A multiple loop vehicle detection system for heterogeneous and lane-less traffic
10 May 2011-pp 1-5
TL;DR: A novel inductive loop sensor which detects large as well as small vehicles and help a traffic control management system in optimizing the best use of existing roads is presented.
Abstract: This paper presents a novel inductive loop sensor which detects large (e.g., bus) as well as small (e.g., bicycle) vehicles and help a traffic control management system in optimizing the best use of existing roads. To accomplish the sensing of large as well as a small vehicle, a multiple loop inductive sensor system is proposed. The proposed sensor structure not only senses and segregates the vehicle type as bicycle or motor cycle or car or bus but also enables accurate counting of the number of vehicles that too in a mixed traffic flow condition. A prototype of the multiple loop sensing system has been developed using a virtual instrumentation scheme 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 multi loop sensor system for any type of traffic has been established.
Citations
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25 Oct 2012
TL;DR: Results from a prototype system developed show that the RF based algorithm provides better accuracy compared to the threshold based and signature based methods.
Abstract: This paper presents a suitable algorithm to classify vehicles detected by a multiple inductive loop system, developed for measuring traffic parameters in a heterogeneous and no-lane disciplined traffic. The proposed classification scheme employs Random Forest (RF) algorithm. This scheme is suited not only for classifying the detected vehicles as bicycle, motorcycle, scooter, car and bus but also for counting them accurately under a mixed traffic condition. The algorithm has been implemented and tested. Its performance has also been compared with other algorithms based on threshold values and signature patterns. The threshold, signature and RF based algorithms use the number of loops a vehicle occupies as an important factor for classification. Results from a prototype system developed show that the RF based algorithm provides better accuracy compared to the threshold based and signature based methods.
15 citations
13 May 2012
TL;DR: In this article, a multiple inductive loop detector system that uses the mutual inductances between an outer loop and multiple inner loops is presented, where small inner loops are placed within a large outer loop.
Abstract: A new multiple inductive loop detector system that uses the mutual inductances between an outer loop and multiple inner loops is presented in this paper. Automated detection, classification and speed measurement of vehicles are a challenging task in a no-lane and heterogeneous traffic. A recently reported multiple loop scheme is a solution but it is complex and less reliable due to large number of electrical connections required to realize the system. This paper proposes a loop sensor wherein small inner loops are placed within a large outer loop. In the new system the outer loop alone is connected to the measurement unit and all the inner loops are simply coupled inductively to the outer loop. This scheme is simple and can be easily employed to convert an existing single loop system to a multiple loop system by incorporating the inner loops. A suitable measurement scheme based on a synchronous detection is employed that guarantees accurate measurement. A special excitation that ensures parallel resonance of the whole inductive system is employed to keep the power consumption minimum. A prototype of the proposed system has been built and the practicality has been tested. The new system correctly sensed the vehicles, categorized and counted them in an undisciplined traffic.
11 citations
Cites background or methods from "A multiple loop vehicle detection s..."
...The inner loop has a special shape [10] as shown in the right side of...
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...This capability is very useful for sensing vehicles effectively in less-lane disciplined traffic [10]....
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...1(b), instead of the single large loop has been reported [10]....
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...In the method reported in [10], all the loops are connected to the measurement system individually, leading to 2n cables (n = number of loops) and associated joints which makes the system quite complex to realize....
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06 May 2013
TL;DR: This paper proposes a complex virtual instruments system architecture which could not only extend the function of virtual instrument but also ease the development process of the system.
Abstract: Virtual instrument system has received amounts of attention and become a common practice in many fields. Virtual instrument is a program that implements functions of an instrument by software which could replace the work of real instrument to save resources. The functions of these systems are limited and they commonly have little related information about sensors, navigation, monitoring objects due to special requirements. The procedure of development and integration often suffers from low efficiency because of non-standard development technologies. In this paper, we propose a complex virtual instruments system architecture which could not only extend the function of virtual instrument but also ease the development process of the system. Our architecture is validated by multiple developed systems. The result shows that the proposed architecture is effective and feasible.
9 citations
23 May 2016
TL;DR: The IoTI designed based on the new model can achieve automatic access to different sensing devices, seamless integration and communication for heterogeneous environments, and improve the development efficiency.
