A project report submitted to the Faculty of Engineering. University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 1997. / The previously disadvantaged communities of Greater Johannesburg generally rely on publlc transport to get from place to place. Disabled people, who can be considered to be part of the previously disadvantaged community, often do not have any form of transport available to them at all. People from these communities wishing to attend an event at the Ellis Park Precinct would either have to use the existing public transport or make their own transport arrangements. Traffic and transportation management plans have been implemented at the Ellis Park Precinct with the intention of ensuring the Precinct's transportation accessibility for all the people of Greater Johannesburg, but the needs of the previously disadvantaged communities, who are captive to public transport, were not formally provided for. This project report provides details of the truffle and transportation management plans that have been implemented and then recummends/suggests various transportation options that could improve the transportation accessibility of the Precinct for these previously disadvantaged communities.

Most U.S. urban traffic signal systems deploy multiple signal timing plans to account for daily variability of traffic demand (i.e. morning peak, midday, afternoon peak, off peak and night). Groups of signals (belonging to the one zone or section) along an urban arterial, usually operate in a coordinated manner. This essentially means that timing plans change at the same time for all the signals in the group, so as to facilitate vehicle progression of through a series of signals. Good traffic signal timing practices assume a certain level of monitoring and maintenance in order to guarantee that they are efficient in servicing current traffic conditions. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015 / FAU Electronic Theses and Dissertations Collection

The objective of this research is to evaluate and introduce a new methodology regarding rural highway safety. Current practices rely on crash prediction models that utilize specific explanatory variables, whereas the depository of knowledge for past research is the Highway Safety Manual (HSM). Most of the prediction models in the HSM identify the effect of individual geometric elements on crash occurrence and consider their combination in a multiplicative manner, where each effect is multiplied with others to determine their combined influence. The concepts of 3-dimesnional (3-D) representation of the roadway surface have also been explored in the past aiming to model the highway structure and optimize the roadway alignment. The use of differential geometry on utilizing the 3-D roadway surface in order to understand how new metrics can be used to identify and express roadway geometric elements has been recently utilized and indicated that this may be a new approach in representing the combined effects of all geometry features into single variables. This research will further explore this potential and examine the possibility to utilize 3-D differential geometry in representing the roadway surface and utilize its associated metrics to consider the combined effect of roadway features on crashes. It is anticipated that a series of single metrics could be used that would combine horizontal and vertical alignment features and eventually predict roadway crashes in a more robust manner. It should be also noted that that the main purpose of this research is not to simply suggest predictive crash models, but to prove in a statistically concrete manner that 3-D metrics of differential geometry, e.g. Gaussian Curvature and Mean Curvature can assist in analyzing highway design and safety. Therefore, the value of this research is oriented towards the proof of concept of the link between 3-D geometry in highway design and safety. This thesis presents the steps and rationale of the procedure that is followed in order to complete the proposed research. Finally, the results of the suggested methodology are compared with the ones that would be derived from the, state-of-the-art, Interactive Highway Safety Design Model (IHSDM), which is essentially the software that is currently used and based on the findings of the HSM.

The major transit systems operating in San Francisco are San Francisco Municipal (MUNI), Bay Area Rapid Transit (BART), and Caltrain. The system of interest for this paper is MUNI, in particular the bus and light rail systems. During the past decade transit ridership in the area has experienced diverging growth, with bus ridership declining while rail ridership is growing significantly (Erhardt et al. 2017). Our data show that between 2009 and 2016, MUNI rail ridership increases from 146,000 to 171,400, while MUNI bus ridership decreases from 520,000 to 450,000. Direct ridership models (DRMs) are used to determine what factors are influencing MUNI light rail and bus ridership. The DRMs predict ridership fairly well, within 10% of the observed change. However, the assumption of no multi-collinearity is voided. Variables, such as employment and housing density, are found to be collinear. Fixed-effects panel models are used to combat the multi-collinearity issue. Fixed-effects panel models assign an intercept to every stop, so that any spatial correlation is removed. A transportation network company, Uber and Lyft, variable is introduced (TNC) to the panel models, to quantify the effect they have on MUNI bus and light rail ridership. The addition of a TNC variable and elimination of multi-collinearity helps the panel models predict ridership better than the daily and time-of-day DRMs, both within 5% of the observed change. TNCs are found to complement MUNI light rail and compete with MUNI buses. TNCs contributed to a 7% growth in light rail ridership and a 10% decline in bus ridership. These findings suggest that the relationship TNCs have with transit is complex and that the modes cannot be lumped together.

Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations.

The magnitudes and relative pressure distributions transmitted to the crosstie-ballast interface of railroad track significantly influences the subsequent behavior and performance of the overall track structure. If the track structure is not properly designed to distribute the heavy-axle loads of freight cars and locomotives, deficiencies and inherent failures of the crossties, ballast, or underlying support layers can occur, requiring substantial and frequent maintenance activities to achieve requisite track geometrical standards. Incorporating an understanding of the pressure distribution at the crosstie-ballast interface, appropriate designs can be applied to adequately provide a high performing and long-lasting railroad track. Although this can be considered a simple concept, the magnitudes and distributions of pressures at the crosstie-ballast interface have historically proven to be difficult to quantifiably measure and assess over the years. This document describes the development and application of a method to measure average railroad track crosstie-ballast interfacial pressures using timber crossties and pressure cells specifically designed for granular materials. A procedure was specifically developed for recessing the cells in the bottoms of timber crossties. The validity of the test method was initially verified with a series of laboratory tests. These tests used controlled loads applied to sections of trackbed constructed in specifically designed resilient frames. The prototype trackbed section was intended to simulate typical in-track loading conditions and ballast response. Cells were subsequently installed at a test site on an NS Railway well-maintained mainline just east of Knoxville, TN. Six successive crossties were fitted with pressure cells at the ballast interface below the rail seat. Pressure cells were also installed at the center of two crossties where the ballast is typically not tamped or consolidated. Trackbed pressures at the crosstie-ballast interface were periodically measured for numerous revenue freight trains during a period of twenty-one months. After raising and surfacing the track, the ballast was permitted to further consolidate under normal train traffic before again measuring pressures. Having the ballast tightly and uniformly compacted under crossties is important to ensuring representative and reproducible pressure measurements. Measured maximum pressures under the rail at the crosstie-ballast interface ranged from 20 to 30 psi (140 to 210 kPa) for locomotives and loaded freight cars with smooth wheels producing negligible wheel/rail impacts. Crosstie-ballast interface pressures were typically 3 psi (20 kPa) maximum for empty freight cars with smooth wheels. Heavily loaded articulated intermodal car pressures for shared trucks tended to reach nearly 40 psi (280 kPa), actually higher than locomotive-produced pressures. The recorded pressures under the center of the ties were normally negligible, less than 1 psi (7 kPa) for locomotives and loaded freight cars. Wheel-Rail force parameters measured by nearby wheel-impact load detectors (WILD) were compared to crosstie-ballast pressure data for the same trains traversing the test site. Increases in peak WILD forces, either due to heavier wheel loads or increased impacts, were determined to relate favorably to increases in recorded trackbed pressures with a power relationship. The ratios between the peak and nominal wheel forces and trackbed pressures also have strong relationships.

Rainfall affects the performance of traffic operations and endangers safety. A common and conventional method (rain gauges) for rainfall measurements mostly provide precipitation records in hourly and 15-minute intervals. However, reliability, continuity, and wide area coverage pose challenges with this data collection method. There is also a greater likelihood for data misrepresentation in areas where short duration rainfall is predominant, i.e., reported values may not reflect the actual equivalent rainfall intensity during subintervals over the entire reporting period. With recent weather and climate patterns increasing in severity, there is a need for a more effective and reliable way of measuring rainfall data used for traffic analyses. This study deployed the use of precipitation radar data to investigate the spatiotemporal effect of rainfall on freeways in Jacksonville, Florida. The linear regression analysis suggests a speed reduction of 0.75%, 1.54%, and 2.25% for light, moderate, and heavy rainfall, respectively. Additionally, headways were observed to increase by 0.26%, 0.54%, and 0.79% for light, moderate, and heavy rainfall, respectively. Measuring precipitation from radar data in lieu of using rain gauges has potential for improving the quality of weather data used for transportation engineering purposes. This approach addresses limitations experienced with conventional rain data, especially since conventional collection methods generally do not reflect the spatiotemporal distribution of rainfall.

