Fuzzy Control Car-Following Model with the Consideration of Driving Style

doi:10.11908/j.issn.0253-374x.19319

Home > Archive>Volume 48, Issue 5, 2020 >694-701. DOI:10.11908/j.issn.0253-374x.19319

Fuzzy Control Car-Following Model with the Consideration of Driving Style
DOI:
                        10.11908/j.issn.0253-374x.19319
                    
CSTR:
                        [cstr]
                    
Author:
                        WU Bing1WU Bing
Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
LUO Xue1LUO Xue
Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
LI Linbo1LI Linbo
Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site

                    
Affiliation:Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201084, China
Clc Number:U491.1
Fund Project:

Article

Figures

Metrics

Reference [25]

Related [20]

Cited by

Materials

Comments

Abstract:

In view of the traditional fuzzy control car-following model, the difference of driving style was less considered, and the effective verification of real data was lack. Based on the fuzzy control theory, the dynamic driving decision-making process adopted by the driver in the following process was simulated, and different driving styles were considered. Based on the analysis of the natural driving data, different driving styles were analyzed by use of the measured data, and the desired time headway parameters of each driving style were obtained. On this basis, the distance error and speed difference between the front and rear cars were used as independent variables, and the fuzzy control rules were established. The numerical analysis results show that the proposed model fits well with natural driving data.

Key words:car-following model;driving style;fuzzy control;desired time headway

Reference

[1] 赵淑芝，张枭雄，贾洪飞，等.利用五轮仪实验数据建立车辆跟驰模型 [J]. 公路交通科技, 2003, 20(1): 132.

[2] CHAKROBORTY P, KIKUCHI S. Evaluation of the general motors based car-following models and a proposed fuzzy inference model [J]. Transportation Research Part C (Emerging Technologies), 1999, 7(4): 209.

[3] KHODAYARI A, KAZEMI R, GHAFFARI A, et al. Design of an improved fuzzy logic based model for prediction of car following behavior[C]/

[4] MAR J, LIN F J. An ANFIS controller for the car-following collision prevention system [J]. IEEE Transactions on Vehicular Technology, 2001, 50(4): 1106.

[5] MAR J, LIN F J, LIN H T, et al. The car following collision prevention controller based on the fuzzy basis function network [J]. Fuzzy Sets and Systems, 2003, 139(1): 167.

[6] MAR J, LIN H T. The car-following and lane-changing collision prevention system based on the cascaded fuzzy inference system [J]. IEEE Transactions on Vehicular Technology, 2005, 54(3): 910.

[7] XIONG Q P. Development of membership degree functions of the car-following models based on fuzzy logic[C]// International Conference on Intelligent Computation Technology & Automation. [S.l.]: IEEE, 2009: 697-699.

[8] 王文清，王武宏，钟永刚，等.基于模糊推理的跟驰安全距离控制算法及实现 [J].交通运输工程学报, 2003, 3(1): 72.

[9] 邱小平，孙若晓，于丹.改进的基于模糊推理的车辆跟驰行为分析方法 [J]. 华南理工大学学报（自然科学版）, 2015, 43(8): 135.

[10] TANG T Q, LI C Y, HUANG H J. A new car-following model with the consideration of the driver’s forecast effect [J]. Physics Letters A, 2010, 374(38): 3951.

[11] PENG G H. A study of wide moving jams in a new lattice model of traffic flow with the consideration of the driver anticipation effect and numerical simulation [J]. Physica A Statistical Mechanics & Its Applications, 2012, 391(23): 5971.

[12] TANG T Q, HUANG H J, SHANG H Y. A new macro model for traffic flow with the consideration of the driver’s forecast effect [J]. Physics Letters A, 2010, 374(15): 1668.

[13] TREIBER M, KESTING A, HELBING D. Delays, inaccuracies and anticipation in microscopic traffic models [J]. Physica A, 2006, 360(1): 71.

[14] 钟益萍，张存保，石永辉.考虑驾驶员行为特性的模糊推理跟驰模型改进研究 [J]. 交通信息与安全, 2010, 28(3):17.

[15] 王雪松，朱美新，邢祎伦.基于自然驾驶数据的避撞预警对跟车行为影响 [J]. 同济大学学报(自然科学版), 2016, 44(7): 1045.

[16] GILL S A, RUDDLE R A. Using virtual humans to solve real ergonomic design problems[C]// IEEE International Conference on Simulation. York, UK: IEEE, 1998: 223-229.

[17] HANSON L. Computerized tools for human simulation and ergonomic evaluation of car interiors [J]. Human Factors & Ergonomics Society Annual Meeting Proceedings, 2000, 44(38): 836.

[18] SANTOS J, SARRIEGI J M, NICOLáS S, et al. Using ergonomic software in non-repetitive manufacturing processes: a case study [J]. International Journal of Industrial Ergonomics, 2007, 37(3): 267.

[19] AL-GHAMDI A S. Analysis of time headways on urban roads [J]. Civil Engineering Systems, 2002, 19(2): 169.

[20] 孟凡兴，张良，张伟.驾驶员车头时距研究[J].工业工程与管理, 2013, 18(2):131.

[21] 吴超仲，严新平，马晓风.考虑驾驶员性格特性的跟驰模型 [J]. 交通运输工程与信息学报, 2007, 5(4): 18.

[22] ZHANG Y, NI P, LI M, et al. A new car-following model considering driving characteristics and preceding vehicle’s acceleration [J]. Journal of Advanced Transportation, 2017, 2017: 1.

[23] 杨纶标，高英仪.模糊数学原理及应用[M].5版.2011.

[24] YANG H H, PENG H, GORDON T J, et al. Development and validation of an errorable car-following driver model[C]// American Control Conference. [S.l.]: IEEE, 2008: 3927-3932.

[25] 孙赫.基于模糊控制的车辆跟驰模型研究[D]. 北京: 北京交通大学, 2013.

Get Citation

WU Bing, LUO Xue, LI Linbo. Fuzzy Control Car-Following Model with the Consideration of Driving Style[J].同济大学学报(自然科学版),2020,48(5):694~701

Copy

Article Metrics

Abstract:
PDF:
HTML:
Cited by:

History

Received:August 06,2019
Revised:
Adopted:
Online: June 05,2020
Published:

Get Citation

Share

Article Metrics

History

Article QR Code