In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.
Gilardi, A., Borgoni, R., Zappa, D. (2019). Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan. In Book of Short Papers SIS2019 (pp.1165-1170). Pearson.
Spatial Logistic Regression for Events Lying on a Network: Car Crashes in Milan
Andrea Gilardi
;Riccardo Borgoni;
2019
Abstract
In this paper we propose a methodology to estimate the probability that a car accident occurs in urban roads. Our approach is based on logistic regression and takes into account the particular nature of the data which conforms to a spatial point pattern on a network. Using the open data on street networks provided within the OpenStreetMap project, we estimate the probability of car accidents for every street in the municipality of Milan.
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