Long, K., Li, X., & Li, Q. (2023). Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction. https://rosap.ntl.bts.gov/view/dot/73219
Long, Keke, Xiaopeng Li, and Qianwen Li. Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction, 2023. https://rosap.ntl.bts.gov/view/dot/73219.
Long, Keke, et al. Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/73219.
Vehicle scheduling in roadway conflict areas is a common yet challenging problem due to the large vehicle population and heterogeneity, including the significant presence of transit vehicles. Traditional methods are time-consuming and fail to meet real-time operation needs. This study proposes a platooning strategy for connected and automated vehicles in conflict areas. Vehicles are clustered into platoons and treated as scheduling units, reducing problem complexity. Theoretical analyses show a bounded solution gap between single-vehicle and platoon-based strategies of vehicle delay. Numerical experiments confirm the superiority of the proposed strategy in reducing problem size without significant loss of optimality. This platooning approach has the potential to optimize vehicle scheduling, including transit vehicles, and enhance network control in heterogeneous vehicle environments where specific groups of vehicles such as transit are prioritized.
Vehicle scheduling in roadway conflict areas is a common yet challenging problem due to the large vehicle population and heterogeneity, including the
...
Long, K., Li, X., & Li, Q. (2023). Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction. https://rosap.ntl.bts.gov/view/dot/73219
Long, Keke, Xiaopeng Li, and Qianwen Li. Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction, 2023. https://rosap.ntl.bts.gov/view/dot/73219.
Long, Keke, et al. Network Control in Realistic Settings with Heterogeneous Vehicles. University of South Florida. National Institute for Congestion Reduction, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/73219.
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