학술논문

Analysis of Vehicle Sequencing at Smart Intersections: A PDMP Approach
Document Type
Conference
Source
2022 41st Chinese Control Conference (CCC) Chinese Control Conference, 2022 41st. :5499-5504 Jul, 2022
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Measurement
Sequential analysis
Connected vehicles
Process control
Switches
Markov processes
Numerical models
Connected and autonomous vehicles
piecewise-deterministic Markov processes
Lyapunov method
Language
ISSN
1934-1768
Abstract
With the development of connected and autonomous vehicles (CAVs), signal-free intersections with both efficiency and safety is under great need. However, macroscopic performance metrics of smart intersections have not been well evaluated. In this paper, we model a signal-free intersection as a piecewise-deterministic Markov process. We use Foster-Lyapunov theory to analyze the macroscopic properties such as intersection capacity and waiting time of the system, and compare the performance of three typical sequencing policies: first-in-first-out (FIFO), minimal switch-over (MSO) and longer queue first (LQF). We reach the conclusion that MSO performs the best while LQF performs the worst. Finally, we apply the results to a numerical example to gain insights for sequencing policy design and validate the proposed model using simulation of urban mobility.