Multi-agent preemptive longest queue first system to manage the crossing of emergency vehicles at interrupted intersections

Ali Louati,Saber Darmoul,Hassen Louati,Sabeur Elkosantini

doi:10.1186/s12544-018-0317-5

Abstract

Favouring the crossing of Emergency Vehicles (EVs) through intersections in urban cities is very critical for people lives. There have been several efforts toward developing Traffic Signal Control Systems (TSCS) dedicated to control efficiently the traffic flow, but few are the efforts toward developing Traffic Signal Priority Systems (TSPS) dedicated to favour the crossing of EVs (such as ambulances, firefighters, police cars, etc.). Multi-Agent Systems were considered to develop several distributed TSCS, while very few works have developed distributed TSPS. Such systems lack on dealing with the EVs crossing issues while maintaining a fluid state of the traffic. In the literature, the Longest Queue First – Maximal Weight Matching (LQF-MWM) is proved to guarantee a stable TSCS. Recently, the LQF-MWM technique is increasingly used to benchmarck and assess adaptive TSCS. Moreover, the preemption is one of the most effective techniques used to prioritise the crossing of EVs. This paper is the first to rely on LQF-MWM assumptions, preemption technique, and Multi-Agent Systems to design a distributed TSPS. The suggested system has two main purposes, which are the guidance of EVs and the control of traffic signals. Nine agents are implemented to govern a network of nine intersections, where each agent uses the Multi Agent System based Preemptive Longest Queue First – Maximal Weight Matching. We have referred to VISSIM traffic simulation software for benchmarking and analysis. To assess the suggested system, we have developed a distributed and preemptive version of VISSIM Optimized Stage-Based Fixed-Time algorithm. Python is considered to develop the suggested systems, and Spade platform is considered as agents’ platform. Several Key Performance Indicators are considered to assess the performance of all controllers including delay time, travel time, vehicles queue occupancy, number of stops, distance traversed, and speed. Experimental results show a competitive performance of the developed system to maintain a fluid traffic and guide efficiency EVs.

Highlights

In an inherently non-static environment, vehicular traffic control on road networks became a complex decision making task
We evaluates the performance of the suggested systems for all scenarios with regard to seven Key Performance Indicators (KPIs), which are the average number of stops of Emergency Vehicles (EVs), the EVs average speed of EVs, the average distance traversed of EVs, the average total travel time per EV, the average total delay per EV, the total travel time of all EVs, and the total delay of all EVs
EVs speed is very critical for people lives, multi-agent systems (MAS)-P-Longest Queue First – Maximal Weight Matching (LQF-MWM) allows a higher average speed which is 30 km/h, while MAS-P-Optimized Stage-Based Fixed-Time algorithm (OSBFX)-60s and MAS-P-OS BFX-240 s give lower speed, which are 20 km/h and 15 km/h, respectively

Summary

Introduction

In an inherently non-static environment, vehicular traffic control on road networks became a complex decision making task. 2.1 An overview on traffic signals control and priority systems Several Traffic Signal Control Systems (TSCS) were developed in the literature to maintain traffic fluidity at signalized intersections Such systems belong to two broad classes which are; the traditional control strategy, named fixed-time or pretimed control such as TRANSYT [29] and MAXBAND [16], and adaptive traffic control strategy such as SCOOT [30], CRONOS [3], and RHODES [23]. Insuring safety especially when disturbances occur, become a major concern of efficient and effective TSCS which is responsible of determining decisions to be sent to traffic signals. These decisions should improve traffic flow and help in protecting people lives

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Conclusion