Equity and social acceptability in multiple hazardous materials routing through urban areas

Garrido, Rodrigo A.; Bronfman, Andrés

doi:10.1016/j.tra.2016.05.018

Cited by 21 publications

(16 citation statements)

References 29 publications

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“…The results show that compared to an explosion, spill, and non-spill are both associated with a decrease in the probability of severe injuries and evacuation. The main reason is that explosion caused by Hazmat accidents would lead to severe consequences due to its characteristic, especially in the urban area and higher population densities [67]. This finding could be explained by the nature of explosion.…”

Section: Accident Factorsmentioning

confidence: 99%

Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China

Xing

Chen

Zhu

et al. 2020

IJERPH

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With the increasing demand of hazardous material (Hazmat), traffic accidents occurred frequently during Hazmat transportation, which had caused widespread concern in communities. Therefore, a good understanding of Hazmat transportation accident characteristics and contributing factors is of practical importance. In this study, 1721 Hazmat accidents that have occurred during road transportation for the period 2014–2017 in China were examined, and a random-parameters ordered probit model was established to explore the influence of contributing factors on the severity of accidents by accounting for unobserved heterogeneity in the data. Both the injuries and the number of people evacuated were considered as the indicator of accident severity and investigated, respectively. Results show that higher injury severity is likely to be associated with type of Hazmat (compressed gas, explosive, and poison), misoperation, driver fatigue, speeding, tunnel, slope, county road, dry road surface, winter, dark, more than two vehicles, rear end crash, and explosion. As for the correlation between risk factors and the severity of evacuation, type of Hazmat (compressed gas, explosive, and poison), quantity of Hazmat (10–39 t), misoperation, county road, dry road surface, weekdays, dusk, explosion significantly contribute to increasing the severity of evacuation of Hazmat accidents.

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Section: Accident Factorsmentioning

confidence: 99%

Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China

Xing

Chen

Zhu

et al. 2020

IJERPH

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show abstract

“…However, despite many studies on the traffic accidents and Hazmat accidents, most of them are studied based on the analysis of specific, isolated, and single factor [25,26]. Moreover, the characteristic of Hazmat was not taken into consideration during the analysis of accidents, limiting the studies of risk factors in Hazmat road transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Moreover, as for the accident consequence, the probability of "spill" decreases; meanwhile the "explosion" (3% to 6%) and fire (11% to 18%) have increased. Due to the special characteristic of Hazmat, explosion and fire would cause a larger area affected and can easily result in casualties, especially in the urban road and higher population densities [26].…”

Section: Causal Inferencementioning

confidence: 99%

Causation Analysis of Hazardous Material Road Transportation Accidents by Bayesian Network Using Genie

Xing

Lü

2018

Journal of Advanced Transportation

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With the increase of hazardous materials (Hazmat) demand and transportation, frequent Hazmat road transportation accidents had arisen the widespread concern in the community. Thus, it is necessary to analyze the risk factors’ implications, which would make the safety of Hazmat transportation evolve from “passive type” to “active type”. In order to explore the influence of risk factors resulting in accidents and predict the occurrence of accidents under the combination of risk factors, 839 accidents that have occurred for the period 2015–2016 were collected and examined. The Bayesian network structure was established by experts’ knowledge using Dempster-Shafer evidence theory. Parameter learning was conducted by the Expectation-Maximization (EM) algorithm in Genie 2.0. The two main results could be likely to obtain the following. (1) The Bayesian network model can explore the most probable factor or combination leading to the accident, which calculated the posterior probability of each risk factor. For example, the importance of three or more vehicles in an accident leading to the severe accident is higher than less vehicles, and in the absence of other evidences, the most probable reasons for “explosion accident” are vehicles carrying flammable liquids, larger quantity Hazmat, vehicle failure, and transporting in autumn. (2) The model can predict the occurrence of accident by setting the influence degrees of specific factor. Such that the probability of rear-end accidents caused by “speeding” is 0.42, and the probability could reach up to 0.97 when the driver is speeding at the low-class roads. Moreover, the complex logical relationship in Hazmat road transportation accidents could be obtained, and the uncertain relation among various risk factors could be expressed. These findings could provide theoretical support for transportation corporations and government department on taking effective measures to reduce the risk of Hazmat road transportation.

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“…On the other hand, some studies select the local risk as a constraint for hazmat transportation optimization models. For example, Bronfman et al [35] maximized the weighted distance between the route and its closest vulnerable centre to minimize the catastrophe consequences for exposed population; Garrido and Bronfman [36] introduced a multiproduct multi-shipment hazmat routing model with equity constraints, aiming to minimize the conditional expectation of the catastrophic accident consequence. Ma et al [37][38][39] developed the multi-objective robust optimization model with maximum local risk constraint for hazmat transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Models for Hazardous Material Transportation Subject to Weight Variation Considerations

et al. 2021

IEEE Trans. Fuzzy Syst.

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Reasonable risk models in hazardous material transportation are of practical significance, for safeguarding the lives and properties, protecting the natural environment, and facilitating the sustainable development. The existing risk models can be classified into summation risk model and maximum risk model, which result in over-reliance on overall risk or local risk. For overcoming these problems, we present two novel risk models considering different aggregation methods on local risks. The first model is supported by ordered weighted averaging (OWA) operator, which assigns the weights according to the position of the segment risk in the process of risk aggregation, and the second model is supported by state variable weight (SVW) vector, which adjusts the weights on segments according to the change of segment risk values. Generally speaking, OWA risk model is used under the situation with complete weighting information, while SVW risk model could be used under the situation with incomplete weighting information. Based on the analysis for variable weight mechanism, we show that both models could effectively balance the overall risk with the local risks assisted by weights variety. Numerical experiments are provided to illustrate the validity of the proposed risk models.

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Equity and social acceptability in multiple hazardous materials routing through urban areas

Cited by 21 publications

References 29 publications

Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China

Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China

Causation Analysis of Hazardous Material Road Transportation Accidents by Bayesian Network Using Genie

Risk Models for Hazardous Material Transportation Subject to Weight Variation Considerations

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