Intelligent Transportation Systems to Mitigate Road Traffic Congestion
This addresses traffic congestion for urban commuters and emergency services, but appears incremental as it builds on existing multi-agent and simulation methods.
The paper tackled road traffic congestion by developing two multi-agent traffic management models, resulting in at least a 50% reduction in average time delay and improved journey times.
Intelligent transport systems have efficiently and effectively proved themselves in settling up the problem of traffic congestion around the world. The multi-agent based transportation system is one of the most important intelligent transport systems, which represents an interaction among the neighbouring vehicles, drivers, roads, infrastructure and vehicles. In this paper, two traffic management models have been created to mitigate congestion and to ensure that emergency vehicles arrive as quickly as possible. A tool-chain SUMO-JADE is employed to create a microscopic simulation symbolizing the interactions of traffic. The simulation model has showed a significant reduction of at least 50% in the average time delay and thus a real improvement in the entire journey time.