Model for accurate speed measurement using double-loop detectors
TL;DR: A new model that uses an error-filtering algorithm to improve the accuracy of speed measurements and it can be concluded that the proposed model significantly improves vehicle-speed-measuring accuracy.
Abstract: Vehicle speed is an important parameter in measurements of road traffic. At present, double-loop detectors are generally used for vehicular speed measurement. However, these detectors incur errors caused by scanning time, spacing between double loops, irregular vehicle trajectories, and the presence of multiple vehicles in the detection zone. This paper suggests a new model that uses an error-filtering algorithm to improve the accuracy of speed measurements. In the field tests, all percent errors of the vehicular speeds measured by the proposed model were within the error tolerance limit (plusmn5%). Furthermore, the variance of percent errors was reduced. Therefore, it can be concluded that the proposed model significantly improves vehicle-speed-measuring accuracy
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TL;DR: It is shown that the sensor system can be used to reliably count the number of right turns at an intersection, with an accuracy of 95% and is compact, portable, wireless, and inexpensive.
Abstract: This paper focuses on the development of a portable roadside magnetic sensor system for vehicle counting, classification, and speed measurement. The sensor system consists of wireless anisotropic magnetic devices that do not require to be embedded in the roadway-the devices are placed next to the roadway and measure traffic in the immediately adjacent lane. An algorithm based on a magnetic field model is proposed to make the system robust to the errors created by larger vehicles driving in the nonadjacent lane. These false calls cause an 8% error if uncorrected. The use of the proposed algorithm reduces this error to only 1%. Speed measurement is based on the calculation of the cross correlation between longitudinally spaced sensors. Fast computation of the cross correlation is enabled by using frequency-domain signal processing techniques. An algorithm for automatically correcting for any small misalignment of the sensors is utilized. A high-accuracy differential Global Positioning System is used as a reference to measure vehicle speeds to evaluate the accuracy of the speed measurement from the new sensor system. The results show that the maximum error of the speed estimates is less than 2.5% over the entire range of 5-27 m/s (11-60 mi/h). Vehicle classification is done based on the magnetic length and an estimate of the average vertical magnetic height of the vehicle. Vehicle length is estimated from the product of occupancy and estimated speed. The average vertical magnetic height is estimated using two magnetic sensors that are vertically spaced by 0.25 m. Finally, it is shown that the sensor system can be used to reliably count the number of right turns at an intersection, with an accuracy of 95%. The developed sensor system is compact, portable, wireless, and inexpensive. Data are presented from a large number of vehicles on a regular busy urban road in the Twin Cities, MN, USA.
145 citations
Cites background or methods from "Model for accurate speed measuremen..."
...Transportation agencies use estimated speed information for setting speed limits and timing traffic signals [17]....
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...In [17], a method for speed estimation is proposed based on signals from two ILDs that are separated by a distance of 6 m using detection times....
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TL;DR: In this article, an IPT vehicle charging system using a series of sectional tracks is studied and the relationship among various key parameters, such as vehicle speed, system efficiency, and power utilization, is studied in detail.
Abstract: Application of inductive power transfer (IPT) to electric vehicles moving along the road can provide more charging flexibility with the reduction of weight and size of charge-storage batteries required in the vehicles. Existing research focuses on the efficiency improvement and alignment tolerance of the IPT transformer. Consideration of the transformer track length and the vehicle speed is rarely discussed. In this paper, an IPT vehicle charging system using a series of sectional tracks is studied. The relationship among various key parameters, such as vehicle speed, system efficiency, and power utilization of the IPT system, is studied in detail. Specifically, the impact on efficiency due to variation of track length and edge correction is reported. The extension of the system from a single pickup to multiple pickups is discussed. The results are verified with finite-element-analysis simulation and a scale-down experimental prototype.
94 citations
Cites background from "Model for accurate speed measuremen..."
...The switching of power among multiple track sections is supported by vehicle speed sensors [30]–[32] and an appropriate wireless feedback arrangement [33]....
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TL;DR: A novel inductive loop sensor that can detect vehicles under a heterogeneous and less-lane-disciplined traffic and thus can be used to support a traffic control management system in optimizing the best use of existing roads is presented.
