Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis

Yuan, Quan; Xu, Xuecai; Wang, Tao; Chen, Yuzhi

doi:10.1108/jicv-04-2022-0012

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…Fifth, describing accident models is a important factor in analyzing traffic accidents. This includes using traffic flow model or Baysian analysis [ 36 , 37 ]. Integration with traffic data may strengthen the value of nationwide clinical data in analyzing traffic accidents.…”

Section: Discussionmentioning

confidence: 99%

Comparison of incidence and outcome between occupational and non-occupational motorcycle injuries in Korea: A 7-years observational study

et al. 2023

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Motorcycles are widely used in various workplaces. Motorcycle use for occupational purposes continues to increase owing to growing e-commerce. Here, we aimed to highlight the importance of occupational motorcycle injuries by analyzing their epidemiologic characteristics and outcomes. We analyzed retrospective data from the Emergency Department-based Injury In-depth Surveillance program from 2012 to 2018. Motor vehicle injuries involving riders aged ≥16 years were included. Patients were divided into occupational motorcycle and non-occupational motorcycle injury groups based on whether or not the injury occurred during work time. General characteristics, injury details, and clinical outcomes such as injury severity and in-hospital mortality were analyzed. Of the 37,194 study patients, 24.2% (8,991) experienced occupational motorcycle injuries. The number of injuries in both groups increased yearly, as did the proportion of occupational injuries among total injuries. In both the groups, patients aged 20–29 years had the highest proportion of injuries. Regarding collision pattern and injury counterpart, side-to-side collisions and injuries involving small four-wheel vehicles were the most frequent. Alcohol intake was significantly lower, while helmet usage was higher in the occupational motorcycle injury group. Moreover, patients with occupational motorcycle injuries had lower injury severity, admission rate, and in-hospital mortality. On multivariable logistic regression analysis, increasing age, time of the injury, alcohol intake, not using a helmet, and collision with a human or animal were associated with higher odds of severe injury. Patients with occupational injuries had higher helmet usage, lower injury severity, lower mortality, and lower admission rate than did patients with non-occupational injuries. Injury severity was associated with the time of injury, collision with other living objects, alcohol consumption, and helmet usage.

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Section: Discussionmentioning

confidence: 99%

Comparison of incidence and outcome between occupational and non-occupational motorcycle injuries in Korea: A 7-years observational study

et al. 2023

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“…Although it was determined that AVs are not responsible for 87% of the accidents they are involved in (Wang and Li, 2019), it is essential to identify the factors that contribute to the severity of the collisions that do occur. When a vehicle is involved in a collision, the severity level can range from no injury to a severe impact on the vehicle and persons involved, and in extreme cases can even result in fatalities (Yuan et al, 2022). It was determined through an analysis of CA DMV collision reports that most AV crashes result in minor damage to both the AV and the other vehicle, and most of the personal injuries involve back pain (Dixit et al, 2016).…”

Section: Identification and Classification Of Crash Severity Factorsmentioning

confidence: 99%

“…Robinson et al (2022) explored the moral dilemma presented by unavoidable collisions and discussed the implications of existing studies; however, they failed to consider the real-world safety of AVs. Many researchers have utilized the CA DMV data to evaluate the actual performance of AVs (Xu et al, 2019;Sinha et al, 2021), and Yuan et al (2022) and Ren et al (2022), analyzed the data to determine the factors that influence the severity of the crashes. Unfortunately, however, they failed to combine the data with that obtained from a literature review or discuss the policy impacts of unavoidable collisions and the public perception of AV safety.…”

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confidence: 99%

Investigating the impacts of autonomous vehicles on crash severity and traffic safety

Almaskati,

Kermanshachi,

Pamidimukkala

2024

Front. Built Environ.

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Traffic accidents are a nationwide public health concern, but autonomous vehicles (AVs) have the potential to significantly reduce accident severity and frequency by eliminating their most common cause, human error. By analyzing the data published by California’s Department of Motor Vehicles, researchers have identified the factors that influence AV crash severity, however, none do so through a literature review. This paper’s aims are multi-faceted: to understand AVs’ operation on public roadways by identifying and classifying the factors contributing to accident severity, to develop a list of strategies that address the public’s safety concerns, and to acknowledge the ethics of unavoidable collisions. To fulfill these objectives, a comprehensive literature review was conducted based on a keyword search. Following a multi-step screening and exclusion process, detailed review was performed of 107 relevant publications, and the factors contributing to increased crash severity were classified into 14 categories. The literature revealed that AVs are not at fault in most accidents, although they have a higher propensity than conventional cars to be involved in rear-end collisions, and they are specifically designed to minimize the number of accidents, but may face unavoidable ones. For the benefit of policymakers and manufacturers, 11 strategies that address the moral dilemma of these accidents and 7 strategies that address concerns about AV safety to improve public perception were identified.

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A study on Autonomous Vehicles’ Driving Behavior Based on Open Road Test Data

Han,

Shao,

Sun

et al. 2023

2023 7th International Conference on Transportation Information and Safety (ICTIS)

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Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis

Cited by 8 publications

References 29 publications

Comparison of incidence and outcome between occupational and non-occupational motorcycle injuries in Korea: A 7-years observational study

Comparison of incidence and outcome between occupational and non-occupational motorcycle injuries in Korea: A 7-years observational study

Investigating the impacts of autonomous vehicles on crash severity and traffic safety

A study on Autonomous Vehicles’ Driving Behavior Based on Open Road Test Data

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