APTE2024
Talks at the 13th Asia-Pacific Conference on Transportation and the Environment (APTE) 1
Posts by Collection
portfolio
APTE2025
Talks on the 14th Asia-Pacific Conference on Transportation and the Environment (APTE) 1
HKSTS2024
Discussion at the 28th International Conference of Hong Kong Society for Transportation Studies (HKSTS2024) 1
publications
Modeling the clustering strength of connected autonomous vehicles and its impact on mixed traffic capacity
Published in Communications in Transportation Research, 2024
Autocorrelation-based Platooning Intensity (API) serves as a robust metric for quantifying the clustering strength of connected autonomous vehicles (CAVs) in mixed traffic. This study explores its application in approximating mixed traffic capacity, along with discussions on its definition, calculation, and probability distribution.
Recommended citation: Zhao, P., Wong, Y. D., & Zhu, F. (2024). Modeling the clustering strength of connected autonomous vehicles and its impact on mixed traffic capacity. Communications in Transportation Research, 4, 100151.
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Modeling and analysis of the platoon size of Connected Autonomous Vehicles in a mixed traffic environment
Published in Transportation Research Part E: Logistics and Transportation Review, 2025
Abstract
Recommended citation: Zhao, P., Wong, Y. D., & Zhu, F. (2025). Modeling and analysis of the platoon size of Connected Autonomous Vehicles in a mixed traffic environment. Transportation Research Part E: Logistics and Transportation Review, 199, 104130.
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A platoon-centric approach to the capacity analysis of mixed traffic comprising connected and autonomous vehicles
Published in Transportation Research Part C: Emerging Technologies, 2025
Abstract
Recommended citation: Zhao, P., Wong, Y. D., & Zhu, F. (2025). A platoon-centric approach to the capacity analysis of mixed traffic comprising connected and autonomous vehicles. Transportation Research Part C: Emerging Technologies, 177, 105170.
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Safety hysteresis in traffic flow: Evidence from vehicle trajectory data
Published in Transportation Research Part C: Emerging Technologies, 2026
Abstract
Recommended citation: Zhao, P., Wong, Y. D., & Zhu, F. (2026). Safety hysteresis in traffic flow: Evidence from vehicle trajectory data. Transportation Research Part C: Emerging Technologies, 190, 105806.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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