A Car-following Model Based on Discrete Choice Theory

Abstract

Abstract:

In the car-following model proposed in this paper, the acceleration and deceleration are incorporated into seven alternatives, and alternativespecific parameters are adopted to capture different attractiveness of each alternative. To avoid interferences from lanechanging behavior, the model is estimated and validated by trajectory data in the high occupancy vehicle (HOV) lane. From the estimation results, most estimated parameters are significantly different from zero at 95% confidence level, which indicates that the chosen variables and the classification of alternatives are effective and reasonable. In addition, according to the proposed model, the changing tendencies of choosing different alternatives at different speeds and gaps are completely consistent with common driving behaviors. The validation results show that, for the chosen alternatives, the percentages of predicted probabilities that are larger than 1/7 (the average probability of choosing each alternative) are more than 87% in the used data sets. From the shares of observations point of view, there are only minor differences between the observed and predicted results. Finally, this model is applied to simulate the 30minute single lane traffic conditions. Through simulation results, it can be found that the proposed model can accurately represent the real traffic conditions on the macroscopic level, while, on the microscopic level, there are some defects needed to be further improved.

Key words: intelligent transportation, traffic simulation, car-following model, discrete choice theory, HOV lane

摘要：

基于离散选择理论，提出了车辆跟驰模型.考虑七个选择肢中的加减速度，采用选择肢特定参数反映出不同选择肢的吸引程度.为了避免换道行为的干扰，利用HOV车道的车辆数据对模型进行标定和验证.结果显示，大多数的标定参数在95%的置信水平下都是较为显著的.此外，模型反映出的不同的车头间距及速度下的驾驶员对不同加减速度的选择趋势与日常驾驶行为完全吻合.验证结果表明，对于实际状况下被选择的选择肢，大于1/7 (每个选择肢的平均预测概率) 的预测概率的比例大于87%.从观测比例的角度看，实际观测值与模型的预测值之间差异并不显著.最后应用模型模拟30分钟的单车道交通状况.

关键词: 智能交通, 交通仿真, 跟驰模型, 离散选择理论, HOV 车道

CLC Number:

U268.6

ZHENG Jian, SUZUKI Koji, FUJITA Motohiro. A Car-following Model Based on Discrete Choice Theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2012, 12(5): 31-38.

郑建, 铃木弘司, 藤田素弘. 基于离散选择理论的跟驰模型[J]. 交通运输系统工程与信息, 2012, 12(5): 31-38.

Add to citation manager EndNote|Ris|BibTeX

URL: http://www.tseit.org.cn/EN/abstract/abstract18460.shtml

http://www.tseit.org.cn/EN/Y2012/V12/I5/31

References

[1]Reuschel A.Vehicle movements in a platoon[J].Oesterreichisches IngenieurArchir, 1950, 4: 193-215.
[2]Pipes L A. An operational analysis of traffic dynamics[J]. J. Appl. Phys, 1953, 24: 274-287.
[3]Gipps P G.A behavioural car following model for computer simulation[J]. Transportation Research Part B: Methodological, 1981, 15: 105-111. Doi: 10.1016/0191-2615(81)90037-0.
[4]Gunay B. Car following theory with lateral discomfort[J]. Transportation Research Part B: Methodological, 2007, 24: 722-735. Doi: 10.1016/j.trb.2007.02.002.
[5]Gazis D C,Herman R,Rothery R W.Nonlinear followtheleader models of traffic flow[J]. Operation Research, 1961, 9: 545-567. 
[6]Nagel K,Schreckenberg M. A cellular automaton model for freeway traffic[J]. Journal de Physique I, France, 1992, 2: 2221-2229.
[7]Bham G H, Benekohal R F. A high fidelity traffic simulation model based on cellular automata and carfollowing concepts[J]. Transportation Research Part C: Emerging Technologies, 2004, 12: 1-32. Doi: 10.1016/j.trc.2002.05.001. 
[8]Newell G F. A simplified carfollowing theory: a lower order model[J]. Transportation Research Part B: Methodological, 2002, 36: 195-205. Doi: 10.1016/S0191-2615(00)00044-8.
[9]Ahn S,Cassidy M J,Laval J. Verification of a simplified carfollowing theory[J]. Transportation Research Part B, 2004, 38: 431-440. Doi: 10.1016/S0191-2615(03)00074-2.
[10]Bando M, Hasebe K, Nakayama A, et al. Dynamical model of traffic congestion and numerical simulation[J]. Physical Review. E, 1995, 51: 1035-1041. Doi: 10.1103/PhysRevE.51.1035.
[11]Brackstone M, McDonald M. Carfollowing: a historical review[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 1999, 2:181-196. Doi: 10.1016/S1369-8478(00)00005-X. 
[12]Toledo T, Driving behaviour: Models and challenges[J]. Transport Reviews, 2007, 27: 65-84. Doi: 10.1080/01441640600823940. 
[13]Revelt D, Train K. Mixed logit with repeated choices: households’ choices of appliance efficiency level[J]. Review of Economics and Statistics, 1998, 80: 647-657. Doi: 10.1162/003465398557735.
[14]Train K. Discrete choice methods with simulation[M]. Cambridge University Press, 2003.
[15]BenAkiva M, Lerman S R. Discrete choice analysis: theory and application to travel demand[M]. The MIT press, 1985.
[16]Bhat C R, Gossen R. A mixed multinomial logit model analysis of weekend recreational episode type choice[J]. Transportation Research Part B: Methodological, 2004, 38: 767-787. Doi: 10.1016/j.trb.2003.10.003. 
[17]Dia H. An agentbased approach to modelling driver route choice behaviour under the influence of realtime information[J]. Transportation Research Part C: Emerging Technologies, 2002, 10: 331-349. Doi: 10.1016/S0968-090X(02)00025-6. 
[18]Toledo T. Koutsopoulos H N, BenAkiva M. Integrated driving behavior modeling[J]. Transportation Research Part C: Emerging Technologies, 2007, 15: 96-112. Doi: 10.1016/j.trc.2007.02.002.
[19]Choudhury C, Ramanujam V, BenAkiva M. Modeling acceleration decisions for freeway merges[J]. Transportation Research Record: Journal of the Transportation Research Board, 2009, 2124: 45-57. Doi: 10.3141/2124-05. 
[20]Minh C C, Sano K, Matsumoto S. Maneuvers of motorcycles in queues at signalized intersections[J]. Journal of Advanced Transportation, 2012,46: 39-53. Doi: 10.1002/atr.144.
[21]Antonini G, Bierlaire M, Weber M. Discrete choice models of pedestrian walking behavior[J]. Transportation Research Part B: Methodological, 2006, 40: 667 -687. Doi: 10.1016/j.trb.2005.09.006. 
[22]Robin T, Antonini G, Bierlaire M, et al. Specification, estimation and validation of a pedestrian walking behavior model[J]. Transportation Research Part B: Methodological, 2009, 43: 36-56. Doi: 10.1016/j.trb.2008.06.010. 
[23]Bradley R E, Antonio L A D, Sandifer C E. Euler at 300: an appreciation[M]. Mathematical Association of America, 2007.
[24]Cambridge Systematics Inc, NGSIM I80 data analysis report. Technical report, Prepared for FHWA[R]. U.S. Department of Transportation, 2005.
[25]Bierlaire M. Biogeme: A free package for the estimation of discrete choice models[C]. Proceedings of the 3rd Swiss Transportation Research Conference, Ascona, Switzerland., 2003.