Optimizing Road Network Weight Calculation for Emergency Vehicles

Abstract

Correctly calculating routes and the future positions of emergency vehicles is impor tant for traffic safety and can reduce response time during distress calls. Carmenta Automotive is a company that supports the EU-funded NordicWay3 project, which aims to create a safer traffic environment. Their objective in the project is to antic ipate the path and location of emergency vehicles with the goal of sending warning messages to road users. This thesis is a continuation of a previous thesis in which an algorithm for pre dicting the routes and positions of emergency vehicles was implemented. However, no data or metric was used to validate the developed algorithm’s performance. In this thesis the goal was to develop validation metrics for this algorithm and try to optimize the cost of selecting each road, called its weight, in the road network. To achieve this an SQL database was created containing the mission data of emergency vehicles, which was used for validation purposes. Two validation metrics were also developed, the first uses the mean distance between the actual and predicted posi tions in a shorter time frame, the second focusing on more extended missions and selecting correct routes. Furthermore, parameters were optimized for three different weight equations, which are used to calculate the weight of each road using infor mation about its speed, size and distance. The parameters were optimized using Competitive Particle Swarm Optimization with respect to one validation metric at a time. Through this process a maximum improvement of 4% and 7% compared to the previous thesis weight equation with respect to the first and second validation metrics was found respectively. Finally, the conclusion reached was that the goal of the thesis was accomplished and in order to further improve the algorithm’s perfor mance, a weight calculation considering more aspects of the road than just its size, length, and speed is required.