• No results found

CHAPTER III DATA AND METHODS

5.2 FURTHER RESEARCH AND LIMITATIONS

This research contributes several techniques which can be attributed to traffic safety mapping in general. The concepts regarding spatial autocorrelation and interpolation, though known in the field, are coupled in a way that spatial and temporal information can be readily drawn from and studied for similar datasets. This research could be taken further by incorporating a more specific dataset containing more information about the crash locations. Also, knowing more specific information about the crash regarding, for example, age, gender, and time could greatly alleviate the steps taken towards drawing solid conclusions.

Until every vehicle is equipped with a crash monitoring and recording system, police officers are trained to record the level of data needed by GIS analysts, and organizations are organized to the point that data is up to date and readily available, traffic safety in regards to the research conducted here will have several limitations. This

need of a more detailed dataset was perhaps the greatest limitation in this study. The fact that aggregated datasets were used at a relatively small scale, for example with more detail than state or national-level studies but less than census tracts, made it difficult to conclude in favor of the proposed hypothesis that crashes were declining as a result of changes spatially and temporally partially respect to those chosen variables. Another limitation was due in part to the complexity of crashes. For example, simply attributing age, gender, location, and population as independent variables cannot fully explain the spatial and temporal variations of traffic crashes. Another limitation stems from the fact that, although crashes were a positive BAC was established were considered alcohol-related, the possibility that the driver died from consequences completely unrelated to alcohol is a possibility. It is believed that a BAC as low as 0.01% can have adverse effects for some, although for most a BAC that low often does not impair driving. It is also important to point out that Texas has wet, partially wet, and dry county laws in regards to allowing or prohibiting the sale of alcoholic beverage. Though the definition of each, respectively, seems rather obvious whereby wet counties, the technicalities and legislations involved in formulating which county falls under which category is rather difficult. For example, various counties may be partially wet in that some of the cities within it are wet or dry. This makes it difficult to assign a single category to various counties. This research also did not put into account the various laws which were discussed in the literature review (21 and up, zero tolerance etc). Finally, aside from Moran’s I values indicating the significance of clustering, conclusions were drawn

without the use of rigorous statistical procedures commonly discussed within the traffic safety literature.

5.3 CONCLUSION

Although traffic safety is a broad and extensive field of research, geography plays an important role in understanding complex relationships between the many variables that play a role in traffic crashes. Understanding the spatial variation of the dependent and independent variables through time and space is a critical part of traffic safety research. GIS is becoming more than a simple tool adopted in traffic safety research and the advances that have been made in recent years are a sure sign that geography continues to contribute imperative information to the field. Digital maps continue to gain importance and respect as representations of space and designated factors which are critical to traffic safety. These methodologies built from advances in geographic knowledge and techniques will continue to contribute a great amount of information for a variety of sectors from civil engineering to traffic safety administration.

REFERENCES

Al-Balbissi, A. H., 2000. Role of gender in road accidents. Traffic Injury Prevention 4, 64-73.

Amoros, E., Martin, J. L., Laumon B., 2003. Comparison of road crashes incidence and severity between some French counties. Accident Analysis and Prevention 35, 537-547.

Clark, D. E., 2003. Effect of population density on mortality after motor vehicle collisions. Accident Analysis and Prevention 35, 965-971.

Dissanayake, S., Lu, J., 2002. Analysis of severity of young driver crashes: Sequential binary logistical regression modeling. Transportation Research Record: Journal of the Transportation Research Board 1784, 108-114.

Evans, L., 2004. Traffic Safety. Science Serving Society, Bloomfield Hills, MI.

Farrow, J. A., Brissing P., 1990. Risk for DIW: A new look at gender differences in drinking and driving influences, experiences, and attitudes among new adolescent drivers. Health Education Quarterly 17 (2), 213-221.

Flahaut, B., Mouchart, M., Martin, S. E., Thomas, I., 2003. The local spatial autocorrelation and the kernel method for identifying black zones a comparative approach. Accident Analysis and Prevention 35, 991-1004.

