The goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large vehicle crashes. Using the crashes involving large vehicles, a model comparison between binary logit model and a Chi-squared Automatic Interaction Detection (CHAID) decision tree model is provided. There were 13 significant factors (i.e. crash type with respect to vehicle types, residency of driver, DUI, rural-urban, etc.) found significant in the logistic procedure while 7 factors found (i.e. posted speed limit, intersection, etc.) in the CHAID model. The model comparison results indicate that the logit analysis procedure is better in terms of prediction power. The following analysis is a modeling structure involving three binary logit models. The first model was conducted to estimate the crash severity of crashes that involved only personal vehicles (PV). Second model uses the crashes that involved large vehicles (LV) and passenger vehicles (PV). The final model estimated the severity level of crashes involving only large vehicles (LV). Significant differences with respect to various risk factors including driver, iii vehicle, environmental, road geometry and traffic characteristics were found to exist between those crash types and models. For example, driving under the influence of Alcohol (DUI) has positive effect on the severity of PV vs. PV and LV vs. PV while it has no effect on LV vs. LV. As a result, 4 of the variables found to be significant were similar in all three models (although often with quite different impact) and there were 11 variables that significantly influenced crash injury severity in PV vs. PV crashes, and 9 variables that significantly influenced crash injury severity in LV vs. PV crashes. Based on the significant variables, maximum posted speed, number of vehicles involved, and intersections are among the factors that have major impact on injury severity. These results could be used to identify potential countermeasures to reduce crash severity in general, and for LVs in particular. For example, restricting the speed limits and enforcing it for large vehicles could be a suggested countermeasure based on this study.

Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Turn (RCUT) intersection design, its implementation remains uneven and close to zero in some large states such as California. This research provides a comprehensive framework to estimate the operational and safety performance of future RCUT designs in California. The framework is demonstrated for five intersections located on high-speed rural expressways in California using VISSIM microsimulation models to measure operational performance for each intersection including the base condition with the existing Two-Way Stop-Controlled (TWSC) intersection and two RCUT designs. To evaluate future safety performance, the microsimulation models were further utilized to compile vehicle trajectory data to use with the Surrogate Safety Assessment Model (SSAM) to develop a surrogate measure-based approach to estimating future safety performance. Detailed Intersection Control Evaluation (ICE) studies found that the RCUT was cost-effective and the preferred alternative. This framework may be applied to the analysis of locations where a RCUT intersection may be appropriate. The framework demonstrated here may be used by agencies to estimate the future benefits of the first-time application of treatments that have been successful elsewhere. Based on simulation results, the proposed RCUT designs reduced or eliminated the more severe crossing conflicts.

Public transportation offers a crucial solution to the travel demand in light of national and global economic, energy, and environmental challenges. If implemented effectively, public transit offers an affordable, convenient, and sustainable transportation mode. Implementation of new technologies for information-harvesting may lead to more effective transit operations. This study examines the potential of automated data collection technologies to analyzing and understand the origin-destination flow patterns, which is essential for transit route planning and stop location placement. This thesis investigates the collection and analysis of data of passengers onboard San Luis Obispo Transit buses in February and March 2017 using Bluetooth (BT) and automatic passenger counter (APC) data. Five BlueMAC detectors were placed on SLO Transit buses to collect Bluetooth data. APC data was obtained from San Luis Obispo Transit. The datasets were used to establish a data processing method to exclude invalid detections, to identify and process origin and destination trips of passengers, and to make conclusions regarding passenger behavior. The filtering methods were applied to the Bluetooth data to extract counts of unique passenger information and to compare the filtered data to the ground-truth APC data. The datasets were also used to study the San Luis Obispo Downtown Farmer’s Market and its impact on transit ridership demand. The investigation revealed that after carefully employing the filters on BT data there were no consistent patterns in differences between unique passenger counts obtained from APC data and the BT data. As a result, one should be careful in employing BT data for transit OD estimation. Not every passenger enables Bluetooth or owns a Bluetooth device, so relying on the possession of Bluetooth-enabled devices may not lead to a random sample, resulting in misleading travel patterns. Based on the APC data, it was revealed that transit ridership is 40% higher during the days during which Higuera Street in Downtown San Luis Obispo is used for Farmer’s Market – a classic example of tactical urbanism. Increase in transit ridership is one of the aspects of tactical urbanism that may be further emphasized. With rapidly-evolving data collection technologies, transit data collection methods could expand beyond the traditional onboard survey. The lessons learned from this study could be expanded to provide a robust and detailed data source for transit operations and planning.

