An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data

XU Jin; YANG Xuemin; ZHANG Xueyu; ZHANG Jie; KONG Fanxing; JIAO Chengwu

doi:10.3963/j.jssn.1674-4861.2023.06.003

Volume 41 Issue 6

Dec. 2023

Turn off MathJax

Article Contents

Article Navigation > Journal of Transport Information and Safety > 2023 > 41(6): 20-31

XU Jin, YANG Xuemin, ZHANG Xueyu, ZHANG Jie, KONG Fanxing, JIAO Chengwu. An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data[J]. Journal of Transport Information and Safety, 2023, 41(6): 20-31. doi: 10.3963/j.jssn.1674-4861.2023.06.003

Citation:

XU Jin, YANG Xuemin, ZHANG Xueyu, ZHANG Jie, KONG Fanxing, JIAO Chengwu. An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data[J]. Journal of Transport Information and Safety, 2023, 41(6): 20-31. doi: 10.3963/j.jssn.1674-4861.2023.06.003

Citation:

XU Jin, YANG Xuemin, ZHANG Xueyu, ZHANG Jie, KONG Fanxing, JIAO Chengwu. An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data[J]. Journal of Transport Information and Safety, 2023, 41(6): 20-31. doi: 10.3963/j.jssn.1674-4861.2023.06.003

PDF( 4404 KB)

An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data

doi: 10.3963/j.jssn.1674-4861.2023.06.003

1.
College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China
2.
Chongqing Chang'an Automobile Co., Ltd., Chongqing 400020, China
3.
CICT Connected and Intelligent Technologies Co., Ltd., Chongqing 404100, China
4.
China Railway Eryuan Engineering Group Co. Ltd., Chengdu 610031, China
5.
Research Institute of Highway Ministry of Transport, Beijing 100088, China

Received Date: 2023-06-14
Available Online: 2024-04-03

Abstract

Abstract

Interchange is an important node of the road traffic network, and as the spacing between neighboring interchanges continues to shrink, a high-density cluster of interchanges is gradually formed, which is prone to traffic congestion, increasing driving load and accident risk. To clarify the operational risks and safety hazards in the entrance and exit sections of high-density interchanges, the field driving test is conducted on the Inner Ring Road of Chongqing. This test takes a cluster of high-density interchanges as the research object. Using onboard instruments, vehicle trajectory data are collected under natural driving conditions. The vehicle trajectory data includes speed, real-time driving position, and lateral distance between the vehicle center and the lane markings on both sides. By analyzing the measured data, the vehicle trajectory pattern of the interchange entrances and exits as well as the relation-ship between the behavioral characteristics of lane selection and the influence of the driver's gender on the trajectory pattern are clarified. The lane-changing behavioral characteristics and driving risk influencing factors in the process of vehicles leaving (merging into) the mainline are explored. The results reveal the following conclusions: ①The type of entrance or exit has a significant influence on lane selection and trajectory shape. Compared to parallel-type exits, direct-type exits have smoother trajectories and fewer lane changing numbers. ②When entering and exiting two adjacent interchanges with a short clearance, drivers tend to choose the auxiliary lane or the outermost lane on the mainline to reduce the number of lane changing. ③The number of mainline lanes near the entrance and exit affect drivers' lane selection behavior. ④When drivers leave the mainline, the lane-changing duration of the parallel-type exit is higher than that of the direct-type exit. The entrance type does not have a significant impact on lane-changing time. The lane-changing time for 78% of drivers is between 5 to 10 seconds. ⑤The operational risks in the exit section are higher than in the entrance section. It is recommended to use solid white lane line to prohibit crossing same-direction lane markings on the left side of the rightmost lane of the exit section. The length should cover from the beginning of the taper section to the diverging point, extending 50 meters forward from the start of the taper section.
- traffic safety,
- high-density interchanges,
- naturalistic driving data,
- small spacing interchanges,
- interchange entrance and exit,
- trajectory

FullText(HTML)

References(27)

