Macroscopic Spatial Analysis of Pedestrian Crashes in Medellin, Colombia

Abstract

Pedestrians are regarded as vulnerable road users as they experience the most severe consequences in collisions with motor vehicles. Pedestrians were involved in fewer than 4% of all traffic accidents but represented more than 12% of traffic fatalities in Medellin, Colombia, from 2009 to 2016. A better understanding of the factors affecting the likelihood of such accidents is an area of interest across local and governmental agencies in Colombia. The paper provides a spatial lag model estimated using spatial two–stage least squares (S2SLS) method to analyze the impact of land use, socioeconomic factors, and transportation modes on vehicle–pedestrian collisions (“crashes”). Consideration is given to spatial spillovers, avoiding inconsistent and inefficient estimates. Commercial land use has a positive correlation with the number of crashes while residential land use correlates with fewer crashes. Analysis of transportation modes demonstrated a higher risk of crashes associated with public transit. In Medellin, buses stop at the passenger’s request instead of at regular bus stops, which increases the likelihood of pedestrians being involved in accidents. The effect of taxi as transportation mode, however, analysed using the number of taxi stands as proxy, is that the number of crashes is reduced. In this transportation mode, the entire trip is covered from point of origin to destination, reducing exposure to the risks of walking. These results might provide a better understanding of the dynamics involved in pedestrian crashes while validating the importance of including spatial econometrics for safety analysis.

Unveiling the relevance of traffic enforcement cameras on the severity of vehicle–pedestrian collisions in an urban environment with machine learning models

“…Unfortunately, the amount of traffic collisions in the city displays a growing trend that concerns the local government. According to Lizarazo and Valencia (2018), pedestrians are one of the most vulnerable groups in this city. Although they were involved in less than 4% of all traffic collisions, they represent more than 12% of the traffic fatalities from 2009 to 2016.…”

Estimation of Safety Performance Functions (SPF) at signalized intersections in Medellín Colombia

“…Statistical models that predict crash frequency and severity have not been commonly used in developing countries. For instance, there are two studies that estimated crash severity using the Medellin database, one by Mesa-Arango et al that used a multinomial logit model (MNL) and one by Lizarazo and Valencia that used a spatial macroscopic approach for studying pedestrian-car collisions [7,8].…”