Investigating the dynamics of collective behavior among pedestrians crossing roads: A multi-user virtual reality approach
Accid Anal Prev. 2024 Feb 15;199:107477. doi: 10.1016/j.aap.2024.107477. Online ahead of print.ABSTRACTThe utility maximization theory, based on the rationality of human beings, has proven effective in modeling pedestrians' decision-making processes while crossing roads. However, there are still unexplained variations in crossing behavior, and deviations from the rational utility model frequently occur in real-life scenarios. This experimental study sheds new light on the presence of inter-individual interactions among pedestrians and the nature of collective behaviors during road crossings. The present study develops a mu...
Source: Accident; Analysis and Prevention. - February 16, 2024 Category: Accident Prevention Authors: Jae-Hong Kwon Jinho Won Gi-Hyoug Cho Source Type: research
Modeling occupant injury severities for electric-vehicle-involved crashes using a vehicle-accident bi-layered correlative framework with matched-pair sampling
This study seeks to investigate occupant injury severities for electric-vehicle-involved crashes and inspect if electric vehicles lead to more serious injuries than fuel-powered vehicles, which have commonly been neglected in past studies. A Bayesian random slope model is proposed aiming to capture interactions between occupant injury severity levels and electric vehicle variable. The random slope model is developed under a vehicle-accident bi-layered correlative framework, which can account for the interactive effects of vehicles in the same accident. Based on the crash report sampling system (CRSS) 2020 and 2021 database...
Source: Accident; Analysis and Prevention. - February 16, 2024 Category: Accident Prevention Authors: Qi Yu Lu Ma Xuedong Yan Source Type: research
Investigation on the dynamic characteristic of occupant during the frontal collision between high-speed train and obstacle
This study aims to investigate the dynamic characteristic of occupant during the frontal collision between high-speed train and obstacle. The finite element method was used to establish the collision model between the head vehicle of the train and obstacle. The frontal collision simulation tests under three collision conditions were established. The dynamic characteristics of occupants under different collision speeds and collision angles were explored. According to the above research, the influences of collision angle and speed on occupant injuries were systematically studied, and the risk boundaries for Railway Group Sta...
Source: Accident; Analysis and Prevention. - February 16, 2024 Category: Accident Prevention Authors: Shuguang Yao Lingxiang Kong Ping Xu Xianliang Xiao Yong Peng Source Type: research
Short-term Safety Performance Functions by Random Parameters Negative Binomial-Lindley model for Part-time Shoulder Use
This study contributes to the safety literature by analyzing various potential crash contributing factors related to PTSU operation and design elements through the development of short-term Safety Performance Functions (SPFs). A comparison of the estimated models demonstrated that by utilizing the mixed distribution and allowing the posterior parameter estimates of explanatory variables to vary from one observation to another, the Random Parameters Negative Binomial-Lindley (RPNB-L) model outperformed the traditional NB and fixed coefficient NB-L models. The results of the proposed RPNB-L model indicated that the PTSU impl...
Source: Accident; Analysis and Prevention. - February 15, 2024 Category: Accident Prevention Authors: Tarek Hasan Mohamed Abdel-Aty Source Type: research
Assessing the effectiveness of psychoeducational interventions on driving behavior: A systematic review and meta-analysis
Accid Anal Prev. 2024 Feb 14;199:107496. doi: 10.1016/j.aap.2024.107496. Online ahead of print.ABSTRACTThis review aimed to quantitatively summarize the evidence concerning the effectiveness of psychoeducational interventions on driving behavior. A final pool of 138 studies, totaling approximately 97,000 participants, was included in the analyses and covered all types of driving behavior targeted by the interventions. Using a random effects model, significant results were found for almost all driving outcomes, both post-intervention and long-term. The strongest effect was for reducing distracted driving at post-interventio...
