Theses and Dissertations at Montana State University (MSU)
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Item Emotional intelligence and dangerous driving behaviors(Montana State University - Bozeman, College of Engineering, 2022) Ahmed, Jubaer; Chairperson, Graduate Committee: Nicholas Ward; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'How does emotional intelligence predict driving behaviors among non-commercial drivers?' in the journal 'Journal of transportation research part F: psychology and behaviour' which is contained within this dissertation.; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'The influence of emotional intelligence on dangerous driving: a comparison between commercial and non-commercial drivers' submitted to the journal 'Journal of safety science' which is contained within this dissertation.; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'Developing a scale to assess emotional intelligence in the context of driving' submitted to the journal 'Journal of personality assessment' which is contained within this dissertation.Dangerous driving behaviors are the leading cause of road crashes and fatalities. Many factors contribute to dangerous driving behaviors including drivers' beliefs, attitudes, personalities, and emotions. Of these, the role of emotions has received less attention. Emotional Intelligence theory provides a framework for understanding how individuals' emotional factors influence their behaviors and interactions with others. Therefore, this research aims to understand how emotional intelligence can be used to investigate and alleviate dangerous driving behaviors. The research aims of this dissertation include 1. Identify the most appropriate measure of emotional intelligence that is currently available for the driving context; 2. Examine the correlations between emotional intelligence and dangerous driving behaviors in different risk exposure groups (commercial and non-commercial drivers); 3. Develop an emotional intelligence measure specific to the context of driving. This research dissertation comprised four survey studies conducted between November 2019 to July 2021 among commercial and non-commercial drivers across the United States. The results further revealed higher emotional intelligence scores related to less dangerous driving behaviors for both commercial and non-commercial drivers. However, the relationship between emotional intelligence and dangerous driving was significantly stronger among commercial drivers than their non-commercial counterparts. In the final study, this research developed a new Drivers' Emotional Intelligence Scale (DEIS) specific to driving. Factor analysis revealed a three-factor structure for DEIS labeled as emotionality, self-control, and anxiety. The results showed that the DEIS subscales were stronger predictors of dangerous driving behaviors compared to the previously used emotional intelligence scales. This research concludes that improving emotional intelligence will be useful to reduce dangerous driving behaviors and suggests incorporating emotional intelligence to design interventions to reduce fatal road crashes. This research acknowledges some limitations such as the use of self-reported surveys and convenience quota samples, which may have limited the generalizability of these results. Future research should continue to gather evidence about the association between emotional intelligence and traffic safety through different experimental designs and longitudinal studies.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 effects of message threat/reflection on psychological reactance in traffic safety messaging(Montana State University - Bozeman, College of Engineering, 2020) Townsend, Asher Campbell; Chairperson, Graduate Committee: Nicholas WardPsychological reactance is a motivation to regain a freedom after it has been lost or threatened, which has led people to largely resist the social influence of others (Steindl et al., 2015). Steindl et al. (2015, pg. 205) also define psychological reactance as 'an unpleasant motivational arousal that emerges when people experience a threat to or loss of their free behaviors.' Seat belt use and distracted driving are two of the highest-fatality behaviors and they pose the greatest threat to other drivers' health and safety on U.S. roadways (NHTSA, 2018a). The purpose of this research is to investigate whether psychological reactance may be a significant factor in influencing people's reactions and their choices to continually engage in risky behaviors. Moreover, this research looks at whether select individuals are more prone to experiencing reactance and how it may influence their willingness to follow driver safety messaging. Specifically, this research will investigate whether varying message threat and message reflection influence the amount of reactance experienced. Three main components of psychological reactance are of concern in the study: Reactance Attitude, Emotional Reactance, and Threat to Freedom. Each of these behaviors is measured for varying message conditions for two different message sets: one for Seat Belt Use and another for Distracted Driving. For the Emotional Reactance and Threat to Freedom reactance measures, there is a significant correlation between the measures and reactance proneness. It was found that as proneness increases, the resulting psychological reactance increases as well. For the Distracted Driving messages, there was a significant effect of Message Threat for the Emotional Reactance and Threat to Freedom conditions such that low threat messages elicited less psychological reactance than high threat messages. From this study, we recommend the following aspects for designing traffic safety messages: 1) Messages should use non-controlling language (consider, can, could, may, try) over controlling language (should, ought, must, need), 2) Messages should aim to be suggesting (try to do this), rather than commanding (you MUST do this!). Additionally, high threat messages