Simulation and Evaluation of Automated Vehicle Identification at Weigh-in-Motion Inspection Stations

2010 ◽  
Vol 2160 (1) ◽  
pp. 140-150 ◽  
Author(s):  
Karim Ismail ◽  
Clark Lim ◽  
Tarek Sayed
Keyword(s):  
Automated Vehicle ◽  
Vehicle Identification ◽  
Weigh In Motion ◽  
Simulation And Evaluation

Electronic licence plate technology: automatic vehicle location and identification

1988 ◽  
Vol 15 (6) ◽  
pp. 1035-1042 ◽  
Author(s):  
A. T. Bergan ◽  
Loyd Henion ◽  
Milan Krukar ◽  
Brani Taylor
Keyword(s):  
Traffic Control ◽  
Urban System ◽  
Road Transport ◽  
The United States ◽  
Point Of View ◽  
Vehicle Classification ◽  
Vehicle Identification ◽  
Weigh In Motion ◽  
Automatic Vehicle Identification ◽  
Highway Network

The purpose of this paper is to discuss the current level of technology in automatic vehicle identification (AVI). The technology is often referred to as electronic licence plate technology, due to the use of unique vehicle identity transponders (electronic licence plates) affixed to particular highway vehicles. Interrogator or roadside receiver units placed at strategic locations or nodes on a highway network can locate and identify the particular vehicle.The main thrust of the paper is on the different types of AVI systems and the technologies employed. The discussion includes the widespread applications for AVI from both a highway administrator and road transport industry point of view. Finally, the paper discusses two AVI demonstration projects. These projects are the urban system implemented in Hong Kong and the highway system in the United States and parts of Canada known as the Heavy Vehicle and Electronic Licence Plate Project (HELP). Key words: automatic vehicle identification, electronic licence plate, road pricing, automatic vehicle classification, weigh-in-motion, commercial transportation, vehicular traffic control, pavement, Heavy Truck and Electronic Licence Plate Project.

Dynamic Origin-Destination Matrix Estimation from Traffic Counts and Automated Vehicle Identification Data

1997 ◽  
Vol 1607 (1) ◽  
pp. 87-94 ◽  
Author(s):  
Nanne J. Van Der Zijpp
Keyword(s):  
Synthetic Data ◽  
Inequality Constraints ◽  
Bayesian Updating ◽  
Problem Definition ◽  
Superior Performance ◽  
License Plate ◽  
Traffic Counts ◽  
Matrix Estimation ◽  
Automated Vehicle ◽  
Vehicle Identification

The problem of estimating time-varying origin-destination matrices from time series of traffic counts is extended to allow for the use of partial vehicle trajectory observations. These may be obtained by using automated vehicle identification (AVI), for example, automated license plate recognition, but they may also originate from floating car data. The central problem definition allows for the use of data from induction loops and AVI equipment at arbitrary (but fixed) locations and allows for the presence of random error in traffic counts and misrecognition at the AVI stations. Although the described methods may be extended to more complex networks, the application addressed involves a single highway corridor in which no route choice alternatives exist. Analysis of the problem leads to an expression for the mutual dependencies between link volume observations and AVI data and the formulation of an estimation problem with inequality constraints. A number of traditional estimation procedures such as discounted constrained least squares (DCLS) and the Kalman filter are described, and a new procedure referred to as Bayesian updating is proposed. The advantage of this new procedure is that it deals with the inequality constraints in an appropriate statistical manner. Experiments with a large number of synthetic data sets indicate in all cases a reduction of the error of estimation due to usage of trajectory counts and, compared with the traditional DCLS and Kalman filtering methods, a superior performance of the Bayesian updating procedure.

A Comparative Study between Private-Sector and Automated Vehicle Identification System Data through Various Travel Time Reliability Measures

2018 ◽  
Vol 2672 (42) ◽  
pp. 103-114
Author(s):  
Whoibin Chung ◽  
Mohamed Abdel-Aty ◽  
Juneyoung Park ◽  
Raj Ponnaluri
Keyword(s):  
Private Sector ◽  
Travel Time ◽  
Time Of Day ◽  
Traffic Information ◽  
Traffic Data ◽  
Travel Time Reliability ◽  
Automated Vehicle ◽  
Vehicle Identification ◽  
Day Of The Week ◽  
Time Periods

