Trajectory Planning of Lane Changing for Intelligent Vehicles

doi:10.3969/j.issn.1674-0696.2013.03.35

Abstract

Abstract: Two defects in the traditional lane changing models at present are pointed out. The first one is the situation in which the front wheel turning angle of 0 degree is ignored in the process of lane changing; the second one is that there are several problems，for example，high lateral acceleration，the jump occurrence，the non-continuous curvature. Comparing the traditional lane changing models with other lane changing models and combining the advantages of lateral acceleration which is 0 constantly with excellent characteristics of smoothness of sine functional lane changing path，a new lane changing model is proposed，which can solve the above mentioned defects which exist in traditional models. Comparing several lane changing models by means of MATLAB simulation test，the feasibility and advantages of proposed lane changing rules are verified.

Key words: lanechangingmodels, modelcomparison, modelperformancecomparison, MATLABsimulation

摘要： 针对目前传统换道模型存在的两个缺陷:一是忽略了换道过程中前轮转向角为0的情况;二是存在侧向加速度过大、产生跃变或轨迹曲率不连续等问题。通过对其它车辆换道模型的比较，并结合等速偏移轨迹函数其侧向加速度恒为0的优点和正弦函数换道轨迹具有优异平滑性的特点，提出了一种新的换道模型，该模型能够较好的解决已有的一些车道变换模型存在的不足。并用MATLAB仿真实验对几个换道模型进行比较，证实所提出的换道规则的可行性和优势。

关键词: 换道模型, 模型比较, 模型性能对比, MATLAB仿真

CLC Number:

U491

Yang Zhigang，Qi Zhijin，Huang Yan. Trajectory Planning of Lane Changing for Intelligent Vehicles[J]. Journal of Chongqing Jiaotong University(Natural Science), 2013, 32(3): 520-524.

杨志刚，戚志锦，黄燕. 智能车辆自由换道轨迹规划研究[J]. 重庆交通大学学报（自然科学版）, 2013, 32(3): 520-524.

References

[1]张秀彬,应俊豪. 汽车智能化技术原理[M]. 上海: 上海交通大学出版社,2 011.
Zhang Xiubin,Ying Junhao. Technology Principle of Automobile Intellectualization [M]. Shanghai: Shanghai Jiaotong University Press,2011.
[2]Hesse T,Sattel T. An Approach to Integrate Vehicle Dynamics in Motion Planning for Advanced Driver Assistance Systems[C]/ / Proceedings IEEE Intelligent Vehicles Symposium. Istanbul: IEEE,2007: 1240-1245.
[3]Wallis G,Chatziastros A,Bulthoff H. An unexpected role for visual feedback in vehicle steering control[J]. Current Biology,2002,12(4) : 295-299.
[4]Salvucci D D,Liu A. The time course of a lane change: driver control and eye-movement behavior[J]. Transportation Research Part F: Traffic Psychology and Behaviour,2002 (5) : 123-132.
[5]Van Winsum W,De Waard D,Brookhuis K A. Lane change manoeuvres and safety margine [J]. Transportation Research Part F:Traffic Psychology and Behaviour,1999,2 (3) : 139-149.
[6]杨建国,王金梅,李庆丰,等. 微观仿真中车辆换道的行为分析建模[J]. 公路交通科技, 2004,21(11) : 93-97.
Yang Jianguo,Wang Jinmei,Li Qingfeng,et al. Behavior analysis and modeling of lane change in traffic micro-simulation[J]. Journal of Highway and Transportation Research and Development,2004,21(11) : 93-97.
[7]孙振平. 自主驾驶汽车智能控制系统[D]. 长沙: 国防科学技术大学,2004.
Sun Zhenping. An Intelligent Control System for Autonomous Land Vehicle[D]. Changsha: National University of Defense Technology, 2004.
[8]游峰. 智能车辆自动换道与自动超车控制方法的研究[D]. 长春: 吉林大学,2005.
You Feng. Study on Autonomous Lane Changing and Autonomous Overtaking Control Method of Intelligent Vehicle[D]. Changchun: Jilin University,2005.
[9]李玮,高德芝,段建民. 智能车辆自由换道模型研究[J]. 公路交通科技,2010(2) : 119-123.
Li Wei,Gao Dezhi,Duan Jianmi. Research on lane change model for intelligent vehicles[J]. Journal of Highway and Transportation Research and Development,2010(2) : 119-123.

[1]	CHENG Qian1, ZHU Xiaoning2, LU Wansheng3. Travel Mode Choice Behavior Model of Intercity Passengers with Medium and Long Haul — A Case Study of High-Speed Railway and Air Transport [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(07): 39-45.
[2]	LIAN Qicai1, LI Han1, SHI Xiaolin1, YAN Zhangcun2. Autonomous Driving Choice Behavior Based on Panel Data Mixed Logit Model [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(07): 46-52.
[3]	QI Chunhua, WANG Xiaonan, ZHU Shoulin, LI Hangtian. Traffic Engineering Facility Information Threshold Based on Drivers Visual Area of Interest [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(07): 53-60.
[4]	LI Shengchao, WU Yue, BAI Xuemeng, WANG Yue, ZHANG Hai. Violation Alarm of Dangerous Goods Vehicle Based on TOPSIS and Gray Correlation [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(07): 61-66.
[5]	YANG Qingfang1,2,3, WANG Liqiang2, ZHENG Lili1,2,3, MENG Fanyun2. Traffic Emission and Fuel Consumption Model of Roundabout [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(07): 67-73.
[6]	BAI Han, ZHANG Kangyu, WANG Xiuguang, YAN Xiang, FENG Qilong. Traffic Capacity of Urban Intersection under the Conditions of Mixed Release of Traffic Flow [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(06): 12-20.
[7]	WANG Tao1, XIE Sihong1, LI Wenhao1,2, LI Wenyong1. Short-Term Traffic Flow Adaptive Prediction Model Based on FFOS-ELM and PF [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(06): 21-27.
[8]	WANG Yonggang, ZHANG Heng, PENG Zhipeng, ZHOU Wanqi. Analysis of Influencing Factors of Taxi Accidents Based on Structural Equation Model [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(06): 36-42.
[9]	ZHENG Yibin, CAI Hangpeng, LAI Weiwei, LIU Guanyu. Characteristics Analysis of Hubei Expressway Network Based on Complex Network [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(05): 31-37.
[10]	PAN Yiyong, WANG Song. Improved Weighted MOBIL Decision Model for Autonomous Lane Change in Networked Autopilot Environment [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(05): 46-52.
[11]	WU Wenjing, SUN Renchao, ZONG Fang, JIA Hongfei. Subjective Attitude Identification and Impact Analysis of Residents Low-Carbon Commuting Travel [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(05): 53-58.
[12]	LI Jun, DENG Yuxin. Cluster Analysis of Taxi Spatiotemporal Behavior Based on Non-negative Matrix Factorization [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(05): 59-65.
[13]	SHI Tianliang, WANG Wenguang. Information View and Particle Swarm Optimization Algorithm in Urban Traffic Congestion [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(04): 19-25.
[14]	HE Yulong1, 2, LIU Lei1,2, CHI Jiaxin1,2. Risk of Vehicle Lane Change Behavior on Highway [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(04): 26-33.
[15]	WANG Lu1, CHEN Xiaoxin2, LI Huaen1. Critical Speed of Vehicles Running Stably on Expressway in the Weather of Rain and Snow under Strong Wind [J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(04): 34-40.