References

[1]	中华人民共和国住房和城乡建设部. 城市快速路设计规程: CJJ129—2009[S]. 2009. Ministry of Housing and Urban-Rural Development of the People's Republic of China. Specification for design of urban expressway: CJJ129—2009[S]. 2009. (in Chinese)
[2]	中华人民共和国交通运输部. 公路立体交叉设计细则: JTGT D21—2014[S]. 2014. Ministry of Transport of the People's Republic of China. Guidelines for design of highway grade-separated intersections: JTGT D21—2014[S]. 2014. (in Chinese)
[3]	潘存书. 基于实车驾驶的城市立交区汽车行驶轨迹特性研究[D]. 重庆: 重庆交通大学, 2021 PAN C S. Study on trajectory of vehicle in urban interchange based on field operational test data[D]. Chongqing: Chongqing Jiaotong University, 2021. (in Chinese)
[4]	ZAKI M H, SAYED T. A framework for automated road-users classification using movement trajectories[J]. Transportation Research Part C: Emerging Technologies, 2013, 33: 50-73. doi: 10.1016/j.trc.2013.04.007
[5]	LI X C, LUO X, HE M C, et al. An improved car-following model considering the influence of space gap to the response[J]. Physica A: Statistical Mechanics and its Applications, 2018, 509: 536-545. doi: 10.1016/j.physa.2018.06.069
[6]	陆键, 王可, 蒋愚明. 基于车辆行驶轨迹的道路不良驾驶行为实时辨识方法[J]. 交通运输工程学报, 2020, 20(6): 227-235. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202006023.htm LU J, WANG K, JIANG Y M. Real-time identification method of abnormal road driving behavior based on vehicle driving trajectory[J]. Journal of Traffic and Transportation Engineering, 2020, 20 (6): 227-235. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202006023.htm
[7]	张婉婷, 杨明明, 张誓童. 基于轨迹数据的交叉口进口道车辆换道行为特性分析[J]. 内蒙古公路与运输, 2023(3): 53-57, 62. https://www.cnki.com.cn/Article/CJFDTOTAL-NMGY202303012.htm ZHANG W T, YANG M M, ZHANG S T. Analysis of lane-changing behavior characteristics of vehicles at intersection entrance based on trajectory data[J]. Highways & Transportation in Inner Mongolia, 2023(3): 53-57, 62. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-NMGY202303012.htm
[8]	COIFMAN B, BEYMER D, MCLAUCHLAN P, et al. A real-time computer vision system for vehicle tracking and traffic surveillance[J]. Transportation Research Part C: Emerging Technologies, 1998, 6 (4), 271-288. doi: 10.1016/S0968-090X(98)00019-9
[9]	ZHAO P, LEE C. Assessing rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure[J]. AccidentAnalysis & Prevention, 2018, 113: 149-158.
[10]	陈景旭, 程文昱, 万剑, 等. 基于NGSIM微观轨迹数据的车辆跟驰行为安全评价[J]. 重庆交通大学学报(自然科学版), 2022, 41 (1): 1-6, 21. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT202201001.htm CHEN J X, CHENG W Y, WAN J, et al. Safety evaluation of car-following behavior based on NGSIM micro trajectory data[J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41 (1): 1-6, 21. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT202201001.htm
[11]	CHEN S Y, CHENG K, YANG J H, et. al. Driving behavior risk measurement and cluster analysis driven by vehicle trajectory data[J]. Applied Sciences, 2023, 13: 5675. doi: 10.3390/app13095675
[12]	HU Y P, LI Y, HUANG H L, et. al. A high-resolution trajectory data driven method for real-time evaluation of traffic safety[J]. Accident Analysis and Prevention, 2022, 165: 106503. doi: 10.1016/j.aap.2021.106503
[13]	邓天民, 罗骁, 邵毅明, 等. 山区公路曲线路段汽车轨迹模式与切弯行为[J]. 东南大学学报(自然科学版), 2019, 49 (2): 388-396. https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201902027.htm DENG T M, LUO X, SHAO Y M, et al. Track patterns and curve cutting behavior on curved sections of mountain roads, Journal of Southeast University(Natural Science Edition), 2019, 49 (2): 388-396. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201902027.htm
[14]	徐进, 罗骁, 张凯, 等. 基于自然驾驶试验的山区公路汽车行驶轨迹特性研究[J]. 中国公路学报, 2016, 29 (7): 38-51. XU J, LUO X, ZHANG K, et al. Investigation on characteristics of vehicle travelling tracks on mountain highways based on natural driving tests[J]. China Journal of Highway and Transport, 2016, 29 (7): 38-51. (in Chinese)
[15]	徐进, 陈莹, 张晓波, 等, 回头曲线路段的轨迹曲率特性和汽车过弯方式[J]. 西南交通大学学报, 2021, 56(6): 1143-1152. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106002.htm XU J, CHEN Y, ZHANG X B, et al. Track curvature behavior and negotiating patterns and on hairpin curves[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1143-1152. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106002.htm