Abstract: As the ‘Industry 4.0’ has been proposed, the need of large-scale systems integration has become more urgent. Currently, Internet of things (IoT) systems used in intelligent manufacturing are commonly developed by different organizations using specific technologies and platforms, which brings a lot of difficulties in monitoring equipment access and seamless integration. To solve the aforementioned problem, a novel model of the Internet of things instrument (IoTI) is proposed. The IoTI designed based on the new model can achieve automatic access to different sensing devices, seamless integration and communication for heterogeneous environments. It can also improve the development efficiency. During the development, integration and application of IoTI, we validate the rationality and feasibility of aforesaid model. The results show that the model is efficient and feasible, which realizes the heterogeneous system integration and improves development efficiency.
8 citations
03 Dec 2015
TL;DR: The historical review of the technology and the recent development of the intelligent traffic light control system are stated and the future studies of the related work are presented.
Abstract: The congestion of the urban traffic is becoming one of critical issues with increasing population and automobiles in cities. Traffic jams not only cause extra delay and stress for the drivers, but also increase fuel consumption, add transportation cost, and increase carbon dioxide air pollution. The traffic controller is one of critical factors affecting the traffic flow. The conventional traffic patterns are nonlinear and complex. As a result, the fixed traffic light controller is not optimized to reduce the traffic jam. Moreover, it does not improve the response time for ambulances, fire trucks, police cars and other emergency vehicles. This paper is written with the endeavor to provide the readers an idea of the research that has been carried out in the intelligent traffic light field and the microcontroller based traffic light control system. The historical review of the technology and the recent development of the intelligent traffic light control system are stated in this paper. In addition, the future studies of the related work are also presented.
7 citations
References
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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
"A multiple loop vehicle detection s..." refers background in this paper
...Research papers discussing improvement of loop detectors for better speed measurement [5] and classification [6]-[9] for lane disciplined traffic conditions were reported....
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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
"A multiple loop vehicle detection s..." refers background in this paper
...Research papers discussing improvement of loop detectors for better speed measurement [5] and classification [6]-[9] for lane disciplined traffic conditions were reported....
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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
89 citations
"A multiple loop vehicle detection s..." refers background or methods in this paper
...The speed of the vehicle can be obtained accurately by using double-loop detector system [5]....
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...Research papers discussing improvement of loop detectors for better speed measurement [5] and classification [6]-[9] for lane disciplined traffic conditions were reported....
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TL;DR: A novel vehicle-classification algorithm that uses the time-variable signal generated by a single inductive loop detector to strengthen the classification accuracy by emphasizing the undercarriage height variation of the vehicle.
Abstract: This paper presents a novel vehicle-classification algorithm that uses the time-variable signal generated by a single inductive loop detector In earlier studies, the noisy raw signal was fed into the algorithm by reducing its size with rough sampling However, this approach loses the original signal form and cannot be the best exemplar vector The developed algorithm suggests three contributions to cope with these problems The first contribution is to clear the noise with discrete Fourier transform (DFT) The second contribution is to transfer the noiseless pattern into the Principal Component Analysis (PCA) domain PCA is exploited not only for decorrelation but for explicit dimensionality reduction as well This goal cannot be achieved by simple raw data sampling The last contribution is to expand the principal components with a local maximum (Lmax) parameter It strengthens the classification accuracy by emphasizing the undercarriage height variation of the vehicle These parameters are fed into the three-layered backpropagation neural network (BPNN) BPNN classifies the vehicles into five groups, and the recognition rate is 9421% This recognition rate has performed best, compared with the methods presented in published works
67 citations
Patent•
23 Jan 1975
TL;DR: In this paper, an inductive loop is used to detect vehicles in the immediate vicinity of the loop, where the vehicle's presence is dependent on whether or not the vehicle is over the loop.
Abstract: Apparatus for use in combination with an inductive loop for detecting metal objects, e.g. vehicles, in the immediate vicinity of said loop. The loop may, for example, be a coil of wire buried in a roadway in a plane parallel to the roadway surface. Oscillator circuitry is operatively connected to the loop with the frequency of oscillation being determined by the loop inductance, which in turn is dependent on whether or not the vehicle is over the loop. The loop frequency is monitored by digital circuitry including a loop counter which counts loop oscillator cycles and a duration counter which measures the time duration of a fixed number of loop oscillator cycles. The measured time duration is compared with an adaptable reference duration to ascertain whether the loop oscillator frequency has increased or decreased. The presence of a vehicle over the loop decreases loop inductance, increases loop frequency, and thus reduces the measured time duration of a fixed number of loop cycles. A reduction in the measured time duration by an amount greater than a preselected threshold value produces an output signal or "call" to indicate the vehicle's presence.
57 citations