This thesis presents the results of a mathematical analysis of various live load combinations on highway bridge spans up to 304.8 meters (1,000 feet) total lengths. The analysis included continuous beams, but only the results for simple beams is presented. The analysis was performed using an independently developed Microsoft EXCEL spreadsheet computation, based on superposition and classical mechanics. In this thesis, several actual bridge live loadings and several hypothetical live loadings were analyzed and compared to the American Association of State Highway and Transportation Officials Load and Resistance Factor Design method. Also considered was the new bridge design method adopted by the Louisiana Department of Transportation in March 2015. The evolution of bridge design loads is discussed, and the concept of the Military Load Classification is introduced and adapted to the bridge design analysis. The results of the analysis are presented, compared and interpreted for use in future bridge design.

Bicycle transportation has become a central priority of urban areas invested in improving sustainability, livability, and public health outcomes. Transportation agencies are striving to increase the comfort of their bicycle networks to improve the experience of existing cyclists and to attract new cyclists. The Oregon Department of Transportation sponsored the development of ORcycle, a smartphone application designed to collect cyclist travel, comfort, and safety information throughout Oregon. The sample resulting from the initial deployment of the application between November 2014 and March 2015 is described and analyzed within this thesis. 616 bicycle trips from 148 unique users were geo-matched to the Portland metropolitan area bicycle and street network, and the self-reported comfort level of these trips was modeled as a function of user supplied survey responses, temporal characteristics, bicycle facility/street typology, traffic volume, traffic speed, topography, and weather. Cumulative logistic regression models were utilized to quantify how these variables were related to route comfort level within separate variable groups, and then the variables were used in a pooled regression model specified by backwards stepwise selection. The results of these analyses indicated that many of the supplied predictors had significant relationships with route comfort. In particular, bicycle miles traveled on facilities with higher traffic volumes, higher posted speeds, steep grades, and less separation between bicycles and motor vehicles coincided with lower cyclist comfort ratings. User supplied survey responses were also significant, and had a greater overall model variance contribution than objectively measured facility variables. These results align with literature that indicates that built environment variables are important in predicting bicyclist comfort, but user variables may be more important in terms of the variance accounted for. This research outlines unique analysis methods by which future researchers and transportation planners may explore crowdsourced data, and presents the first exploration of bicyclist comfort perception data crowdsourced using a smartphone application.

Ramp metering is an effective management strategy, which helps to keep traffic density below the critical value, preventing breakdowns and thus maintaining the full capacity of the freeway. Warrants for ramp metering installation have been developed by a number of states around the nation. These warrants are generally simple and are based on the traffic, geometry, and safety conditions in the immediate vicinity of each ramp (local conditions). However, advanced applications of ramp metering utilize system-based metering algorithms that involve metering a number of on-ramps to address system bottleneck locations. These algorithms have been proven to perform better compared to local ramp metering algorithms. This has created a disconnection between existing agency metering warrants to install the meters and the subsequent management and operations of the ramp metering. Moreover, the existing local warrants only consider recurrent conditions to justify ramp metering installation with no consideration of the benefits of metering during non-recurrent events such as incidents and adverse weather. This dissertation proposed a methodology to identify the ramps to meter based on system-wide recurrent and non-recurrent traffic conditions. The methodology incorporates the stochastic nature of the demand and capacity and the impacts of incidents and weather using Monte Carlo simulation and a ramp selection procedure based on a linear programming formulation. The results of the Monte Carlo simulation are demand and capacity values that are used as inputs to the linear programming formulation to identify the ramps to be metered for each of the Monte Carlo experiments. This method allows the identification of the minimum number of ramps that need to be metered to keep the flows below capacities on the freeway mainline segment, while keeping the on-ramp queues from spilling back to the upstream arterial street segments. The methodology can be used in conjunction with the existing local warrants to identify the ramps that need to be metered. In addition, it can be used in benefit-cost analyses of ramp metering deployments and associated decisions, such as which ramps to meter and when to activate in real-time. The methodology is extended to address incidents and rainfall events, which result in non-recurrent congestion. For this purpose, the impacts of non-recurrent events on capacity and demand distributions are incorporated in the methodology.