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Analysis of the Driver’s Breaking Response in the Safety Cut-in Scenario Based on Naturalistic Driving
ISSN: 0148-7191, e-ISSN: 2688-3627
Published November 04, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
For the personification of automotive vehicle function performance under common traffic scenarios, analysis of human driver behavior is necessary. Based on China Field Operational Test (China-FOT) database of China Natural Driving Study project, this paper studies the driver's response in the common cut-in scenario. A total of 266 cut-in cases are selected by manual interception of driving recorder video. The relevant traffic environment characteristics are also extracted from video, including light conditions, road conditions, scale and lateral position of cut-in vehicle, etc. Dynamic information is decoded form CAN, such as speed, acceleration and so on. Then image processing results, such as relative speed and distance of cut-in and subject vehicles, are calculated. Statistical results based on above information show the response type and distribution of human driver: the behavior of keeping lane is 96.24%, in which the ratio of braking response is 51.13%. According to this, we choose to further research the behavior of keeping lane, and analyze the influencing factors of braking response. Statistical methods, such as Chi-square test, Spearman correlation test, are used to verify the relativity between the factor introduced above and braking. And test results indicated traffic flow, cut-in vehicle type, relative speed and distance of two vehicles are significantly correlated with the driver's braking response. Finally, a logistic regression model of the braking response probability is established with the relevant parameter. The model shows the braking probability of human drivers, when faced with cut-in vehicle.
CitationZhang, J., Ma, Z., and Zhu, X., "Analysis of the Driver’s Breaking Response in the Safety Cut-in Scenario Based on Naturalistic Driving," SAE Technical Paper 2019-01-5053, 2019, https://doi.org/10.4271/2019-01-5053.
Data Sets - Support Documents
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- Liu , L. , Zhu , X. , Chen , M. , and Ma , Z.A. Systematic Scenario Typology for Automated Vehicles Based on China-FOT SAE Technical Paper 2018-01-0039 2018 10.4271/2018-01-0039
- Wang , W. , Zhao , D. , Xi , J. et al. Development and Evaluation of Two Learning-Based Personalized Driver Models for Car-following Behavior 2017 American Control Conference 2017
- Roman , S. , Cunda , O. , and Harald , W. Analysis and Adaptive Estimation of Human Car Following Behavior for Advanced Driver Assistance Systems SAE Technical Paper 2017-01-0044 2017 10.4271/2017-01-0044
- Liao , Y. , Wang , W. , Yu , J. et al. Brake Behavior Analysis in Low-Speed Vehicle Cut-In Condition The 16th Conference of Automotive Safety Technology 2013
- Kim , S. , Wang , J. , and Guenther , D. Analysis of Human Driver Behavior in Highway Cut-in Scenarios SAE Technical Paper 2017-01-1402 2017 10.4271/2017-01-1402
- Lin , M. , Xichan , Z. , and Liu , L. et al. Typical Traffic Risk Scenarios with Steering Space Related to Vehicles’ Conflicts in Same Direction Proceedings of the 12thInternational Forum of Automotive Traffic Safety 2015 130 139
- Holzmann , F. Adaptive Cooperation between Driver and ADAS Regensburg, Germany Springer 2008
- Mohamed , B. and Lutz , E. Detection of Critical Driving Situations for Naturalistic Driving Studies by Means of an Automated Process Journal of Intelligent Transportation and Urban Planning 2 1 11 21 2014
- Lin , L. , Zhu , X. , and Ma , Z. Driver Braking Behavior under Near-Crash Scenarios Int. J. Vehicle Safety.
- Chen , M. , Zhu , X. , Zhixiong , M. et al. Brake Response Time under Near-crash Cases with Cyclist 2016 IEEE Intelligent Vehicle Symposium
- Zhang , Y. , William , C. , and Yuen-Kwok , S. A Pattern-Recognition Approach for Driving Skill Characterization IEEE Transactions on Intelligent Transportation Systems 11 4 2010
- Wang , C. , Zhang , X. , Guo , K. et al. Application of Stochastic Model Predictive Control to Modeling Driver Steering Skills SAE Technical Paper 2016-01-0462 2016 10.4271/2016-01-0462