Ecofriendly Navigation System Development for Heavy-Duty Trucks

摘要: Heavy-duty trucks are a critical component of the U.S. goods movement system; however, they consume large amount fuel and emit significant pollutant greenhouse gas emissions. The trucking industry is always looking for any measure to improve their operations reduce consumption, including efficient routing. Many existing fleet management routing systems based on minimizing total miles traveled which does not necessarily minimize consumption or emissions, particularly under congestion in areas having changes road grade. In this paper, we describe new Eco-Friendly Navigation (EFNav) algorithms that were developed specifically emissions from heavy-duty trucks. An EFNav mesoscale model was rich set truck energy data collected by UC-Riverside’s Mobile Emissions Laboratory (MEL) robust simulated wide range operating conditions using CE-CERT’s model. basis algorithm provides more accurate projection use than standard average speed estimation accounting vehicle mass A prototype implementation eco-routing system performed heavily loaded class-8 truck. It shown navigation system, with real-time traffic information, able estimate projected within 7.5% over test routes simulation work showed variance between an empty fully as much 240% selected route.