may tend to elicit stronger reactance independent of reactance proneness, supporting the proposal of avoiding high threat messages for traffic safety.Item A systemic pedestrian safety planning tool for rural and small urban areas(Montana State University - Bozeman, College of Engineering, 2018) Jamali, Amir; Chairperson, Graduate Committee: Yiyi WangRural areas bear a disproportionate number of pedestrian fatalities: the fatality rate per 100 million vehicle miles traveled is 2.5 times higher in rural areas than in urban areas. To measurably improve pedestrian safety, it is paramount to predict crash hot spots and apply cost-effective countermeasures. This dissertation work developed a new systemic pedestrian safety tool to enhance crash hotspot identification and safety project prioritization for rural and small urban areas. This new tool suggested a six-step systemic safety framework: (1) initial screening, which identifies what type of facilities are more prone to pedestrian crashes, (2) pedestrian exposure estimation, which provides an area-level exposure metric using National Household Travel Survey (NHTS) 2009, (3) crash risk factor identification, which identifies the factors that contribute to the occurrence and high severity levels of pedestrian crashes, (4) hotspot identification, which identifies the locations that are more likely to experience pedestrian crashes using two-step floating catchment area (2SFCA) method, (5) countermeasure selection, which provides candidate countermeasures through literature sources, and (6) project prioritization, which ranks safety projects through a mixed linear programming. This study incorporated three states' pedestrian crash data from 2011 to 2013: Texas, Oregon, and Montana. It was found that in rural and small urban areas pedestrian safety is associated negatively with male and elderly drivers, shoulder presence, bike lane presence, higher speed limit, number of lanes, wet surface, pedestrian exposure, hospital distance, population density, median income, share of industrial and commercial areas, and dark hours. In contrast, the pedestrian safety is associated positively with signal control, sidewalk and warning sign presence, median presence, icy and snowy surface, higher AADT, and high densely household areas. To validate the proposed hotspot and project prioritization methods, this study used the pedestrian crash data set from 2014 to 2016 in the City of Bozeman, a small urban area. According to findings, about 60 percent of crash locations fall on areas with a high crash risk index. Reasonable countermeasures were suggested for twenty intersections with highest crash risk index. It was found that budget of $100,000 is the optimal budget, where the crash risk index was reduced by 63 percent.Item A study on dynamic bicycle detection and warning device(Montana State University - Bozeman, College of Engineering, 2018) Relph, David Edward; Chairperson, Graduate Committee: Ahmed Al-KaisyThis research pertains to the effectiveness and reliability of a Dynamic Bicycle Detection and Warning sign. In rural areas there are fewer safety options due to financing and environmental design restrictions. Rural roads normally have higher speeds and reduced lane widths with limited or no shoulders. Thus, safety on roads in rural environments should be of great concern for designers. Data concerning interactions between bicycles and vehicles was collected to determine the effectiveness and reliability of the system. Before- and after-installation data was collected via radar traffic recorders and video cameras at two sites along Rim Rock Drive. The data collected before-installation was used to determine a baseline for the interactions between drivers and bicyclists. Two indicators of drivers' reaction were used: vehicle speed and lateral placement in the lane. Three other variables were tested for their effect on the two aforementioned variables: time to opposing vehicle arrival, time between a bicycle and a vehicle, and vehicle class. The variable, lights flashing was added to determine the effects of the system on speed and lateral placement. Results suggest vehicle speed and lateral placement are both affected by the presence of bicyclists. Before-installation affects were primarily seen when the vehicle was observed within 10 seconds or less of a bicycle, or within approximately 400 feet. After-installation the affects were seen up to four minutes after the bicycle passed the site. Driver reactions were similar before and after up to 20 seconds. After 20 seconds drivers moved over more and after 30 seconds drivers slowed down more after-installation. The system detected a bicycle 86% of the time and detected something else 11% of the time. In conclusion the system reduced speeds and encouraged drivers to move over. However, no change in driver behavior occurred under 20 seconds. Speeds averaged around 26 miles per hour which is over the posted speed limit. Most drivers were still utilized the right third of the lane. Therefore, the system was reliable and effective, enhancing bicyclist safety, but driver behavior still poses a danger to bicyclists on Rim Rock Drive.Item Empirical assessment of a congestion and weather-responsive advisory variable speed limit system(Montana State University - Bozeman, College of Engineering, 2016) Siddiqui, Sohrab; Chairperson, Graduate Committee: Ahmed Al-KaisyTraffic congestion and safety along urban corridors have become major challenges for most highway agencies in the United States. Adverse weather conditions also present a considerable challenge, both in terms of safety and operations. All these problems along with the increasingly limited resources for infrastructure expansion have urged transportation agencies to investigate innovative traffic management approaches. One of these approaches is the use of Active Traffic Management (ATM) strategies. Within ATM, the practice of Variable Speed Limit (VSL) systems is well suited to improving safety and operations. These systems