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Entry-lane capacity analysis of roundabouts in Texas using VISSIM, SIDRA, and the highway capacity manualMills, Alison Fayre 29 September 2011 (has links)
Road safety and traffic congestion are two of the critical issues facing the transportation profession today. As a means to promote safety and efficiency at United States intersections modern roundabouts are becoming more and more common. Over the last ten years, roundabouts implementation methodologies have been developed using data collected at U.S. roundabouts. These methodologies were first published in National Cooperative Highway Report 572: Roundabouts in the United States and more recently in the second edition of the national roundabout guidelines. This work attempts to validate the use of these methodologies for roundabouts in the state of Texas and also enhance guidelines for evaluating roundabout operations by exploring the effects of exiting flow, origin-destination patterns, and mean speed on roundabout entry-lane capacity. Capacity results from VISSIM are compared to the Highway Capacity Manual entry-lane capacity curve and results from SIDRA. / text
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Modeling Truck Motion along Grade SectionsYu, Bin 22 March 2005 (has links)
Roadway grades have a diverse effect on vehicle speeds, depending on vehicle and roadway characteristics. For example, passenger cars can generally negotiate grades of 5 percent or less without considerable reductions in vehicle speeds, while heavy-duty trucks are affected significantly by grades because of their inferior operating capability. Consequently, due to the potential significant speed differential between automobiles and heavy-duty trucks, these trucks can have a significant impact on the quality of flow, throughput, and safety of a traffic stream. Truck climbing lanes are typically constructed in an attempt to lessen this negative impact. Currently, the American Association of State Highway and Transportation Officials (AASHTO) and Highway Capacity Manual (HCM) represent the state-of-art and state-of-practice procedures for the design of truck climbing lanes. These procedures only consider the tangent vertical profile grades in the design of climbing lanes and do not capture the impact of vertical curvature on truck performance.
The dissertation describes the TruckSIM framework for modeling vehicle motion along roadway sections by considering both the longitudinal and lateral forces acting on a vehicle. In doing so, the tool reflects the impact of horizontal and vertical alignment on a vehicle's longitudinal motion. The model is capable of reading Global Positioning System (GPS) (longitude, latitude, and altitude), roadway, and vehicle data. The dissertation demonstrates the validity of the software modeling procedures against field data and the HCM procedures. It is anticipated that by automating the design procedures and considering different vehicle and roadway characteristics on truck motion, the TruckSIM software will be of considerable assistance to traffic engineers in the design of roadways.
The Global Positioning System (GPS) was originally built by the U.S. Department of Defense to provide the military with a super-precise form of worldwide positioning. With time, GPS units were introduced into the civilian domain and provided transportation professionals with an opportunity to capitalize on this unique instrumentation. With this GPS capability, this research investigates the feasibility of using inexpensive WAAS-capable units to estimate roadway vertical and horizontal profiles. The profiles that are generated by these inexpensive units (less than $500) are compared to the profiles generated by expensive carrier-phase DGPS units ($30,000 per unit including the base station). The results of this study demonstrate that the use of data smoothing and stacking techniques with the WAAS data provides grade estimates that are accurate within 10% of those generated by the carrier-phase DGPS units and thus offer a cost effective tool for providing input data to the TruckSIM software.
Using the TruckSIM software, this research effort investigates truck performance reflective of various truck and road characteristics. These characteristics include vehicle engine power, weight-to-power ratio, pavement type, pavement condition, aerodynamic aid features, engine efficiency, tire type, and percentage mass on tractive axle. The study demonstrates that the vehicle weight-to-power ratio, vehicle engine power, pavement surface condition, tire type, aerodynamic aids, and engine efficiency are critical factors in the design of truck climbing lanes. / Ph. D.
