摘要 :
This project entailed the development of the following four traffic volume adjustment factors from 1995 and 1996 permanent traffic recorder data: (1) A truck (axle) adjustment factor for single pneumatic tube counters (2) A factor...
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This project entailed the development of the following four traffic volume adjustment factors from 1995 and 1996 permanent traffic recorder data: (1) A truck (axle) adjustment factor for single pneumatic tube counters (2) A factor for estimating Design Hourly Volume (DHV) from Peak Hour Volume (PHV) (3) A factor for estimating the % trucks in the Average Daily Traffic (ADT) from the % trucks in the PHV (4) A factor for estimating the % trucks in the ADT from the % trucks in the typical hours in a manual classification study, which are 7am-10am, 11am -1pm, and 2pm-6pm.
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Three objectives were undertaken as part of this research. First, a literature review and national survey of growth factor estimation procedures was conducted. Of particular interest were the frequency, duration, and spatial densi...
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Three objectives were undertaken as part of this research. First, a literature review and national survey of growth factor estimation procedures was conducted. Of particular interest were the frequency, duration, and spatial density of counts collected to support the estimation of growth factors. It was determined that PENNDOT might improve their growth factor estimation program through the collection of traffic data at more locations for a shorter (than three weeks) duration. Second, historical PENNDOT traffic data were used to test the impact of reducing the duration of control counts from three weeks and to determine the benefits of including more locations. It was found that the three-week duration provided little if any benefit over 48-hour counts. In contrast, the additional locations improved the growth factor estimates. Finally, historical PENNDOT traffic data were used to cluster the existing permanent continuously operating automated traffic recorded (ATRs) according to monthly factors and other criteria. It was determined that the existing Traffic Pattern Groups developed by PENNDOT should be retained.
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As traffic congestion increases, the K-factor, defined as the proportion of the 24-hour traffic volume that occurs during the peak hour, may decrease. This behavioral response is known as peak spreading: as congestion grows during...
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As traffic congestion increases, the K-factor, defined as the proportion of the 24-hour traffic volume that occurs during the peak hour, may decrease. This behavioral response is known as peak spreading: as congestion grows during the peak travel times, motorists may shift their departure time to a non-peak hour. Knowing whether K-factors will remain constant or will change will affect the estimation of travel demand, and the resultant transportation performance, since the traffic volume during a given hour may affect travel speed and vehicle emissions. The purpose of this study was to develop a model for forecasting peak spreading whereby peak spreading is measured as change in the K-factor. Data were collected from 32 continuous count stations in the six Northern Virginia counties of Arlington, Fairfax, Fauquier, Loudoun, Prince William, and Stafford for the period 1997-2010. Because some stations gave twodirectional counts and some gave only one-directional counts, there were 52 station-direction combinations, or sites, for analysis purposes. The data collected showed that the average annual K-factor adjusted for months for which data were not available decreased by an average of 0.006 (p < 0.01), from 0.103 to 0.097, during the period. The 24-hour volume-to-capacity ratio, which is a surrogate for travel congestion, increased by an average of 0.7 (p < 0.01), from 7.3 to 8.0. Both changes were statistically significant.
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The project sought to establish if there is a relationship between accident rates and volume to capacity ratios on rural highways. The data base for the study consisted of traffic volume data from 44 permanent count stations and t...
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The project sought to establish if there is a relationship between accident rates and volume to capacity ratios on rural highways. The data base for the study consisted of traffic volume data from 44 permanent count stations and traffic accident data in the vicinity of these stations. The study found that the highest accident rates occurred at nighttime during hours with the lowest traffic volumes. As volumes increased, up to V/C ratios of approximately 0.2, accident rates tended to decrease. The major component of the hourly variation was found to be the much higher single vehicle accident rates at night. The sites studied in the project did not have sufficiently high traffic volumes to permit an examination of the full range of V/C ratios. Preliminary studies of several urban intersections and sections of urban freeways suggest that accident rates may begin to increase when the V/C ratios exceed 0.7.
