Showing papers on "Traffic count published in 2004"

Estimating Vehicle Speed from Traffic Count and Occupancy Data

Abstract: Automatic vehicle detectors are now common on road systems across the world. Many of these detectors are based on single inductive loops, from which data on traffic volumes (i.e. vehicle counts) and occupancy (i.e. proportion of time during which the loop is occupied) are available for 20 or 30 second observational periods. However, for the purposes of traffic management it is frequently useful to have data on (mean) vehicle speeds, but this is not directly available from single loop detectors. While detector occupancy is related in a simple fashion to vehicle speed and length, the latter variable is not measured on the vehicles that pass.In this paper a new method for speed estimation from traffic count and occupancy data is proposed. By assuming a simple random walk model for successive vehicle speeds an MCMC approach to speed estimation can be applied, in which missing vehicle lengths are sampled from an exogenous data set. Unlike earlier estimation methods, measurement error in occupancy data is explicitly modelled. The proposed methodology is applied to traffic flow data from Interstate 5 near Seattle, during a weekday morning. The efficacy of the estimation scheme is examined by comparing the estimates with independently collected vehicle speed data. The results are encouraging.

Application of regression analysis for identifying factors that affect seasonal traffic fluctuations in southeast florida

Abstract: Traffic variations occur at different time scales—time of day, day of week, and season of the year. Among the known temporal fluctuations of traffic stream, seasonal variation is probably of the most concern in traffic monitoring. In the current practice of the Florida Department of Transportation, district offices determine seasonal factor categories from a group of selected permanent telemetry traffic monitoring sites and assign them to short-term traffic count sites for estimating annual average daily traffic. Assignment of short-count sites to factor groups is based largely on their spatial proximity to a permanent traffic count site and engineering judgment. Although location may be an important factor, this process may be oversimplified and somewhat subjective. Regression analyses for estimating seasonal factors shed light on the factors contributing to seasonal changes in traffic volumes. The method could reduce the subjectivity of current practice either by allowing seasonal factors to be estimate...

Road-traffic pollution and asthma – using modelled exposure assessment for routine public health surveillance

Abstract: Asthma is a common disease and appears to be increasing in prevalence. There is evidence linking air pollution, including that from road-traffic, with asthma. Road traffic is also on the increase. Routine surveillance of the impact of road-traffic pollution on asthma, and other diseases, would be useful in informing local and national government policy in terms of managing the environmental health risk. Several methods for exposure assessment have been used in studies examining the association between asthma and road traffic pollution. These include comparing asthma prevalence in areas designated as high and low pollution areas, using distance from main roads as a proxy for exposure to road traffic pollution, using traffic counts to estimate exposure, using vehicular miles travelled and using modelling techniques. Although there are limitations to all these methods, the modelling approach has the advantage of incorporating several variables and may be used for prospective health impact assessment. The modelling approach is already in routine use in the United Kingdom in support of the government's strategy for air quality management. Combining information from such models with routinely collected health data would form the basis of a routine public health surveillance system. Such a system would facilitate prospective health impact assessment, enabling policy decisions concerned with road-traffic to be made with knowledge of the potential implications. It would also allow systematic monitoring of the health impacts when the policy decisions and plans have been implemented.

Benefits of auto-configuring traffic sensing equipment

Abstract: The sensitivity of traffic monitoring equipment from inductive loops to non-intrusive sensors must be calibrated in order to optimize detection of traffic variables within their detection zones. In addition, non-intrusive sensors need to determine the positions of traffic lanes within their field of view. Non-intrusive traffic sensing equipment that auto-configures both the lane definitions and sensitivity settings has the following benefits: (1) configuration and verification timeframe is reduced to ten to fifteen minutes; (2) accurate configuration is obtained using unbiased statistical sampling; (3) cost of cross-training personnel on detector technologies is lowered; (4) rapid-deployment is feasible in the face of aggressive ITS schedules; (5) site survey results are representative instead of best case scenario; (6) work-zone and temporary traffic count applications become practical; (7) configuration maintenance can be performed remotely when needed; and (8) threat to personal safety is mitigated thanks to convenience of process. The degree to which each of these benefits is realized depends primarily upon the nature of the learning curve provided by the automated process. The learning curve of the auto-configuration system embedded in a state-of-the-art FMCW radar detector, the SmartSensor descends rapidly in free-flow traffic conditions to provide greater than 95% overall volume accuracy in just a few minutes. Auto-configuration simplifies and speeds-up the configuration process by over-sampling the traffic stream in all lanes simultaneously to probe for the underlying statistical distributions. Optimal decision boundaries for the lane definitions and sensitivity settings can be calculated using the sample distributions of vehicle ranges and vehicle brightness.

