Characteristics of arterial travel time distributions with mixed traffic of human- driven and connected and autonomous vehicles
ID:1423 View Protection:ATTENDEE Updated Time:2021-12-03 10:50:03 Hits:238 Poster Presentation

Start Time:2021-12-17 10:56(Asia/Shanghai)

Duration:1min

Session:P1 Poster2020 » P1T1Track 1 Advanced Transportation Information and Control Engineering

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Abstract
Travel time information serves as a basis for travel planning, route guidance and congestion avoidance. The advances of connected and autonomous vehicle (CAV) technologies offer vehicles the potential of reduced travel time compared to conventional human-driven vehicles (HDVs). In the future, the road will be shared by both HDVs and CAVs, leading to mixed traffic flows that can significantly differ from the single-class HDV traffic flow. Thus, to explore the characteristics of travel time with mixed traffic will be an essential issue for better traffic operation and management. In this study, travel time distribution was investigated along the arterial with three continuous intersections established by VISSIM microsimulation. A series of simulation experiments were conducted, and finite mixture of regression models were used to characterize the mean, variance and mixing weight of different components. The impact factors such as traffic volume, cycle length, CAV penetration rate and driving behavior variables were all scrutinized.
Keywords
CICTP
Speaker
Ali Mamat
BUAA

Submission Author
Ali Mamat BUAA
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Important Date
  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
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