M. Stencel

Bio: M. Stencel is an academic researcher from AGH University of Science and Technology. The author has contributed to research in topics: Induction loop & Weigh in motion. The author has an hindex of 8, co-authored 22 publications receiving 321 citations.

A vehicle classification based on inductive loop detectors

Abstract: The class of vehicle is one of more important parameters in the process of road traffic measurement. Up to now, strip piezoelectric sensors and video systems have been used. The use of very cheap inductive loop detectors for vehicle classification is also possible. Such vehicle classification systems are based on magnetic profiles recorded from inductive loops. The magnetic profile is sensitive to the loop dimensions. This paper presents a discussion concerning the influence of loop length (in direction of vehicle movement) on differences between characteristics describing the magnetic profiles of the vehicles belonging to the different classes. As characteristics describing the magnetic profile of the vehicle have been used: magnetic profiles in time domain (normalized in amplitude), probability density function and magnetic profiles in vehicle length domain. For real time applications, the conversion of the measured signal into a vector of numerical parameters (a few only) is also proposed. The influence of loop dimensions on a chosen signal parameter was investigated. The case of extremely short loop (10 cm), which allows detection of the number of axles, was also analyzed.

Application of inductive loops as wheel detectors

Abstract: This article presents the findings of model and field research into narrow inductive loop used as vehicle wheels detector in normal traffic conditions. The efficiency of the solution was compared with that of strip, polymeric piezoelectric detectors. The findings confirmed that narrow inductive loops can be successfully applied as wheel detectors.

Measurements of Road Traffic Parameters Using Inductive Loops and Piezoelectric Sensors

Abstract: The basic problems corresponding to the traffic measurements have been presented in the paper. Authors gave the general overview of the parameters and characteristics describing the vehicles and traffic flow. The current sensors’ technologies used in measuring systems has been presented. Moreover the measuring systems used in traffic measurements have been described. Special attention has been paid to the more sophisticated problems like the vehicle’s classification based on the analysis of its magnetic signature and to vehicles’ weigh-in-motion technique. The presented results base on the Authors’ experience in designing and exploitation of the measuring systems equipped with inductive loops and piezoelectric sensors.

Road traffic parameters measuring system with variable structure

Abstract: Systems of road traffic parameters measurement play a key role in the process of road traffic control, its supervision as well as in gathering and processing information for statistical purposes. Expectations of users of such systems mainly concern automation and provision of measurement continuity, possibility of selection of the measured road traffic parameters and high accuracy along with reliability of obtained results. In order to meet the requirements set for such systems, at the Department of Instrumentation and Measurement of the AGH University of Science and Technology in Cracow a new prototype system of road traffic parameters measurement – Traffic-1 - has been constructed. The innovativeness of the solution is manifested in the structure of the system that can be modified by the user adequately to current measurement needs and in the used algorithms of signals processing. The work contains a brief description of the constructed system with particular focus on the used innovations that are the result of many years of research work of the designers.

Regularization Of Inverse Problems

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Random Data Analysis And Measurement Procedures

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Traffic Surveillance by Wireless Sensor Networks: Final Report

Abstract: This report describes the prototype design, development, analysis and performance of a traffic surveillance system that is based on wireless sensor networks. Vehicle classification and reidentification schemes for low-cost, low-power platforms with limited computation resources were developed and tested. Both acoustic and magnetic sensors were tested. A robust real-time vehicle detection algorithm for both sensors was developed, and the magnetic sensor was shown to be superior to the acoustic sensor. The detection accuracy was shown to be comparable to that of inductive loop detectors while also having a much higher configuration flexibility, thus allowing the wireless sensor network system to be scalable and deployable everywhere in the traffic networks.

Speed estimation and length based vehicle classification from freeway single-loop detectors

Abstract: Roadway usage, particularly by large vehicles, is one of the fundamental factors determining the lifespan of highway infrastructure. Operating agencies typically employ expensive classification stations to monitor large vehicle usage. Meanwhile, single-loop detectors are the most common vehicle detector and many new, out-of-pavement detectors seek to replace loop detectors by emulating the operation of single-loop detectors. In either case, collecting reliable length data from these detectors has been considered impossible due to the noisy speed estimates provided by conventional data aggregation at single-loop detectors. This research refines non-conventional techniques for estimating speed at single-loop detectors, yielding estimates that approach the accuracy of a dual-loop detector's measurements. Employing these speed estimation advances, this research brings length based vehicle classification to single-loop detectors (and by extension, many of the emerging out-of-pavement detectors). The classification methodology is evaluated against concurrent measurements from video and dual-loop detectors. To capture higher truck volumes than empirically observed, a process of generating synthetic detector actuations is developed. By extending vehicle classification to single-loop detectors, this work leverages the existing investment deployed in single-loop detector count stations and real-time traffic management stations. The work also offers a viable treatment in the event that one of the loops in a dual-loop detector classification station fails and thus, also promises to improve the reliability of existing classification stations.