- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | YANG Tao, MA Yuqin, LIU Meng, YAO Zhihong, JIANG Yangsheng. Vehicle Trajectory Reconstruction Model of Signalized Intersection in Connected Automated Environments[J]. Journal of Southwest Jiaotong University, 2024, 59(5): 1148-1157. doi: 10.3969/j.issn.0258-2724.20220321
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Vehicle trajectory data provides abundant spatial-temporal traffic flow information, which can be used for traffic research. Traditional vehicle trajectory models mostly focus on the artificial driving environment and fail to consider the impact of mixed traffic flows composed of regular vehicles (RVs), connected vehicles (CVs), and connected automated vehicles (CAVs). To solve this problem, a full sample vehicle trajectory reconstruction model of signalized intersections in connected automated environments was proposed. Firstly, the composition of vehicles at signalized intersections of urban roads and the passage of queues in connected automated environments were analyzed. Secondly, a model for estimating the number of trajectories of mixed traffic flows on urban roads was constructed, and the concept of virtual vehicles was further proposed to estimate the traffic status of different vehicles according to the queuing of front and rear vehicles. Finally, a numerical simulation test was designed to analyze the influence of traffic flow density and penetration rate of CAVs and CVs on the model, and the model was verified by NGSIM data. The results show that the error of the number and position of the model decreases with the increase in traffic flow density and the penetration rate of CAVs and CVs. For example, when the traffic flow density increases from 20 veh/km to 50 veh/km, both the error of the number and position of the model shows a decreasing trend, and the maximum error is no more than 6.88% and 8.02 m. Compared with that of CVs, the penetration rate of CAVs has a greater impact on the model results.
| [1] |
SHI X W, LI X P. Constructing a fundamental diagram for traffic flow with automated vehicles: methodology and demonstration[J]. Transportation Research Part B: Methodological, 2021, 150: 279-292. doi: 10.1016/j.trb.2021.06.011
|
| [2] |
冉斌,谭华春,张健,等. 智能网联交通技术发展现状及趋势[J]. 汽车安全与节能学报,2018,9(2): 119-130. doi: 10.3969/j.issn.1674-8484.2018.02.001
RAN Bin, TAN Huachun, ZHANG Jian, et al. Development status and trend of connected automated vehicle highway system[J]. Journal of Automotive Safety and Energy, 2018, 9(2): 119-130. doi: 10.3969/j.issn.1674-8484.2018.02.001
|
| [3] |
HU X W, SUN J. Trajectory optimization of connected and autonomous vehicles at a multilane freeway merging area[J]. Transportation Research Part C: Emerging Technologies, 2019, 101: 111-125. doi: 10.1016/j.trc.2019.02.016
|
| [4] |
LU G Y, NIE Y, LIU X B, et al. Trajectory-based traffic management inside an autonomous vehicle zone[J]. Transportation Research Part B: Methodological, 2019, 120: 76-98. doi: 10.1016/j.trb.2018.12.012
|
| [5] |
张惠玲,刘晓晓,许裕东. 基于车辆轨迹重构的信号交叉口延误提取研究[J]. 交通运输系统工程与信息,2020,20(2): 237-243. doi: 10.16097/j.cnki.1009-6744.2020.02.035
ZHANG Huiling, LIU Xiaoxiao, XU Yudong. Delay extraction based on vehicle’s trajectory reconstruction at signalized intersection[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 237-243. doi: 10.16097/j.cnki.1009-6744.2020.02.035
|
| [6] |
PUNZO V, BORZACCHIELLO M T, CIUFFO B. On the assessment of vehicle trajectory data accuracy and application to the next generation simulation (NGSIM) program data[J]. Transportation Research Part C: Emerging Technologies, 2011, 19(6): 1243-1262. doi: 10.1016/j.trc.2010.12.007
|
| [7] |
COIFMAN B. Estimating travel times and vehicle trajectories on freeways using dual loop detectors[J]. Transportation Research Part A: Policy and Practice, 2002, 36(4): 351-364. doi: 10.1016/S0965-8564(01)00007-6
|
| [8] |
MU J T, HAN Y, ZHANG C, et al. An unscented Kalman filter-based method for reconstructing vehicle trajectories at signalized intersections[J]. Journal of Advanced Transportation, 2021, 2021: 1-12.
|
| [9] |
WANG Y P, WEI L, CHEN P. Trajectory reconstruction for freeway traffic mixed with human-driven vehicles and connected and automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2020, 111: 135-155. doi: 10.1016/j.trc.2019.12.002
|
| [10] |
HAN X, MA R, ZHANG H M. Energy-aware trajectory optimization of CAV platoons through a signalized intersection[J/OL]. Transportation Research Part C: Emerging Technologies, 2020, 118: 102652.1- 102652.16.
|
| [11] |
蒋阳升,刘梦,王思琛,等. 基于跟驰特性的智能网联车混合交通流轨迹重构[J]. 西南交通大学学报,2021,56(6): 1135-1142,1132.
JIANG Yangsheng, LIU Meng, WANG Sichen, et al. Trajectory reconstruction for traffic flow mixed with connected automated vehicles based on car-following characteristics[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1135-1142,1132.
|
| [12] |
OSAMA O A, BAKHIT P R, ISHAK S. Analysis of queue estimation process at signalized intersections under low connected vehicle penetration rates[J]. Canadian Journal of Civil Engineering, 2021, 48(10): 1398-1408. doi: 10.1139/cjce-2020-0366
|
| [13] |
张驰,杨少伟,潘兵宏,等. 交通仿真中驾驶人空间视野感知模型[J]. 交通运输工程学报,2010,10(4): 115-120. doi: 10.3969/j.issn.1671-1637.2010.04.019
ZHANG Chi, YANG Shaowei, PAN Binghong, et al. Perception model of driver spatial vision in traffic simulation[J]. Journal of Traffic and Transportation Engineering, 2010, 10(4): 115-120. doi: 10.3969/j.issn.1671-1637.2010.04.019
|
| [14] |
潘兵宏,赵一飞,梁孝忠. 动视觉原理在公路线形设计中的应用[J]. 长安大学学报(自然科学版),2004,24(6): 20-24. doi: 10.19721/j.cnki.1671-8879.2004.06.005
PAN Binghong, ZHAO Yifei, LIANG Xiaozhong. Application of dynamic vision theory in highway alignment design[J]. Journal of Chang’an University (Natural Science Edition), 2004, 24(6): 20-24. doi: 10.19721/j.cnki.1671-8879.2004.06.005
|
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