Estimation and Measurement of Travel Time by Vehicle Detectors and License Plate Readers

1991 ◽  
Author(s):  
Sadao Takaba ◽  
Takeshi Morita ◽  
Takashi Hada ◽  
Tsutomu Usami ◽  
Morie Yamaguchi
Keyword(s):  
Travel Time ◽  
License Plate ◽  
License Plate Readers

Freight Vehicle Travel Time Analysis: A Case Study of Birgunj Nagdhunga Corridor

2021 ◽  
Vol 08 (02) ◽  
pp. 1-13
Author(s):  
Abhishek Jha ◽  
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
License Plate ◽  
Monitoring Method ◽  
Factors Affecting ◽  
Average Travel Time ◽  
Major Factors ◽  
Vehicle Travel Time ◽  
Freight Vehicles

This study covers the freight vehicle, which clears the custom clearance process for Kathmandu and transports the same goods to Kathmandu from Birgunj. In this study average travel time for freight vehicles from Birgunj to Nagdhunga has been studied, along with the factors affecting the travel time from Birgunj to Nagdhunga. License plate monitoring method of the freight vehicles was done to find the average travel time and a questionnaire survey was done to identify the factors affecting travel time of the freight vehicle. The travel time from Birgunj to Nagdhunga is different for different types of, vehicle and good. The fastest average travel time is of fixed container of 40 feet size with 23.2 hours and longest average time is for fixed container of 20 feet size with 28.95 hours. The average travel time for non-degradable goods is 26.5 hours and for degradable goods is 22.38 hours. Major factors affecting the travel time are traffic congestion along the route, bad road condition along the route and hilly road with sharp bends, turns and grade.

Advanced Techniques for Travel Time Data Collection

1996 ◽  
Vol 1551 (1) ◽  
pp. 51-58 ◽  
Author(s):  
Shawn M. Turner
Keyword(s):  
Data Collection ◽  
Travel Time ◽  
Real Time ◽  
Cellular Phone ◽  
License Plate ◽  
Time Data ◽  
Video Imaging ◽  
Advantages And Disadvantages ◽  
Travel Time Data ◽  
Time Information

Travel time information is becoming more important for applications ranging from congestion measurement to real-time travel information. Several advanced techniques for travel time data collection are discussed, including electronic distance-measuring instruments (DMIs), computerized and video license plate matching, cellular phone tracking, automatic vehicle identification (AVI), automatic vehicle location (AVL), and video imaging. The various advanced techniques are described, the necessary equipment and procedures are outlined, the applications of each technique are discussed, and the advantages and disadvantages are summarized. Electronic DMIs are low in cost but typically limited to congestion monitoring applications. Computerized and video license plate matching are more expensive and would be most applicable for congestion measurement and monitoring. Cellular phone tracking, AVI, and AVL systems may require a significant investment in communications infrastructure, but they can provide real-time information. Video imaging is still in testing stages, with some uncertainty about costs and accuracy.

Estimating the Effects of Police Technology Using Quasi-Experimental Methods

2017 ◽  
Vol 8 (3) ◽  
pp. 360-368 ◽  
Author(s):  
Jillian B. Carr
Keyword(s):  
Law Enforcement ◽  
Public Safety ◽  
License Plate ◽  
Law Enforcement Agencies ◽  
Difference In Differences ◽  
The Public ◽  
Fast Pace ◽  
Quasi Experimental ◽  
Police Technology ◽  
License Plate Readers

Law enforcement agencies are adopting a variety of new surveillance technologies at a fast pace. These technologies could have substantial benefits in terms of public safety, but, for many of them, their ability to reduce crime is unknown. Although a small experimental literature addresses some of these technologies, many of the implementations have been too small to provide an accurate measurement of their potential. In this paper, I explore the advantages and make general suggestions about the use of quasi-experimental methodologies in estimating the public safety benefits of police technology. I also consider the specific case of license plate readers and provide some examples of difference-in-differences approaches that could be used to study their efficacy.

scholarly journals Reliable Estimation of Urban Link Travel Time Using Multi-Sensor Data Fusion

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 267
Author(s):  
Yajuan Guo ◽  
Licai Yang
Keyword(s):  
Data Fusion ◽  
Travel Time ◽  
Sensor Data ◽  
License Plate ◽  
Traffic Data ◽  
Characteristic Analysis ◽  
Reliable Estimation ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Link Travel Time

Travel time is one of the most critical indexes to describe urban traffic operating states. How to obtain accurate and robust travel time estimates, so as to facilitate to make traffic control decision-making for administrators and trip-planning for travelers, is an urgent issue of wide concern. This paper proposes a reliable estimation method of urban link travel time using multi-sensor data fusion. Utilizing the characteristic analysis of each individual traffic sensor data, we first extract link travel time from license plate recognition data, geomagnetic detector data and floating car data, respectively, and find that their distribution patterns are similar and follow logarithmic normal distribution. Then, a support degree algorithm based on similarity function and a credibility algorithm based on membership function are developed, aiming to overcome the conflicts among multi-sensor traffic data and the uncertainties of single-sensor traffic data. The reliable fusion weights for each type of traffic sensor data are further determined by integrating the corresponding support degree with credibility. A case study was conducted using real-world data from a link of Jingshi Road in Jinan, China and demonstrated that the proposed method can effectively improve the accuracy and reliability of link travel time estimations in urban road systems.

Optimizing the geographic deployment of hot spot patrols with license plate readers

2019 ◽  
Vol 15 (4) ◽  
pp. 641-650
Author(s):  
Christopher S. Koper ◽  
Bruce G. Taylor ◽  
Sangjun Park
Keyword(s):  
Hot Spot ◽  
License Plate ◽  
License Plate Readers

Vehicle License Number Recognition System for Measuring Travel Time

1993 ◽  
Vol 5 (2) ◽  
pp. 192-197 ◽  
Author(s):  
Hisashi Kurosaki ◽  
◽  
Makoto Yagi ◽  
Hisanori Yokosuka
Keyword(s):  
Travel Time ◽  
Road Traffic ◽  
Recognition Rate ◽  
Recognition System ◽  
Letter Recognition ◽  
License Plate ◽  
Night Time ◽  
The Road ◽  
Moving Vehicles ◽  
Number Recognition

A vehicle license number recognition system for measuring travel time has been developed. This is a vehicle license number recognition system by applying image processing. A series of four-digit numbers are transmitted to the center. With the recognition results being matched at the center, the system is capable of directly measuring travel time which is an important parameter for the operation of the road traffic surveillance and control system. This paper will discuss (1) a hardware composition for solving problems associated with the imaging processing to be done outdoors and problems such as processing speed, etc.; (2) the method of extracting each letter by extracting license plate region from complicated images, and the letter recognition system based on peripheral-pattern matching; and (3) experiments for evaluation in the field. As a result of experiments for evaluation, the processing time is within a second, and the recognition rate for all moving vehicles has been as high as over 85% at day time and night time.

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