Pedestrian Safety: Drivers’ Stopping Behavior at Crosswalks

David Nkurunziza (), Rahman Tafahomi and Irumva Augustin Faraja
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David Nkurunziza: College of Science and Technology, University of Rwanda, Kigali P.O. Box 3900, Rwanda
Rahman Tafahomi: College of Science and Technology, University of Rwanda, Kigali P.O. Box 3900, Rwanda
Irumva Augustin Faraja: College of Science and Technology, University of Rwanda, Kigali P.O. Box 3900, Rwanda

Sustainability, 2023, vol. 15, issue 16, 1-17

Abstract: The safety of a pedestrian crossing may depend on infrastructure, vehicular and pedestrian traffic characteristics. This academic research typically portrays the safety challenges knowingly caused by vehicles on crosswalks in the city of Kigali. Through carefully observing the stopping of local drivers in pedestrian crossing events, the study aims to objectively evaluate drivers’ questionable behavior against traffic flow parameters. Ten collection sites were ultimately selected purposefully and randomly to suit observations for data recording. A grand total of 10,259 crossing events were properly recorded within 280 h. Statistical analyses, practical tests and binary logistic regression models were promptly used to adequately evaluate the specific behaviors. Woefully, 82.4% of drivers violate crosswalks, endangering crossing pedestrians. Motorcyclists typically exhibit the most aggressive behavior. Car drivers are relatively less aggressive, whereby 60% managed to brake in the events. Local buses and authorized bicycles enthusiastically shared a negligible collective percentage of 2%, being aggressive and not stopping. In general, cars are 10.389 times more likely to voluntarily and justly stop compared to bicycles. Maintaining more vehicles in a row is safer for a pedestrian to cross, as for each unit increase on the vehicle density scale, there were 1.956 more chances that every driver would stop. In brief, 13% to 21% of traffic variables positively predict the considerable variance in the stopping behavior model.

Keywords: pedestrian safety; traffic characteristics; city of Kigali; binary logistic regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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