Food accessibility has lately been of primary interest given its impact on public health outcomes. This thesis illustrates the gaps in food access by applying spatial analysis in Massachusetts accounting for a variety of demographic and socioeconomic factors. The number of grocery stores, farmers markets, and convenience stores within 1/4 and 1 mile of the Census tracts’ centroids are the two accessibility metrics used in the spatial analysis. In addition, a regression model is developed using the Gradient Boosting machine learning method to show the relationship between the socioeconomic factors and the number of grocery stores within 1 mile of the Census tracts’ centroids. Percent of minority population, population in poverty, vehicle ownership, and population density are the factors used as explanatory variables. The results include histograms and maps for the spatial analysis, which show that access to food services is higher in urban high-density areas regardless of high poverty and minority percent values. The regression model results include partial dependence plots, variable importance plot as well as a map that illustrates the standard deviation of the residual values. This research can inform that when the vehicle ownership, the minority and poverty percent increase, the number of grocery stores increases, as these values are high in big cities where there is high availability of food retailers.

Due to comfort, convenience, and flexibility, taxis become more and more prevalent in China, especially in large cities. According to a survey reported by Beijing Traffic Development Research Center, there were 696 million taxi person-rides in Beijing in 2011. However, many violations and road crashes that were related to taxi drivers occurred more frequently. The survey showed that there were a total of 17,242 taxi violations happened in Beijing in only one month in 2003, which accounted for 56% of all drivers' violations. Besides, taxi drivers also had a larger accident rate than other drivers, which showed that nearly 20% of taxi drivers had accidents each year. This study mainly focuses on investigating differences in driving behavior between taxi drivers and non-professional drivers. To examine the overall characteristics of taxi drivers and non-professional drivers, this study applied a hierarchical driving behavior assessment method to evaluate driving behaviors. This method is divided into three levels, including low-risk level, medium-risk level, and high-risk level. Low-risk level means the basic vehicle control. Medium-risk level refers to the vehicle dynamic decision. High-risk level represents the driver avoidance behavior when facing a potential crash. The Beijing Jiatong University (BJTU) driving simulator was applied to test different risk level scenarios which purpose is to find out the differences between taxi drivers and non-professional drivers on driving behaviors. Nearly 60 subjects, which include taxi drivers and non-professional drivers, were recruited in this experiment. Some statistical methods were applied to analyze the data and a logistic regression model was used to perform the high-risk level. The results showed that taxi drivers have more driving experience and their driving style is more conservative in the basic vehicle control level. For the car following behavior, taxi drivers have smaller following speed and larger gap compared to other drivers. For the yellow indication judgment behavior, although taxi drivers are slower than non-professional drivers when getting into the intersection, taxi drivers are more likely to run red light. For the lane changing behavior, taxi drivers' lane changing time is longer than others and lane changing average speed of taxi drivers is lower than other drivers. Another different behavior in high-risk level is that taxi drivers are more inclined to turn the steering wheel when facing a potential crash compared to non-professional drivers. However, non-professional drivers have more abrupt deceleration behaviors if they have the same situation. According to the experiment results, taxi drivers have a smaller crash rate compared to non-professional drivers. Taxi drivers spend a large amount of time on the road so that their driving experience must exceed that of non-professional drivers, which may bring them more skills. It is also speculated that because taxi drivers spend long hours on the job they probably have developed a more relaxed attitude about congestion and they are less likely to be candidates for road rage and over aggressive driving habits.

In 1975, C.S. Bauer completed a doctoral dissertation at the University of Florida which treated the Green Band Merging Control System on I-75 in Tampa, Florida. In this work, Bauer suggested the possibility for the use of computer graphics as a toll for analysis of the bands generated by the Green Band Control System Simulation developed in his dissertation. The use of computer generated movies of the bands displayed to ramp drivers by the system allows the comparison of various band control strategies without the need for field implementation and testing. With the goal of producing such films in mind, the research topic discussed in this paper was undertaken. The report introduces the reader to some of the basic aspects of computer graphics and presents specialized computer software and interface hardware for producing automated computer graphics movies from a Tektronix 4010 storage display. A brief discussion of the Tampa System and its associated simulation program is presented, and representative frames from the moves of the Tampa System produced in the research are discussed. Suggestions for additional work that could be undertaken in the research area conclude the report.

