Do the mobility patterns for city taxicabs impact road safety?

Abstract

Recently, large investments have been made by cities such as Singapore, New York City, and London towards creating smart city initiatives in the areas of traffic safety enhancement and higher mobility. In this article, we investigate the impact of various network topology measures on the number of vehicle crashes in a city mobility network. Extant literature on mobility in city traffic networks has not studied the impact of network structure on road accidents. We fill this important gap by identifying the structural properties of critical zones in the city traffic network, which have a high risk of vehicle crashes. We use econometric methods to analyze a large dataset on city mobility from the New York Taxi and Limousine Commission, and a dataset on motor vehicle collisions from the New York Police Department

and derive various insights on the scope of traffic safety issues in a smart city. Our dataset has information on about 100,000,000 taxi trips over the year 2018. In this year, around 1,500,000 vehicle crash events were reported in New York City. One would expect that due to a large number of shortest paths, the number of accidents should be significantly more in the high betweenness centrality zones in the traffic mobility network. However, our analysis reveals that zones with high betweenness centrality tend to have a lower number of accidents. Furthermore, zones with a high degree centrality in the traffic mobility network are associated with a higher number of vehicle crash incidents. Our study reveals some crucial pointers for smart city policymakers and the operations managers of ride-sharing companies on how information on the mobility patterns of the high accident risk zones can be leveraged to reduce motor vehicle collisions.