Development of pedestrian- and vehicle-related safety performance functions using Bayesian bivariate hierarchical models with mode-specific covariates

Singh, Mankirat; Cheng, Wen; Samuelson, Dean; Kwong, Jerry; Li, Bengang; Cao, Menglu; Li, Yihua

doi:10.1016/j.jsr.2021.05.008

Cited by 6 publications

(4 citation statements)

References 51 publications

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“…On the other hand, Bayesian Poisson regression gives better accuracy than Poisson regression. Thus, previous studies recommended using the Bayesian approach to resolve the issues found in Poisson regression, with many added benefits of the process mentioned below ( 2 , 10 , 33 ). The Bayesian approach can produce accurate parameter estimates and good predictive capabilities for a smaller sample size.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Previous studies investigated the safety effectiveness of AV and CAV technologies in reducing general vehicle-to-vehicle crash occurrences using the following four methods: field operation test (FOT), simulator study, statistical analysis methodology, and safety impact methodology (SIM) ( 4 ), of which FOT and SIM are the two commonly used methods. The safety effectiveness was estimated based on selected AV and CAV technologies’ ability to reduce certain types of crashes, including rear-end collision, angle or sideswipe collision, single-vehicle crashes with pedestrians and animals, and others ( 1 , 2 ). The results of past studies found that each evaluation tool would suggest different safety effectiveness.…”

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confidence: 99%

“…Given these abilities, AVs and CAVs can sense their surrounding environment more efficiently than humans, which can minimize common human mistakes (i.e., fatigue, driving under drug and alcohol influences, dangerous driving, etc.) ( 2 ). Therefore, it is believed that AVs and CAVs can significantly reduce road crashes ( 3 ).…”

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confidence: 99%

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Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes

Susilawati

Wong

Pang

2022

Transportation Research Record: Journal of the Transportation R

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This research aims to study the safety effectiveness of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) in reducing pedestrian crashes in various scenarios. The proposed methodology involves (1) identifying factors that contribute to pedestrian crashes, (2) developing crash-frequency models to predict the pedestrian crash and identifying the model that performs the best, (3) identifying the AV and CAV technologies that can minimize and remove those identified factors, and (4) assessing the effectiveness of AV and CAV technologies in reducing pedestrian crashes for various road classifications. Using crash data obtained from San Francisco Transportation Injury Mapping System (TIMS) for 2016 to 2020, a two-level Bayesian Poisson lognormal (TLBPL) model is developed to assess the effectiveness of AVs and CAVs in reducing pedestrian crashes. The outcomes of the TLBPL model suggest that weather, lighting, and road classifications tend to influence more vehicle–pedestrian crashes in all road classifications. The results of TLBPL indicate that driver faults related to prediction ability contribute more to pedestrian crashes for all road classifications, while driver fault related to sensing (perception) on urban arterials is the factor contributing most to pedestrian crashes. This paper provides a framework for researchers and engineers to evaluate AVs’ and CAVs’ safety effectiveness by considering crash contributing factors and road classifications.

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Section: Literature Reviewmentioning

confidence: 99%

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confidence: 99%

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Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes

Susilawati

Wong

Pang

2022

Transportation Research Record: Journal of the Transportation R

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“…Replete studies in the past considered walking activity an important mode to reduce congestion, decrease motor-vehicles gas emissions, improve public health, and increase social connection opportunities [1]. However, the percentage of total trips undertaken by pedestrians compared to other modes is very low.…”

Section: Introductionmentioning

confidence: 99%

Comparative evaluation for alternative variable importance rankings for pedestrian injury severities

Cheng,

Zhang

2023

J. Phys.: Conf. Ser.

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Little research is dedicated to evaluating the performance difference of various metrics in ranking predictor importance in the traffic safety field. To this end, the main objective of the current paper is to evaluate and quantify different methods for sorting the variable importance related to crash severity. A comprehensive database for pedestrian-related crashes in the state of California was developed. Four popular measurement metrics used in the past were chosen for evaluation purpose: Mean Decrease Accuracy (MDA), Mean Decrease Gini (MDG), log-likelihood ratio test associated with multinomial logit model, and Principal Component Analysis (PCA). The former two metrics come under the same umbrella of the Random Forest (RF) technique, while the latter two are methods belonging to different domains. The results show the alternative methods yield different variable importance rankings with PCA being isolated from others. The two methods under the same domain of the random forest, or MDG and MDA, have the most common results, but still reveal a 17% ranking difference. It is anticipated that the results could raise more awareness of the importance of selecting the appropriate metrics to evaluate the predictor importance from different perspectives.

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A ward level analysis of child pedestrian casualty frequencies in Greater London

Chibwe,

Heydari,

Shoari

2024

Journal of Safety Research

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Development of pedestrian- and vehicle-related safety performance functions using Bayesian bivariate hierarchical models with mode-specific covariates

Cited by 6 publications

References 51 publications

Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes

Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes

Comparative evaluation for alternative variable importance rankings for pedestrian injury severities

A ward level analysis of child pedestrian casualty frequencies in Greater London

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