Members of the University of Florida Transportation Institute, along with researchers from Florida International University (FIU), developed a new procedure for optimizing signal control considering environmental and safety impacts.  The results of the work have been implemented into the Highway Capacity Software (http://mctrans.ce.ufl.edu/mct/index.php/HCS7/).  The research was funded by the US DOT through the STRIDE Center (provide STRIDE website), and it is documented in a report titled “Signal Timing Optimization with Consideration of Environmental and Safety Impacts”  and authored by Gustavo R. de Andrade, Dr. Lily Elefteriadou, Lei Zhang, Bill Sampson and Vishal Khanapure from UF and  Dr. Mohammed Hadi from FIU.

The main performance indicators  used in  setting signal timings  have traditionally focused on  mobility (for example delays, travel time, speed, and queue length).  The goal of this study was to develop a signal timing optimization algorithm that could consider mobility, safety, and environmental measures simultaneously in order to produce optimal signal timings along coordinated arterials. The objectives of the research were: (a) review relevant research that could be used to evaluate safety at signalized intersections as a function of various signal timing -related parameters, (b) select a prediction model to estimate the probability of crash occurrence as a function of intersection characteristics and signal control, (c) develop a methodology for optimizing signal control in terms of safety (crashes), environmental impacts (emissions), and mobility  (delay), (d) implement the proposed methodology in the Highway Capacity Software, and (e) conduct a sensitivity analysis of the model results to gain an understanding of the optimal performance measures obtained as a function of key variables that affect mobility, safety, and emissions outputs.

Optimization results and statistical analysis of the sensitivity scenarios showed that the effect of each variable on the overall performance of the model is highly dependent on other variables. For example, the use of shared turns and permitted left could improve both mobility and safety to a degree which is a function of the traffic volumes and turning percentage levels. The size of the intersection, defined as a function of the number of lanes on the arterial, was found to be the most significant variable in the model, largely affecting all performance measures.