Decision Support Systems for Hazardous Materials Transportation Risk Analyses

A Decision Support System (DSS) may facilitate hazardous materials transportation risk management by integrating vehicle routing and emergency response planning decisions

(Zografos and Androutsopoulos, 2005). The DSS for hazardous materials transportation includes network modeling, routing software, and GIS application. These systems can be used in

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hazardous materials transportation route planning and risk analyses (Chin et al., 2006). In this section, I highlight some studies and literature about the development and application of DSS in hazardous materials transportation risk analyses.

2.5.1 Transportation Network Model

There are several large-scale transportation network models that can be used for route analyses. The Princeton Transportation Network Model (PTNM) (ALK, 1988) is one such model and it uses the Surface Transportation Board (STB) carload waybill sample data to generate the traffic flow map (Kornhauser and Bodden, 1983; Lorig, 2002). It contains over 23,000 links and 43,000 nodes in the North American rail network. A useful feature is that both traffic volume and flow direction can be conveniently displayed on the map (Kawprasert and Barkan, 2008). Previous UIUC railroad engineering program research that has used PTNM includes Day (2002) study of seismic impact on the Midwestern rail network and Anand (2006) study of environmental risk of hazardous materials transportation. I found PTNM to be a useful tool for understanding

hazardous material traffic patterns of Toxic Inhalation Hazard (TIH) materials and Environmentally Sensitive Chemicals (ESC).

There are also other network models for freight transportation analyses, including the CACI multimodal Transportation Network Model (TNM) of the University of

Pennsylvania/Argonne Lab, the Freight Network Equilibrium Model (FNEM), and the

Generalized Spatial Price Equilibrium Model (GSPEM). Munshi and Sullivan (1989) reviewed and described the basic features and algorithms of these transportation network models.

2.5.2 Rail Routing Software

INTERLINE is a rail routing model developed by the Oak Ridge National Laboratory (ORNL) to investigate potential routes for transporting radioactive materials. INTERLINE Version 5.0 routing algorithms have the ability to predict alternative routes, barge routes, and population statistics for any route. Its transportation network contains the U.S. rail network of over 15,000 rail and barge links and over 13,000 stations, interchange points, ports, and other locations (nodes). All rail lines, with the exception of industrial spurs, are included in the INTERLINE network (Johnson et al., 1993). This software has been later superseded by TRAGIS.

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PC*HazRoute is a decision support system developed by ALK Associates (ALK, 1994) that offers objective and scientific analysis of the risk of shipping hazardous materials over the U.S. highway and railroad network. Its database includes population data as well as accident probabilities. For a given origin-destination (OD), the software can find the routes that minimize route length, accident probability, release incident probability, total population exposure, and risk (Erkut and Glickman, 1997; Erkut and Verter, 1998). Examples of recent research in which this software had been used include Kara et al. (2003) and Erkut and Ingolfsson (2005).

PC*MILER | Rail (ALK, 2006) is a point-to-point rail routing and mileage software that contains the North American rail network of over 240,000 miles, 49,856 active freight stations, 699 rail carriers, and over 3,600 unique junction interchanges. It allows the user to determine the routes based on specified OD pairs and rail carriers, with routing options including shortest, practical, intermodal, coal/bulk, and auto rack train routes. The detailed algorithms or route formulae for each routing option are not disclosed. According to software Help documentation, “the practical routings are based on mileage as well as on the mainline/branchline code to simulate most likely movements of general merchandise traffic; the shortest routes minimize the distance between two points; intermodal, coal/bulk, or auto racks may be used to determine the exceptional routings that these types of trains sometimes require.” I made extensive use of this software in my research (Kawprasert and Barkan, 2008; 2009), and it has been used in several other hazardous materials risk analysis projects at UIUC. Its network database is more up-to-date than PTNM. One of the significant features of PC*MILER | Rail is that it can generate a detailed geocode report that contains the list of locations enroute that can be used in the consequence analysis with GIS.

2.5.3 Geographic Information Systems

Geographic Information Systems (GIS) have been widely used in the field of transportation. Transportation applications of GIS are often referred to as GIS-T (Waters, 1999; Goodchild, 2000). Application of GIS is also widely used in risk analysis of transportation of hazardous materials (Lepofsky et al., 1993; Panwhar et al., 2000). It enables improved decision support in managing transportation safety (Abkowitz et al., 1990). In particular, it helps facilitate the process of consequence estimation to identify the potential receptors along hazardous materials

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shipment routes. GIS is well suited for design and management of hazardous materials routes because of its ability to integrate multiple data themes and data sources into an operational information system (Frank et al., 2000).

Phanwar at el. (2000) described a probabilistic risk assessment framework, in which GIS is incorporated to perform spatial analyses and to assist in the optimization procedure. In

particular, the Network Analyst, which is one of the extensions of ArcView GIS, was used to determine the route for road transportation of hazardous materials. In their study, the risk for each segment was calculated, then the optimized route for transportation of hazardous materials was determined.

Verter and Kara (2001) developed a GIS-based model for truck shipment of hazardous materials on the Canadian highway network and evaluated the risks associated with routing alternatives, i.e. the routes that minimize distance, probability of incident, population exposure, and expected number of people to be evacuated in case of an incident.

A number of studies over the past decade have used GIS for rail hazardous materials transportation route risk analyses. These include Lovett et al. (1997), Zhang et al. (2000), Bubbico et al. (2004), and Glickman and Evans (2008).

2.5.4 Transportation Routing Analysis Geographic Information System (TRAGIS)

The Transportation Routing Analysis Geographic Information System (TRAGIS) (Johnson, 1995) is a GIS-based transportation and analysis model, first developed in 1995 by the Oak Ridge National Laboratory of the U.S. Department of Energy (DOE). It has a comprehensive transportation network, including rail, truck, and waterways and has a user interface to graphically display the calculated routes. The TRAGIS output can be used as source data for other risk analysis models, such as RISKIND (Yuan et al., 1995) and RADTRAN (Neuhauser and Kanipe, 2000). The web-based version of TRAGIS, WebTRAGIS (Johnson and

Michelhaugh, 2003), was developed to be accessible over the World Wide Web. The WebTRAGIS home page is located at https://tragis.ornl.gov/ (last accessed May 30, 2009). TRAGIS replaced its original routing models, HIGHWAY and INTERLINE, that were

previously developed by ORNL. Further review of these computerized tools for risk assessment of the U.S. DOE was provided by Chen and Kapoor (2003).

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Recent development of TRAGIS includes the Rail Routing and Visualization Application (RRVA) (Johnson, 2006). According to Peterson and Church (2007), RRVA is a rail-specific extension to TRAGIS and uses a 1:100,000 scale railroad network developed by the Federal Railroad Administration (FRA). The network consists of over 24,000 nodes and 28,000 link segments contained within 97 sub-networks. These networks identify the various railroads, railroad operators, owners, and trackage rights that comprise the available rail track mileage for each US railroad. RRVA, however, does not account for the consequences of release of a particular material or the probability of a release (Hartong et al., 2007).