Eco-Routing: An ant colony based approach

Abstract

Global warming, environmental pollution, and fuel shortage are currently major worldwide challenges. Ecorouting is one of several tools that attempt to address this challenge by minimizing network-wide vehicle fuel consumption and emission levels. Eco-routing systems select the most environmentally friendly route. The subpopulation feedback eco-routing (SPF-ECO) algorithm that is implemented in the INTEGRATION software can produce a reduction in fuel consumption levels by approximately 17%. However, in some cases, due to delayed updates or the lack for updates, its performance degrades. In this paper, we propose the ant colony based eco-routing technique (ACO-ECO), which is a novel feedback eco-routing and cost updating algorithm to overcome these shortcomings. In the ACO-ECO algorithm, real-time performance measures on various roadway links are shared. Vehicles build their minimum path routes using the latest real-time information to minimize their fuel consumption and emission levels. ACO-ECO is also able to capture randomness in route selection, pheromone updating, and pheromone evaporation. The results show that the ACO-ECO algorithm and SPF-ECO have similar performances in normal cases. However, in the case of link blocking, the ACO-ECO algorithm reduces the network-wide fuel consumption and CO2 emission levels in the range of 2.3% to 6.0%. It also reduces the average trip time by approximately 3.6% to 14.0%.