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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07 Dec 2020
TL;DR: In this article, the authors use physical context-based authentication as a second factor of authentication to oracles and demonstrate that their proposal makes oracles' authentication more robust, since it aggregates physical context information and so offers natural protection against attacks involving measurements tampering.
Abstract: Oracles are entities that feed blockchains with information from the external world. In this work, we use physical context-based authentication as a second factor of authentication to oracles. This idea takes advantage of information from the physical world to identify an oracle based on its behavior. Thus this strategy does not depend on trusty third parties. We implement our proposal for a distributed measuring system describe in the literature. Our results demonstrate that our proposal makes oracles’ authentication more robust, since it aggregates physical context information and so offers natural protection against attacks involving measurements tampering. Resumo. Oráculos são entidades que proveem informação do mundo externo para smart contracts em um blockchain. Neste trabalho, usamos autenticação de contexto fı́sico como segundo fator de autenticação para oráculos. Essa ideia vale-se do uso informações do mundo fı́sico para caracterizar o comportamento do oráculo, sem a dependência de terceiras partes confiáveis. Nossa proposta é implementada de forma prática sobre um sistema distribuı́do de medição baseado em blockchains, descrito na literatura. Os resultados demonstram que nossa proposta torna o processo de autenticação de oráculos mais robusto, uma vez que agrega informações do seu contexto fı́sico, e serve naturalmente como proteção contra ataques envolvendo fraude de medições.
2 citations
Cites background from "A multiple loop vehicle detection s..."
...Medidores de velocidade são uma solução eficiente para estimar o uso de vias públicas, obter estatı́sticas de tráfego de veı́culos e também fiscalizar limites de velocidade [Ki and Baik 2006, Ali et al. 2011]....
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TL;DR: A new empirical model was developed to estimate congestion levels using real time road Traffic Parameters (TPs) such as vehicle density, speed, class and vehicle-to-vehicle (V2V) gap, which is very useful for public and user departments for planning and decision making processes.
Abstract: . Rapid increase in road traffic density results into a serious problem of Traffic Congestion (TC) in cities. During peaks hours TC is very high and hence public search least congested path for their journeys in order to minimize ravel time and hence transportation cost. In this study, a new empirical model was developed to estimate congestion levels using real time road Traffic Parameters (TPs) such as vehicle density, speed, class and vehicle-to-vehicle (V2V) gap. These real time road TPs were collected using latest generation Inductive Loop Detector (ILD) technology. Further, a WebGIS based Road Traffic Information System (RTIS) for Dehradun city was developed for real time TD analyses and visualisation. This RTIS is very useful for public and user departments for planning and decision making processes. No other such system is available in India, which handles multiple traffic parameters simultaneously to provide solution of day-to-day problems.
2 citations
Patent•
21 Feb 2016TL;DR: In this article, a Lagrangian inertial measurement unit can have a processor, an accelerometer, a gyroscope, and a wireless transmitter, which can be configured to wirelessly transmit estimated vehicle speed and/or estimated vehicle attitude.
Abstract: An apparatus, system, and method for traffic monitory can have a Lagrangian inertial measurement unit. The Lagrangian inertial measurement unit can have a processor, an accelerometer, a gyroscope, and/or a wireless transmitter. The processor can have an integrated direction cosine matrix. The accelerometer can be configured to measure linear accelerations of a vehicle and/or can communicate measured linear acceleration to the processor. The gyroscope can be configured to measure rotational accelerations of the vehicle and/or can communicate measured rotational acceleration to the processor. The processor can be configured to calculate estimated vehicle speed and/or estimated vehicle attitude. The wireless transmitter can be configured to wirelessly transmit estimated vehicle speed and/or estimated vehicle attitude. The apparatus, system, and method can be integrated with a wireless sensor network.
1 citations
DOI•
22 Dec 2022
TL;DR: In this paper , the authors proposed an approach based on game theory to design a decentralized intersection traffic controller, able to adaptively react to changing traffic conditions and minimize the waiting time of the cars in queue.
Abstract: Future smart cities are expected to have efficient control of vehicular traffic to provide satisfactory mobility and transportation of people and goods. Reliable and efficient control schedule design for signalized intersections is needed to alleviate vehicular congestions and improve the overall road network management. In the present paper, we propose an approach based on game theory to design a decentralized intersection traffic controller, able to adaptively react to changing traffic conditions and minimize the waiting time of the cars in queue. We adopt a Bayesian dynamic game framework, which is able to improve the existing state of the art alternatives by reducing the amount of data exchanged from monitoring roadside units. Moreover, we also introduce a tunable sharing factor that is a design element available to the traffic planner controlling the priority of access and allowing for prioritization. Finally, the proposed solution is extensively evaluated via simulation in different scenarios.
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