In urban road transportation, intersections are traffic bottlenecks with increased waiting delays and associated adverse effects. A recently proposed intelligent intersection management (IIM) approach, the Synchronous Intersection Management Protocol (SIMP), synchronizes the vehicles access to simple single-lane isolated intersections, outperforming competing approaches in various performance metrics. In this paper, we apply SIMP to multi-lane intersections, increasing significantly the applicability of the protocol while dealing with the additional complexity emerging from the multiple crossing conflicts. Using the SUMO simulator, we compare the performance of SIMP with two conventional (Round-Robin - RR and Trivial Traffic Light Control - TTLC) and two IIM approaches (Intelligent Traffic Light Control - ITLC and Q-learning based Traffic Light Control - QTLC) under continuous and interrupted upstream traffic flows scenarios in urban settings. The results using a maximum speed of $30 km/h$ confirm the superiority of SIMP, improving traffic throughput (up to 14.4%) and reducing travel delays (up to 64.4%) and associated fuel consumption (up to 25.5%) when compared to the best of the other approaches.
Áreas temáticas de ASJC Scopus
- Ciencia de la Computación General
- Ciencia de los Materiales General
- Ingeniería General