Automated Intersection Management with MiniZinc

TL;DR

This paper presents an automated intersection management system using MiniZinc to optimize traffic flow, significantly reducing vehicle waiting times and preventing deadlocks in urban traffic control.

Contribution

It introduces a flexible MiniZinc-based constraint satisfaction model for intersection management, independent of data extraction methods, improving traffic efficiency.

Findings

Reduces mean vehicle waiting time

Prevents deadlocks at intersections

Outperforms existing systems in traffic flow efficiency

Abstract

Ill-managed intersections are the primary reasons behind the increasing traffic problem in urban areas, leading to nonoptimal traffic-flow and unnecessary deadlocks. In this paper, we propose an automated intersection management system that extracts data from a well-defined grid of sensors and optimizes traffic flow by controlling traffic signals. The data extraction mechanism is independent of the optimization algorithm and this paper primarily emphasizes the later one. We have used MiniZinc modeling language to define our system as a constraint satisfaction problem which can be solved using any off-the-shelf solver. The proposed system performs much better than the systems currently in use. Our system reduces the mean waiting time and standard deviation of the waiting time of vehicles and avoids deadlocks.