A two-dimensional surrogate safety measure based on fuzzy logic model
Accid Anal Prev. 2024 Mar 4;199:107529. doi: 10.1016/j.aap.2024.107529. Online ahead of print.ABSTRACTSurrogate Safety Measures (SSM) are extensively applied in safety analysis and design of active vehicle safety systems. However, most existing SSM focus only on the one-dimensional interactions along the vehicle traveling direction and cannot handle the crash risks associated with vehicle lateral movements such as sideswipes and angle crashes. To bridge this important knowledge gap, this study proposes a two-dimensional SSM defined based on Fuzzy Logic and the Inverse Time to Collision (FL-iTTC), which accounts for neighbo...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Yueru Xu Wei Ye Yuanchang Xie Chen Wang Source Type: research
Spot speed cameras in a series - Effects on speed and traffic safety
In conclusion, the Swedish strategy with spot speed cameras in a series led to an increased speed compliance and a comprehensive reduction in mean speeds and of the number of fatalities.PMID:38442631 | DOI:10.1016/j.aap.2024.107525 (Source: Accident; Analysis and Prevention.)
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Anna Vadeby Christian Howard Source Type: research
Quantification of safety improvements and human-machine tradeoffs in the transition to automated driving
Accid Anal Prev. 2024 Mar 4;199:107523. doi: 10.1016/j.aap.2024.107523. Online ahead of print.ABSTRACTThe assumption of reduced human error-related crashes with increasing levels of automation in pursuing Level 5 automation lacks empirical evidence. As automation levels rise, human error-induced safety hazards are anticipated to decrease, while machine error-induced hazards will increase. However, a quantitative index capturing this tradeoff is absent. Additionally, theoretical modeling of safety improvements during the transition to automated driving remains unexplored, particularly concerning reducing human error-related...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Song Wang Zhixia Li Yi Wang Wenjing Zhao Heng Wei Source Type: research
Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics
Accid Anal Prev. 2024 Mar 4;199:107517. doi: 10.1016/j.aap.2024.107517. Online ahead of print.ABSTRACTPedestrians represent a group of vulnerable road users who are at a higher risk of sustaining severe injuries than other road users. As such, proactively assessing pedestrian crash risks is of paramount importance. Recently, extreme value theory models have been employed for proactively assessing crash risks from traffic conflicts, whereby the underpinning of these models are two sampling approaches, namely block maxima and peak over threshold. Earlier studies reported poor accuracy and large uncertainty of these models, w...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Fizza Hussain Yasir Ali Yuefeng Li Md Mazharul Haque Source Type: research
A two-dimensional surrogate safety measure based on fuzzy logic model
Accid Anal Prev. 2024 Mar 4;199:107529. doi: 10.1016/j.aap.2024.107529. Online ahead of print.ABSTRACTSurrogate Safety Measures (SSM) are extensively applied in safety analysis and design of active vehicle safety systems. However, most existing SSM focus only on the one-dimensional interactions along the vehicle traveling direction and cannot handle the crash risks associated with vehicle lateral movements such as sideswipes and angle crashes. To bridge this important knowledge gap, this study proposes a two-dimensional SSM defined based on Fuzzy Logic and the Inverse Time to Collision (FL-iTTC), which accounts for neighbo...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Yueru Xu Wei Ye Yuanchang Xie Chen Wang Source Type: research
Spot speed cameras in a series - Effects on speed and traffic safety
In conclusion, the Swedish strategy with spot speed cameras in a series led to an increased speed compliance and a comprehensive reduction in mean speeds and of the number of fatalities.PMID:38442631 | DOI:10.1016/j.aap.2024.107525 (Source: Accident; Analysis and Prevention.)
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Anna Vadeby Christian Howard Source Type: research
Quantification of safety improvements and human-machine tradeoffs in the transition to automated driving
Accid Anal Prev. 2024 Mar 4;199:107523. doi: 10.1016/j.aap.2024.107523. Online ahead of print.ABSTRACTThe assumption of reduced human error-related crashes with increasing levels of automation in pursuing Level 5 automation lacks empirical evidence. As automation levels rise, human error-induced safety hazards are anticipated to decrease, while machine error-induced hazards will increase. However, a quantitative index capturing this tradeoff is absent. Additionally, theoretical modeling of safety improvements during the transition to automated driving remains unexplored, particularly concerning reducing human error-related...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Song Wang Zhixia Li Yi Wang Wenjing Zhao Heng Wei Source Type: research
Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics
Accid Anal Prev. 2024 Mar 4;199:107517. doi: 10.1016/j.aap.2024.107517. Online ahead of print.ABSTRACTPedestrians represent a group of vulnerable road users who are at a higher risk of sustaining severe injuries than other road users. As such, proactively assessing pedestrian crash risks is of paramount importance. Recently, extreme value theory models have been employed for proactively assessing crash risks from traffic conflicts, whereby the underpinning of these models are two sampling approaches, namely block maxima and peak over threshold. Earlier studies reported poor accuracy and large uncertainty of these models, w...
Source: Accident; Analysis and Prevention. - March 5, 2024 Category: Accident Prevention Authors: Fizza Hussain Yasir Ali Yuefeng Li Md Mazharul Haque Source Type: research
Safety performance evaluation of freeway merging areas under autonomous vehicles environment using a co-simulation platform
Accid Anal Prev. 2024 Mar 3;199:107530. doi: 10.1016/j.aap.2024.107530. Online ahead of print.ABSTRACTMerging areas serve as the potential bottlenecks for continuous traffic flow on freeways. Traffic incidents in freeway merging areas are closely related to decision-making errors of human drivers, for which the autonomous vehicles (AVs) technologies are expected to help enhance the safety performance. However, evaluating the safety impact of AVs is challenging in practice due to the lack of real-world driving and incident data. Despite the increasing number of simulation-based AV studies, most relied on single traffic/vehi...
