Vehicle Sequencing at Signal-Free Intersections: Analytical Performance Guarantees Based on PDMP Formulation
arxiv(2023)
摘要
Signal-free intersections are a representative application of smart and
connected vehicle technologies. Although extensive results have been developed
for trajectory planning and autonomous driving, the formulation and evaluation
of vehicle sequencing have not been well understood.In this paper, we consider
theoretical guarantees of macroscopic performance (i.e., capacity and delay) of
typical sequencing policies at signal-free intersections. We model intersection
traffic as a piecewise-deterministic Markov process (PDMP). We analytically
characterize the intersection capacity regions and provide upper bounds on
travel delay under three typical policies, viz. first-in-first-out,
min-switchover, and longer-queue-first. We obtain these results by constructing
policy-specific Lyapunov functions and computing mean drift of the PDMP. We
also validate the results via a series of micro-simulation-based experiments.
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