Floating car data-based method for detecting flooding incident under grade separation bridges in Beijing

The congestion caused by a special type of incident that is different from a normal incident, namely the flooding incident under grade separation bridges, has shown to be a serious issue in Beijing because of several horrible recent experiences. To investigate the characteristics of the congestion, this study strives to develop a floating car data (FCD)-based method for detecting the flooding incident under grade separation bridges. The study first examines the applicability of using an improved cumulative sum (CUSUM) method. However, it is found that the improved CUSUM method does not function properly when all lanes are blocked by the flooding under bridges. Then, the study proposes an analytical method by analysing characteristics of FCD. Three decision parameters, sample losing rate, speed and accumulated discrepancy, are proposed, which play a synergistic effect in the detection. It is shown from case studies that the proposed method performs satisfactorily for detecting flooding incidents under grade separation bridges. The proposed method can be used to further investigate the congestion spreading regularities to develop quick and real-time response process to mitigating the congestion triggered by the flooding.