Showing papers on "Traffic count published in 1994"

Operational evidence of changing travel patterns: a case study

Abstract: This study uses traffic count data collected between 1976 and 1985 in Montgomery County, Maryland, a Washington, D.C. suburb, to shed fresh light on changes in patterns of traffic. The study considered County trends, volume trends, spreading of the peak traffic, reverse commuting, and discretionary and nondiscretionary travel. The analysis reviewed traffic count data to identify changing travel patterns. Peak volumes on suburban links were found to increase faster than population, and the number of suburb-to-suburb trips, as measured by volumes on lateral links, is increasing as a share of trips, but in the congested peak directions, discretionary travel is declining in the peak period. These and other findings are presented and discussed.

Autocounts: a way to analyse automatic traffic count data.

Abstract: Automatic traffic counts (ATCs) provide a simple and reliable method of monitoring traffic flows.

Practical approach to deriving peak-hour estimates from 24-hour travel demand models

Abstract: The Clean Air Act Amendments of 1990 have created a need for accurate and reliable estimates of peak-period travel and the speeds at which vehicles operate during that time period. State transportation agencies are faced with the problem of generating the volume and speed data needed to develop mobile source emissions inventories. This problem is compounded by the absence of current time-of-day travel characteristics. Although some of the software vendors that developed programs for the four-step travel demand forecasting process are also developing postprocessors that prepare the 24-hr model output for input to the emissions calculations models, a critical need to be able to respond to clean air agency needs required the development of an immediate response mechanism. The focus is on the application of a travel demand model and an annual traffic count program as the prime ingredients for a process that can be used to convert the 24-hr travel demand model output to peak-hour estimates of travel. The approach is a practical, how-to procedure that enables the user to estimate volumes and speeds for any hour of the day and for any day of the year, with the ultimate objective of preparing a base year inventory of mobile on-road emissions. Current data sources are evaluated and applied in the process.

Investigation of bonding materials for piezoelectric traffic monitoring equipment

Abstract: Proper highway design requires the use of accurate traffic data. Such data are collected by traffic monitoring equipment installed in the road surface. This equipment usually consists of piezoelectric sensors either l.8 meters or 3.6 meters long (6 or 12 feet long), installed in a groove cut into the pavement and held in place by a bonding agent. This study was undertaken at the request of the Texas Department of Transportation (TxDO7), in an effort to End bonding agents applicable to this use. Preliminary research consisted of a literature search, DOT survey, and manufacturers' survey to determine the current practice. Materials were selected and screened with some basic laboratory tests to determine their basic physical and material properties. Compatibility tests were conducted to determine the bond characteristics. Field tests were also conducted to determine the installation parameters of the materials. Finally, the test results were analyzed to determine which materials would perform satisfactorily in actual use. Recommendations are made, listing the most promising materials and the selection criteria to be used in future evaluations.

An automated system for accumulating count recorder (ACR) field data collection

Abstract: The Texas Department of Transportation (TxDOT) records traffic counts at tens of thousands of locations throughout the state. Such traffic information is crucial to statewide planning, forecasting, and roadway design programs. Moreover, such information is reviewed by the federal government in determining the amount of highway funds to be allocated to a state. This report describes the development of an automated system for collecting state traffic count data, specifically accumulative count recorder (ACR) field data. As part of this effort the researchers carried out a market survey of available computer hardware appropriate for field operations, and then developed, tested, and refined a system software capable of improving speed, efficiency, and accuracy of data transmission. This system, when fully implemented by TxDOT, will replace an operation that, at the present time, is carried out manually. Included in the report is a user's guide that describes all operations pertaining to the collection of data and the two-way transmission of schedule files and ACR data files between the field operating computers and TxDOTs base computer.

Transportation activity modeling for San Joaquin emissions inventory

Abstract: As the air pollution problem in the major metropolitan areas of the United States has increased, new interest has emerged for greater accuracy in the estimation of emissions from mobile sources Gridded emissions estimates owing to vehicular travel are generally produced from roadway travel data generated by transportation planning models, but the transportation planning models have generally been designed and used by transportation analysts to evaluate the effects of increased development on roadway level of service and to determine roadway capacity needs for a local or regional area and are not always ideally suited to support gridded mobile source emissions development The results of a new methodology that significantly enhances the emissions prediction capability of regional travel models are reported The methodology was developed for the eight counties in the San Joaquin Valley of California Most transportation models produce travel estimates only on an average basis and only for average weekday conditions The levels of vehicle travel vary significantly by hour throughout the day and from weekdays to weekends as well When investigating hour-specific air quality episodes that result from pollutant or precursor emissions generated during previous hours, this poor temporal resolution of the transportation model severely lowers the accuracy of the hourly estimated mobile source inventory The methodology discussed includes combining regional forecasts with supplemental traffic count data on time-of-day and vehicle type distribution of travel to improve the temporal resolution of the model-based travel activity data

An automated system for accumulating count recorder (acr) field data collection. final report

Abstract: The Texas Department of Transportation (TxDOT) records traffic counts at tens of thousands of locations throughout the state. Such traffic information is crucial to statewide planning, forecasting, and roadway design programs. Moreover, such information is reviewed by the federal government in determining the amount of highway funds to be allocated to a state. This report describes the development of an automated system for collecting state traffic count data, specifically accumulative count recorder (ACR) field data. As part of this effort, the researchers carried out a market survey of available computer hardware appropriate for field operations, and then developed, tested, and refined a system software capable of improving the speed, efficiency, and accuracy of data transmission. This system, when fully implemented by TxDOT, will replace an operation that, at the present time, is carried out manually. Included in the report is a user's guide that describes all operations pertaining to the collection of ACR field data and the two-way transmission of schedule files and ACR data files between the field operating computers and TxDOT's base computer.

Traffic count accuracy and monitoring programmes.

Abstract: Traffic demand and its anticipated growth is a major input parameter in determining value of any land transport project. This paper reviews current practice of estimating traffic counts and details findings of a major research project. Guidance in identifying typical traffic groups from short term samples as given.