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Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate
Joint Authors
Guo, Xiaoyu
Qi, Yong
Ding, Fan
Chen, Tao
He, Shanglu
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-13
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Connected and autonomous vehicles (CAVs) are on the way to the field application.
In the beginning stage, there will be a mixed traffic flow, containing the regular human-driven vehicles and CAVs with a low penetration rate.
Recently, the discussion about the impact of a small proportion of CAVs in the mixed traffic is controversial.
This paper investigated the possibility of applying the limited data from these lowly penetrated CAVs to estimate the average freeway link speeds based on the Kalman filtering (KF) method.
First, this paper established a VISSIM-based microsimulation model to mimic the mixed traffic with different CAV penetration rates.
The characteristics of this mixed traffic were then discussed based on the simulation data, including the sample size distribution, data-missing rate, speed difference, and fundamental diagram.
Accordingly, the traditional KF-based method was introduced and modified to adapt data from CAVs.
Finally, the evaluations of the estimation accuracy and the sensitive analysis of the proposed method were conducted.
The results revealed the possibility and applicability of link speed estimation using data from a small proportion of CAVs.
American Psychological Association (APA)
He, Shanglu& Guo, Xiaoyu& Ding, Fan& Qi, Yong& Chen, Tao. 2020. Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175321
Modern Language Association (MLA)
He, Shanglu…[et al.]. Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate. Journal of Advanced Transportation No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1175321
American Medical Association (AMA)
He, Shanglu& Guo, Xiaoyu& Ding, Fan& Qi, Yong& Chen, Tao. Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175321
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175321