MPTR: Multi-Parameter based Travel Time Reduction for Emergencies

Abstract

Modern cultures struggle with a lot of congestion. Congestion on road increases travel time and costs while also having a significant impact on the environment. We propose a system for optimizing fire engine travel time based on constraints such as road type, speed, vehicle density, and vehicle type and the length of each path. One type of mobile network is the Vehicular Ad-hoc Network (VANET). This paper proposes a Multi-Parameter Travel Time Reduction Method [MPTR] algorithm for reducing fire engine travel time. This proposed algorithm seeks to select the optimal path from a list of various options based on parameters such as road type, speed, and distance. The time of day, vehicle type, distance between paths, and other factors are all taken into account. This is simulated using the open-source simulator SUMO. Traffic flow in SUMO is a multimodal, open source, microscopic system. It enables the user to simulate how a specific traffic demand performance on a given road network would look. When it comes to choosing the best path and avoiding crowded areas, MPTR shows promising results. It was discovered that when MPTR is used, travel time decreases gradually. According to the computed results, the MPTR algorithm outperforms in terms of performance, dependability, duration, distance, and throughput.