VMT Estimation Associated with ITS Data and Maintenance of Loop Detectors

Abstract: Continuous or coverage count stations in the Highway Performance Monitoring System and the traffic count stations in a traffic control and management system coexist on some roadway segments and can be used together to derive vehicle mile traveled (VMT), an important measure of the utilization of highway systems by vehicles. This study focused on the comparison of the qualities of the data from these two systems and the identification of factors that influence the life duration of the loop detectors in these two systems. The data quality issue is investigated by identifying the probabilistic relationship between the accuracy of VMT estimation and the number of missing day data. Given a traffic count with certain number of missing day data, the relationship can be used to determine the probability that the traffic operation data based VMT is better than the coverage count based VMT. This relationship is incorporated into a procedure proposed in this study to calculate VMT for the whole area of the study area, the Virginia’s Hampton Roads area. To conquer the computational problem caused by the large number of comparisons between coverage count based and traffic operation count based VMT, the Monte Carlo method is applied. The relationship between loop detector’s life duration and the influencing factors is investigated by developing linear regression models by which the life duration and the influencing factors (primarily traffic volume) are correlated. By having such a relationship identified, the maintenance policy developed based on the life duration can be evaluated for different level of traffic volume that is forecasted for future.

An Innovative Approach to Truck Modeling

Abstract: A Federal Highway Administration freight analysis forecasts that freight tonnage and truck vehicle miles of travel (VMT) will double in the next twenty years. Interest in modeling truck traffic will, therefore, increase in response to increasing truck traffic in many areas. The traditional approach to creating a truck model has been to conduct a survey on truck movements to use to develop a model of truck trip rates, distribution patterns, and routes. This approach is generally not feasible, however, due to the difficulty and high cost inherent in conducting a statistically valid truck survey. An innovative, faster, less costly approach to developing a truck model has been developed using a technique called “adaptable assignment.” Adaptable assignment is a practical method of synthesizing a trip table from count data. Detailed classification count data was available at over 600 locations throughout the Baltimore Metropolitan council (BMC) modeled network. An initial model was created using parameters from another urban area. This initial trip table was modified by the adaptable assignment process, to produce a new table whose assignment much more closely matched the count data. The resulting trip table was systematically compared to the initial table to understand the differences. Numerous adjustments were then made to the initial model to reflect those differences. An improved method of estimating external travel was also developed. The final model consists of standard generation and distribution steps, a table of calibration adjustments, and an assignment process that specifically recognizes trucks. The calibration adjustments are applied to all future trip tables. This process was applied twice, to develop separate models for Medium Trucks (F5 vehicles in the FHWA classification scheme) and Heavy Trucks (F6-F13). The new models were incorporated into the framework of the Baltimore Region Travel Demand Model and the TP+/VIPER software. The Baltimore Region Travel Demand Model is the traditional four step model maintained by BMC staff for air quality conformity analysis, corridor studies, and long range planning. The new process for modeling accounted for areas of heavy trucking activity, land use, truck prohibitions, and truck passenger car equivalencies (PCEs). In areas of heavy trucking activity, e.g., port facilities, land fills, etc., a total of 127 truck special generator zones were identified. The model results showed significant improvement over the previous model and compared well to traffic count data. This presentation describes the process of developing a truck model using “adaptable assignment,” presents model results, and discusses the benefits of this approach over traditional methods.

Feasibility of using urban planning models to support intermediate traffic forecasts

Abstract: This paper focuses on analyzing traffic facilities for an intermediate time frame. There are two methodologies examined in this work, the first uses extrapolated, historical traffic count data and the second uses an urban transportation model. Using several intersections within Huntsville, Ala., as case study intersection locations, this paper applies both methodologies to forecast near-future traffic and compares the forecasted results with the actual traffic counts to determine which methodology better replicated actual volumes. The results of this work indicate that a properly validated and applied urban transportation planning model has the ability to provide more accurate traffic forecasts to support the traffic engineering analysis decision than the commonly used extrapolated traffic trends.

Traffic state determination by using fuzzy logic

Abstract: The proposed paper discusses a method to transform data from stationary counting stations into useful traffic information for road users by means of fuzzy logic. The data used for processing are traffic density and medium speed data, delivered by permanent traffic counting stations. An adjustment of the method is not necessary, since it adapts automatically to the location-related traffic parameters.

Transport impacts of the Copenhagen metro in the Frederiksberg area

Abstract: The impact of the Copenhagen metro in Denmark on traffic growth, induced traffic ad choice of mode and destination in the Frederiksberg area were studied. The history, alignment and characteristics of the metro are described. In phase 2 of the metro, lines were opened between Norreport and Frederiksberg and between Frederiksberg and Vanlose. The traffic impact study involved traffic counts of private cars, buses, bicycles and metro passengers and panel interviews to obtain data on trip rates, travel modes, travel purpose and choice of destination. The study showed increases in traffic, use of public transport and trip rate. There was a modal shift from bus and car to metro use. For the covering entry of this conference please seeITRD E132365