An ASP Framework for Efficient Urban Traffic Optimization

TL;DR

This paper introduces an ASP-based framework for simulating and optimizing urban traffic flow, effectively reducing congestion, travel times, and emissions in large road networks using formal encoding and real-world data analysis.

Contribution

It presents a novel ASP encoding framework combined with SUMO for efficient urban traffic simulation and optimization, demonstrating improved traffic management capabilities.

Findings

Optimized vehicle routes reduce travel times.

Framework effectively minimizes emissions.

Demonstrated scalability on large networks.

Abstract

Avoiding congestion and controlling traffic in urban scenarios is becoming nowadays of paramount importance due to the rapid growth of our cities' population and vehicles. The effective control of urban traffic as a means to mitigate congestion can be beneficial in an economic, environmental and health way. In this paper, a framework which allows to efficiently simulate and optimize traffic flow in a large roads' network with hundreds of vehicles is presented. The framework leverages on an Answer Set Programming (ASP) encoding to formally describe the movements of vehicles inside a network. Taking advantage of the ability to specify optimization constraints in ASP and the off-the-shelf solver Clingo, it is then possible to optimize the routes of vehicles inside the network to reduce a range of relevant metrics (e.g., travel times or emissions). Finally, an analysis on real-world traffic data is performed, utilizing the state-of-the-art Urban Mobility Simulator (SUMO) to keep track of the state of the network, test the correctness of the solution and to prove the efficiency and capabilities of the presented solution.