Calculating Average Driving Speeds of Emergency Vehicles by Road Type based on Emergency Call Data

Abstract

Emergency services provide essential and life-saving services, requiring prompt and reliable response times. Accurate travel time prediction is crucial for efficient dispatching and resource allocation, yet existing routing engines often rely on generalized speed profiles unsuitable for emergency vehicles. This paper presents an approach to derive average driving speeds for emergency vehicles on different road types. We combine an OpenStreetMap data-based route estimation with a linear regression model to analyze an ambulance dispatch dataset of over 97,000 calls from a large city in Germany. The results provide average ambulance driving speeds for seven road types. We compare results for six different daily time intervals, finding that high traffic indicators like rush hour times have a low impact on driving speeds, whereas driving during the night leads to a 22% speed reduction.