Hazmat Transportation Research Articles

Routing Hazmat Multimodal Transportation Based on CVaR Assessment

Multimodal plays a more significant role in long distances transportation of hazardous materials, while there haven’t been systemic risk evaluation methods to hazmat multimodal transportation. Considering that the risk of hazmat transportation has the characteristics of low probability and high consequence, this paper studies how CVaR applied to the routing optimization of hazmat multimodal transportation while CVaR could better compute the tail loss of risk. We build a multimodal hazmat transportation risk assessment model in this paper, and prove its effectiveness by a computational study. Results show that the proposed model can provide a CVaR optimal transportation path to hazmat multimodal transportation in realistic.

Factors influencing injury severity of crashes involving HAZMAT trucks

Abstract This paper investigates factors affecting injury severity of crashes involving HAZMAT large trucks. It uses the crash data in the state of California from the Highway Safety Information System, from 2005 to 2011. The explanatory factors include the occupant, crash, vehicle, roadway, environmental, and temporal characteristics. Both fixed- and random-parameters ordered probit models of injury severity (where possible outcomes are major, minor, and no injury) were estimated; the random-parameters model captures possible unobserved effects related to factors not present in the data. The model results indicate that the occupants being male, truck drivers, crashes occurring in rural locations, under dark-unlighted, under dark-lighted conditions, and on weekdays were associated with increased probability of major injuries. Conversely, the older occupants (age 60 and over), truck making a turn, rear-end collision, collision with an object, crashes occurring on non-interstate highway, higher speed limit highway (≥65 mph), and flat terrain were associated with decreased probability of major injuries. This study has identified factors that explain injury severities of crashes involving HAZMAT, and as such, it could be used by policy makers and transportation agencies to improve HAZMAT transport, and thus, the overall highway safety.

Integrated fleet mix and routing decision for hazmat transportation: A developing country perspective

In developing countries, truck purchase cost is the dominant criteria for fleet acquisition-related decisions. However, we contend that other cost factors such as loss due to the number of en route truck stoppages based on a truck type and recovery cost associated with a route choice decision, should also be considered for deciding the fleet mix and minimizing the overall costs for long-haul shipments. The resulting non-linear model, with integer variables for the number and type of trucks, and the route choices, is solved via genetic algorithm. Using real data from a bulk liquid hazmat transporter, the trade-offs between the cost of travel, loss due to number of truck stoppages, and the long-term recovery cost associated with the risk of exposure due to a hazmat carrier accident are discussed. The numerical experiments show that when factors related to public safety and truck stoppages are taken into account for transportation, the lowest total cost and optimal route choice do not align with the cheapest truck type option; rather, the optimal solution corresponds to another truck type and route with total costs significantly less than the total costs associated with the cheapest truck type. Our model challenges the current truck purchasing strategy adopted in developing countries using the cheapest truck criteria.

The future is now! Extrapolated riskscapes, anticipatory action and the management of potential emergencies

Anticipating the future is a key practice for the management of potential emergencies. Anticipatory action needs the future to become ready-to-hand. Focusing on the logics and practices of anticipatory action the paper discusses the relations between time and space in the context of risk and uncertainty. Spatializations of simulation technologies, preemptive emergency management and anticipatory action aim to disclose and extrapolate the future. In general, infrastructures are technologies which aim to materialize expectations concerning the future. In the case of emergency management infrastructural measures enable and/or constrain practices by inheriting specific logics.The concept of riskscapes (Müller-Mahn and Everts, 2013) poses to be a promising framework to grasp these issues. In our perspective, extrapolated riskscapes treat the future as an already interpreted and symbolically structured world. This involves not only looking at the temporality of riskscapes, but also dealing with geographies of inscribed futurity. Two case studies focusing on emergency management practices of firefighters will be deployed for illustration: the first observes the logics of preemptive emergency management and anticipatory action inscribed into materialities of infrastructures in the context of rail-bound hazmat transports; the second shows how computer simulations for crowded geographies facilitate decision-making and action for policing and crowd management.Instead of treating future in riskscapes as neutral, we highlight the politically situated practices that co-evolve with these technologies and their spatializations. The article discusses the dimension of time within riskscapes to gain a better understanding of the temporalization of space as in simulations and the spatialization of time as in infrastructures of emergency management.

