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Articles 1 - 3 of 3
Full-Text Articles in Automotive Engineering
Crash Severity Analysis Of Rear-End Crashes In California Using Statistical And Machine Learning Classification Methods, Alidad Ahmadi, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Crash Severity Analysis Of Rear-End Crashes In California Using Statistical And Machine Learning Classification Methods, Alidad Ahmadi, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Psychology Faculty Articles and Research
Investigating drivers’ injury level and detecting contributing factors that aggravate the damage level imposed on drivers and vehicles is a critical subject in the field of crash analysis. In this study, a comprehensive vehicle-by-vehicle crash data set is developed by integrating 5 years of data from California crash, vehicles involved, and road databases. The data set is used to model the severity of rear-end crashes for comparing three analytic techniques: multinomial logit, mixed multinomial logit, and support vector machine (SVM). The results of the crash severity models and the role of contributing factors to the severity outcome of rear-end crashes …
Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Psychology Faculty Articles and Research
The emerging technology of connected vehicles generates a vast amount of data that could be used to enhance roadway safety. In this paper, we focused on safety applications of a real field connected vehicle data on a horizontal curve. The database contains connected vehicle data that were collected on public roads in Ann Arbor, Michigan with instrumented vehicles. Horizontal curve negotiations are associated with a great number of accidents, which are mainly attributed to driving errors. Aggressive/risky driving is a contributing factor to the high rate of crashes on horizontal curves. Using basic safety message data in connected vehicle data …
Investigating The Relationship Between Latent Driving Patterns And Traffic Safety Using Smartphone-Based Mobile Sensor Data, Kenneth Wynne
Investigating The Relationship Between Latent Driving Patterns And Traffic Safety Using Smartphone-Based Mobile Sensor Data, Kenneth Wynne
Civil & Environmental Engineering Theses & Dissertations
Crash frequency modelling has been used in the past as an attempt to quantify the expected number of crashes occurring on a certain segment of roadway given a set of variables and factors describing the roadway segment and the traffic along that segment. These models are referred to as the Safety Performance Functions (SPFs) in the Highway Safety Manual (HSM). In past studies, these SPFs have focused primarily on roadway geometric information along with limited traffic exposure data such as traffic volume. Alternate data sources for probe vehicle data are increasingly available and this research sought to exploit this new …