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
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
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
Enhancing autonomous vehicle hyperawareness in busy traffic environments: A machine learning approach
This study aims to contribute to the ever-evolving algorithms used by AVs during travel in busy urban districts, as well as explore the potential utilization of AV sensor data to identify safety hazards to surrounding road users in real time. Accordingly, the study incorporates AV data collected from multiple cities in the United States to detect and categorize traffic conflicts that involve the source AVs, as well as conflicts that involve other surrounding road users. Then, a machine learning conflict prediction model is trained with Isolation Forest - Convolutional Neural Network - Long Short-Term Memory (IF-CNN-LSTM) l...
Source: Accident; Analysis and Prevention. - January 26, 2024 Category: Accident Prevention Authors: Abdul Razak Alozi Mohamed Hussein Source Type: research
Risk of motor vehicle collision associated with cannabis and alcohol use among patients presenting for emergency care
CONCLUSIONS: Alcohol use alone or in conjunction with cannabis was consistently associated with higer odds for MVC. However, the relationship between measured levels of cannabis and MVC was not as clear. Emphasis on actual driving behaviors and clinical signs of intoxication to determine driving under the influence has the strongest rationale.PMID:38277855 | DOI:10.1016/j.aap.2024.107459 (Source: Accident; Analysis and Prevention.)
Source: Accident; Analysis and Prevention. - January 26, 2024 Category: Accident Prevention Authors: Esther K Choo Stacy A Trent Daniel K Nishijima Angela Eichelberger Steve Kazmierczak Yu Ye Karen J Brasel Ariane Audett Cheryl J Cherpitel Source Type: research
Novice driver crashes: The relation between putative causal factors, countermeasures, real world implementations, and policy - A case study in simple, scalable solutions
This article is a case study in the United States of how a better understanding of the causes of novice driver crashes led to training countermeasures targeting teen driving behaviors with known associations with crashes. These effects on behaviors were large enough and long-lasting enough to convince insurance companies to develop training programs that they offered around the country to teen drivers. The success of the training programs at reducing the frequency of behaviors linked to crashes also led to several large-scale evaluations of the effect of the training programs on actual crashes. A reduction in crashes was o...
Source: Accident; Analysis and Prevention. - January 25, 2024 Category: Accident Prevention Authors: Donald L Fisher Ravi Agrawal Gautam Divekar Malek Abdul Hamid Akhilesh Krishnan Hasmik Mehranian Jeff Muttart Anuj Pradhan Shannon Roberts Matthew Romoser Siby Samuel Willem Vlakveld Yusuke Yamani Jared Young Tracy Zafian Lisa Zhang Source Type: research
Exploring the influence of drivers' visual surroundings on speeding behavior
This study investigates the influence of visual surroundings on drivers in 15 US cities using 3,407,253 driver view images from Lytx, covering 4,264 miles of roadways. By segmenting and analyzing these images along with vehicle-related variables, the study examines factors affecting speeding behavior. After filtering the images, to ensure an accurate representation of the driver's view, 1,340,035 driver view images were used for analysis. Statistical models, including hurdle beta and bivariate probit models with random driver effects as well as Machine Learning's eXtreme Gradient Boosting (XGBoost), were employed to estima...
Source: Accident; Analysis and Prevention. - January 21, 2024 Category: Accident Prevention Authors: Mohamed Abdel-Aty Jorge Ugan Zubayer Islam Source Type: research
Evaluating safety and compliance of pedestrian crossings in rural contexts: A before and after study of RRFBs and LED-embedded signs
Accid Anal Prev. 2024 Jan 19;198:107462. doi: 10.1016/j.aap.2024.107462. Online ahead of print.ABSTRACTImproving the safety of pedestrian and cyclist infrastructure is critical for reducing traffic-related injuries and fatalities. Pedestrian traffic safety risks are heightened in rural contexts. A key area of focus is the protection of pedestrians crossing roadways between intersections and in high-risk areas such as rural to urban transition zones. One way to reduce safety risks for pedestrians is through the use of crossing treatments such as rectangular rapid flashing beacons (RRFBs) and pedestrian activated LED-embedde...
Source: Accident; Analysis and Prevention. - January 20, 2024 Category: Accident Prevention Authors: Parsa Pezeshknejad Dana Rowangould Source Type: research
Identifying the latent relationships between factors associated with traffic crashes through graphical models
Accid Anal Prev. 2024 Mar;197:107470. doi: 10.1016/j.aap.2024.107470. Epub 2024 Jan 13.ABSTRACTTraffic safety field has been oriented toward finding the relationships between crash outcomes and predictor variables to understand crash phenomena and/or predict future crashes. In the literature, the main framework established for this purpose is based on constructing a modelling equation in which crash outcome (e.g., frequencies) is examined in relation to explanatory variables chosen based on the problem at hand. Despite the importance and success of this approach, there are two issues that are generally not discussed: 1) th...
Source: Accident; Analysis and Prevention. - January 14, 2024 Category: Accident Prevention Authors: Mehmet Baran Ulak Eren Erman Ozguven Source Type: research
Predicting pedestrian-involved crash severity using inception-v3 deep learning model
Accid Anal Prev. 2024 Mar;197:107457. doi: 10.1016/j.aap.2024.107457. Epub 2024 Jan 13.ABSTRACTThis research leverages a novel deep learning model, Inception-v3, to predict pedestrian crash severity using data collected over five years (2016-2021) from Louisiana. The final dataset incorporates forty different variables related to pedestrian attributes, environmental conditions, and vehicular specifics. Crash severity was classified into three categories: fatal, injury, and no injury. The Boruta algorithm was applied to determine the importance of variables and investigate contributing factors to pedestrian crash severity, ...
Source: Accident; Analysis and Prevention. - January 14, 2024 Category: Accident Prevention Authors: Md Nasim Khan Subasish Das Jinli Liu Source Type: research
