Influence of Lane Change on Driving Behaviours in Traffic Oscillations Based on Vehicle Trajectory Data from Aerial Videos
- 19 Downloads
Many Car-Following (CF) models and analysis methods have been applied to many practical and theoretical studies, relatively, only a few in Lane-changing (LC) development. This research aims to fill the gap by proposing a new tracking lane-changing trajectory and theoretical method to study date. In this paper, we employed Unmanned Aerial Vehicle (UAV) to record the moving data of the vehicles in Nanjing, China. Based on existing research methods, we study the influence of lane-changing (LC), a comprehensive data analysis indicates that drivers show similarity of their lane-changing habit but with variety, and different drivers’ lane-change trajectory data show different lane-change “personality” including aggressive and timid characteristic. By analyzing the data and comparing it with the related research based on NGSIM, we can obtain the corresponding changes in driver characteristics: (i) A timid (aggressive) driver tends to become less timid (aggressive) or convert to slightly aggressive (timid) after experiencing LC; (ii) These changes were systematic and suggest that drivers tend to become more aggressive (characterized by decreasing average time headway after LC) perhaps to prevent another LC occurring. The research conclusions of this paper are similar to those of the existing research results, but also have some innovation points, so it can be proved that the data extraction method and the theoretical analysis method in this study are reasonable and innovative. Therefore, what we found in this paper are significantly helpful to study the characteristics of Chinese drivers, and which have enlightening effect to intelligent transportation system (ITS), unmanned driving and other new technology application in traffic field.
KeywordsLane-changing analysis Traffic flow Trajectory extraction Unmanned aerial vehicle application
The authors appreciate the funding support from the Innovation Project of Guangxi Graduate Education (YCSW2018146), the National Natural Science Foundation of China (51508122, 51478113, 51508094), Guangxi science and technology projects (1524800210, Guike-AB16380280, Guike-AB17292087), the Natural Science Foundation of Guangxi (Grant No. 2015GXNSFBA139216), the Natural Science Foundation of Jiangsu (BK20150612), Shanghai Rising-Star Program (16QB1403000), Shanghai Urban-Rural Development Transportation Talents Special Funds, as well as The Scientific research project of Chinese National Ministry of Housing and Urban-Rural Construction (2017-K2-009). Scientific Research Project of Nanning University (2018XJ39).
- 6.Nagel K, Schreckenber M (1992) A cellular automaton model for freeway traffic. J Phys I 12(2):2221–2229Google Scholar