This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Analysis of Driver’s Behavior under Following-Go Scenario
Technical Paper
2019-01-1018
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
The driver’s behavior under following-go scenario, which has been involved in little research so far, is an important part of the driver's following behavior. Analysis of driver's behaviour under following-go scenario is important for improving the performance and the adaptability of ACC (Adaptive Cruise Control) systems in urban traffic environment. In this paper driver’s behavior under following-go scenario in real traffic is studied based on naturalistic driving data. Starting reaction time and starting distance from the target vehicle are used to evaluate driver’s starting timing under following-go scenario. Starting acceleration is used to evaluate the effect of driver’s acceleration operation under following-go scenario. The naturalistic driving data collected in china is screened and classified and the following-go scenario is obtained. The driver’s behaviour parameters under following-go scenario are extracted and the statistical characteristics are obtained. Influence factors are analyzed with univariate ANOVA (Analysis of Variance) and regression analysis. The results show that the starting reaction time and the starting distance from the target vehicle approximately obey the lognormal probability distribution and the starting acceleration approximately obeys the normal probability distribution. Environmental factors such as road type, target vehicle type and lighting condition don’t have obvious influence on the driver's behaviour under following-go scenario. The starting distance from the target vehicle is mainly affected by the stopping distance from the target vehicle and increases with it while the starting reaction time and the starting acceleration are mainly affected by the starting acceleration of the target vehicle. As the starting acceleration of the target vehicle increases, the starting reaction time is shorter and the starting acceleration is larger.
Recommended Content
Technical Paper | Interactive Information Delivery Navigation System |
Journal Article | Prediction of Preceding Driver Behavior for Fuel Efficient Cooperative Adaptive Cruise Control |
Ground Vehicle Standard | Adaptive Cruise Control (ACC) Operating Characteristics and User Interface |
Authors
Citation
Xia, L., Zhu, X., and Ma, Z., "Analysis of Driver’s Behavior under Following-Go Scenario," SAE Technical Paper 2019-01-1018, 2019, https://doi.org/10.4271/2019-01-1018.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 |
Also In
References
- Moon , S. and Yi , K. Human Driving Data-Based Design of a Vehicle Adaptive Cruise Control Algorithm Vehicle System Dynamics 46 8 661 690 2008
- Zheng , P. and Mcdonald , M. Manual vs. Adaptive Cruise Control - Can Driver’s Expectation Be Matched? Transportation Research Part C13 5 421 431 2005
- Wei , Y. , Rui , F. , Yong , M. , Yingshi , G. et al. A Study on Driver’s Vehicle-Following Model Based on High Speed Real Driving Data Automotive Engineering 6 679 685 2015
- Xiaofei , Z. , Zhaodu , L. , Guocheng , M. et al. Multi-Mode Switching Controller for Adaptive Cruise Control System Journal of Mechanical Engineering 48 10 96 102 2012
- Dianhai , W. and Sheng , J. Review and Outlook of Modeling of Car Following Behaviour China Journal of Highway and Transport 25 1 115 127 2012
- Mingyang , C. , Xichan , Z. , Zhixiong , M. , and Lin , L. Analysis of Driver’s Emergency Braking Behavior to Pedalcyclist in Real Traffic International Forum of Automotive Traffic Safety 2015
- Benmimoun , M. and Eckstein , L. Detection of Critical Driving Situations for Naturalistic Driving Studies by Means of an Automated Process Bowen Publishing 2014 11 21
- Administration, National Highway Traffic Safety Integrated Vehicle-Based Safety Systems: Light Vehicle Field Operational Test, Key Findings Report 1 Annals of Emergency Medicine 58 2 205 206 2011
- Qin , F. Research on Hazard Assessment Methods Based on Typical Hazardous Conditions Quality and Standardization 10 51 54 2014
- Victor , T. , Moeschlin , F. , Magnus H. et al.
- U.S. Department of Transportation National Highway Traffic Safety Administration The 100-Car Naturalistic Driving Study: Phase II - Results of the 100-Car Field Experiment 2006
- U.S. Department of Transportation National Highway Traffic Safety Administration Evaluation of Adaptive Cruise Control Interface Requirements on the National Advanced Driving Simulator 2015
- Lin , L. , Xi , Z. , Ying , L. et al. Typical Traffic Risk Scenarios Related to Pedal Cyclists Journal of Tongji University (Natural Science) 42 7 1082 1087 July 2014
- Zhiwei , F. , Xuehan , M. , Lan , X. , Xichan , Z. et al. Analysis of Driver Initial Brake Time Under Risk Cut-in Scenarios International Forum of Automotive Traffic Safety 2017
- Zhifa , Y. and Jingwei , Z. Multivariate Statistical Analysis Science Press 2002 2010
- Xiaoqun , H. Application of Multivariate Statistical Analysis China Statistics Press 2010 2006
- Chuanhua , Y. SPSS and Statistical Analysis Electronic Industry Press 2007 2002