Theses and Dissertations at Montana State University (MSU)
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Item Developing a network screening method for low volume roads(Montana State University - Bozeman, College of Engineering, 2020) Huda, Kazi Tahsin; Chairperson, Graduate Committee: Ahmed Al-KaisyCrash occurrences on rural low-volume roads (LVRs) are usually more severe in nature. This is mostly because of higher speeds and outdated infrastructure designs. Therefore, safety management programs for these roads are equally as important as their urban and high-volume counterparts. Network screening is an important aspect of safety management programs. However, traditional network screening methods based on historical crash data may not provide accurate results for LVRs. This is because of the sporadic nature of crash occurrence and the lower volumes. Therefore, the purpose of this research is to develop a suitable network screening method for LVRs. The literature review of this research identified a few existing network screening methods. A state-of-practice survey was also carried out in order to understand the LVR safety management practices across the United States. Then the identified methods were assessed for their suitability for LVRs. The method using a combination of crash frequency, severity and rate, and the Empirical Bayes (EB) method scored the highest. However, the EB method was selected for further analysis as it is not entirely dependent on historical crash experience and it incorporates risk factors. Actual LVR data from Oregon was used to analyze the EB method. This analysis indicated that the safety performance functions (SPFs) of the EB method overestimates the predicted crash numbers. This overestimation is mostly due to the high accident modification factors (AMF) for sharp horizontal curves. Finally, an alternative method was proposed. Two multiple linear regression models for estimating expected crashes mostly using risk factor categories were developed. The risk factor data were categorized using Classification and Regression Tree (CART) analysis. Both models have R square values of more than 0.90.Item The repeal of Montana's medical marijuana act and traffic fatalities(Montana State University - Bozeman, College of Agriculture, 2020) Lantz, Scott Bryan; Chairperson, Graduate Committee: Mark AndersonOver the last several years, marijuana legalization has become a popular piece of state legislation. While most legislation is focused on the passage of these laws for marijuana use, Montana, in 2011, rescinded a previously passed medical marijuana law with Senate Bill 423. This thesis examines the relationship between rescinding a medical marijuana law and traffic fatalities, one of the leading causes of death in America, in Montana after Senate Bill 423 was passed. I test for a causal effect using a synthetic control approach along with a weighted regression using data from the Fatal Analysis and Reporting System with data from 2001-2017. I find that the synthetic control groups saw similar patterns in traffic fatalities despite not rescinding a medical marijuana law. The weighted regression analysis also shows that there is no statistical difference in traffic fatalities after the policy in Montana.Item Mapping risky driver behavior and identifying their contributory factors : a spatial statistical approach(Montana State University - Bozeman, College of Engineering, 2016) Sharda, Shivam; Chairperson, Graduate Committee: Yiyi WangThe goal of this study is to develop risk maps that predict zones that have an increased risk of traffic crashes for utility service trucks of the electric power industry. This study employed a national dataset that contains video logs of driving events from 10,009 utility truck drivers from 2010 to 2014. The study consists of four steps. Step 1 focused on finding whether certain driver behaviors (e.g., traffic violation, distraction, etc.) cluster in the same location as crashes and, therefore, suggest behaviors that are predictive of crashes. The study used Getis-Ord Gi* hot-spot analysis to reveal the clustering pattern within a standard unit of area (at the grid cell level: 1,640 feet by 1,640 feet). The finding of this research indicated that four behaviors ('risky behaviors') consistently cluster with the collision outcomes: distraction, lack of awareness, following too close, and eating/drinking. In Step 2, negative binomial models were used to relate the occurrence of the risky behaviors to a host of geospatial variables (e.g., land use, traffic, and socio-economics) while controlling for the exposure at the grid level (200 feet by 200 feet, roughly the size of a street block). Step 2 was implemented on the three datasets that were assembled based on different levels of availability of the geospatial features. Results indicated that well-balanced land use, road network density, lane-mile density of secondary and primary roads (if urban areas), and high concentration of elderly people (65 years and above) contributed to the prevalence of risky behaviors. Residential neighborhood, local road (if rural area), and average household size were shown to dampen incidence of risky behaviors. Step 3 developed the scoring systems to estimate the overall risk of each risky behavior for a given location (grid). Finally, Step 4 developed risk maps on a 2-D scale to delineate locations into different levels of hazards. In sum, this study confirmed the linkage between driver behavior and collisions and proposed a new way to anticipate crashes. While the test dataset pertains to utility service