Prediction of motorcyclist traffic crashes in Cartagena (Colombia): development of a safety performance function

Motorcyclists account for more than 380 000 deaths annually worldwide from road traffic accidents. are the most vulnerable users to safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% low- or middle-income countries. Colombia has a rate 9.7 per 100 inhabitants, which places it 10th in world. Motorcycles correspond 57% fleet generate an average 51% fatalities year. This study aims identify significant factors environment, volume, infrastructure predict number accidents year focused only on motorcyclists. The prediction model used negative binomial regression definition Safety Performance Function (SPF) In second stage, Bayes’ empirical approach is implemented motorcycle crash-prone sections. applied Cartagena, one capital cities crashes motorcyclists dedicated informal transportation (motorcycle taxi riders) Colombia. data 2884 between 2016 2017 analyzed. proposed identifies that kilometer have such as volume daily motorcyclist traffic, accesses (intersections) kilometer, commercial areas, type 55 critical accident-prone research evidences coherent consistent results previous studies requires effective countermeasures benefit