Routing Around the Queue: An Evaluation of Eco-Routing Protocol on different Traffic Scenarios
Leandros Maglaras, George Boustras, Azidine Guezzaz, Naghmeh Moradpoor
We evaluate ErouVe, a vehicular eco-routing protocol in which roadside units (RSUs) collect per-segment travel-time and CO2 reports from passing vehicles and answer route requests with the lowest-cost alternative, across a range of road architectures and traffic scenarios. We conduct the evaluation with a working implementation of the protocol inside Veins, adapted to drive SUMO's own router rather than a hand-rolled shortest-path search, on a network offering a short, signal-controlled route and a longer, signal-free bypass, under two traffic scenarios. This evaluation reveals clear strengths and weaknesses of the protocol. Under light, uncongested traffic, ErouVe's fleet-wide effect is light. Under traffic dense enough to stress the signalized route's throughput and produce a real, growing queue, the same protocol succeeds a medium fleet-wide CO2 reduction, with diverted vehicles individually saving even more fuels. We use these findings to propose three targeted corrective methods; a knowledge-gated cost-acceptance rule, a diversion-locking rule, and a distance-normalized CO2 cost function, that respectively address a cold-start knowledge asymmetry, decision flapping under noisy crowd-sourced data, and a per-second CO2 metric that rewards idling. Each of these weaknesses are generic pitfalls for any crowd-sourced routing signal and all proposed methods measurably restore protocol effectiveness.
尚无 AI 解读，展示原文摘要