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The objectives of the study were to develop a predictive algorithm for freewaycongestion and to investigate and evaluate the current TSMC definition of freeway congestion or 'bottleneck' conditions. Data were collected along a sec...
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The objectives of the study were to develop a predictive algorithm for freewaycongestion and to investigate and evaluate the current TSMC definition of freeway congestion or 'bottleneck' conditions. Data were collected along a section of the I-5 mainline northbound beginning at Downtown Station 108 and ending at Montlake Terrace Station 193 using two approaches: (1) time series modeling, and (2) pattern recognition. A pattern recognition approach was used to identify the best criteria for 'bottleneck' definition and also to identify the best criteria for predicting 'bottleneck' conditions. The time period for collection was 2:30 to 6:30 p.m. with a data time interval of 20 seconds.
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The study was performed to investigate potential occlusions that may arise from211 the use of a laser-radar (LADAR) based sensor configuration. The study was 211 suggested to determine any potential risk in the development.
摘要 :
This study was designed with two principal objectives in mind: (1) to identifyfactors that contribute to reduced peak-period mobility in four of Houston's urban activity centers: the central business district, Greenway Plaza, Upto...
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This study was designed with two principal objectives in mind: (1) to identifyfactors that contribute to reduced peak-period mobility in four of Houston's urban activity centers: the central business district, Greenway Plaza, Uptown/Galleria, and the Texas Medical Center; and (2) develop a strategy that will encourage commuters to commit to alternative travel options. Each activity center has its own unique transportation characteristics, therefore the research included the examination of street designs, total numbers of employees, availability of public and private transportation, and pedestrian conditions. Analysis of these and other variables revealed numerous conditions that contribute to varying levels of congestion during the peak-period, including turning lane queue space, pedestrian signal systems, the spacing between passenger shelters, and configuration of street corridors.
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Within the Houston metropolitan area, a major commitment has been made to develop a system of physically separated transitways in the medians of the existing freeway network. These lanes are reserved for the exclusive use of high-...
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Within the Houston metropolitan area, a major commitment has been made to develop a system of physically separated transitways in the medians of the existing freeway network. These lanes are reserved for the exclusive use of high-occupancy vehicles. Phase 1 of the first completed transitway opened on the Katy Freeway (I-10W) in October 1984. Initially, only authorized buses and vanpools were designated as eligible users of the transitway. To encourage increased vehicular utilization of the facility, carpools were allowed to use the transitway on a test basis beginning in April 1985. The research study, sponsored by the Metropolitan Transit Authority of Harris County and the Texas State Department of Highways and Public Transportation, was initiated in order to conduct a comprehensive analysis of the effects of permitting carpools to use the transitway. The report documents data collected in October 1989, 4.5 years after carpool utilization of the transitway began. The report compares the 1989 data to similar data collected before carpool utilization was permitted (March 1985) and after carpool utilization was permitted (April 1986, October 1987, October 1988). These comparisons address numerous concerns and provide an indication of the effectiveness of allowing carpools onto the transitway.
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TDIP (Traffic Data Input Program) is a software program used for collecting traffic volume data and vehicle delay data. TDIP is used with a standard IBM-compatible personal computer in the office to collect traffic data while obse...
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TDIP (Traffic Data Input Program) is a software program used for collecting traffic volume data and vehicle delay data. TDIP is used with a standard IBM-compatible personal computer in the office to collect traffic data while observing a videotape of traffic flow at an intersection. The computer keyboard is used in place of the traditional traffic counterboard.
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The overall objective of the project was to gain a better understanding of the relationships between traffic speed, volume, and fuel consumption for congested freeway conditions. This was done by using computerized data collection...
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The overall objective of the project was to gain a better understanding of the relationships between traffic speed, volume, and fuel consumption for congested freeway conditions. This was done by using computerized data collection equipment to gather large quantities of information and correlating this empirical data with the output of the vehicle fuel consumption prediction model VECH.
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