Estimating Average Automobile Occupancy from Accident Data in New York State

Abstract

Average automobile occupancy (AAO) data are valuable input to congestion management systems (CMS). Continuous field collection of these data at the system level has been lacking because of high costs associated with current data collection methodology. It is shown how the New York State Department of Transportation (NYSDOT) has built upon prior research by the Connecticut Department of Transportation, which uses traffic accident data to calculate estimates of vehicle occupancy, and has tailored the process to meet NYSDOT's CMS needs. Accident data covering a 3-year period are used to estimate AAOs by county, year of occurrence, month of year, day of week, and time-of-day intervals. Occupancy rates are calculated to be lowest during the morning peak traffic period and highest during the evening period between 6:00 and 11:00 p.m. Occupancy rates are highest for summer months and lowest for winter months. Occupancy rates are highest for the weekends and lowest for weekdays. Accident-based AAOs are compared to multiple-station roadside-observed AAOs. Adjustment factors are developed to convert the former to be comparable to the latter. It is concluded that using accident data to estimate AAO is a viable and economical approach to continuous monitoring of system-level AAO performance. NYSDOT is currently using accident-based AAO data as an integral part of its CMS.

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