• No results found

RECOMMENDATIONS, AND CONCLUSION 5.1 Summary

5.2.2 Recommendations for Future Research

The number of incidents utilized in this study is minute compared to the overall amount of HazMat incidents involving flammable-combustible commodities. To generate more concrete findings, it is suggested that a more thorough analysis involving a greater sample of states and incidents be carried out. It may also prove essential for an analysis of incident distributions by distance and a time series analysis for short/long-haul shipments be carried out on a state by state basis.

Because incidents in this study occurred at random locations, data assortment did not differentiate between various origin-incident/destination pairs. Another suggestion is to perform an analysis where the destination of commodity shipment is utilized and controlled for within the analysis. For instance, specific origin-destination nodes which generate high volumes of delivery traffic should be focused on (i.e. California to Texas). This may provide a clearer description of how incidents are occurring relative to distance. In doing so, it can also be understood if incidents are occurring at some arbitrary point within transport or at its final destination.

One final idea is to utilize the months and regions synonymous to incidents in hopes of introducing a seasonal parameter. It may me possible to analyze annual peaks in incidents. This may enable a frequency analysis of incidents by month or seasons. An analysis of this form may result in the calculation of incident probability based on time of year.

5.3 Conclusion

With increasing traffic volumes of HazMats, concerns over the safe transport of HazMats have continued to grow (Madala, 2000). Government and industry alike, see a need

for safety and policy analysis to plan the minimum risk movement of these dangerous substances over the world’s network of highways, railroads, waterways, and other transportation (Madala, 2000). In this study, forecasted time series trends have indicated continuing occurrences of HazMat incidents. There is clearly a need to improve safety measures various aspects of land transport to tackle the growing frequency detected in the occurrence of incidents (Oggero et al., 2006). The findings of this study have given reason in reaffirming the need to better regulate the transportation of HazMats by the trucking industry. Future research within this field could build upon this study with the development of a

density function model which generates incident probability based on length of commodity travel.

REFERENCES

Abkowitz M.D., Abkowitz, S.B., & Lepofsky M. (1989). Analysis of human factors effects on the safety of transporting radioactive waste materials. Office of Transportation Systems and Planning. Retrieved March 27, 2007, from

http://www.osti.gov/energycitations/servlets/purl/6110870-DssKQ5/6110870.PDF Argesti, A., & Finlay, B. (1997).Statisitcal Methods for the Social Sciences. Prentice Hall Bakshi R., Knoblock C.A., & Thakkar S. (2004). Exploiting online sources to accurately

geocode addresses. Paper presented at the 12th annual ACM international workshop on Geographic Information Systems. Retrieved March 8, 2007, from

http://www.isi.edu/integration/papers/bakshi04-acmgis.pdf

Bergoggi G.E.G., & Wallace W.A. (1991). Closing the gap: Transit control for hazardous material flow. Journal of Hazardous Materials, 2 (7), 61-75

Bow, J.D.C., Waters N.M., Faris, P.D., Seidel, J.E., Galbraith, P.D., Knudtson, M.L., & Ghali, W.A. (2004). The Approach Investigators: Accuracy of City Postal Code Coordinates as a Proxy for Location of Residence. International Journal of Health

Geographics. Retrieved March 2, 2007, from

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=394341

Caldwell, J.G. The Box-Jenkins Forecast Technique. 2006. Retrieved May 30, 2007, from http://www.foundationwebsite.org/BoxJenkins.htm# Toc145736383

Campell, R.L., & Langford, R.E. 1991. Fundamentals of Hazardous Material Incidents. Chelsea, Mich: Lewis Publishers.

Comparative Risks of Hazardous Materials Truck Shipment Accidents/Incidents. (2001). Federal Motor Carrier Safety Administration

Cook W.H., Grala, K., & Wallis, R.C. (2006). Avian GIS models to signal human risk for West Nile virus in Mississippi. International Journal of Health Geographics, 5(36), Retrieved April 3, 2007, from

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1618835 Cuchi, E.P., Vilchez, J.A., & Casal J. (1999). Fire and Explosion Hazards during

filling/emptying tanks. Journal of Loss Prevention in the Process Industries, 12(6), 479-483

Cuttler, S., & Ji, M. (1997). Trends in U.S. hazardous materials transportation spills.

