Selection of a Traffic Control Strategy for Long-Range Travel Forecasting

The problem of determining the number and placement of signals on traffic networks for long-range urban travel forecasting is addressed. An algorithm for determining the signalization strategy was developed and given a large-scale test on the network for a metropolitan area of about 150,000 people. The algorithm attempts to mimic the actions of traffic engineers as they make adjustment to the traffic system over a long period of time. Tests indicate that the algorithm produces a network that closely approximates one that has been optimized for vehicle hours traveled but still respects safety and fairness issues. The algorithm is highly computational, so limits needed to be arbitrarily placed on the precision of the traffic forecast, the precision of optimization steps, and the number of intermediate forecast years.