
- evolutionary game theory /
- the conflict between pedestrian and vehicle /
- evolution mechanism /
- dynamic model
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[2] Mesterton-Gibbons M 1990 Math. Comput. Model. 13 9
[3] Chen O J, Ben-Akiva M E 1998 Transport. Res. Rec. 1617 179
[4] Michael. G. H. Bell. 2000 Transport. Res. B:Meth. 34 533
[5] Medda F 2007 Int. J. Proj. Manag. 25 213
[6] Agarwal R, Ergun Ö, Houghtalen L, Ozener O O 2009 Optimization and Logistics Challenges in the Enterprise (Germany:Springer) pp373-401
[7] Xie J J, Xue Y 2012 Acta Phys. Sin. 61 194502 (in Chinese) [谢积鉴, 薛郁 2012 物理学报 61 194502]
[8] Wang L, Ye S Q, Xie N G 2015 Acta Phys. Sin. 64 120201 (in Chinese) [王璐, 叶顺强, 谢能刚 2015 物理学报 64 120201]
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[10] Sun X Y, Jiang R, Hao Q Y, Wang B H 2010 Eur. Phys. Lett. 92 18003
[11] Perc M 2007 New J. Phys. 9 3
[12] Alvarez I, Poznyak A 2010 International Conference on Control, Automation and System Gyeonggi-do,Korea, October 27-30, 2010 p2164
[13] Li L J 2015 M. S. Thesis (Beijing:Beijing Jiaotong University) (in Chinese) [李林静 2015 硕士学位论文 (北京:北京交通大学)]
[14] Du W B, Cao X B, Hu M B, Wang W X 2009 Eur. Phys. Lett. 87 60004
[15] Xia H J, Li P P, Ke J H, Lin Z Q 2015 Chin. Phys. B 24 40203
[16] Hao D, Rong Z H, Zhou T 2014 Chin. Phys. B 23 78905
[17] Yang B, Fan M, Liu W Q, Chen X S 2017 Acta Phys. Sin. 66 196401 (in Chinese) [杨波, 范敏, 刘文奇, 陈晓松 2017 物理学报 66 196401]
[18] Wang J F, Guo J L, Liu H, Shen A Z 2017 Acta Phys. Sin. 66 180203 (in Chinese) [王俊芳, 郭进利, 刘瀚, 沈爱忠 2017 物理学报 66 180203]
[19] Chen C Q, Dai Q L, Han W C, Yang J Z 2017 Chin. Phys. Lett. 34 28901
[20] Dou S H, Gou J Q (in Chinese) [窦水海, 苟娟琼 2015 北京交通大学学报 14 66]
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[1] Wardrop J G Mesterton-Gibbons M Chen O J, Ben-Akiva M E 1998 Transport. Res. Rec. 1617 179
[2] Mesterton-Gibbons M 1990 Math. Comput. Model. 13 9
[3] Chen O J, Ben-Akiva M E 1998 Transport. Res. Rec. 1617 179
[4] Michael. G. H. Bell. 2000 Transport. Res. B:Meth. 34 533
[5] Medda F 2007 Int. J. Proj. Manag. 25 213
[6] Agarwal R, Ergun Ö, Houghtalen L, Ozener O O 2009 Optimization and Logistics Challenges in the Enterprise (Germany:Springer) pp373-401
[7] Xie J J, Xue Y 2012 Acta Phys. Sin. 61 194502 (in Chinese) [谢积鉴, 薛郁 2012 物理学报 61 194502]
[8] Wang L, Ye S Q, Xie N G 2015 Acta Phys. Sin. 64 120201 (in Chinese) [王璐, 叶顺强, 谢能刚 2015 物理学报 64 120201]
[9] Nakata M, Yamauchi A, Tanimoto J, Hagishima A 2010 Physica A 389 5353
[10] Sun X Y, Jiang R, Hao Q Y, Wang B H 2010 Eur. Phys. Lett. 92 18003
[11] Perc M 2007 New J. Phys. 9 3
[12] Alvarez I, Poznyak A 2010 International Conference on Control, Automation and System Gyeonggi-do,Korea, October 27-30, 2010 p2164
[13] Li L J 2015 M. S. Thesis (Beijing:Beijing Jiaotong University) (in Chinese) [李林静 2015 硕士学位论文 (北京:北京交通大学)]
[14] Du W B, Cao X B, Hu M B, Wang W X 2009 Eur. Phys. Lett. 87 60004
[15] Xia H J, Li P P, Ke J H, Lin Z Q 2015 Chin. Phys. B 24 40203
[16] Hao D, Rong Z H, Zhou T 2014 Chin. Phys. B 23 78905
[17] Yang B, Fan M, Liu W Q, Chen X S 2017 Acta Phys. Sin. 66 196401 (in Chinese) [杨波, 范敏, 刘文奇, 陈晓松 2017 物理学报 66 196401]
[18] Wang J F, Guo J L, Liu H, Shen A Z 2017 Acta Phys. Sin. 66 180203 (in Chinese) [王俊芳, 郭进利, 刘瀚, 沈爱忠 2017 物理学报 66 180203]
[19] Chen C Q, Dai Q L, Han W C, Yang J Z 2017 Chin. Phys. Lett. 34 28901
[20] Dou S H, Gou J Q (in Chinese) [窦水海, 苟娟琼 2015 北京交通大学学报 14 66]
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