Benefit

Eco-routing optimization strategy focused on shortest routing reduces average trip time by 3.6 to 14.0 percent in simulation.

Two eco-routing algorithms, one optimized for shortest path and one optimized for fuel consumption, were developed at the University of Idaho.


April 2017


Summary Information

The study developed two eco-routing systems and used them to investigate and quantify the system-wide impacts of implementing an eco-routing system. The first algorithm enhanced previous eco-routing applications by introducing ant colony optimization (ACO-ECO) strategies. The other algorithm, the Linear Programming Feedback Eco-routing System (LPS-ECO) utilized fuel consumption feedback and considered road capacity along with current traffic conditions to load-balance the traffic to reduce congestion and minimize fuel consumption and emissions.

Methodology

Ant colony optimization is a meta-heuristic iterative technique inspired by the foraging behavior of some ant species. In the ant colony, ants walking to and from a food source mark the path to be followed by other members of the colony. The shorter the path, the more marks on that route, and consequently, the preferable this route is. In the ACO-ECO algorithm, vehicles are employed as artificial ants, the mark is the inverse of the fuel consumption cost for each link. Each artificial ant periodically deposits their mark by updating the fuel consumption cost for the link it is traversing.

The proposed linear programming stochastic-based eco-routing technique (LPS-ECO) tries to minimize the network-wide fuel consumption but guarantee route continuity for each individual traffic flow by using all the available network resources (roads) toward the destination. The flow balance at a given intermediate node means that the summation of the traffic entering that node equals that exiting it. The combination of the objective function and the individual flow balance at each node guarantees the route continuity.

Findings

ACO-ECO reduces average trip time by 3.6 to 14.0 percent. LPS-ECO also reduces average travel time.

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Source

Developing and Field Implementing a Dynamic Eco-Routing System

Author: Rakha, Hesham; Ahmed Elbery; and Jinghui Wang

Published By: National Institute for Advanced Transportation Technology

Source Date: April 2017

URL: http://tranliveutc.org/~/media/UIdaho-Responsive/Files/engr/research/tranlive/reports/VT_TranLIVE_Final_Developing%20and%20Field%20Implementing%20a%20Dynamic%20Eco-Routing%20System.ashx

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Goal Areas

Mobility

Typical Deployment Locations

Statewide

Keywords

eco-routing, shortest trip, travel time

Benefit ID: 2017-01219