Traffic Signal Timing Optimization

Choosing an appropriate objective function in optimizing traffic signals in urban transportation networks is not a simple and straightforward task because the choice likely will affect the set of constraints, modeling variables, obtained outputs, and necessary computer and human resources. A methodology for selection of an appropriate objective function for the problem of signal timing optimization was developed. The methodology was applied to a realistic case study network under four demand patterns (symmetric, asymmetric, undersaturated, oversaturated). Selection is made from a pool of five candidates: minimizing the delay, minimizing the travel time, maximizing the throughput-minus-queue, maximizing the number of completed trips (or trip maximization), and maximizing the weighted number of completed trips (or weighted trip maximization). Findings indicate that for all demand patterns, weighted trip maximization improved network performance compared with the other objective functions. Weighted trip maximization reduced system total delay by 0.1% to 5.2% in symmetric undersaturated demand, by 1.0% to 2.4% in asymmetric undersaturated demand, by 1.2% to 16.6% in symmetric oversaturated demand, and by 11.7% to 27.4% in asymmetric partially oversaturated demand. These figures indicate that the weighted trip maximization objective function is the most suitable of the candidates in oversaturated conditions, especially when demand is not symmetric. Throughput-minus-queue and trip maximization were the second most suitable objective functions for oversaturated conditions, and trip maximization was slightly more suitable when demand was asymmetric.