Abstract: This paper presents a novel inductive loop sensor that can detect vehicles under a heterogeneous and less-lane-disciplined traffic and thus can be used to support a traffic control management system in optimizing the best use of existing roads. The loop sensor proposed in this paper detects large (e.g., bus) as well as small (e.g., bicycle) vehicles occupying any available space in the roadway, which is the main requirement for sensing heterogeneous and lane-less traffic. To accomplish the sensing of large as well as small vehicles, a multiple loop system with a new inductive loop sensor structure is proposed. The proposed sensor structure not only senses and segregates the vehicle type as bicycle, motor cycle, scooter, car, and bus but also enables accurate counting of the number of vehicles even in a mixed traffic flow condition. A prototype of the multiple loop sensing system has been developed and tested. Field tests indicate that the prototype successfully detected all types of vehicles and counted, correctly, the number of each type of vehicles. Thus, the suitability of the proposed sensor system for any type of traffic has been established.
92 citations
Cites background or methods from "Model for accurate speed measuremen..."
...Research papers discussing improvement of loop detectors for better speed measurement [8], [9] and classification [10]–[16] for lane-disciplined traffic conditions were reported....
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...accurately obtained by using double-loop detector system [8]....
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TL;DR: A new algorithm for ILD using back-propagation neural networks is suggested to improve the vehicle-classification accuracy compared to the conventional method based on ILD.
Abstract: Vehicle class is an important parameter in the process of road-traffic measurement. Currently, inductive-loop detectors (ILD) and image sensors are rarely used for vehicle classification because of their low accuracy. To improve the accuracy, the authors suggest a new algorithm for ILD using back-propagation neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and frequency waveform. The output is five classified vehicles. The developed algorithm was assessed at test sites, and the recognition rate was 91.5%. The results verified that the proposed algorithm improves the vehicle-classification accuracy compared to the conventional method based on ILD
91 citations
Cites methods from "Model for accurate speed measuremen..."
...For several years, we have conducted speed-accuracy tests for automated speed-enforcement systems using loop detectors [ 20 ]....
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01 Mar 2019
TL;DR: A comprehensive study of different coil structures and algorithms for speed and misalignment estimation in a DWPT-VDS, along with their comparison is presented, to maximize theMisalignment detection range for a given size of test coils and provide a robust solution for vehicles with different ground clearances.
Abstract: To overcome the range limitation associated with electric vehicles (EVs), the emerging technology of dynamic wireless power transfer (DWPT) can be employed. Electrified road infrastructure and wirelessly charged vehicle constitute a complex dynamic system whose successful operation requires coordination between the two subsystems and a certain level of knowledge regarding the EV position and speed on the road. A comprehensive vehicular detection system (DWPT-VDS) operating on magnetic principle and intended for DWPT applications is proposed in this paper. The following functionalities are integrated into the DWPT-VDS: a vehicle detection mechanism, the measurement of the vehicle lateral misalignment, vehicle speed measurement, driver information system (DIS), as well as the wireless communication between a roadside power controller and the DIS. When integrated with a DWPT charging system, the DWPT-VDS allows some critical functions, such as correction of the lateral position of the vehicle by the driver, an extended range of full-power reception for a misaligned vehicle, as well as the smooth transition between adjacent pads. This paper presents a comprehensive study of different coil structures and algorithms for speed and misalignment estimation in a DWPT-VDS, along with their comparison. The objective is to maximize the misalignment detection range for a given size of test coils and provide a robust solution for vehicles with different ground clearances. A three-coil system for vehicle misalignment and speed detection is selected as part of a proof-of-concept design. Part of the system is embedded in the road, and the rest is mounted on a wirelessly charged electric bus. The implemented system has been successfully tested in an outdoor environment. A DIS visualizing speed and misalignment information is also developed and tested to help the driver align the vehicle with the road-embedded primary pads.
70 citations
Cites background from "Model for accurate speed measuremen..."
...It is also possible to do vehicle classification [10] and speed measurement [11] using inductive loops....
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References
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01 Feb 1996
TL;DR: This "Traffic Control Systems Handbook" updates the 1985 edition and broadens the scope to include Intelligent Transportation Systems (ITS) technology and concepts and recommends decision-making processes in selection, implementation and operations of a traffic control system.