dynamically utilize real-time traffic and/or weather data to post appropriate speeds that are thought to improve safety and operations along a corridor. The overall aim of this thesis is to investigate the benefits of a recently installed advisory VSL system along OR-217 freeway in Portland, Oregon. This corridor is characterized by high traffic levels, severe congestion and unreliable travel times. The congestion of the freeway contribute to crash rates exceeding the statewide averages for this type of facility. Pacific Northwest's unpredictable climate presents another challenge that doubles the congestion and safety problems along the corridor. The effectiveness of this system was explored through an in-depth 'before and after' and 'on-and-off' analyses. The study was designed in a way that it encompasses both the safety and mobility benefits of the system. Besides, driver compliance with the system was also measured under different scenarios. The results indicated that the system had significant impacts on both mobility and safety. In terms of mobility it was found that system had lowered the average speeds along the corridor. The advisory VSL activation also resulted in reduced capacities. Safety assessment of the system suggested that, VSL has decreased crash rates and temporal and lateral variations of speed. Under certain scenarios, the system also decreased the longitudinal variations of speed. Further, it was also found that due to the advisory nature of the system, the majority of drivers do not comply with the system. However, VSL has resulted in reducing the percentage of aggressive drivers and have increased the number of drivers complying the static speed limit.Item An analysis of road traffic factors and road safety strategies that predict road fatalities over time across fifty states in USA(Montana State University - Bozeman, College of Engineering, 2017) Benzaman; Chairperson, Graduate Committee: Nicholas WardStrategizing to decrease statewide road fatalities is an important aspect in road safety research in the United States. But obtaining information on a variety of variables, such as economic, socio-cultural, demographic and political factors, at the state level can be a difficult task. The public databases sometimes do not provide full information on these variables due to missing data. If these variables are neglected from the analysis because of missing data points. valuable information is lost in the process. Therefore, analyzing missing data has been considered as an additional step towards variable selection process in this thesis study. In order to impute the missing data, multiple imputation method was chosen. After the data imputation, the significant variables associated with road fatalities in 50 states were identified. This was done using a linear regression model which revealed that the top reasons for road fatalities are drunk driving, distracted driving and unemployment. In the process of linear regression modelling 48 predictive models were obtained. During the process of data collection, it was observed that data sources did not offer necessary information on road safety culture, behaviors, norms, attitudes and beliefs related to road fatality. This study offers two solutions for inferring a road safety culture and understanding its effects. The first solution was to analyze residuals from random effects two-way panel regression model and to generate performance indicator of inferred road safety culture. From the value of the indicators it was clear which state was the safest twenty years ago and which state is the safest now. Through the change in the value of the indicator, a state's progress in terms of safety culture was also measured. The second solution was to use people's political views on the democratic party and the republican party as a proxy for the road safety culture. This resulted in a significant increase in the goodness of fit for the linear regression model. This thesis provides prediction models, significant factors, and performance indicators of a road safety culture which can be used in state level road safety strategy development and policy making.Item Characterizing commercial vehicle safety in rural Montana(Montana State University - Bozeman, College of Engineering, 2001) Burke, Patricia WalshItem A feasibility case study of Automated Highway Systems in the Greater Yellowstone priority corridor(Montana State University - Bozeman, College of Engineering, 1998) Gomke, Russell ScottItem Where does a deer cross a road? : road and landcover characteristics affecting deer crossing and mortality across the U.S. 93 corridor on the Flathead Indian Reservation, Montana(Montana State University - Bozeman, College of Letters & Science, 2007) Camel, Whisper; Chairperson, Graduate Committee: Sharon Eversman; Jody Hilty (co-chair)Reducing deer vehicle collisions (DVCs) on highways is an issue facing highway planners and wildlife managers. In western Montana, federal, state and tribal governments intend to reduce DVCs along a 51-mile stretch of US Highway 93 (US 93) on the Flathead Indian Reservation using on site reconstruction and highway engineering. This project was part of pre-construction wildlife monitoring that forms the baseline for evaluating effectiveness of mitigation measures associated with the US 93 reconstruction project. Road and landcover variables were recorded at randomly sampled locations along US 93. DVC site selections were made based on Montana Department of Transportation maintenance and Montana Highway Patrol accident reports from 1998- 2003. Observed crossing areas were based on 32 sand tracking beds (each 100 m long) placed randomly in three key areas along the route. Variables collected included habitats types, topography, and rural residential developments and anthropogenic effects. A geographic information system was used to determine proportion of landcover variables at three spatial scales centered on the highway, encompassing 0.16 km (0.5 mi), 0.32 km (1 mi), 0.64 km (2 mi).