Intersection Collision Avoidance for Autonomous Vehicles Using Petri Nets
Abstract
Autonomous vehicles currently dominate the automobile field for their impact on humanity and society. Connected and Automated Vehicles (CAV’s) are vehicles that use different communication technologies to communicate with other vehicles, infrastructure, the cloud, etc. With the information received from the sensors present, the vehicles analyze and take necessary steps for smooth, collision-free driving. This thesis talks about the cruise control system along with the intersection collision avoidance system based on Petri net models. It consists of two internal controllers for velocity and distance control, respectively, and three external ones for collision avoidance. Fault-tolerant redundant controllers are designed to keep these three controllers incheck. The model is built using a PN toolbox and tested for various scenarios. The model is also validated, and its distinct properties are analyzed.
Degree
M.Sc.
Advisors
Li, Purdue University.
Subject Area
Design|Communication|Aerospace engineering|Computer science|Transportation
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.