Estimating the risk of traffic incidents using causal analysis

Traffic management centres aim to keep the traffic flowing regardless of traffic disturbances. This paper presents a new method for quantitative incident analysis via causality and observations. It is applied to estimate the risk ofvehicular traffic tunnel closures in the city of Tampere, Finland, where the tunnel on a national main road bypasses the city centre. A tunnel closure rapidly causes traffic jams on alternative routes in the city. Also, traffic incidents near the tunnel may propagate and cause tunnel closures. We restrict our analyses to the westbound direction of the traffic on the main road. We combine various open data sources providing information about traffic and driving conditions. The analysis is based on a probabilistic and statistical framework augmented with causal reasoning. We have identified several event paths from congestion after the tunnel to the tunnel closing, as well as approximate capacity limits near selected critical locations.