scholarly journals Research of Distorted Vehicle Magnetic Signatures Recognitions, for Length Estimation in Real Traffic Conditions

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7872
Author(s):  
Donatas Miklusis ◽  
Vytautas Markevicius ◽  
Dangirutis Navikas ◽  
Mindaugas Cepenas ◽  
Juozas Balamutas ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Correlation Method ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Magnetic Sensors ◽  
Vehicle Speed ◽  
Personal Privacy ◽  
Length Estimation ◽  
Magnetic Signature ◽  
Magnetic Signatures

Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, in this paper we introduce a traffic flow parameterization system, using a built-in pavement sensing hub of a pair of AMR (anisotropic magneto resistance) magnetic field and MEMS (micro-electromechanical system) accelerometer sensors. In comparison with inductive loops, AMR magnetic sensors are significantly cheaper, have lower installation price and cause less intrusion to the road. The developed system uses magnetic signature to estimate vehicle speed and length. While speed is obtained from the cross-correlation method, a novel vehicle length estimation algorithm based on characterization of the derivative of magnetic signature is presented. The influence of signature filtering, derivative step and threshold parameter on estimated length is investigated. Further, accelerometer sensors are employed to detect when the wheel of vehicle passes directly over the sensor, which cause distorted magnetic signatures. Results show that even distorted signatures can be used for speed estimation, but it must be treated with a more robust method. The database during the real-word traffic and hazard environmental condition was collected over a 0.5-year period and used for method validation.

scholarly journals Analysis of Methods for Long Vehicles Speed Estimation Using Anisotropic Magneto-Resistive (AMR) Sensors and Reference Piezoelectric Sensor

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3541
Author(s):  
Vytautas Markevicius ◽  
Dangirutis Navikas ◽  
Donatas Miklusis ◽  
Darius Andriukaitis ◽  
Algimantas Valinevicius ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Polyvinylidene Fluoride ◽  
Correlation Method ◽  
Transportation Systems ◽  
Experimental Result ◽  
Percentage Error ◽  
Prototype System ◽  
Vehicle Speed ◽  
Data Set

With rapidly increasing traffic occupancy, intelligent transportation systems (ITSs) are a vital feature for urban areas. This paper analyses methods for estimating long (L > 10 m) vehicle speed and length using a self-developed system, equipped with two anisotropic magneto-resistive (AMR) sensors, and introduces a method for verifying the results. A well-known cross-correlation method of magnetic signatures is not appropriate for calculating the vehicle speed of long vehicles owing to limited resources and a long calculation time. Therefore, the adaptive signature cropping algorithm was developed and used with a difference quotient of a magnetic signature. An additional piezoelectric polyvinylidene fluoride (PVDF) sensor and video camera provide ground truth to evaluate the performances. The prototype system was installed on the urban road and tested under various traffic and weather conditions. The accuracy of results was evaluated by calculating the mean absolute percentage error (MAPE) for different methods and vehicle speed groups. The experimental result with a self-obtained data set of 600 unique entities shows that the average speed MAPE error of our proposed method is lower than 3% for vehicle speed in a range between 40 and 100 km/h.

scholarly journals LPWAN-based hybrid backhaul communication for intelligent transportation systems: architecture and performance evaluation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Area Network

AbstractIncreased number of the vehicles on the streets around the world has led to several problems including traffic congestion, emissions, and huge fuel consumption in many regions. With advances in wireless and traffic technologies, the Intelligent Transportation System (ITS) has been introduced as a viable solution for solving these problems by implementing more efficient use of the current infrastructures. In this paper, the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and NB-IoT, for ITS applications has been investigated. LTE-M and NB-IoT are designed to provide long range, low power and low cost communication infrastructures and can be a promising option which has the potential to be employed immediately in real systems. In this paper, we have proposed an architecture to employ the LPWAN as a backhaul infrastructure for ITS and to understand the feasibility of the proposed model, two applications with low and high delay requirements have been examined: road traffic monitoring and emergency vehicle management. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end-to-end latency per user. Simulation of Urban MObility has been used for realistic traffic generation and a Python-based program has been developed for evaluation of the communication system. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

scholarly journals The One-Stage Detector Algorithm Based on Background Prediction and Group Normalization for Vehicle Detection

2020 ◽  
Vol 10 (17) ◽  
pp. 5883
Author(s):  
Fei Lu ◽  
Fei Xie ◽  
Shibin Shen ◽  
Jiquan Yang ◽  
Jing Zhao ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Network Models ◽  
Vehicle Detection ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Neural Network Models ◽  
Detector Performance ◽  
One Stage ◽  
Complex Scenes ◽  
The One

Vehicle detection in intelligent transportation systems (ITS) is a very important and challenging task in traffic monitoring. The difficulty of this task is to accurately locate and classify relatively small vehicles in complex scenes. To solve these problems, this paper proposes a modified one-stage detector based on background prediction and group normalization to realize real-time and accurate detection of traffic vehicles. The one-stage detector firstly adds a module to adjust the width and height of anchors and predict the target background, which avoids the problem of the target vehicle missing detection or wrong detection due to the influence of the complicated environments. Then, group normalization and the loss function based on weight attenuation can improve the one-stage detector performance in the training process. The experimental results on traffic monitoring datasets indicate that the improved one-stage detector is superior to the other neural network models in terms of precision at 95.78%.

