Crash Prediction Method for Freeway Facilities with High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT) Lanes

This study developed methods for estimating the expected crash frequency of urban freeway segments with High Occupancy Vehicle (HOV) or High Occupancy Toll (HOT) lanes. The safety impacts of the type of separation between the managed lanes and general purpose lanes were examined. Separate models were estimated for fatal and injury (FI) crashes and all crashes. The models for facilities with HOV lanes were estimated using five years’ of data from California, Washington, and Florida. All these facilities have one HOV in each direction (included in the count of total number of lanes). The effect of separation type on crash rates is found to be statistically significant only in the models for ten-lane facilities. The models for freeways with HOT lanes were estimated using four years’ of data from 27 miles (48 segments) of freeways from the states of California, Texas, and Florida. All these facilities have two HOT lanes in each direction. Facilities with a 1-foot separation are estimated to have more crashes than those that have a 3-foot separation which in turn have more crashes than facilities with a 20-foot separation. All the estimated models have been implemented in a spreadsheet program which will enable analysts to apply these equations for crash prediction. Overall, this study provides procedures that will help Florida Department of Transportation (FDOT) consider safety in decisions about planning and designing freeways with HOV or HOT lanes.

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