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Development of Passenger Car Equivalents for Basic Freeway SegmentsIngle, Anthony 21 July 2004 (has links)
Passenger car equivalents (PCEs) are used in highway capacity analysis to convert a mixed vehicle flow into an equivalent passenger car flow. This calculation is relevant to capacity and level of service determination, lane requirements, and determining the effect of traffic on highway operations. The most recent Highway Capacity Manual 2000 reports PCEs for basic freeway segments according to percent and length of grade and proportion of heavy vehicles. Heavy vehicles are considered to be either of two categories: trucks and buses or RVs. For trucks and buses, PCEs are reported for a typical truck with a weight to power ratio between 76.1 and 90.4 kg/kW (125 and 150 lb/hp). The weight to power ratio is an indicator of vehicle performance. Recent development of vehicle dynamics models make it possible to define PCEs for trucks with a wider variety of weight to power ratios. PCEs were calculated from the relative impact of trucks on traffic density using the simulation model INTEGRATION. The scope of this research was to evaluate PCEs for basic freeway segments for trucks with a broader range of weight to power ratios. Such results should make freeway capacity analysis more accurate for mixed vehicle flow with a non-typical truck population. In addition, the effect of high proportion of trucks, pavement type and condition, truck aerodynamic treatment, number of freeway lanes, truck speed limit, and level of congestion was considered. The calculation of PCEs for multiple truck weight to power ratio populations was not found to be different from single truck weight to power ratio populations. The PCE values were tabulated in a compatible format to that used in the Highway Capacity Manual 2000. / Master of Science
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Avaliação do nível de serviço em estradas de faixa de rodagem única segundo o HCM 2010Azeredo, Válter Iúri Valente de January 2012 (has links)
Tese de mestrado integrado. Engenharia Civil. Área de Especialização de Vias de Comunicação. Faculdade de Engenharia. Universidade do Porto. 2012
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Development of a Bicycle Level of Service Methodology for Two-Way Stop-Controlled (TWSC) IntersectionsJohnston, Nathan R 01 March 2014 (has links)
This thesis fills a missing piece in research on multimodal performance measures for traffic on streets and highways. The Highway Capacity Manual (HCM) published by the Transportation Research Board (TRB) provides Level of Service (LOS) methodologies which enable engineers and planners to evaluate the overall performance of roadways and highways based on the physical characteristics of facilities. This allows for the evaluation of those facilities and offers a means for recognizing issues and planning, designing, implementing, and ultimately assessing improvements. Originally, level of service was developed for automotive traffic only, but with recent developments as part of the complete streets movement, the performance of infrastructure for alternative transportation modes have also started being assessed in this fashion. There are methodologies in HCM 2010 for bicycle traffic at signalized intersections, all-way stop-controlled intersections, roadway and highway segments, but as of yet, no bicycle level of service methodology exists for two-way stop-controlled intersections. This work attempts to fill this gap. The methodology utilized for this report includes video collection of sample two-way stop-controlled intersections throughout California, collection of survey responses from viewers of video, and linear regression of collected survey responses with physical attributes of each sample intersection as the explanatory variables. Data was analyzed from both combined and individual street movements to determine the final equation set. The final methodology involves two separate procedures for major and minor streets at TWSC intersections. Final factors deemed significant in bicycle level of service analysis include sight distances, speed limits, presence of bus stops, presence and type of bicycle infrastructure, street widths and types of lanes present, pavement quality, and traffic flows.
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Capacity Modeling of Freeway Weaving SectionsZhang, Yihua 27 June 2005 (has links)
The dissertation develops analytical models that estimate the capacity of freeway weaving sections. The analytical models are developed using simulated data that were compiled using the INTEGRATION software. Consequently, the first step of the research effort is to validate the INTEGRATION lane-changing modeling procedures and the capacity estimates that are derived from the model against field observations. The INTEGRATION software is validated against field data gathered by the University of California at Berkeley by comparing the lateral and longitudinal distribution of simulated and field observed traffic volumes categorized by O-D pair on nine weaving sections in the Los Angeles area. The results demonstrate a high degree of consistency between simulated and field observed traffic volumes within the various weaving sections. Subsequently, the second validation effort compares the capacity estimates of the INTEGRATION software to field observations from four weaving sections operating at capacity on the Queen Elizabeth Way (QEW) in Toronto, Canada. Again, the results demonstrate that the capacity estimates of the INTEGRATION software are consistent with the field observations both in terms of absolute values and temporal variability across different days. The error was found to be in the range of 10% between simulated and field observed capacities.
Prior to developing the analytical models, the dissertation presents a systematic analysis of the factors that impact the capacity of freeway weaving sections, which were found to include the length of the weaving section, the weaving ratio (a new parameter that is developed as part of this research effort), the percentage of heavy vehicles, and the speed limit differential between freeway and on- and off-ramps. The study demonstrates that the weaving ratio, which is currently defined as the ratio of the lowest weaving volume to the total weaving volume in the 2000 Highway Capacity Manual, has a significant impact on the capacity of weaving sections. The study also demonstrates that the weaving ratio is an asymmetric function and thus should reflect the source of the weaving volume. Consequently, a new definition for the weaving ratio is introduced that explicitly identifies the source of the weaving volume. In addition, the study demonstrates that the length of the weaving section has a larger impact on the capacity of weaving sections for short lengths and high traffic demands. Furthermore, the study demonstrates that there does not exist enough evidence to conclude that the speed limit differential between mainline freeway and on- and off-ramps has a significant impact on weaving section capacities. Finally, the study demonstrates that the HCM procedures model the heavy duty vehicle impacts reasonably well.
This dissertation presents the development of new capacity models for freeway weaving sections. In these models, a new definition of the weaving ratio that explicitly accounts for the source of weaving volume is introduced. The proposed analytical models estimate the capacity of weaving sections to within 12% of the simulated data, while the HCM procedures exhibit errors in the range of 114%. Among the newly developed models, the Artificial Neural Network (ANN) models performs slightly better that the statistical models in terms of model prediction errors. However, the sensitivity analysis results demonstrate unrealistic behavior of the ANN models under certain conditions. Consequently, the use of a statistical model is recommended because it provides a high level of accuracy while providing accurate model responses to changes in model input parameters (good response to the gradient of the input parameters). / Ph. D.
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