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Harnessing connected and automated vehicle technologies to control lane changes at freeway merge bottlenecks in mixed traffic

https://doi.org/10.1016/j.trc.2020.102950

Chen, Danjue; Srivastava, Anupam; Ahn, Soyoung (February 2021, Transportation Research Part C: Emerging Technologies)
null (Ed.)
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On multi-class automated vehicles: Car-following behavior and its implications for traffic dynamics

https://doi.org/10.1016/j.trc.2021.103166

Kontar, Wissam; Li, Tienan; Srivastava, Anupam; Zhou, Yang; Chen, Danjue; Ahn, Soyoung (July 2021, Transportation Research Part C: Emerging Technologies)
null (Ed.)
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Traffic dynamics under speed disturbance in mixed traffic with automated and non-automated vehicles

https://doi.org/10.1016/j.trpro.2019.05.037

Chen, Danjue; Srivastava, Anupam; Ahn, Soyoung; Li, Tienan (January 2019, Transportation Research Procedia)

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Modeling and Control Using Connected and Automated Vehicles with Chained Asymmetric Driver Behavior under Stop-and-Go Oscillations

https://doi.org/10.1177/0361198120962494

Srivastava, Anupam; Chen, Danjue; Ahn, Soyoung (November 2020, Transportation Research Record: Journal of the Transportation Research Board)

This paper presents a behavioral car following model, named the chained asymmetric behavior model, that improves on the asymmetric behavior model. This model is inspired by the empirical observation that vehicles react proportionately to the magnitude of disturbance experienced when traversing through a stop-and-go oscillation, deviating from a constant following behavior observed in equilibrium conditions. Findings from simulation experiments suggest that this “second-order” effect significantly affects traffic throughput and evolution under disturbances. Knowledge obtained from the model is leveraged toward designing control for connected automated vehicles in mixed traffic streams.
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