Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes

Champahom, Thanapong; Jomnonkwao, Sajjakaj; Watthanaklang, Duangdao; Karoonsoontawong, Ampol; Chatpattananan, Vuttichai; Ratanavaraha, Vatanavongs

doi:10.1016/j.aap.2020.105537

Cited by 42 publications

(17 citation statements)

References 39 publications

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“…A survey for poorly lighted crash-prone areas should be first conducted. There is previous research that suggested this point such as Champahom et al [42], Se et al [68], Se et al [69]. These works mentioned that the DOH should survey the dark road segments and consider installing lighting poles.…”

Section: Conclusion and Implementationmentioning

confidence: 99%

“…γ 00 is the intercept for or β 0j and γ k0 is the intercept for β kj . µ 0j and µ kj stand for the prediction errors in information at the road level and demonstrate the unique effect of road j. Kim et al [19], Huang et al [20], Xiao et al [40], Se et al [41], Champahom et al [42] provide for extended details on the calculation presented above.…”

Section: Y Ij =mentioning

confidence: 99%

“…This resulted in only few instances of death. The studies concluded that rear-end collisions in urban areas were less violent than those in rural areas [42]. That is, a single crash led to fewer instances of death.…”

Section: Crash Severity Modelmentioning

confidence: 99%

“…In Thailand, the campaign or the training topic of awareness of collision types are a low priority. The previous research recommended that the DOH should highlight some crash types such as rear-end crashes, single crashes and head-on crashes [42,67,68]. These studies suggest some policies, for example, the driver should be aware of the appropriate headway with the front vehicle.…”

mentioning

confidence: 99%

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Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

et al. 2021

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Currently, research on the development of crash models in terms of crash frequency on road segments and crash severity applies the principles of spatial analysis and heterogeneity due to the methods’ suitability compared with traditional models. This study focuses on crash severity and frequency in Thailand. Moreover, this study aims to understand crash frequency and fatality. The result of the intra-class correlation coefficient found that the spatial approach should analyze the data. The crash frequency model’s best fit is a spatial zero-inflated negative binomial model (SZINB). The results of the random parameters of SZINB are insignificant, except for the intercept. The crash frequency model’s significant variables include the length of the segment and average annual traffic volume for the fixed parameters. Conversely, the study finds that the best fit model of crash severity is a logistic regression with spatial correlations. The variances of random effect are significant such as the intersection, sideswipe crash, and head-on crash. Meanwhile, the fixed-effect variables significant to fatality risk include motorcycles, gender, non-use of safety equipment, and nighttime collision. The paper proposes a policy applicable to agencies responsible for driver training, law enforcement, and those involved in crash-reduction campaigns.

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Section: Conclusion and Implementationmentioning

confidence: 99%

Section: Y Ij =mentioning

confidence: 99%

Section: Crash Severity Modelmentioning

confidence: 99%

mentioning

confidence: 99%

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Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

et al. 2021

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“…In rural regions, traffic hazards are severe. 29–33 Therefore, the second approach is more convenient to minimize the risk very effectively. The receiver node assigns an initial credit value β to each sender node.…”

Section: Trust Management Modelmentioning

confidence: 99%

A hybrid dual-mode trust management scheme for vehicular networks

Abdo

Shaikh

Hassan

2020

International Journal of Distributed Sensor Networks

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Vehicular ad-hoc networks allow vehicles to exchange messages pertaining to safety and road efficiency. Building trust between nodes can, therefore, protect vehicular ad-hoc networks from malicious nodes and eliminate fake messages. Although there are several trust models already exist, many schemes suffer from varied limitations. For example, many schemes rely on information provided by other peers or central authorities, for example, roadside units and reputation management centers to ensure message reliability and build nodes’ reputation. Also, none of the proposed schemes operate in different environments, for example, urban and rural. To overcome these limitations, we propose a novel trust management scheme for self-organized vehicular ad-hoc networks. The scheme is based on a crediting technique and does not rely on other peers or central authorities which distinguishes it as an economical solution. Moreover, it is hybrid, in the sense it is data-based and entity-based which makes it capable of revoking malicious nodes and discarding fake messages. Furthermore, it operates in a dual-mode (urban and rural). The simulation has been performed utilizing Veins, an open-source framework along with OMNeT++, a network simulator, and SUMO, a traffic simulator. The scheme has been tested with two trust models (urban and rural). The simulation results prove the performance and security efficacy of the proposed scheme.

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Jointly modeling the dependence of injury severity and crash size involved in motorcycle crashes in Cambodia using a copula-based approach

Li,

Virakvichetra,

Zhang

et al. 2024

Front. Eng. Manag.

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Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes

Cited by 42 publications

References 39 publications

Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

A hybrid dual-mode trust management scheme for vehicular networks

Jointly modeling the dependence of injury severity and crash size involved in motorcycle crashes in Cambodia using a copula-based approach

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