Source: Accident; Analysis and Prevention. - February 15, 2024 Category: Accident Prevention Authors: Lorena Tirla Paul S ârbescu Andrei Rusu Source Type: research
Short-term Safety Performance Functions by Random Parameters Negative Binomial-Lindley model for Part-time Shoulder Use
This study contributes to the safety literature by analyzing various potential crash contributing factors related to PTSU operation and design elements through the development of short-term Safety Performance Functions (SPFs). A comparison of the estimated models demonstrated that by utilizing the mixed distribution and allowing the posterior parameter estimates of explanatory variables to vary from one observation to another, the Random Parameters Negative Binomial-Lindley (RPNB-L) model outperformed the traditional NB and fixed coefficient NB-L models. The results of the proposed RPNB-L model indicated that the PTSU impl...
Source: Accident; Analysis and Prevention. - February 15, 2024 Category: Accident Prevention Authors: Tarek Hasan Mohamed Abdel-Aty Source Type: research
Assessing the effectiveness of psychoeducational interventions on driving behavior: A systematic review and meta-analysis
Accid Anal Prev. 2024 Feb 14;199:107496. doi: 10.1016/j.aap.2024.107496. Online ahead of print.ABSTRACTThis review aimed to quantitatively summarize the evidence concerning the effectiveness of psychoeducational interventions on driving behavior. A final pool of 138 studies, totaling approximately 97,000 participants, was included in the analyses and covered all types of driving behavior targeted by the interventions. Using a random effects model, significant results were found for almost all driving outcomes, both post-intervention and long-term. The strongest effect was for reducing distracted driving at post-interventio...
Source: Accident; Analysis and Prevention. - February 15, 2024 Category: Accident Prevention Authors: Lorena Tirla Paul S ârbescu Andrei Rusu Source Type: research
Identifying contributing factors and locations of pedestrian severe crashes using hazard-based duration model
Accid Anal Prev. 2024 Feb 10;198:107500. doi: 10.1016/j.aap.2024.107500. Online ahead of print.ABSTRACTPedestrian safety remains a significant concern, with the growing number of severe pedestrian crashes resulting in substantial human and economic costs. Previous research into pedestrian crashes has extensively analyzed the influences of weather, lighting, and pedestrian demographics. However, these studies often overlook the critical spatial variables that contribute to pedestrian crashes. Our study aims to explore these overlooked spatial variables by examining the distance pedestrians travel before encountering a sever...
Source: Accident; Analysis and Prevention. - February 11, 2024 Category: Accident Prevention Authors: Anahita Kakhani Mohammad Jalayer Emmanuel Kidando Carlos Roque Deep Patel Source Type: research
Identifying contributing factors and locations of pedestrian severe crashes using hazard-based duration model
Accid Anal Prev. 2024 Feb 10;198:107500. doi: 10.1016/j.aap.2024.107500. Online ahead of print.ABSTRACTPedestrian safety remains a significant concern, with the growing number of severe pedestrian crashes resulting in substantial human and economic costs. Previous research into pedestrian crashes has extensively analyzed the influences of weather, lighting, and pedestrian demographics. However, these studies often overlook the critical spatial variables that contribute to pedestrian crashes. Our study aims to explore these overlooked spatial variables by examining the distance pedestrians travel before encountering a sever...
Source: Accident; Analysis and Prevention. - February 11, 2024 Category: Accident Prevention Authors: Anahita Kakhani Mohammad Jalayer Emmanuel Kidando Carlos Roque Deep Patel Source Type: research
Optimization of Forward Collision Warning Algorithm Considering Truck Driver Response Behavior Characteristics
Accid Anal Prev. 2024 Feb 9;198:107450. doi: 10.1016/j.aap.2023.107450. Online ahead of print.ABSTRACTForward collision warning (FCW) systems have been widely used in trucks to alert drivers of potential road situations so they can reduce the risk of crashes. Research on FCW use shows, however, that there are differences in drivers' responses to FCW alerts under different scenarios. Existing FCW algorithms do not take differences in driver response behavior into account, with the consequence that the algorithms' minimum safe distance assessments that trigger the warnings are not always appropriate for every driver or situa...