Traffic data from private-sector sources is increasingly used to estimate the travel time reliability of major road infrastructure. However, there is as yet no study evaluating the difference in estimating travel time reliability between the private-sector data and automated vehicle identification (AVI) based on radio frequency identification. As ground truth data, the AVI data were collected from an AVI system using toll tags and aggregated into five-minute intervals. As one of the representative traffic information providers, data from HERE was obtained through the Regional Integrated Traffic Information System, calculated in five-minute intervals. For the comparison, four kinds of measures were selected and estimated on the basis of the day of the week, specific time periods, and time of day in five-minute, 15-minute, and one-hour intervals. The statistical difference in travel time reliability was assessed through paired t-tests. According to the results, AVI and HERE data are comparable based on day of the week, specific time periods, and time of day at one-hour intervals, whereas at five-minute and 15-minute intervals, HERE and AVI data are not generally comparable. Thus, when estimating travel time reliability in real time, travel time reliability derived from HERE data may be different from the true travel time reliability. Considering that private-sector traffic data are currently used to estimate travel time reliability measures, the measures should be harmonized on the basis of robust statistics to provide more consistent measures related to the true travel time reliability.

Dynamic OD Estimation under Automated Vehicle Identification Environment

2011 ◽  
Vol 467-469 ◽  
pp. 835-840
Author(s):  
Da Shan Chen ◽  
Jian Sun ◽  
Ke Ping Li
Keyword(s):  
Traffic Control ◽  
Theoretical Models ◽  
State Equation ◽  
Estimation Accuracy ◽  
Estimation Model ◽  
Od Estimation ◽  
Automated Vehicle ◽  
Vehicle Identification ◽  
Estimation Problems ◽  
Control And Management

In order to solve the current dynamic OD estimation problems on the background of gradual application of automated vehicle identification facilities, the relationship between dynamic OD estimation and traffic parameters under AVI environment is analyzed. The dynamic OD estimation model basing on Kalman filter algorithm is established. The coefficient matrixes of state equation and observation equation are calibrated dynamically by neural network respectively. The simulation results show that the model has higher estimation accuracy for OD pairs with great flows. The model can be adopted as one of the theoretical models for dynamic OD estimation supporting traffic control and management.

scholarly journals Genetic algorithms approach to the problem of the automated vehicle identification equipment locations

2002 ◽  
Vol 36 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Dusan Teodorovic ◽  
Michel van Aerde ◽  
Fulin Zhu ◽  
Francois Dion
Keyword(s):  
Genetic Algorithms ◽  
Automated Vehicle ◽  
Vehicle Identification

Truck Travel Time Around Weigh Stations: Effects of Weigh in Motion and Automatic Vehicle Identification Systems

2000 ◽  
Vol 1716 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Rahim F. Benekohal ◽  
Yoassry M. El-Zohairy ◽  
Stanley Wang
Keyword(s):  
High Speed ◽  
Cost Effective ◽  
Average Delay ◽  
The Road ◽  
Playing Field ◽  
Electronic Screening ◽  
Vehicle Identification ◽  
Weigh In Motion ◽  
Automatic Vehicle Identification ◽  
On The Road

Weigh in motion (WIM) technology may provide an efficient and cost-effective complement to static weighing. An evaluation of the effectiveness of an automated bypass system around a weigh station in Illinois is presented. The system combines the use of automatic vehicle identification (AVI), high-speed weigh in motion (HSWIM), and low-speed weigh in motion (LSWIM) technologies to facilitate preclearance for trucks at the weigh station. The preinstallation conditions were compared with post-installation conditions of WIM/AVI so that the effects and benefits of the system could be evaluated. During preinstallation, average delay was 4.9 min/truck, and 7 percent of trucks had delays of more than 10 min. The station was intermittently closed to prevent the truck queue from backing up onto the Interstate highway, allowing 15 to 51 percent of trucks to bypass the station without being weighed. In postinstallation, the delay for trucks equipped with transponder and allowed to bypass on the freeway was reduced by 4.17 min. The delay for trucks equipped with transponders and allowed to bypass inside the weigh station was reduced by 2.02 min. The delay for trucks that reported to the weigh station decreased by 1.25 min. On the other hand, less than 1 percent of trucks that have been observed in after-study were able to bypass on the freeway. With greater numbers of trucks being checked, fewer trucks on the road may exceed the allowable weight limits. Consequently, electronic screening minimizes road deterioration and risks to public safety and levels the playing field for illegally operating carriers and carriers who operate in compliance with the law.

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