MT-ERBS
Simulation-based exploration of emergency traffic prioritization.
Problem and authorship
MT-ERBS explores traffic-signal coordination for ambulance passage. The manuscript title is “Manipulating Traffic for Effective Rescue by Bypassing the Signals.” I co-authored it with Arjun V L and Gokulramanan V.
The work combines a broad proposed architecture with a narrower simulation study. A proposed citywide emergency coordination system is much broader than a grid-based traffic benchmark.
Implemented simulation
The manuscript describes a Python benchmarking tool with a grid of intersections, stochastic vehicle arrivals, queues, traffic signals, and a single ambulance on a predetermined route. It compares a fixed-time baseline with signal manipulation along the ambulance corridor.
Recorded outputs include blocking time, travel time, vehicle delay, spillbacks, throughput, and signal switching. The paper includes two visual test cases and links to benchmark code.
Proposed architecture
The wider design includes perception, route planning, coordinated signal control, and multi-ambulance handling. The future-work section places richer road networks, deployed IoT infrastructure, AI-based control, dynamic rerouting, and multiple concurrent ambulances beyond the implemented benchmark.
Evaluation and limitations
The benchmark explores signal-control behavior in a simplified simulation. Its assumptions include a predetermined route and one ambulance; richer road networks, concurrent emergencies, and real-world driver behavior remain outside that evaluation.
This is simulation-based earlier research. The manuscript and archived demonstration document the prototype; field deployment and safety validation remain separate research and engineering tasks.