Source: Accident; Analysis and Prevention. - February 10, 2024 Category: Accident Prevention Authors: Yanli Bao Xuesong Wang Source Type: research
Investigating the impact of HMI on drivers' merging performance in intelligent connected vehicle environment
Accid Anal Prev. 2024 Feb 9;198:107448. doi: 10.1016/j.aap.2023.107448. Online ahead of print.ABSTRACTIntelligent Connected Vehicle (ICV) is considered one of the most promising active safety technologies to address current transportation challenges. Human-Machine Interface (HMI) plays a vital role in enhancing user driving experience with ICV technology. However, in an ICV environment, drivers may exhibit excessive reliance on HMI, resulting in diminished proactive observation and analysis of the road environment, and subsequently leading to a potential decrease in drivers' situational awareness. This reduced situational ...
Source: Accident; Analysis and Prevention. - February 10, 2024 Category: Accident Prevention Authors: Yugang Wang Nengchao Lyu Chaozhong Wu Zijun Du Min Deng Haoran Wu Source Type: research
A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity
This study first constructed a multidimensional indicator to quantify pedestrian exposure, considering factors such as Point of Interest (POI) attributes, POI intensity, traffic volume, and pedestrian walkability. Following risk interpolation and feature engineering, a comprehensive data source for risk prediction was formed. Finally, based on risk factors, the VT-NET deep learning network model was proposed, integrating the algorithmic characteristics of the VGG16 deep convolutional neural network and the Transformer deep learning network. The model involved training non-temporal features and temporal features separately....
Source: Accident; Analysis and Prevention. - February 9, 2024 Category: Accident Prevention Authors: Manze Guo Bruce Janson Yongxin Peng Source Type: research
Integrating visual large language model and reasoning chain for driver behavior analysis and risk assessment
Accid Anal Prev. 2024 Feb 7;198:107497. doi: 10.1016/j.aap.2024.107497. Online ahead of print.ABSTRACTDriver behavior is a critical factor in driving safety, making the development of sophisticated distraction classification methods essential. Our study presents a Distracted Driving Classification (DDC) approach utilizing a visual Large Language Model (LLM), named the Distracted Driving Language Model (DDLM). The DDLM introduces whole-body human pose estimation to isolate and analyze key postural features-head, right hand, and left hand-for precise behavior classification and better interpretability. Recognizing the inhere...
Source: Accident; Analysis and Prevention. - February 8, 2024 Category: Accident Prevention Authors: Kunpeng Zhang Shipu Wang Ning Jia Liang Zhao Chunyang Han Li Li Source Type: research
Modeling and analyzing self-resistance of connected automated vehicular platoons under different cyberattack injection modes
Accid Anal Prev. 2024 Feb 7;198:107494. doi: 10.1016/j.aap.2024.107494. Online ahead of print.ABSTRACTThe high-level integration and interaction between the information flow at the cyber layer and the physical subjects at the vehicular layer enables the connected automated vehicles (CAVs) to achieve rapid, cooperative and shared travel. However, the cyber layer is challenged by malicious attacks and the shortage of communication resources, which makes the vehicular layer suffer from system nonlinearity, disturbance randomness and behavior uncertainty, thus interfering with the stable operation of the platoon. So far, schol...
Source: Accident; Analysis and Prevention. - February 8, 2024 Category: Accident Prevention Authors: Dongyu Luo Jiangfeng Wang Yu Wang Jiakuan Dong Source Type: research
Lane-change intention recognition considering oncoming traffic: Novel insights revealed by advances in deep learning
This study constructs a high-fidelity simulated two-lane two-way road to develop a Transformer model that accurately recognizes LC intention. We propose a novel LC labelling algorithm combining vehicle dynamics and eye-tracking (VEL) and compare it against traditional time window labelling (TWL). We find the LC recognition accuracy can be further improved when oncoming vehicle features are included in the LC dataset. The Transformer demonstrates state-of-the-art performance recognizing LC 4.59 s in advance with 92.6 % accuracy using the VEL labelling method compared to GRU, LSTM and CNN + LSTM models. To interpret the Tran...
Source: Accident; Analysis and Prevention. - February 7, 2024 Category: Accident Prevention Authors: Hao Liu Tao Wang Wenyong Li Xiaofei Ye Quan Yuan Source Type: research
