Abstract:
This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic and tests whether greater traffic reduces the per-vehicle crash rate, a phenomenon referred to as “safety in numbers” (SIN). We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Testing a two-part model of crashes, we reveal that both the average of annual average daily traffic (AADT) over a 14-year period and the estimated daily bicyclist traffic (DBT) have a diminishing return to scale in crashes. This accentuates the positive role of SIN. Higher volumes of vehicles and cyclists lowers not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the average of AADT across the time window increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the estimated DBT increases the probability of crashes by 0.09% and the number of crashes by 0.50%.