Hazmat Transport Safety and Alternative Transport Modes

This paper analyzes 21 years of data related to unintentional hazardous materials (hazmat) releases on air, marine, and rail transportation modes reported in the United States (U.S.) -- although their origins and destinations may be outside the U.S. The authors' analysis reveals thousands of cases have occurred and their impacts vary by mode. These impacts include material losses, carrier damages, property damages, response costs, and remediation and clean-up costs. There appears to be some reduction in the frequency of incidents and accidents as regulations have been promulgated, although the authors cannot attribute causation. They review suggests that enhanced regulations and attentiveness have probably led to better reporting of hazmat occurrences. Moreover, developing and maintaining safer processes and designing safer products, containers, and systems can play an important role in minimizing hazmat releases.

Time-Dependent Hazardous-Materials Network Design Problem

We extend the hazardous-materials (hazmat) network design problem to account for the time-dependent road closure as a policy tool to reduce hazmat transport risk by altering carriers’ departure times and route choices. We formulate the time-dependent network design problem using an alternative-based model with each alternative representing a combined path and departure-time choice. We also present an extended model that can not only account for consecutive time-based road closure policies but also allow stopping at the intermediate nodes of the network in the routing/scheduling decisions of the carriers. Heuristic algorithms based on column generation and label setting are presented. To illustrate the advantages that can be gained through the use of our methodology, we present results from numerical experiments based on a transportation network from Buffalo, New York. To investigate the impact of the extensions, we consider three versions of the problem by gradually refining the model. We show that under consideration of extensions, the design policies are more applicable and effective. The online appendix is available at https://doi.org/10.1287/trsc.2016.0698 .

A Multi-objective Compromise Weight Model for Hazmat Transportation Problems with the Consideration of Response Capability

A Multi-objective Compromise Weight Model for Hazmat Transportation Problems with the Consideration of Response Capability

Real-Time Microservices Based Environmental Sensors System for Hazmat Transportation Networks Monitoring

Abstract The transportation of dangerous goods represents one of the most critical risks particularly in urban areas. For example, every day large quantities of hazardous substances are transported by roads or railways inside areas with high density of population. Thus, to ensure urban and public safety the first challenge that we tackle is to find an environmental information system, which is able to provide risk management and monitoring. Moreover, it can capture urban transportation dynamics and offer specific services, visualization, analyses and evaluation of the hazmat risk in various high-risk zones. In addition, due to wireless technologies and real time intelligent sensors, the risk of dangerous goods can be carried out in real time. In this work, we adopt a microservices based architecture to have a real-time environmental sensors system that have highly scalable applications on cloud environment. By definition, this architecture consists of a set of loosely coupled and independently deployable services. In addition, the proposed system is conducted with a smart data collector, visualization abilities and a variety of distributed sensors in order to enhance the hazmat transportation network monitoring. Finally, we show how to integrate efficiently into the system prototype the hazmat routing container embedded microservice, and illustrate the orchestration with other microservices to improve this system with hazmat routing capabilities using various routing algorithms particularly bi-directional A* algorithm. This work constitutes the first step to build the Hazmat planning aid system that provides valuable data and knowledge to urban planner and decision makers

Safest and shortest itineraries for transporting hazardous materials using split points of Voronoï spatial diagrams based on spatial modeling of vulnerable zones

Abstract: In this paper, we propose a new approach for routing and planning of hazardous materials transportation in an urban environment. The aim of this paper is to find safest and shortest itineraries for hazmat transportation. This allows us to reduce risk and to minimize damage and ultimately keeping people, property and the environment as far away as possible from the effects and consequences of hazardous materials. Indeed, we propose a calculation process based on Voronoi spatial modeling of the transportation network of hazardous materials. The development of such spatial model will make it possible to assess the proximity of vulnerable areas to risk by calculating the distance separating these spatial objects from the vehicles itineraries. The weighting of these spatial structures with socio-economic data constitutes an important spatial support for spatially analyzing the urban environment and geo-governing the transportation network of hazardous materials.

