Assessing the Economic Impact of Speed Limit Changes on Safety and Mobility in California

This project estimates the safety and mobility impact of changing speed limits on California highways. The safety impact is estimated using statistical models to predict the change in the frequency of all crashes and fatal-or-severe crashes that would result by varying the design speed (85th percentile speed). Statewide crash and traffic data (from the Statewide Integrated Traffic Records System, the Highway Safety Information System, and the Performance Measurement System) were combined to develop a balanced and sampled dataset for the statistical models. Three different increases in differential speed limits (DSLs; whereby trucks and cars have different speed limits) lead to increases in the frequency of all crashes, including fatal and severe crashes, for all of the classified segments (urban, rural, and different design speed segments). The operational condition (speed, travel time, delay) is tested using seven simulation segments with urban-rural classification. Four different DSL scenarios and four uniform speed limit (USL) scenarios are tested for each of the simulation segments. The results show a decrease of travel time but an increase of fuel consumption as the speed limits get higher. The safety cost of crashes and operational costs were also estimated based on the simulation models. In general, as the speed limits are increased, the safety costs increase with the predicted increases in crashes, particularly severe and fatal crashes. The operational costs, on the other hand, generally decrease as the speed limits are increased. However, the amount of operational cost decreases are subject to greater uncertainty than the safety cost estimates are, due to uncertainties in sampling and demand estimation and in negligence of construction costs of roadway and signage changes to accommodate the new speed limits. From the economic perspective in this study, raising speed limits on rural California highways could reduce monetary costs, as savings in operational costs would exceed losses from more crashes.