Accidents continue to affect both the people involved and the flow of traffic. Timely and accurate accident detection can greatly benefit emergency services and traffic management, as a delay of minutes can determine the difference between life and death. This study introduces a method for detecting accidents using floating car data. The algorithm analyzes vehicle trajectories based on criteria derived from Kerner’s three-phase traffic theory, determining a high likelihood of an accident at a specific time and location. Validation using third-party data confirms the occurrence of real accidents. Empirical examples from a large feet of connected vehicles demonstrate the method’s effectiveness: it can swiftly and accurately detect freeway accidents, distinguishing them from normal congestion. A median improvement in detection time of 6.5 minutes is achieved compared to ground truth.      «

Accidents continue to affect both the people involved and the flow of traffic. Timely and accurate accident detection can greatly benefit emergency services and traffic management, as a delay of minutes can determine the difference between life and death. This study introduces a method for detecting accidents using floating car data. The algorithm analyzes vehicle trajectories based on criteria derived from Kerner’s three-phase traffic theory, determining a high likelihood of an accident at a sp...     »