Data Mining - Concepts and Techniques.

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has been an area of research focus for many decades. However, in the absence of detailed driving data that would help improve the identification of cause and effect relationships with individual vehicle crashes, most researchers have addressed this problem by framing it in terms of understanding the factors that affect the frequency of crashes - the number of crashes occurring in some geographical space (usually a roadway segment or intersection) over some specified time period. This paper provides a detailed review of the key issues associated with crash-frequency data as well as the strengths and weaknesses of the various methodological approaches that researchers have used to address these problems. While the steady march of methodological innovation (including recent applications of random parameter and finite mixture models) has substantially improved our understanding of the factors that affect crash-frequencies, it is the prospect of combining evolving methodologies with far more detailed vehicle crash data that holds the greatest promise for the future.

http://ceprofs.tamu.edu/dlord/Papers/Lord-Mannering_Review.pdf

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

https://www.ce.utexas.edu/prof/bhat/ABSTRACTS/AMAR_review_article.pdf

Analytic methods in accident research: Methodological frontier and future directions

http://ceprofs.civil.tamu.edu/dlord/Papers/Savolainen_et_al._Crash-Severity-Review-Final.pdf

The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives.

The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions.

Consideration of highway safety studies in a time-space domain is used to introduce the concept that different study designs result in different underlying probability distributions describing accident occurrence Poisson regression is proposed as a superior alternative to conventional linear regression for many safety studies because it requires smaller sample sizes and has other desirable statistical properties Models are estimated using accident, travel mileage, and environmental data from the Indiana Toll Road A pooled model including all accidents revealed that accident occurrence increases with automobile vehicle miles of travel (VMT), truck VMT, and hours of snowfall Segmentation of the data into subsets that describe different types of collisions revealed that automobile accidents are much more sensitive to environmental conditions than are truck accidents Use of the segmentation technique allowed a much clearer understanding of the effects of travel mileage on accident occurrence than could have been obtained from the pooled data alone

Modeling the relationship of accidents to miles traveled

This study aimed to investigate the relationship between age, gender, and risky behaviors of motorcyclists and their involvement in accidents. The results of a self-reported survey on motorcyclist behavior in the Taipei metropolitan area were analyzed. A two-step cluster analysis was used to classify motorcyclist behavior to different levels of risk within each of three risky behavior types. This was used to examine the regression relationship with accident risk. The results indicated that young and male riders were more likely to disobey traffic regulations, and that young riders also had a higher tendency towards negligence of potential risk and motorcycle safety checks. These "error" and "violation" behaviors increased the likelihood of an accident. However, in addition to these risks, there are additional factors that put young riders, particularly young female riders with the least riding experience, at increased risk of having an accident. These additional factors may be poor driving skills and less experience, all of which may result from the slack motorcycle licensing system. There should be increased emphasis on the necessity of providing appropriate training and a lower risk environment for novice riders.

https://ir.nctu.edu.tw:443/bitstream/11536/14334/1/000244055900004.pdf

Motorcyclist accident involvement by age, gender, and risky behaviors in Taipei, Taiwan

Single-vehicle crash data for 2000 from Taiwan's Road Accident Investigation & Reporting System were employed to compare fatality risk factors between non-motorcycle drivers and motorcyclists. On average, motorcyclists had approximately a three times higher fatality risk than non-motorcycle drivers after adjusting for the driving mileage. Two respective logistic regression models for these two categories of drivers indicated that some common features, such as being male, a higher age, and crashes occurring between the hours of 2200 and 0600 revealed a greater likelihood of fatality. On the other hand, the risk discrepancies between these two drivers included the restraint-use effect, speeding, and impairment as the main crash cause, roadway class, and vehicle type. To reduce the high risk of fatality sustained by these two classes of drivers, enhancing the driver's seatbelt-use rate, the management of running speed, the rider's risk perceptions, and the road quality and facilities of the lowest roadway class are particularly recommended.

https://ir.nctu.edu.tw:443/bitstream/11536/12574/1/000235569300006.pdf

Hsin-Li Chang

Papers

Modeling the relationship of accidents to miles traveled

Motorcyclist accident involvement by age, gender, and risky behaviors in Taipei, Taiwan

Risk Factors to Driver Fatalities in Single-Vehicle Crashes: Comparisons between Non-Motorcycle Drivers and Motorcyclists

Disaggregate model of highway accident occurrence using survival theory

Formulating accident occurrence as a survival process