Source: Accident; Analysis and Prevention. - March 4, 2024 Category: Accident Prevention Authors: Peng Chen Haoyuan Ni Liang Wang Guizhen Yu Jian Sun Source Type: research
Safety performance evaluation of freeway merging areas under autonomous vehicles environment using a co-simulation platform
Accid Anal Prev. 2024 Mar 3;199:107530. doi: 10.1016/j.aap.2024.107530. Online ahead of print.ABSTRACTMerging areas serve as the potential bottlenecks for continuous traffic flow on freeways. Traffic incidents in freeway merging areas are closely related to decision-making errors of human drivers, for which the autonomous vehicles (AVs) technologies are expected to help enhance the safety performance. However, evaluating the safety impact of AVs is challenging in practice due to the lack of real-world driving and incident data. Despite the increasing number of simulation-based AV studies, most relied on single traffic/vehi...
Source: Accident; Analysis and Prevention. - March 4, 2024 Category: Accident Prevention Authors: Peng Chen Haoyuan Ni Liang Wang Guizhen Yu Jian Sun Source Type: research
High-risk event prone driver identification considering driving behavior temporal covariate shift
Accid Anal Prev. 2024 Mar 2;199:107526. doi: 10.1016/j.aap.2024.107526. Online ahead of print.ABSTRACTDrivers who perform frequent high-risk events (e.g., hard braking maneuvers) pose a significant threat to traffic safety. Existing studies commonly estimated high-risk event occurrence probabilities based upon the assumption that data collected from different time periods are independent and identically distributed (referred to as i.i.d. assumption). Such approach ignored the issue of driving behavior temporal covariate shift, where the distributions of driving behavior factors vary over time. To fill the gap, this study t...
Source: Accident; Analysis and Prevention. - March 3, 2024 Category: Accident Prevention Authors: Ruici Zhang Xiang Wen Huanqiang Cao Pengfei Cui Hua Chai Runbo Hu Rongjie Yu Source Type: research
What can we learn from the AV crashes? - An association rule analysis for identifying the contributing risky factors
The objective of this study is to explore the contributing risky factors to Autonomous Vehicle (AV) crashes and their interdependencies. AV crash data between 2015 and 2023 were collected from the autonomous vehicle collision report published by California Department of Motor Vehicles (DMV). AV crashes were categorized into four types based on vehicle damage. AV crashes features including crash location and time, driving mode, vehicle movements, crash type and vehicle damage, traffic conditions, and among others were used as potential risk factors. Association Rule Mining methods (ARM) were utilized to identify sets of con...
Source: Accident; Analysis and Prevention. - March 1, 2024 Category: Accident Prevention Authors: Pei Liu Yanyong Guo Pan Liu Hongliang Ding Jiandong Cao Jibiao Zhou Zhongxiang Feng Source Type: research
Critical risk factors associated with fatal/severe crash outcomes in personal mobility device rider at-fault crashes: A two-step inter-cluster rule mining technique
This study addresses this gap by identifying uniform groups of PMD rider-at-fault crashes and investigating cluster-specific key factor associations and determinants of fatal/severe crash outcomes using Seoul's PMD rider-at-fault crash data from 2017 to 2021. A comprehensive two-step framework, integrating Cluster Correspondence Analysis (CCA) and Association Rules Mining (ARM) techniques is employed to segment PMD rider-at-fault crash data into homogeneous groups, revealing unique risk factor patterns within each cluster and further exploring the combination of factors associated with fatal/severe PMD rider-at-fault crash...
Source: Accident; Analysis and Prevention. - March 1, 2024 Category: Accident Prevention Authors: Reuben Tamakloe Kaihan Zhang Ahmed Hossain Inhi Kim Shin Hyoung Park Source Type: research
Crash risk estimation of Heavy Commercial vehicles on horizontal curves in mountainous terrain using proactive safety method
This study addresses this gap by employing an SSM known as anticipated collision time (ACT) to explore the impact of horizontal curves on the crash risk of HCVs in mountainous terrain. To perform the crash risk analysis, a collection of videos was gathered from horizontal curves in the mountainous terrain along the Guwahati-Shillong bypass in the Northeastern region of India. Subsequently, trajectories were extracted from these videos using semi-automated image processing software. Traffic conflicts were identified using ACT, and the crash risk was estimated through the Peak-Over Threshold (POT) approach of the Extreme Val...
Source: Accident; Analysis and Prevention. - March 1, 2024 Category: Accident Prevention Authors: Pranab Kar Suvin P Venthuruthiyil Mallikarjuna Chunchu Source Type: research
Real-time combined safety-mobility assessment using self-driving vehicles collected data
Accid Anal Prev. 2024 Feb 29;199:107513. doi: 10.1016/j.aap.2024.107513. Online ahead of print.ABSTRACTThe study presents a real-time safety and mobility assessment approach using data generated by autonomous vehicles (AVs). The proposed safety assessment method uses Bayesian hierarchical spatial random parameter extreme value model (BHSRP), which can handle the limited availability and uneven distribution of conflict data and accounts for unobserved spatial heterogeneity. The approach estimates two real-time safety metrics: the risk of crash (RC) and return level (RL), using Time-To-Collision (TTC) as conflict indicator. ...
Source: Accident; Analysis and Prevention. - March 1, 2024 Category: Accident Prevention Authors: Ahmed Kamel Tarek Sayed Mohamed Kamel Source Type: research