Abstract: This "Traffic Control Systems Handbook" updates the 1985 edition (FHWA-IP-85-11; TRIS 00475445) and broadens the scope to include Intelligent Transportation Systems (ITS) technology and concepts. The Handbook recommends decision-making processes in selection, implementation and operations of a traffic control system and describes ITS plans and programs. The "Traffic Control Systems Handbook": serves as a basic reference in planning, designing and implementing effective traffic control systems; provides an updated compendium of existing traffic control technology for the advanced designer and user; describes existing and evolving traffic control system technology; and aids understanding and facilitates training in the traffic control system field. The Handbook targets: administrators; traffic engineers; transportation planners; and students. In addition to summarizing the state-of-the-practice, chapters include "A Look to the Future" section where appropriate. In this way, the material separates proven technology from systems and elements currently under development.
245 citations
25 Aug 2001
TL;DR: This study suggests that real-time speed and travel time estimates derived from single-loop detector data assuming a common g-factor for all detectors in the district can be in error by 50 percent, and so they are of little value to travelers.
Abstract: Presents the PeMS algorithms for the accurate, adaptive, real-time estimation of the g-factor and vehicle speeds from single-loop detector data. The estimates are validated by comparison with independent, direct measurements of the g-factor and vehicle speeds from 20 double-loop detectors on I-80 over a three-month period. The algorithm is used to process data from all freeways in Caltrans District 12 (Orange County, CA) over a 20-month period beginning January 1998. Analysis of those data shows that the g-factors for different loops in the district differ by as much as 100 percent, and the g-factor for the same loop can vary up to 50 percent over a 24-hour period. Many transportation districts now post real-time speed and travel time estimates on the World Wide Web. Those estimates often are derived from single-loop detector data assuming a common g-factor for all detectors in the district. This study suggests that those estimates can be in error by 50 percent, and so they are of little value to travelers. The use of the PeMS algorithm will reduce those errors.
194 citations
Additional excerpts
...According to the literature, use of the magnetic profiles of loop detectors was very efficient in many applications [6]–[10]....
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21 May 2001
TL;DR: In this article, 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 is discussed, and the case of extremely short loop (10 cm) which allows detection of the number of axles is also analyzed.
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.
148 citations
TL;DR: The improved derivation of fundamental real-time traffic parameters, such as speed, volume, occupancy, and vehicle class, from single loop detectors and inductive signatures is demonstrated.
Abstract: Accurate traffic data acquisition is essential for effective traffic surveillance, which is the backbone of advanced transportation management and information systems (ATMIS). Inductive loop detectors (ILDs) are still widely used for traffic data collection in the United States and many other countries. Three fundamental traffic parameters—speed, volume, and occupancy—are obtainable via single or double (speed-trap) ILDs. Real-time knowledge of such traffic parameters typically is required for use in ATMIS from a single loop detector station, which is the most commonly used. However, vehicle speeds cannot be obtained directly. Hence, the ability to estimate vehicle speeds accurately from single loop detectors is of considerable interest. In addition, operating agencies report that conventional loop detectors are unable to achieve volume count accuracies of more than 90% to 95%. The improved derivation of fundamental real-time traffic parameters, such as speed, volume, occupancy, and vehicle class, from si...
95 citations
TL;DR: In this article, an algorithm using signal processing and statistical methods was developed to extract speeds from inductive waveforms, which is robust under different traffic conditions and is transferrable across surveillance sites without the need for recalibration.
Abstract: Travel time is the reciprocal of speed and is a useful measure of road congestion and traffic system performance. Travel time is also a basic traffic variable that is used in many intelligent transportation system strategies such as route guidance, incident detection, and traveler information systems. Previously, speeds were mainly acquired from double inductive loops configured as speed traps, because single loop speed estimates based on assumptions of a constant vehicle length were inaccurate. However, more accurate measurements of speed can now be accomplished with single loops by utilizing inductive waveforms of vehicles that are output from newer detector cards. An algorithm using signal processing and statistical methods was developed to extract speeds from inductive waveforms. The results show that the proposed algorithm performs better than conventional single loop estimation methods. The results also show that the algorithm is robust under different traffic conditions and is transferrable across surveillance sites without the need for recalibration. The use of the extensive single loop surveillance infrastructure is a cost-effective way of obtaining more accurate networkwide travel time information.
84 citations