Authors:
Ahmed Elbery
1
;
Hesham Rakha
1
;
Mustafa Y. ElNainay
2
;
Wassim Drira
3
and
Fethi Filali
3
Affiliations:
1
Virginia Tech, United States
;
2
Alexandria University, Egypt
;
3
Qatar Mobility Innovations Center, Qatar
Keyword(s):
Eco-routing, Ant Colony, Fuel Consumption, Emissions, Travel Time, Vehicle Routing, ITS.
Related
Ontology
Subjects/Areas/Topics:
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Systems Modeling and Simulation
Abstract:
Global warming, environmental pollution, and fuel shortage are currently major worldwide challenges. Eco-routing 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 lev
els. 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%.
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