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

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

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

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

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

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

Evaluation of driver navigational errors and acceptance of a simulated J-turn intersection
This study provides an examination of how naïve or first-time drivers may initially navigate J-turns during their first and early exposures to the novel intersection design. Thirty-six participants with limited previous experience and knowledge of J-turns participated in a simulation study to examine their acceptance of J-turns and left turning navigational performance at three simulated J-turn intersections in counterbalanced order, each featuring one of three signage levels. Results revealed participants committed slightly more frequent minor errors (e.g., inefficient lane selection) and significantly more major errors ...
Source: Accident; Analysis and Prevention. - February 7, 2024 Category: Accident Prevention Authors: Nichole L Morris Katelyn R Schwieters Disi Tian Curtis M Craig 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

An exploratory study of parent acceptance of sanctions for driving offenses committed by their children
CONCLUSIONS: These exploratory findings suggest that family size and income may be important influences on parent acceptance of sanctions on behalf of their offending children. The findings related to the psychosocial variables are discussed considering other research and the limitations of the study.PMID:38324628 | DOI:10.1080/15389588.2023.2296861 (Source: Traffic Injury Prevention)
Source: Traffic Injury Prevention - February 7, 2024 Category: Accident Prevention Authors: David Rodwell Source Type: research

Driver yield and safe child pedestrian crossing behavior promotion by a school traffic warden program at primary school crossings: A cluster-randomized trial
CONCLUSION: The school traffic warden program is associated with increased driver yield and safe child pedestrian crossing behavior, i.e., stopping at the curb, walking while crossing, and not crossing between vehicles. Therefore, the school traffic warden program could be promoted to supplement other road safety measures, such as pedestrian safety road infrastructure, legislation, and enforcement that specifically protects children in school zones.PMID:38324586 | DOI:10.1080/15389588.2024.2305426 (Source: Traffic Injury Prevention)
Source: Traffic Injury Prevention - February 7, 2024 Category: Accident Prevention Authors: Jimmy Osuret Ashley Van Niekerk Olive Kobusingye Lynn Atuyambe Victoria Nankabirwa Source Type: research

Safety-oriented automated vehicle longitudinal control considering both stability and damping behavior
This study aims to demonstrate the significance of explicitly considering safety in addition to stability in AV longitudinal control through damping behavior analysis. Specifically, it proposes a safety-oriented AV longitudinal control and provides recommendations on the control parameters. For the proposed AV control, an Adaptive Cruise Control (ACC) model is integrated with damping behavior analysis to model AV safety under continuous traffic perturbations. Numerical simulations are conducted to quantify the relationship between mobility and safety for AVs considering both damping behavior and control stability. Differen...
Source: Accident; Analysis and Prevention. - February 4, 2024 Category: Accident Prevention Authors: Yulu Dai Chen Wang Yuanchang Xie Source Type: research

Understanding the relationship between road users and the roadway infrastructure in Ghana
Accid Anal Prev. 2024 Feb 2;198:107475. doi: 10.1016/j.aap.2024.107475. Online ahead of print.ABSTRACTGhana exemplifies the contribution of road crashes to mortality and morbidity in Africa, partly due to a growing population and increasing car ownership, where fatalities have increased by 12 to 15 % annually since 2008 (National Road Safety Authority (NRSA), 2017). The study described in this paper focused on understanding driver behavior at unsignalized junctions in the Ashanti Region of Ghana. Understanding driver behavior at unsignalized junctions is particularly important since failure to stop or yield can seriously a...
Source: Accident; Analysis and Prevention. - February 3, 2024 Category: Accident Prevention Authors: Brianna P Lawton Shauna L Hallmark Guillermo Basulto-Elias Daniel Atuah Obeng Williams Ackaah Source Type: research

Modeling road user response timing in naturalistic traffic conflicts: A surprise-based framework
We present a novel framework for measuring and modeling response times in naturalistic traffic conflicts applicable to automated driving systems as well as other traffic safety domains. The framework suggests that response timing must be understood relative to the subject's current (prior) belief and is always embedded in, and dependent on, the dynamically evolving situation. The response process is modeled as a belief update process driven by perceived violations to this prior belief, that is, by surprising stimuli. The framework resolves two key limitations with traditional notions of response time when applied in natura...
Source: Accident; Analysis and Prevention. - January 31, 2024 Category: Accident Prevention Authors: Johan Engstr öm Shu-Yuan Liu Azadeh Dinparastdjadid Camelia Simoiu Source Type: research

Use of smartphone apps while driving: Variations on driving performances and perceived risks
This study aims to understand the impacts of smartphone application distractions, in particular social media activities (e.g., video, feed, message), on different road geometries using a mixed-method analysis consisting of a survey, a driving simulator experiment, and individual interview. Results from the interview and simulation experiments show that most social media activities cause unsafe lane changes regardless of road geometry. Among various social-media activities, watching reels (videos) represent an unintentional but deeper level of engagement that consequently causes a driver to deviate in their lane, make unint...
Source: Accident; Analysis and Prevention. - January 30, 2024 Category: Accident Prevention Authors: Juana Perez Kate Hyun Jobaidul Alam Boni Source Type: research

Assessing the collective safety of automated vehicle groups: A duration modeling approach of accumulated distances between crashes
Accid Anal Prev. 2024 Jan 29;198:107454. doi: 10.1016/j.aap.2023.107454. Online ahead of print.ABSTRACTIdeally, the evaluation of automated vehicles would involve the careful tracking of individual vehicles and recording of observed crash events. Unfortunately, due to the low frequency of crash events, such data would require many years to acquire, and potentially place the motorized public at risk if defective automated technologies were present. To acquire information on the safety effectiveness of automated vehicles more quickly, this paper uses the collective crash histories of a group of automated vehicles, and applie...
Source: Accident; Analysis and Prevention. - January 30, 2024 Category: Accident Prevention Authors: Soheil Sohrabi Dominique Lord Bahar Dadashova Fred Mannering Source Type: research