DUE-STR: A Heuristic Extension Of The Selfless Traffic Routing Model Utilizing Dynamic User Equilibrium



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Routing vehicles through a traffic network such as a modern-day city has been a much- studied topic, with routing algorithms such as Dynamic User Equilibrium (DUE) having been well documented. The focus of many such works has been on the optimization of average travel time through traffic networks aiming for the more efficient routing of vehicles. In this thesis, we outline our plans for routing to satisfy arrival deadlines, where vehicles are routed with the primary objective of getting somewhere on time. We consider vehicle routing through a smaller section of a city, known as a traffic sub-network, using a centralized scheme as a guiding traffic assignment agent. We introduce our preliminary implementation of a routing algorithm built on the Selfless Traffic Routing (STR) model and Dynamic User Equilibrium (DUE) to show the viability of such a scheme on a traffic network. We present our experimental results from running this scheme on a real-world traffic network. We consider a pre-vehicle movement rerouting scheme capable of being competitive against more informative real-time models. We evaluate DUE-STR and these models using the number of arrival-deadline misses and the average travel time performance metrics for vehicles. We find mixed results between DUE-STR and other models, with our DUE- STR model mostly having better results when considering deadline misses and mostly having worse results when considering average vehicle travel time. We explore reasons why the results may not be quite as good as well as potential solutions to solve these issues.



Traffic Routing, Selfless model, Real-Time, Equilibrium


Portions of this document appear in: T. Carroll, A. M. K. Cheng and G. Dai, "Work In Progress: A Solution Based on Dynamic User Equilibrium Toward the Selfless Traffic Routing Model," in IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS), Milano, 2022. © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.