HighlightsIntroduce new control variables of dynamic reaction time to model adaptive platoon formation.Develop a theoretically rigorous optimization model for multi-vehicle trajectory optimization.Dynamic programming based trajectory optimization model under complex traffic conditions.Numerical experiment for capacity bottlenecks and obstacles of moving trajectories.
AbstractJointly optimizing multi-vehicle trajectories is a critical task in the next-generation transportation system with autonomous and connected vehicles. Based on a space-time lattice, we present a set of integer programming and dynamic programming models for scheduling longitudinal trajectories, where the goal is to consider both system-wide safety and throughput requirements under supports of various communication technologies. Newell's simplified linear car following model is used to characterize interactions and collision avoidance between vehicles, and a control variable of time-dependent platoon-level reaction time is introduced in this study to reflect various degrees of vehicle-to-vehicle or vehicle-to-infrastructure communication connectivity. By adjusting the lead vehicle's speed and platoon-level reaction time at each time step, the proposed optimization models could effectively control the complete set of trajectories in a platoon, along traffic backward propagation waves. This parsimonious multi-vehicle state representation sheds new lights on forming tight and adaptive vehicle platoons at a capacity bottleneck. We examine the principle of optimality conditions and resulting computational complexity under different coupling conditions.
Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models
Transportation Research Part B: Methodological ; 106 ; 102-129
2017-10-25
28 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch