Developing Eco-Routing Strategies

Dynamic traffic routing is defined as the process of dynamically selecting the sequence of roadway segments from a trip origin to a trip destination. Dynamic routing typically entails using time-dependent roadway travel times to compute this sequence of roadway segments. As with the general case of modeling human behavior, modeling driver travel behavior has always been complicated, never accurate enough, and in constant demand for further research.

Among the early attempts to model human choice behavior is the economic theory of the “economic man”; who in the course of being economic is also “rational” (Simon 1955). According to Simon’s exact words, “actual human rationality-striving can at best be an extremely crude and simplified approximation to the kind of global rationality that is implied, for example, by game-theoretical models.”

This project combines energy and emission models with navigation programs. The idea is to help consumers make "greener" choices about their routes. For example, an earlier study by the principal investigator found that choosing an artery-based route that takes about five minutes longer than a highway-based route reduced fuel usage by 23 percent (it was shorter and had slower speeds). Over the past year, that would have amounted to almost $300 in savings for a commuter. Adding real-time traffic information would help, too. For example, some research found that mildly congested roads actually promote fuel efficiency, since they slow drivers down and make for a more even flow.

It's strange to think of willingly following a navigation program's directions to a more congested route but this could result in significant environmental savings. This task will investigate the potential of integrating energy and environmental measures within the traffic routing decision framework. The impact of this routing strategy on the network-wide efficiency (vehicle delay) will be quantified and the potential for integrating system efficiency with environmental measures will be investigated. This task is divided into several sub-tasks, as follows: 1. Incorporate energy and emissions within current routing algorithms. 2. Investigate the impact of such routing strategies using sample networks assuming perfect knowledge of system performance. 3. Quantify the minimum number of probe vehicles required for successful implementation of the algorithms. 4. Evaluate the routing strategies associated with different vehicle types.