trucks, the methods can be adapted for predicting locations where the risk of future crashes is higher.Item Risk factors associated with high potential for crashes on low-volume roads(Montana State University - Bozeman, College of Engineering, 2016) Hossain, Fahmid; Chairperson, Graduate Committee: Ahmed Al-KaisyA significant portion of the roadway mileage in the U.S. is comprised of the low volume roads. As these roads experience very low crash frequencies, the identification of hazardous locations based on crash history alone is difficult. However, these low-volume roads may be associated with higher level of risks and consequently higher crash rates due to substandard geometry on these roads. Therefore, an approach to identify hazardous locations on low volume roads which accounts for geometric and roadside features as well as crash history seemed to be necessary. For this purpose, roadway data from Oregon's low volume roads and 10-years of crash data on the selected sample were collected and analyzed to identify the roadway geometric and roadside features that contribute to the crash occurrence. Length of the horizontal and vertical curves under 100 feet, degree of curvature over 30 degrees, vertical grade over 5 percent, lane width narrower than 11 feet, shoulder width of 0 feet, and driveway density of 5 driveways/mile were found as the most restrictive features contributing to higher crash rate. Based on these analyses a quantitative tool was developed for assessing the level of risk on low volume roads. The developed risk index, which is a function of roadway geometry, roadside features, traffic exposure, and crash history, is proactive in nature, as it does not rely heavily on crash occurrence in assessing crash risks. Application of the crash risk index on the three corridors of Oregon showed that, the use of risk index provides new information about the level of hazard along highway segments compared to using crash history alone. Economic feasibility of some potential low-cost safety countermeasures was analyzed to identify which countermeasures would ensure the maximum return on investments. Installation of the rumble strips, object markers, safety edge, centerline and edge-line markings were found to be most cost effective with benefit/cost ratio over 8. The same procedure can be followed by other states, with similar road and traffic conditions, to identify the contributing factors of crashes and identify the most-effective countermeasures to improve the safety of the road.Item Characterizing commercial vehicle safety in rural Montana(Montana State University - Bozeman, College of Engineering, 2001) Burke, Patricia WalshItem Identifying weather-related factors affecting crash severity and consequent response actions : a comparative analysis of the multinomial logit and ordered probit model forms(Montana State University - Bozeman, College of Engineering, 2001) Blomquist, Daniel ThomasItem Haptic and auditory interfaces as a collision avoidance technique during roadway departures and driver perception of these modalities(Montana State University - Bozeman, College of Engineering, 2006) Stanley, Laura Michelle; Chairperson, Graduate Committee: Robert J. MarleyRoadway departure fatalities accounted for 55 percent of all roadway fatalities in the United States in 2003. In an effort to reduce the number of roadway departures, many transportation agencies have introduced static rumble strips using physical alterations of the roadway surface in shoulder and/or centerline sections of the roadway. Recently, more advanced technology has been developed in the form of in-vehicle advanced lane departure warning systems that automatically detect the vehicle's lane position and warn of possible roadway departures. These systems are currently showing their value in some commercial trucks in Europe, and are now available in some U.S. passenger cars. Two critical factors will govern their ultimate success; (1) their ability to warn the driver in an effective and timely manner to make the correct action, and (2) their success in gaining driver trust and acceptance. The primary goal of this research was to better understand basic human factors principles of haptic and auditory interfaces as a collision avoidance technique during run-off-road and head-on collisions and driver perception of these modalities. In this simulator study, fifteen participants received alerting cues in three sensory modalities; haptic (seat vibration), auditory ("rumble strip" sound), and combined auditory and haptic sensory warnings. A preliminary psychophysical study was conducted to determine appropriate and comparable intensities of the warning modalities. The results of this study determined that the haptic modality produced significantly faster reaction times than both the auditory and combination modalities. The auditory modality produced significantly more maximum steering response than the haptic and combination condition. Drivers perceived the haptic modality to be the least annoying with least interference, while the combination modality was the most preferred in benefit of driving, most likely to purchase, level of trust, level of appropriateness, level of urgency, and overall preference. Haptic (seat vibration) warnings demonstrate promise as an alerting strategy over auditory and combination modalities in reducing roadway departures. With a decrease in reaction time, less erratic steering responses, and relatively advantageous perceptions from drivers, haptic warnings have the potential to better assist drivers in returning to the lane more quickly and safely.