A risk-averse signal setting policy for regulating hazardous material transportation under uncertain travel demand

To effectively regulate risk associated with hazmat transportation and minimize travel cost over road network under uncertain travel demand, a min-max bi-level programming problem (MMBLPP) is proposed to determine traffic signal settings. A risk-averse signal setting policy using budget of uncertainty (BOU) is presented against the worst-case realization of uncertainty in travel demand. A risk-averse model determining system optimum routes for hazmat carriers is presented where travel delay incurred by regular traffic at downstream junctions has been taken into account. A min-max single-level model (MMX) and a bundle-like solution method are proposed to determine risk-averse signal settings under BOU-based travel demand. To investigate the effectiveness of proposed model, numerical evaluations using real-world road network are empirically made with various scenarios of transport policies. These results reported obviously indicate that the proposed model achieved relatively better results than did traditional one against high-consequence scenarios of uncertain travel demand while substantially mitigating risk in the worst cases.

Worst-Case Conditional Value-at-Risk Minimization for Hazardous Materials Transportation

Despite significant advances in risk management, the routing of hazardous materials (hazmat) has relied on relatively simplistic methods. In this paper, we apply an advanced risk measure, called conditional value-at-risk (CVaR), for routing hazmat trucks. CVaR offers a flexible, risk-averse, and computationally tractable routing method that is appropriate for hazmat accident mitigation strategies. The two important data types in hazmat transportation are accident probabilities and accident consequences, both of which are subject to many ambiguous factors. In addition, historical data are usually insufficient to construct a probability distribution of accident probabilities and consequences. This motivates our development of a new robust optimization approach for considering the worst-case CVaR (WCVaR) under data uncertainty. We study important axioms to ensure that both the CVaR and WCVaR risk measures are coherent and appropriate in the context of hazmat transportation. We also devise a computational method for WCVaR and demonstrate the proposed WCVaR concept with a case study in a realistic road network.

A comprehensive modeling framework for hazmat network design, hazmat response team location, and equity of risk

This paper considers a bi-level hazmat transportation network design problem in which hazmat shipments have to be transported over a road network between specified origin-destination points. The bi-level framework involves a regulatory authority and hazmat carriers. The control variables for the regulatory authority are locations of hazmat response teams and which additional links to include for hazmat travel. The regulatory authority (upper level) aims to minimize the maximum transport risk incurred by a transportation zone, which is related to risk equity. Our measure of risk incorporates the average response time to the hazmat incidents. Hazmat carriers (lower level) seek to minimize their travel cost. Using optimality conditions, we reformulate the non-linear bi-level model as a single-level mixed integer linear program, which is computationally tractable for medium size problems using a commercial solver. For large size problems, we propose a greedy heuristic approach, which we empirically demonstrate to find good solutions with reasonable computational effort. We also seek a robust solution to capture stochastic characteristics of the model. Experimental results are based on popular test networks from the Sioux Falls and Albany areas.

Hazardous Materials Transportation with Multiple Objectives: A Case Study in Taiwan

Hazardous material (hazmat) transportation has been an important issue for handling hazardous materials, such as gases and chemical liquids. In the past, researchers have made great efforts to develop policies and route planning methods for hazmat transportation problems. In 2014, Kaohsiung City in Taiwan suffered a gas pipeline explosion at midnight; 32 people were killed, and hundreds of people were injured. After the incident, policies and routing strategies for hazardous materials (hazmat) transportation in Kaohsiung were initiated to avoid pipeline transportation. Although methodologies for hazmat transportation have been proposed and implemented to minimize potential risks, multiple objectives need to be considered in the process to facilitate hazmat transportation in Taiwan. In order to consider both government and operators’ aspects, a multi-objective formulation for the hazmat problem is proposed and a compromise programming method is applied to solve the problem with two objectives: travel cost and risk. The path risk is defined based on risk assessment indexes, such as road characteristics, population distribution, link length, hazardous material characteristics, and accident rates. An aggregate risk indicator is proposed for roadway segments. The compromise programming approach is developed from the concept of compromise decision and the main idea is to search the compromise solution closest to the ideal solution. The proposed method is applied to Kaohsiung City, Taiwan. The results show that two conflicting objectives keep making trade-offs between each other until they finally reach a compromise solution.

