/Accomodating High Value-of-Time Drives in Market-Driven Traffic Signal Control

Accomodating High Value-of-Time Drives in Market-Driven Traffic Signal Control

Isaac Isukapati and Stephen Smith
Conference Paper, 2017 IEEE Intelligent Vehicles Symposium, June, 2017

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.


In this paper, we propose a market-driven approach to traffic signal control. In contrast to traditional traffic engineering approaches, our approach gives agency and decision-making influence to individual drivers and exploits auction mechanisms to make traffic control decisions. Drivers make payments to their corresponding movement managers (each responsible for a particular directional flow through the intersection), and movement managers then compete for control of the signal. These financial transactions, if treated literally provide an alternate source of funding transportation infrastructure. Previous work with this model has demonstrated the ability to achieve better overall traffic flow performance than actuated control, a simple adaptive traffic signal control strategy based on detection and monitoring of waiting vehicles. Here we consider the design and analysis of bidding strategies capable of factoring in a given driver’s value of time (VOT), as indicated by the amount of voluntary contributions that are made on top of the fixed fee that every driver is charged. We analyze the potential for expediting high VOT drivers without undue disruption of overall traffic flows.

BibTeX Reference
author = {Isaac Isukapati and Stephen Smith},
title = {Accomodating High Value-of-Time Drives in Market-Driven Traffic Signal Control},
booktitle = {2017 IEEE Intelligent Vehicles Symposium},
year = {2017},
month = {June},
publisher = {IEEE},
keywords = {Game Theory Control, Intelligent Transportation Systems, Artificial Intelligence, Auction Based Signal Control},