Although vehicle miles traveled (VMT) has become the standard for assessing transportation related impacts in California, some have concerns that many VMT estimates are not properly grounded or informed by real world data, potentially resulting in flawed estimates and impact assessments. This is especially true of special generators, like college and university campuses, which have complex travel patterns distinct from that of the general public. This thesis attempts to resolve a significant disparity observed between two credible VMT estimates for Cal Poly’s campus wide VMT. As part of a campus master planning effort, a VMT estimate was produced in 2019 for an environmental impact report (EIR), using a travel demand model (TDM) based approach. This result was quite divergent from a prior 2018 estimate which used contemporaneous survey data (a data source often used to ground and calibrate/validate TDM results), leaving an approximate difference of 200 million VMT to be accounted for. In an attempt to address this disparity, this investigation considered three distinct analyses, including a quantitative assessment of variability of the 2018 travel survey estimate (via a bootstrap), an accounting of missing VMT not captured by the 2018 estimate, and a final comparison of the reliability and credibility of the 2018 and 2019 estimates based on both qualitative (scope and methodological issue of the estimates) and quantitative (benchmarking reported metrics) factors. Based on this investigation’s findings, although the disparity can be partially explained, a significant deficit of over 100 million VMT remained, suggesting the 2019 estimate may have overstated campus VMT and its impacts. It also suggests that campuses have significant VMT generating functions beyond the frequently studied commuter and residential travel behaviors. The lessons learned from this thesis provide a roadmap to improving future VMT estimates for college and university campuses as well as how regulators may approach setting appropriate analysis requirements and impact thresholds for these unique land uses.

Due to the presence of deep deposits of organic soils at shallow depths, roadways in western Palm Beach County, FL show premature distress and failure requiring frequent rehabilitation. In an effort to develop effective mitigation strategies, 24 test sections, containing various types of pavement reinforcing materials, were constructed during Fall of 2008. This study presents a forensic investigation and dynamic characterization of reinforced asphalt cores obtained from SR15/US98 for evaluating the uniformity of test sections, qualitative comparisons, and developing empirical models for predicting permanent deformation and material damage with stress cycles simulating traffic loading. / by Rodrigo Ledezma-Campodonico. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

published_or_final_version / Architecture / Master / Master of Architecture

Thesis (MEng (Civil Engineering))--University of Stellenbosch, 2001. / This Traffic Impact Assessment (TIA) was commissioned in March 1998 as a supporting document to an application for the rezoning of an ert in Noordhoek from general housing to commercial use. The proposal at the time was to develop a medium·sized 15 000 m2 GLA shopping centre with supporting offices and a Health & Racquet Club. All the work (including managing the traffic counting team) was carried out by myself under the guidance of Dr Piet Jordaan at Gibb Africa Consulting Engineers. As financial backing and anchor tenants were secured for the development, the size of the proposed shopping centre was increased from a local facilily to a regional facilily of 31 000 m2 GFA to be developed in two phases. This necessitated a complete revision of the approach and content of the TIA. Owing to the regional nature of the new development, the TIA was expanded to include a wider geographical area of influence and a longer development period. This revised TIA was carried out by myself between September 1998 and March 1999 under the guidance of Dr Herman Joubert. Longbeach Mall opened for business in April 2001 complete with upgraded road network as recommended in the TIA The TIA is submitted as the final-year project for my Master's Degree in Traffic & Transportation Engineering. For the purposes of completion, an after·study of current traffic conditions on the local road infrastructure has also been included. The after·study was carried out in October 2001 (6 months after Longbeach Mall opened) and includes traffic counts at critical intersections during the Saturday morning peak period, observations of parking area utilisation, observations of shopping centre occupancy and discussions of the possible reasons for differences between predicted and actual traffic volumes. Confirmation that the study is original and was carried out by myself and permission from Arcus Gibb (Ply) Ltd to use the study as part of my final-year project, is provided in Appendix A.