Dynamic Model of Peak Period Traffic Congestion with Elastic Arrival Rates

Abstract

The paper develops a dynamic model of peak period traffic congestion that considers a limited number of bottlenecks. The model predicts the temporal distribution of traffic volumes with an elastic demand model. In response to changes in the traffic conditions travelers can switch to a different mode, divert to an alternate route, or shift the trip forward or backward in time to avoid a long delay. A simple example would be the case of two parallel routes with travelers jointly selecting route and departure time. The choice of route and mode are dependent on travel times and travel costs. The choice of departure time is based on the trade-off between travel time and schedule delay which is the difference between the actual and the desired arrival times. The delays at the bottlenecks are modeled with a deterministic queueing model that determines waiting time as a function of the length of the queue at the time of arrival at the bottleneck. The day to day adjustment of the distribution of traffic is derived from a dynamic Markovian model. The model is used to perform simulation experiments. The results demonstrate the response of the traffic conditions at the bottlenecks to a change in the system. The model is used to analyze the impacts of alternative pricing policies and preferential treatment of high occupancy vehicles.