您当前的位置:
首页 >
文章列表页 >
Connected mixed traffic flow car-following model and stability analysis considering multiple vehicles response
更新时间:2025-07-21
    • Connected mixed traffic flow car-following model and stability analysis considering multiple vehicles response

    • In the field of intelligent transportation, experts have established a car following model for connected mixed traffic flow, providing theoretical basis for improving the stability of mixed traffic flow.
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 54, Issue 11, Pages: 3220-3230(2024)
    • 作者机构:

      1.青岛理工大学 机械与汽车工程学院,山东 青岛 266520

      2.淄博职业学院 人工智能与大数据学院,山东 淄博255300

    • DOI:10.13229/j.cnki.jdxbgxb.20221645    

      CLC: U491
    • Received:31 December 2022

      Published:01 November 2024

    移动端阅览

  • SONG Hui,QU Da-yi,WANG Shao-jie,et al.Connected mixed traffic flow car-following model and stability analysis considering multiple vehicles response[J].Journal of Jilin University(Engineering and Technology Edition),2024,54(11):3220-3230. DOI: 10.13229/j.cnki.jdxbgxb.20221645.

  •  
  •  

0

Views

10

下载量

1

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

An improved car⁃following model for connected and automated vehicles considering impact of multiple vehicles
Lane⁃changing model of autonomous vehicle in weaving area of expressway in intelligent and connected mixed environment
Car⁃following dynamics characteristics and model based on Lennard⁃Jones potential
Characteristics of passenger-cargo mixed traffic flow in intelligent network and agglomeration lane-change strategy
Safety distance between semi-underground hub interchange ramp tunnel exit and secondary diversion points

Related Author

XU Yin
TAN Yi-fan
PU Yun
LIU Hai-xu
LIU Jia-ming
XIE Li-peng
ZHANG Wei-hua
DING Heng

Related Institution

School of Transportation and Logistics, Southwest Jiaotong University
National Engineering Laboratory of Application Technology of Integrated Transportation Big Data SWJTU, Southwest Jiaotong University
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University
Department of Civil and Environment Engineering, University of Wisconsin-Madison
School of Automotive and Transportation Engineering, Hefei University of Technology
0