Fridstrom, L., Ingebrigtsen, S., 1991. An aggregate accident model based on pooled, regional time-series data. Accident Analysis and Prevention 23 (5), 363-368.

Gmel, G., Bissery, A., Gammeter, R., Givel, C., Calmes, M., Yersin, B., Daeppen, J-B., 2006. Alcohol-attributable injuries in admissions to a Swiss Emergency room – An analysis of the link between volume of drinking, drinking patterns, and preattendance drinking. Alcoholism: Clinical and Experimental Research.

30 (3), 501-509.

Goodchild, M. F., 1992. Geographical data modeling. Computers and Geosciences 18, 401-408.

Goodchild, M. F., 2000. GIS and transportation: Status and challenges. Geoinformatica 4 (2), 127-139.

Gorman, D. M., Huber JR J. C., Carozza, S. E., 2006. Evaluation of the Texas 0.08 BAC law. Alcohol & Alcoholism 41 (2), 193-199.

Hauer, E., 1992. Empirical Bayes approach to the estimation of “Unsafety”: The multivariate regression method. Accident Analysis and Prevention 24 (5), 457-477.

Holubowycz, O. T., Kloeden, G. N., McLean A. J., 1994. Age, sex and blood alcohol concentration of killed and injured drivers, riders and passengers. Accident Analysis and Prevention 26 (4), 483-492.

Keane, C., Maxim, P. S., Teevan, J. J., 1993. Drinking and driving, self-control, and gender: Testing a general theory of crime. Journal of Research in Crime and Delinquency, 30 (1), 30-46.

Kim, K., Levine, N., 1996. Using GIS to improve highway safety. Computer, Environment, and Urban System 20 (4/5), 289-302.

Laapotti, S., Keskinen, E., 2004. Has the difference in accident patterns between male and female drivers changed between 1984 and 2000?. Accident Analysis and Prevention 36, 577-584.

Lam, L. T., 2002. Distractions and the risk of car crash injury: The effect of drivers’

age. Journal of Safety Research 33, 411-419.

Levine, N., Kim, K., Nitz, H. L., 1995. Spatial analysis of Honolulu motor vehicle crashes: 1. spatial patterns. Accident Analysis and Prevention 27 (5), 663-674.

Levine, N., and K. E. Kim, 1998. The location of motor vehicle crashes in Honolulu: A methodology for geocoding intersections. Computers, Environment and Urban Systems, 22 (6), 557-576.

Li, Linhua., Zhu, Li., Sui, Daniel Z., 2007. A GIS-based Bayesian approach for analyzing spatial-temporal patterns of intra-city motor vehicle crashes. Journal of Transport Geography 15, 274-285.

Loo, B. P. Y., 2006. Validating crash locations for quantitative spatial analysis: A GIS-based approach. Accident Analysis and Prevention 38 (5), 879-886.

Massie, D. L., Green, P. E., Campbell, K. L., 1997. Crash involvement rates by driver gender and the role of average annual mileage. Accident Analysis and Prevention 29 (5), 675-685.

McGwin, G. Jr., Brown, D. B., 1999. Characteristics of traffic crashes among young, middle-aged, and older drivers. Accident Analysis and Prevention 31, 181-198.

Mercer, W. G., 1987. Influences on passenger vehicle casualty accident frequency and severity: Unemployment, driver gender, driver age, and restraint device use.

Accident Analysis and Prevention 19 (3), 231-236.

Messner, F. S., and Anselin, L., 2004. Spatial analysis of homicide with areal data.

Spatially Integrated Social Science Ed. Goodchild, M., and Janelle, D., 127-144.

Miller, T. T., Lestina D. C., Spicer R. S.. 1998. “Highway crash costs in the united states by driver age, blood alcohol level, victim age, and restraint use”. Accident Analysis and Prevention. 30(2): 137-150.

Miller, T. T., Spicer, R. S., Levy, D. T.. 1999. “How intoxicated are divers in the United States? Estimating the extent, risks and costs per kilometer of driving by blood alcohol level”. Accident Analysis and Prevention. 31: 515-523.