Damodaran, M., Daniel, J., & Luke, A.C. (2002). Probability of a Hazardous Material Truck

Accident in New Jersey. Paper presented at the 82ndAnnual Meeting of the

Transportation Research Board. Retrieved January 24, 2007

Dobie, K., & Glisson, L.M. (2005) Investigation of the Safety Training of Motor Carrier Drivers. Final Report: Southeastern Transportation Institute.

Dramowicz, E., Three Standard Geocoding Methods. 2004 Retrieved on May 8, 2007, from http://www.directionsmag.com/article.php?article_id=670&trv=1

Erkut, E., & Verter, V. (1998). Modeling of transport risk for hazardous materials.

Operations Research, 46 (5), 625-642.

Garson, D.G. (2006). Statistics Solutions Inc.Time Series Analysis. Retrieved May 29, 2007, from http://www.statisticsolutions.com/Time-Series-Analysis.htm)

Geocoding and Buffering Addresses in ArcGIS. (n.d.). Spatial Structures in the Social Sciences. Retrieved May 8, 2007, from

http://www.s4.brown.edu/S4/Training/Modul2/Instructions.pdf

Glickman, T., & Sontag, M.A. (1996). The tradeoffs associated with rerouting highway shipments of hazardous materials to minimize risk. Risk Analysis, 15(1), 61-68. Grubesic, T.H., & Matisziw, T.C. (2006). On the use f ZIP code and ZIP code tabulation

areas (ZCTAs) for the spatial analysis of epidemiological data. International Journal

of Health Geographics. Retrieved February 7, 2007, from

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1762013

Grubesic, T.H. (2007). Zip codes and spatial analysis: Problems and prospects. Socio-

Economic Planning Sciences (In Press)

Haghani, A., & Chen, Y.J. (2003). Routing and Scheduling for Hazardous Material

Shipments on Networks with Time Dependent Travel Times. A paper submitted for the annual meeting of the Transportation Research Board. Retrieved May 2, 2007. Hanowski, R.J. (2000). The Impact of Local/Short Haul Operations on Driver Fatigue. PhD

Dissertation. Virginia Polytechnic Institute and State University. Retrieved from Virginia Polytechnic Institute and State University Digital Thesis

Hanowski, R.J., Wierwille, W.W., and Dingus, T.A. (2003). An on road study to investigate fatigue in local/short haul trucking. Accident Prevention and Analysis. 35(2), 153-60 Harwood, D.W., Viner, J.G., & Russel, E.E.R. (1993). Procedure for developing truck

accident and release rates for Hazmat Routing. Journal of Transportation

Hobeika, A.G., & Signon, K. (1993). Databases and Need for Risk Assessment of

Hazardous Materials Shipments by Trucks. In L.N. Moses & D. Lindstrom (Eds.), Transportation of Hazardous Materials (pp 135-157) Boston: Kluwer.

Huang, B., & Fery, P. (2002). Aiding Route Decision for Hazardous Material Transportation. Retrieved February 13, 2007, from

http://projects.battelle.org/trbhazmat/Presentations/TRB2005-PF.pdf

Jenkins, G., & Box, G.E.P. (1970). Time Series Analysis, Forecasting and Control, Holden Day, San Francisco, CA

Krieger, N., Waterman, P., Chen, J.T., Soobader, M.J., Subramanian, S.V., & Carson, R. (2002). Zip Code Caveat: Bias Due to Spatiotemporal Mismatches Between Zip Codes and US Census–Defined Geographic Areas—The Public Health Disparities Geocoding Project. American Journal of Public Health, 92 (7), 1100-1102

Lepofsky, M., Abkowitz, M., & Cheng, P. (1993). Transportation Hazard Analysis in Integrated GIS Environment. Journal of Transportation Engineering, 119 (2), 239- 254

List, G.F., Mirchandani, P.B., Turnquist, M.A., & Zografos, K.G. (1991). Modeling and Analysis for Hazardous Materials Transportation: Risk analysis, Routing/Scheduling and Facility Location. Transportation Science, 25 (2), 100-14

Luedke, J., & White III, C.C. (2002). Hazmat Transportation and Security: Survey and Direction for Future Research. Technical Report. Retrieved March 20, 2007, from http://www2.isye.gatech.edu/setra/reports/hazmat.pdf

Madala, B.P.R. (2000). A simulation Study for Hazardous Materials Transportation Risk Assessment. Masters Thesis. Concordia University. Retrieved from Concordia University Digital Thesis

Massie, D.L., Blower, D., & Campell, K.L. (1997). Short-Haul Trucks and Driver Fatigue (DTFH61-C-00038). Washington, DC: Office of Motor Carriers, Federal Highway Administration Report.

