Dynamic routing algorithms with SUMO

Abstract

Traffic congestion is a persistent challenge in modern transportation systems, especially as urban populations grow, leading to increased travel times, emissions and fuel consumption. This final year project explores dynamic routing algorithms as a solution to optimize traffic flow and hence alleviate congestion. Both traditional routing algorithm and precomputing-based algorithms will be compared in this project, namely Dijkstra, A*, Contraction Hierarchies and A*, Landmarks and Triangle Inequality (ALT) algorithms. Mobility metrics such as travel times, waiting times and average speed of vehicles, as well as performance metrics like computation time are used to evaluate each algorithm. Simulation of Urban Mobility (SUMO), an open source microscopic traffic simulator, will be used to simulate the road networks of Jurong West during peak hours, periodically re-routing vehicles if a faster route is found given current traffic conditions. The pre-computation based algorithm ALT is found to perform significantly better in terms of computation time compared to the other algorithms. All 4 algorithms have similar performance when it comes to minimizing mobility metrics.