HazMat transportation risk assessment: A revisitation in the perspective of the Viareggio LPG accident

The Seveso accident triggered a virtuous process towards the development of methods, models and tools for safety and risk assessment and management. Among the more relevant results of such process was the stemming of methods and tools addressing the transportation of hazardous substances in the framework of a holistic approach to the control of major accident hazards related to dangerous substances. The present study aims at the analysis of reference procedures and tools available for the analysis of the risk in the transportation of dangerous substances in the light of the Viareggio accident. The Viareggio accident represents a paradigmatic event involving the transportation of dangerous substances. The accident, that took place in Italy in 2009, was analyzed in the perspective of current approaches to the analysis of risk in the transportation of hazardous materials. The results pointed out that the Viareggio scenario, although of particular severity, is comprised within those accounted in quantitative risk analysis.

A toll-based bi-level programming approach to managing hazardous materials shipments over an intermodal transportation network

This research proposes a bi-level bi-objective model to regulate the usage of rail intermodal terminals for hazardous materials (hazmat) shipments, where government imposes tolls to deter carriers from using certain terminals. The complexity of the resulting mathematical program motivates the development of a hybrid speed-constrained multi-objective particle swarm optimization algorithm, which is then integrated with CPLEX, to solve the model. Through a real problem instance based on the intermodal service chain of Norfolk Southern in US, the toll-setting model is examined and further compared with a regular network design approach, in which certain terminals are closed to hazmat containers. The computational results show that the toll-setting policy is more practical and efficient, and the two models can be combined as a two-stage strategy in long-term hazmat transportation regulations. Additional managerial insights are derived for different stakeholders.

A Game-Theoretic Approach for Regulating Hazmat Transportation

In this paper, we study a novel toll setting policy to regulate hazardous material (hazmat) transportation, where the regulator (e.g., a government authority) aims at minimizing not only the network total risk but also at spreading the risk in an equitable way over a given road network. The idea is to use a toll setting policy to discourage carriers transporting hazmat from overloading portions of the network with the consequent increase of the risk exposure of the population involved. Specifically, we assume that the toll paid by a carrier on a network link depends on the usage of that link by all carriers. Therefore the route choices of each carrier depend on the other carrier’s choices, and the tolls deter the carriers from using links with a high total risk. The resulting model is a mathematical programming with equilibrium constraints (MPEC) problem, where the inner problem is a Nash equilibrium problem (game) having as players the carriers, each one wishing to minimize his or her travel cost (including tolls); the outer problem is addressed by the government authority, whose aim is finding the link tolls that induce the carriers to choose route plans that minimize both the network total risk and the maximum link total risk among the network links (to address risk equity). To guarantee the stability of the solution, we study conditions for the existence and uniqueness of the Nash equilibrium, and propose a local search heuristic for the MPEC problem. Computational results are carried out on a real road network, comparing the performance of our toll setting policy with the toll setting approach proposed in the literature.

유해화학물질 수송용 차량의 사고 대응 가이드라인에 관한 연구

Accidents of HAZMAT transport vehicle are generally dealt by unskilled firefighters. As a result, firefighters became 2nd victims of accidents in some case because of this reason, and it is required to prepare an accident response guidelines against HAZMAT transport vehicle accidents. In this study, risk assessment methods and making methods of guidelines were investigated to make accident response guidelines of HAZMAT transport vehicle accidents. and It identifies hazards and combines with guideword for making guideline items. At last, we determine criteria or detailed methods by referring survey regulations and existed methods.