Moses, L.N., & Savage, I. (1993). Characteristics of Motor Carriers of Hazardous Materials. Published in Transportation of Dangerous Goods: Assessing the Risks. University of Waterloo, Institute of Risk Research.

Oggero, A., Darbra, R.M., Munoz, M., Planas, E., & Casal, J. (2006). A survey of accidents occurring during the transport of hazardous substances by road and rail. Journal of

Pijawka, K.D., & Radwan, A.E. (1985). The Transportation of Hazardous Materials: Risk Assessment and Hazard Management. Dangerous Properties of Industrial Materials Report, 2-11.

Pipeline and Hazardous Material Safety Administration. (2005). Office of Hazardous

Material Safety Hazardous Material Incident System. Retrieved on January 23, 2007, from http://hazmat.dot.gov/pubs/inc/hmisframe.htm

Purdy, G. (1993). Risk Analysis of the transportation of dangerous goods by road and rail.

Journal of Hazardous Materials, 33 (2), 229-259

Qiao, Y., Keren, N., & Mannan, S.M. (2005).Predicting Accident Frequency of

Transportation of Hazardous Materials. Proceeding of the AIChE Process Plant Safety Symposium

Qiao, Y., Keren, N., & Mannan, S.M. (2007). Optimum Route Selection for Hazardous Materials Transportation Incorporating Security and Cost-Effectiveness

Considerations. Process Plant Safety Symposium. National American Institute of Chemical Engineers Meeting

Quarentelli, E.L. (1991). Disaster planning for transportation accidents involving hazardous materials. Journal of Hazardous Materials, 27, 49-60.

Rogers, G.O., & Sorenson, J.H. (1989). Warning and response in two hazardous materials transportation accidents in the U.S. Journal of Hazardous Materials, 22, 57-74. Sorenson, J.H., & Rogers, G.O. (1988). Local Preparedness for Chemical Accidents: A

Survey of U.S. Communities. Industrial Crisis Quarterly, 2, 89-108

Tabachnick, B.G., & Fidell, L.S. (2000). Using Multivariate Statistics- Fourth Edition-Allyn & Bacon

Thorvaldsen, Ø.E. (2006). Geographical Location of Internet Hosts using a Multi-Agent System. Masters Thesis. Norwegian University of Science and Technology. Retrieved June 6, 2007, from www.diva-portal.org/diva/getDocument?urn_nbn_no_ntnu_diva- 1271-1__fulltext.pdf

U.S. Census Bureau. (2001). Zip Code Tabulation Areas. U.S. Census Bureau: Geography Division. Retrieved on May 4, 2007, from

http://www.census.gov/geo/ZCTA/zctafaq.html

U.S. Code of Federal Regulations. (1999). Title 40. Protection of Environment. Part 355. Emergency Planning and Notification

U.S. Department of Commerce. (1994).Truck Inventory and Use. Bureau of the Census, Washington D.C.

Viichez, J.A., SeviUa, S., Montielt, H., & Casalt, J. (1995). Historical Analysis of accidents in chemical plants and in the transportation of hazardous materials. Journal of Loss

Prevention in the Process Industry, 8 (2), 87-96

Wylie, C.D., Shultz, T., Miller, J.C., Mitler, M.M., Mackie, R.R., 1996. Commercial motor vehicle driver fatigue and alertness study: technical summary. FHWA Report no. FHWA-MC-97-001. US Department of Transportation, Federal Highway

Administration, Washington, DC.

Zhang, P.G. (2003). Time Series forecasting using hybrid ARIMA and neural network and model. Neurocomputing, 50,159-175

Zimmerman, D.L., Fang, X., Mazmumdar, S., & Rushton, G. (2007). Modeling Probability of positional Errors Incurred by Residential Address Geocoding. International

Journal for Health Geographics. Retrieved March 2, 2007, from

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1781422

Zografos, K., & Androutsopoulos, K. (2005). A decision support system for hazardous

materials transportation and emergency management. Proceedings of the 84th

Transportation Research Board Annual Meeting. Retrieved January 18, 2007, from http://projects.battelle.org/trbhazmat/Presentations/TRB2005-KZ.pdf

Related documents