[16]	陈莹, 王晓辉, 张晓波, 等. 山区公路回头曲线的车道偏移行为与自由行驶轨迹模型[J]. 交通运输工程学报, 2022, 22 (4): 382-395. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202204029.htm CHEN Y, WANG X H, ZHANG X B, et al. Lane offset behavior and free driving trajectory model of hairpin curves of mountain roads[J]. Journal of Traffic and Transportation Engineering, 2022, 22 (4): 382-395. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202204029.htm
[17]	张苇冲, 杨涛, 吕能超. 基于车辆位置与速度特征的驾驶行为模式分类方法[J]. 交通信息与安全, 2023, 41 (1): 85-94. doi: 10.3963/j.jssn.1674-4861.2023.01.009 ZHANG W C, YANG T, LYU N C. A method for classifying driving behavior based on vehicle position and speed[J]. Journal of Transport Information and Safety, 2023, 41(1): 85-94. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2023.01.009
[18]	LYU N, CHAO Y, WU C, et al. The effect of gender, occupation and experience on behavior while driving on a freeway deceleration lane based on field operational test data[J]. Accident Analysis & Prevention, 2018, 121: 82-93.
[19]	陈秋香. 基于匝道区数据的恶劣天气下换道行为研究[D]. 成都: 西南交通大学, 2014. CHEN Q X. Study on lane-changing behavior in bad weather based on data of ramp section[D]. Chengdu: Southwest Jiaotong University, 2014. (in Chinese)
[20]	黄利华. 城市快速路立交桥出口指路标志影响分析及效用评估研究[D]. 北京: 北京工业大学, 2015. HUANG L H. Research on influence analysis and effectiveness evaluation of interchange exit guide signs in urban expressway[D]. Beijing: Beijing University of Technology, 2015. (in Chinese)
[21]	杨登松. 高密度互通立交区域标志标线组合精细化设计研究[J]. 智能城市, 2021, 7 (4): 1-3. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNCS202104002.htm YANG D S. Refined design of sign marking combinations in high-density interchange areas[J]. Intelligent City, 2021, 7 (4): 1-3. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZNCS202104002.htm
[22]	徐进, 孙子秋, 王思棋, 等. 高密度互通立交出口匝道驾驶人视觉搜索行为特征[J]. 东南大学学报(自然科学版), 2022, 52 (6): 1189-1198. https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX202206020.htm XU J, SONG Z Q, WANG S Q, et al. Characteristics of driver's visual search behavior in exit ramp of high-density interchanges[J]. Journal of Southeast University (Natural Science Edition), 2022, 52 (6): 1189-1198. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX202206020.htm
[23]	裴玉龙, 金英群, 陈贺飞. 基于脑电信号分析的不同年龄驾驶人疲劳特性[J]. 中国公路学报, 2018, 31 (4): 59-65, 77. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201804009.htm PEI Y L, JIN Y Q, CHEN H F. Fatigue characteristics in drivers of different ages based on analysis of EEG[J]. China Journal of Highway and Transport, 2018, 31(4): 59-65, 77. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201804009.htm
[24]	刘智, 马强强, 邵海鹏, 等. 高速公路单车道出口匝道车辆驶出特性及安全性影响研究[J]. 公路, 2023, 68(7): 333-342. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL202307054.htm LIU Z, MA Q Q, SHAO H P, et al. Research on safety and vehicle driving characteristics on single-laned exit ramp of expressway[J]. Highway, 2023, 68(7): 333-342. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL202307054.htm
[25]	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 道路交通标志和标线第3部分: 道路交通标线: GB 5768.3—2009. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Certification and Accreditation Administration. Road traffic signs and markings - Part 3: Road traffic markings: GB 5768. 3—2009. 2009. (in Chinese)
[26]	沈航先. 车辆换道意图识别和轨迹预测模型研究[D]. 哈尔滨: 东北林业大学, 2021. SHEN H X. Research on vehicle lane change intention recognition and trajectory prediction model[D]. Harbin: Northeast Forestry University, 2021. (in Chinese)
[27]	马小龙, 余强, 刘建蓓, 等. 基于无人机视频拍摄的高速公路小型车换道行为特性[J]. 中国公路学报, 2020, 33 (6): 95-105. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006010.htm MA X L, YU Q, LIU J B, et al. Analysis of lane change behavior of passenger cars on the freeway using UAVs[J]. China Journal of Highway and Transport, 2020, 33(6): 95-105. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006010.htm

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(11) / Tables(5)

Get Citation

PDF

XML

Article Metrics

Article views (411) PDF downloads(139)

An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data

doi: 10.3963/j.jssn.1674-4861.2023.06.003

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

An Investigation on Vehicle Trajectory Characteristics at Exit and Entrance of High-density Interchanges Based on Naturalistic Driving Data

doi: 10.3963/j.jssn.1674-4861.2023.06.003

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content