Haiyan Hao1, Yingfeng Eric Li2, Alejandra Medina3, Ronald B Gibbons4, Linbing Wang5. 1. Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24060, United States. Electronic address: haiyan94@vt.edu. 2. Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24060, United States. Electronic address: eli@vtti.vt.edu. 3. Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24060, United States. Electronic address: amedina@vtti.vt.edu. 4. Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24060, United States. Electronic address: rgibbons@vtti.vt.edu. 5. Virginia Polytechnic Institute and State University, 750 Drillfield Drive, 200 Patton Hall, Blacksburg, VA 24061, United States. Electronic address: wangl@vt.edu.
Abstract
INTRODUCTION: Crashes involving roadway objects and animals can cause severe injuries and property damages and are a major concern for the traveling public, state transportation agencies, and the automotive industry. This project involved an in-depth investigation of such crashes based on the second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS) data including detailed information and videos about 2,689 events. METHODS: The research team conducted a variety of logistic regression analyses, complemented by Support Vector Machine (SVM) analyses and detailed case studies. RESULTS: The logistic regression results indicated that driver behavior/errors, involvement of secondary tasks, roadway characteristics, lighting condition, and pavement surface condition are among the factors that contributed significantly to the occurrence and/or increased severity outcomes of crashes involving roadway objects and animals. Among these factors, improper turning movements (odds ratio = 88), avoiding animal or other vehicle (odds ratio = 38), and reaching/moving object in vehicle (odds ratio = 29) particularly increased the odds of crash occurrence. Factors such as open country roadways, sign/signal violation, unfamiliar with roadway, fatigue/drowsiness, and speeding significantly increased the severity outcomes when such crashes occurred. The sensitivity analysis of the three SVM classifiers confirmed that driver behavior/errors, critical speed, struck object type, and reaction time were major factors affecting the occurrence and severity outcomes of events involving roadway objects and animals. Practical Applications: The study provides insights on risk factors influencing safety events involving roadway objects, including their occurrence and the severity outcomes. The findings allow researchers and traffic engineers to better understand the causes of such crashes and therefore develop more effective roadway- and vehicle- based countermeasures. Published by Elsevier Ltd.
INTRODUCTION: Crashes involving roadway objects and animals can cause severe injuries and property damages and are a major concern for the traveling public, state transportation agencies, and the automotive industry. This project involved an in-depth investigation of such crashes based on the second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS) data including detailed information and videos about 2,689 events. METHODS: The research team conducted a variety of logistic regression analyses, complemented by Support Vector Machine (SVM) analyses and detailed case studies. RESULTS: The logistic regression results indicated that driver behavior/errors, involvement of secondary tasks, roadway characteristics, lighting condition, and pavement surface condition are among the factors that contributed significantly to the occurrence and/or increased severity outcomes of crashes involving roadway objects and animals. Among these factors, improper turning movements (odds ratio = 88), avoiding animal or other vehicle (odds ratio = 38), and reaching/moving object in vehicle (odds ratio = 29) particularly increased the odds of crash occurrence. Factors such as open country roadways, sign/signal violation, unfamiliar with roadway, fatigue/drowsiness, and speeding significantly increased the severity outcomes when such crashes occurred. The sensitivity analysis of the three SVM classifiers confirmed that driver behavior/errors, critical speed, struck object type, and reaction time were major factors affecting the occurrence and severity outcomes of events involving roadway objects and animals. Practical Applications: The study provides insights on risk factors influencing safety events involving roadway objects, including their occurrence and the severity outcomes. The findings allow researchers and traffic engineers to better understand the causes of such crashes and therefore develop more effective roadway- and vehicle- based countermeasures. Published by Elsevier Ltd.