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Author:

Wang, T. (Wang, T..) | Lu, H. (Lu, H..) | Sun, Z. (Sun, Z..) | Wang, J. (Wang, J..) | Du, X. (Du, X..)

Indexed by:

Scopus SCIE

Abstract:

Connected autonomous vehicles (CAV) are currently under development, and the mixed flow with CAV would make the traffic states more complicated. Due to the lack of mature applications, the future traffic with CAV are still full of uncertainties. Under the new situation, the traditional cellular automata (CA) model is in need of upgrade. To discover the characteristics of traffic flow under different CAV penetration rates, and considering the particularity of the ramp segments on freeway, this paper updates the current CA model and analyzes the car-following and lane-changing behavior of mixed traffic flow under the intelligent network. Results show that, as the CAV penetration rate continues to increase, the road operation performance continues to improve, and the capacity of the road segment increases accordingly.  © 2023 World Scientific Publishing Company.

Keyword:

driving behavior ramp mixed traffic flow Cellular automata

Author Community:

  • [ 1 ] [Wang T.]Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing, 100084, China
  • [ 2 ] [Lu H.]Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing, 100084, China
  • [ 3 ] [Sun Z.]Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing, 100084, China
  • [ 4 ] [Sun Z.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Wang J.]Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
  • [ 6 ] [Du X.]Faculty of Civil Engineering and Geoscience, Delft University of Technology, Delft, 2628 CN, Netherlands

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Source :

Modern Physics Letters B

ISSN: 0217-9849

Year: 2023

Issue: 6

Volume: 37

1 . 9 0 0

JCR@2022

ESI Discipline: PHYSICS;

ESI HC Threshold:17

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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