Road Traffic Monitoring System Based on Mobile Devices and Bluetooth Low Energy Beacons

The paper proposes a method, which utilizes mobile devices (smartphones) and Bluetooth beacons, to detect passing vehicles and recognize their classes. The traffic monitoring tasks are performed by analyzing strength of radio signal received by mobile devices from beacons that are placed on opposite sides of a road. This approach is suitable for crowd sourcing applications aimed at reducing travel time, congestion, and emissions. Advantages of the introduced method were demonstrated during experimental evaluation in real-traffic conditions. Results of the experimental evaluation confirm that the proposed solution is effective in detecting three classes of vehicles (personal cars, semitrucks, and trucks). Extensive experiments were conducted to test different classification approaches and data aggregation methods. In comparison with state-of-the-art RSSI-based vehicle detection methods, higher accuracy was achieved by introducing a dedicated ensemble of random forest classifiers with majority voting.

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Penghitungan Objek Berdasarkan Berdasarkan Jenis Kendaraan Bermotor pada CCTV Lalu Lintas Berbasis Pengolahan Citra Digital Menggunakan Metode Background Subtraction dan Blob Detection

JTIM : Jurnal Teknologi Informasi dan Multimedia ◽

10.35746/jtim.v2i2.98 ◽

2020 ◽

Vol 2 (2) ◽

pp. 92-99

Author(s):

Andhika Putra Cahyono ◽

Utomo Budiyanto

Keyword(s):

Traffic Engineering ◽

Moving Objects ◽

Road Traffic ◽

Confusion Matrix ◽

Digital Processing ◽

Detection Methods ◽

The Road ◽

Blob Detection ◽

Vehicle Type ◽

Traffic Conditions

In the road traffic space which is often encountered by passing traffic type of vehicle. To find out the traffic conditions that are needed to calculate vehicle traffic, such as using counting or recording CCTV video. This continues the long and long process that was completed on the error data and the slow pace of traffic engineering decisions. This method is difficult to do in full because of the limited number of counters. This can be done by involving digital processing and CCTV video to be able to classify and transfer vehicle type objects. There are several methods for sharing object imagery, such as SIFT, edge detection and Monte Carlo. This research tries to use the Background Substraction and Blob Detection methods because of its superiority in determining objects and backgrounds and being able to maintain moving objects as well as analyzing screen area calculations. The results of testing with this method obtained the MSE value at the threshold of 100 and 3x3 kernel filter with a pixel area of motorcycle 34-63 pixel-X, 67-155 pixel-Y and cars 73-200 pixel-X, 79-307 pixel-Y and bus / truck 130-128 pixel-X, 305-376 pixel-Y. On evaluation, use the confusion matrix obtained in the morning with an average total of 92% and at night with a total average of 73%. It can be concluded by using CCTV installation parameters and the method used can yields higher accuracy in the morning than at night with the weakness of compiling objects that can make it easier to make objects and test the night to obtain light from vehicle lights generated as vehicle objects the flight.

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Evaluation of ecological extremes of vehicles in road emission tests

Archives of Transport ◽

10.5604/01.3001.0014.5516 ◽

2020 ◽

Vol 56 (4) ◽

pp. 33-46

Author(s):

Jacek Pielecha ◽

Kinga Skobiej

Keyword(s):

