Observing rerouting phenomena in dynamic traffic networks

This paper shows how rerouting phenomena can be observed from the available data and how to derive valuable input to estimate the rerouting models. By rerouting we mean changing the currently chosen path in road network after either receiving some information or observing consequences of an unexpected traffic event. Recently we have proposed Information Comply Model (ICM) to address the rerouting phenomena in Dynamic Traffic Assignment (DTA) [1]. In this paper we focus on estimation framework for the model and verify the assumptions on the rerouting behavior. The paper identifies two datasets where rerouting can be observed: (1) direct - path trajectories; (2) indirect - traffic flows over the cut-set of the network. Proposed method of formal analysis derives from the data the input to estimate the rerouting behavior, namely flow: information spreads (speed and range), drivers observe (how an atypical delay leads to rerouting), drivers decide (utility of rerouting used in discrete-choice model). Indirect estimation method from traffic flows is illustrated with a field-data from Warsaw bridges observed over several consecutive days including day of the event. Central findings are: a) about 20% of the affected traffic flow reroutes, b) rerouting flows are increasing in time, c) drivers show strategic capabilities, d) and maximize their utility while rerouting. Which were assumed while conceiving the ICM model.