Traffic safety has been a major concern in many developing countries overthe past 2 decades. Rapid growth in car-ownership/ usage in contrast withslow cultural adaptation has made a great enemy out of road transportation. Current practice regarding crashes is mainly based on short-term traffic engineering measures. However, one important issue in dealing with traffic crashes is long-range safety plans that account for future changes in transportation demand. This requires specialized tools and methods to predict current and future number of crashes. One such a tool is Aggregate (macro) Crash Prediction Models (ACPM). This research paper introduces crash generation models (CGM) that are developed based on the trip generation phase of the four step demand modeling technique. The models are capable of forecasting future number of crashes in urban traffic analysis zones (TAZ) based on the forecasted number of trips generated by purpose. CGMs may be used for immediate checking of the impact of future trip generations on crash frequencies in comprehensive transportation planning studies (i.e. ability to forecast crashes at each time-step trips are being forecasted). They will help safety planners develop travel demand management scenarios and simultaneously assess their perceived impact on the overall safety of the urban areas. The models prove an effective step towards incorporating safety into long-range transportation planning.
Samenvatting