| description abstract | There is an increasing interest in signal-timing optimization methods that can consider mobility, safety, and emissions measures simultaneously. The introduction of new models increases the complexity of the required inputs and the relationships between inputs and outputs. This study developed and implemented such a method in an existing computational engine, presenting a sensitivity analysis conducted to provide insight on the effects and order of relevance of 20 key variables on the model’s outcomes and the associated trade-offs among mobility, safety, and emissions. This insight will help the designer, signal control engineer, and traffic analyst when designing intersection geometry and signal control. The statistical analysis of the results showed that the effect of each variable on the overall performance of the model is highly dependent on the combination of other variables. The traffic demand and the size of the intersection, defined by the number of lanes on the arterial, were found to be the most significant variables, affecting all performance measures. Mobility improvement performance usually coincides with emissions improvements, but sometimes occurs at the expense of safety. | |