Nyberg, A.. Gregersen, N. P., 2007. Practicing for and performance on drivers license tests in relation to gender differences in crash involvement among novice drivers.

Journal of Safety Research 38, 71-80.

Pawlovich, D. M., Souleyrette R. R., Strauss, T., 1998. A methodology for studying crash dependence on demographic and socioeconomic data. Transportation Conference Proceedings, 1-7.

Smink, B. E., Ruiter, B., Lusthof K. J., Gier, de J. J., Uges, D. R. A., Egberts, A. C. G., 2005. Drug use and the severity of a traffic accident. Accident Analysis and Prevention 37, 427-433.

Stevenson, M., R. D. Brewer, and Lee, V., 1998. The spatial relationship between lincesnsed alcohol outlets and alcohol-related motor vehicle crashes in Gwinnet County Georgia. Journal of Safety Research 29 (3), 197-203.

Subramanian, R., 2002. Transitioning to Multiple Imputation – A new method to estimate missing blood alcohol concentration (BAC) values in FARS.

Mathematical Analysis Division, National Center for Statistics and Analysis http://www-nrd.nhtsa.dot.gov/Pubs/809-403.PDF (Accessed 7-10-08)

Thill, J. C., 2000. Geographic information ystems for transportation in perspective.

Transportation Research Part C 8, 3-12.

Thomas, I., 1996. Spatial data aggregation: exploratory analysis of road accidents.

Accident Analysis and Prevention 28 (2), 251-264.

US Department of Transportation, National Highway Traffic Safety Administration, 2005. Traffic Safety Facts: 2005 Data Alcohol. Washington DC. http://www-nrd.nhtsa.dot.gov/pdf/nrd-30/ncsa/tsf2005/2005tsf/810_616/images/alcohol.pdf (accessed 4-29-07)

US Department of Transportation, National Highway Traffic Safety Administration, 2006. Traffic Safety Facts: 2006 Alcohol-Impaired Driving. Washington DC http://www-nrd.nhtsa.dot.gov/Pubs/810801.PDF (Accessed 5-30-08)

Valverde, J., and Jovanis, P., 2006. Analysis of fatal and injury crashes in Pennsylvania.

Accident Analysis and Prevention 38 (3), 618-625.

Wageneaar, A. C., Toomey, T. L., 2002. Effects of minimum drinking age laws:

Review and analyses of the literature from 1960 to 2000. Journal of Studies on Alcohol/Supplement 14, 1-21.

Winn, R. C., Giacopassi, D., 1993. Effects of county-level alcohol prohibition on motor vehicle accidents. Social Science Quarterly 74 (4), 1-11.

Yagil, D.. 1998. “Gender and age-related differences in attitudes toward traffic laws and traffic violations”. Transportation Research Part F. 1: 123-135.

Zador, P. L., Krawchuk, S. A., Voas, R. B., 2000. Alcohol-related risk of driver fatalities and driver involvement in fatal crashes in relation to driver age and gender: An update using 1996 data. Journal of Studies on Alcohol 61 (3), 387-395.

VITA

Gabriel A. Rolland received his Bachelor of Science degree in geography from Texas A&M University in December 2005. Prior to graduation, he studied geography while focusing on GIS and cartography. Furthermore, he earned several awards including an induction into the International Geographical Honor Society in 2004 and a Distinguished Student Award in 2003. He entered the geography program at Texas A&M University in August 2006 and received his Master of Science degree in geography on December 2008. His research interests include GIS analysis, traffic safety, remote sensing, and both physical and human geography. He plans to publish one or more research articles on these topics, focusing on alcohol crashes in Texas. Finally, he hopes to pursue an interest in meteorology concerning natural disasters and modeling, forecasting, and emergency preparedness.

Name: Gabriel A. Rolland

Address: 10696 Edenoaks St., San Diego, California 92131 Email Address: [email protected]

Education: B.S., Geography, Texas A&M University, 2005 M.S., Geography, Texas A&M University, 2008