Objective Function ◽

Road Traffic ◽

Exhaust Emissions ◽

Motor Vehicles ◽

Road Test ◽

Testing Procedures ◽

Functional Relationships ◽

Traffic Conditions ◽

Road Emission ◽

Real Traffic

New testing procedures for determining road emissions of exhaust pollutants for passenger vehicles were established in 2018. New road testing procedures are designed to determine actual exhaust emissions, which may not always reflect laboratory emissions. Test procedures for the emission of pollutants in real traffic conditions are divided into four stages. The latest research on the emission of pollutants from motor vehicles in road traffic conditions, carried out using mobile measuring systems, reflects the actual ecological state of vehicles. The article compares the results of exhaust emissions obtained in road tests using the latest legislative proposals for passenger cars. Then, an attempt was made to determine the engine operating parameters in which exhaust road emission would be the lowest. Solution scenarios were defined as part of permissible changes to dynamic parameters that are included in European legislation on RDE testing. For this purpose, an optimization tool was used, allowing on the basis of given input data to determine the minimum objective function, defined as the smallest emission value of individual harmful compounds. The results of the exhaust gas emissions in the RDE test were used to determine the road emissions of individual harmful compounds. A thorough analysis of the emission intensity of individual compounds has shown that it is possible to approximate such values using functional relationships or adopting them as a constant value. This division was used to determine the extremes (in this case the minima) of the objective function (minimum road emissions of harmful exhaust compo-nents). This task resulted in obtaining (within the permissible tolerances of all driving parameters and durations of individual road test sections) the value of exhaust emissions in the range from 26% to 81% lower than in the actual road test. This means that there is a tolerance range, where you can obtain the value of emissions in road tests. As a result, you can use the process of determining the minimum emissions tests RDE calibration of the drive units already at the stage of preparation so that in the real traffic conditions characterized by the lowest exhaust emissions.

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A Survey and Comparison of Low-Cost Sensing Technologies for Road Traffic Monitoring

Sensors ◽

10.3390/s18103243 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3243 ◽

Cited By ~ 19

Author(s):

Marcin Bernas ◽

Bartłomiej Płaczek ◽

Wojciech Korski ◽

Piotr Loska ◽

Jarosław Smyła ◽

...

Keyword(s):

Road Traffic ◽

Low Cost ◽

Pedestrian Detection ◽

Traffic Monitoring ◽

Detection Methods ◽

Detection Accuracy ◽

Active Sensors ◽

Wide Range ◽

Passive Sensors ◽

Supporting Structures

This paper reviews low-cost vehicle and pedestrian detection methods and compares their accuracy. The main goal of this survey is to summarize the progress achieved to date and to help identify the sensing technologies that provide high detection accuracy and meet requirements related to cost and ease of installation. Special attention is paid to wireless battery-powered detectors of small dimensions that can be quickly and effortlessly installed alongside traffic lanes (on the side of a road or on a curb) without any additional supporting structures. The comparison of detection methods presented in this paper is based on results of experiments that were conducted with a variety of sensors in a wide range of configurations. During experiments various sensor sets were analyzed. It was shown that the detection accuracy can be significantly improved by fusing data from appropriately selected set of sensors. The experimental results reveal that accurate vehicle detection can be achieved by using sets of passive sensors. Application of active sensors was necessary to obtain satisfactory results in case of pedestrian detection.

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Road Traffic Monitoring

IEE Review ◽

10.1049/ir:19890083 ◽

1989 ◽

Vol 35 (5) ◽

pp. 188

Author(s):

P.L. Belcher

Keyword(s):

Road Traffic ◽

Traffic Monitoring

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

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01918-2 ◽

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.

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Night-time disability glare of constant-light LED traffic monitoring fill light

Lighting Research and Technology ◽

10.1177/1477153520982269 ◽

2021 ◽

pp. 147715352098226

Author(s):

X Cai ◽

L Quan ◽

J Wu ◽

Y He

Keyword(s):

Dynamic Range ◽

Road Traffic ◽

Reaction Times ◽

High Dynamic Range ◽

Luminance Contrast ◽

Traffic Monitoring ◽

Constant Light ◽

Night Time ◽

Disability Glare ◽

Small Targets

Fill light, used to helps cameras capture road traffic conditions at night, can lead to serious visual consequences for drivers. Research on disability glare from LED fill light is scarce and therefore this study explored strategies for controlling disability glare of constant-light LED traffic monitoring fill light. The threshold increment was used as an index to evaluate disability glare. The effective disability glare area of LED traffic monitoring fill light was determined based on high dynamic range technology. According to visual efficacy theory, there is a relationship between disability glare conditions and reaction times. The influencing factors include background luminance, luminance contrast and fill light luminance. The results showed that disability glare was the most intense in a range of 20 m to 30 m in front of LED fill light. To reduce the effect of disability glare on drivers, luminance contrast between small targets and the road surface should be greater than 0.5. The fill light luminance should not be greater than 100,000 cd/m2.

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