Simulation of an Arterial Incident Environment with Probe Reporting Capability

1998 ◽  
Vol 1644 (1) ◽  
pp. 116-123 ◽  
Author(s):  
Natacha Thomas ◽  
Bader Hafeez
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Simulation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Incident Detection ◽  
Travel Times ◽  
Control Center ◽  
Microscopic Traffic Simulation ◽  
Arterial Streets ◽  
Detection Systems

Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.

scholarly journals Networked Electronic Equipments Using the IEEE 1451 Standard—VisioWay: A Case Study in the ITS Area

2012 ◽  
Vol 8 (4) ◽  
pp. 467124 ◽  
Author(s):  
F. Barrero ◽  
S. L. Toral ◽  
M. Vargas ◽  
J. Becerra
Keyword(s):  
Video Processing ◽  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
New Paradigm ◽  
Ieee 1451 ◽  
The Impact ◽  
Smart Transducer

The concept of Intelligent Transportation Systems (ITSs) has been recently introduced to define modern embedded systems with enhanced digital connectivity, combining people, vehicles, and public infrastructure. The smart transducer concept, on the other hand, has been established by the IEEE 1451 standard to simplify the scalability of networked electronic equipments. The synergy of both concepts will establish a new paradigm in the near future of the ITS area. The purpose of this paper is to analyze the integration of electronic equipments into intelligent road-traffic management systems by using the smart transducer concept. An automated video processing sensor for road-traffic monitoring applications is integrated into an ITS network as a case study. The impact of the IEEE 1451 standard in the development and performance of ITS equipments is analyzed through its application to this video-based system, commercialized under the name VisioWay.

scholarly journals A New Distributed and Scalable Network Protocol Targeting Intelligent Transportation Systems

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
M. Meribout
Keyword(s):  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Response Times ◽  
Cluster Head ◽  
Data Communication ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Traffic Information ◽  
Scalable Network

Vehicular networks are the major ingredients of the envisioned Intelligent Transportation Systems (ITS) concept. An important component of ITS which is currently attracting wider research focus is road traffic monitoring. The actual approaches for traffic road monitoring are characterized by longer response times and are also subject to higher processing requirements and possess high deployment costs. In this paper, we propose a completely distributed and scalable mechanism for wireless sensor network-based road traffic monitoring. The approach relies on the distributed and bidirectional exchange of traffic information between the vehicles traversing the routes and a miniature cluster head and takes into consideration both the security and reliability of data communication. In addition, the communication between nodes is collision-free since the underlined data link layer protocol relies on a heuristic time multiplexed-based protocol. The performance analysis shows that the proposed mechanism usually outperforms other algorithms for different traffic densities.

scholarly journals IoT based Real Time Traffic Monitoring System Using M/G/1 Queuing Research

2019 ◽  
Vol 8 (6) ◽  
pp. 3818-3822
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Queuing Theory ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Theory Approach ◽  
The Road ◽  
Traffic Conditions ◽  
Performance Framework ◽  
Real Time Traffic

Vehicular Traffic crowding is paramount worry in urban cities. The use of technologies like Intelligent Transportation systems and Internet of Things can solve the problem of traffic congestion to some extent. The paper analyses the traffic conditions on a particular urban highway using queuing theory approach. It researches on performance framework such as time for waiting and queue length. The results can provide significant analysis to predict traffic congestion during peak hours. A congestion controlling action can be generated to utilize the road capacity fully during peak hours by using these results

scholarly journals LPWAN-Based Hybrid Backhaul Communication for Intelligent Transportation Systems: Architecture and Performance Evaluation

2020 ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Data Exchange ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Communication Infrastructure

Abstract There are more than 1.3 billion vehicles around the world and rapidly growing which causing worldwide challenges such as congestion, huge fuel consumption, and emissions. The solution to these issues could be expansion of infrastructure or making efficient use of the current infrastructure using current technological advances by implementing Intelligent Transportation Systems (ITSs). In this paper, we proposed and explored the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and Narrowband Internet of Things (NB-IoT), for ITS applications. LTE-M and NB-IoT are designed to provide long-range, low power, and lowcost communication infrastructure and can be a viable promising option for immediate implementation in the real world. In order to understand the feasibility of using LPWAN for ITS, we investigated two applications with low and high delay requirements: road traffic monitoring and emergency vehicle management and preemption. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end to end latency per user. SUMO traffic simulator has been used for realistic traffic generation and a Python-based program with the ability to live data exchange with SUMO has been developed for communication performance evaluations. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure where it was in favor of the LTE-M over NB-IoT.

scholarly journals The Optimal Sampling Period of a Fingerprint Positioning Algorithm for Vehicle Speed Estimation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Ding-Yuan Cheng ◽  
Chi-Hua Chen ◽  
Chia-Hung Hsiang ◽  
Chi-Chun Lo ◽  
Hui-Fei Lin ◽  
...  
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Sampling Period ◽  
Transportation Systems ◽  
Analytical Models ◽  
Traffic Information ◽  
Optimal Sampling ◽  
Vehicle Speed ◽  
Real Time Traffic ◽  
Positioning Algorithm

Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs). However, a high sampling frequency generates a substantial load for ITS servers, and traffic information cannot be provided instantly when the sampling period is long. In this paper, two analytical models are proposed to analyze the optimal sampling period based on communication behaviors, traffic conditions, and two consecutive fingerprint positioning locations from the same call and estimate vehicle speed. The experimental results show that the optimal sampling period is 41.589 seconds when the average call holding time was 60 s, and the average speed error rate was only 2.87%. ITSs can provide accurate and real-time speed information under lighter loads and within the optimal sampling period. Therefore, the optimal sampling period of a fingerprint positioning algorithm is suitable for estimating speed information immediately for ITSs.

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