A Rule-Based Decision Support System in Intelligent Hazmat Transportation System

This paper develops a new rule-based decision support system (RB-DSS) to find the safest solutions for routing, scheduling, and assignment in Hazmat transportation management. To define the safe program in RB-DSS, the accident frequency and severity are estimated for different scenarios of transportation, and they are used to classify the scenarios by a new structure of decision tree (DT), which is proposed to select branching variables at the primary levels according to the experts' perception. The outputs of the DT are stated in the form of if–then rules trained by a multilayer perceptron neural network to generalize the safe programs for Hazmat transportation. To illustrate the performance of this approach, the UK road accident data set is used.

Bayesian network-based risk assessment for hazmat transportation on the Middle Route of the South-to-North Water Transfer Project in China

A Bayesian network-based risk assessment (BN-RA) model was developed to assess the risk of hazmat transportation by identifying, modeling, and quantitatively calculating the risk on the Middle Route of the South-to-North Water Transfer Project (MRSNWTP) in China. First, we selected seven parameters from five categories of impact factors (i.e., human, vehicle, tank, weather, and road environment) as quintessential risk factors for accidents. Second, we used the developed BN-RA model to predict the probability of accidents. Third, using bidirectional inference in the BN approach, we analyzed and ranked the importance of the effects of these factors. The developed model was subsequently applied to assess the risks of major bridges crossing canals with different pavement grades and traffic flow levels both at present and in the future for the Beijing-Shijiazhuang Section of the MRSNWTP. The results indicated the following: (1) Although the overall potential risk of hazmat transportation accidents on all bridges in the Beijing-Shijiazhuang Section was fairly low (e.g., 0.08 %), the impacts cannot be ignored because of the potential for huge losses. (2) According to the analysis of many factors that may affect accidents, the driving patterns of drivers exerted the strongest influence on the probability of an accident, followed by vehicle conditions and lighting conditions. (3) If a vehicle were to fail, the highest probability (0.17 %) of an accident would arise if it were traveling on a road with no street lighting and poor road conditions at night. (4) Assuming that a vehicle was in good condition, the highest probability (0.12 %) of an accident arised when the vehicle suddenly encountered poor road conditions with no lights on a foggy night. (5) The predicted probabilities of accidents on Bridge TCWRR (short for the Tang County West Ring Road Bridge) in the short (i.e., the year 2017), medium (i.e., the year 2022) and long terms (i.e., the year 2027) were 3.25 × 10−4, 5.37 × 10−4, and 8.89 × 10−4, respectively. For Bridge DNR (short for the Dian Bridge on the North Road), these values were 8.64 × 10−6, 1.02 × 10−5, and 1.21 × 10−5, respectively. Based on the risk assessment results, to lower the accident probability and avoid the serious consequences resulting from hazmat transportation accidents, we developed an appropriate emergency response program to reduce potential hazards. This research resolved the problems of randomness and uncertainty associated with hazmat transportation in the MRSNWTP and can provide a reference for the effective prevention of hazmat transportation accidents and scientific decision-making in risk management.

Developing a chaotic pattern of dynamic risk definition for solving hazardous material routing-locating problem

In the case of determining routes and locations for constructing distribution centers on hazardous materials (Hazmat) transportation, risk and cost are considered as the main attributes for developing mathematical models. Since, Hazmat transport risk may be defined as a chaotic factor, using dynamic risk changes the selected routes and optimized locations for constructing distribution centers.In the present paper, an iterative procedure has been proposed to determine the best routes and optimized locations of distribution centers for transporting hazardous materials based on the concept of chaos theory in which hazmat transport risk is defined as a dynamic variable. A mathematical model has been developed for solving Hazmat routing and locating problems, simultaneously. Daily transport risk, defined as a chaotic variable, is iteratively updated using one-dimensional logistic map equation over the time period (year). An experimental road network, consists of eighty nine nodes and one hundred and three two-way edges, has been selected for analytical process and model validation. Results revealed that although different amounts of risk and cost priorities change optimized locations of distribution centers and their associated supplies, but the most frequent set of optimized centers remains independent. Therefore, the proposed procedure is capable to determine the best routes and optimized locations for distributing hazardous materials. While risk is iteratively updated over a specific time period, results show that the main property of chaos theory known as dependency upon initial condition would not be a serious concern for decision makers who are dealing with Hazmat management.