scholarly journals Vehicle Traffic Flow Detection System Based on Video Images under Haze Environment

IARJSET ◽  
2016 ◽  
Vol 3 (10) ◽  
pp. 60-63 ◽  
Author(s):  
Liu Jun-Fei ◽  
Wu Jian-Zhen ◽  
Li Hong-Qin
Keyword(s):  
Traffic Flow ◽  
Detection System ◽  
Vehicle Traffic ◽  
Video Images ◽  
Flow Detection

Vehicle Detection System with Statistical Functions Based on 3-Axis Anisotropic Magnetoresistive Using Wireless Communication Technology

2020 ◽  
Vol 17 (7) ◽  
pp. 2876-2881
Author(s):  
Xingguo Cheng ◽  
Chaomeng Chen
Keyword(s):  
Traffic Flow ◽  
Detection System ◽  
Experimental Result ◽  
Control Technique ◽  
Vehicle Speed ◽  
Single Chip ◽  
Novel Approach ◽  
Novel Method ◽  
Flow Detection ◽  
Statistical Functions

In terms of current issues that the sensor’s output signal drifts along with the surrounding strong magnetic field by using the single or dual-axis analog anisotropic magnetoresistive (AMR) sensor in the traffic flow detection, a traffic flow detection system based on ZigBee wireless sensor network is developed and a novel approach by exercising the new digital three-axis AMR sensor to detect the traffic flow is proposed to solve these issues as mentioned above. Using Single Chip Microcomputer (SCM) control technique and utilizing wireless transmitting, an effective algorithm is designed. The algorithm makes it possible to classify vehicle, calculate vehicle speed and count vehicle, in the meantime it provides a reliable and efficient method to collect intelligent transportation data. Even more important, the algorithm has a statistical functions based on MATLAB. The experimental result shows that the novel method has much better measurement accuracy, reliability and redundancy than single or dual-axis method.

scholarly journals LoRa-Based Traffic Flow Detection for Smart-Road

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 338
Author(s):  
David Asiain ◽  
Diego Antolín
Keyword(s):  
Traffic Flow ◽  
Detection System ◽  
Field Tests ◽  
Area Network ◽  
Vehicle Speed ◽  
Wide Area Network ◽  
Communication Signal ◽  
Accurate Comparison ◽  
Comparison Field ◽  
Flow Detection

This paper presents a wireless traffic flow detection system, mainly focused on conditions in which the traffic flow is slow or stopped, which increases the risk of highway accidents. To achieve this goal, a Low Power Wide Area Network (LPWAN) based on LoRa called Short LoRa has been developed. This LoRa sub-network complies with the European Telecommunications Standards Institute (ETSI) harmonized standard for its compatibility in Europe countries. In addition, the development of the devices has allowed them to also work on a LoRaWAN network. The introduced development has been compared to a reference system mounted with laser barriers that provided a high accurate comparison. Field tests of the system have been carried out and the data obtained in the measurement has been analyzed with two different methods, and both of them were valid for the application. The results can determine vehicle speed with adequate precision at low speeds. The attenuating behavior of the communication signal is also analyzed through the Radio Signal Strength Indicator (RSSI). The relationship between vehicle speed, gate distances and RSSI attenuation has been studied. The system is proven to have efficient results in detecting traffic flow under the conditions for which it has been developed.

Research and Design of Road Traffic Flow Detection System

2014 ◽  
Vol 945-949 ◽  
pp. 3291-3295 ◽  
Author(s):  
Zan Song ◽  
Qing Ye
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Detection System ◽  
Frequency Change ◽  
Traditional System ◽  
Arm Processor ◽  
Loop Detection ◽  
Flow Detection ◽  
Research And Design ◽  
Type Classification

A road traffic flow detection system is designed based on induction loop, and the control platform is constructed based on the most advanced 32-bit ARM processor and CPLD. The systems hardware framework and software design process are introduced in this paper. The defects of traditional system such as deficient processing capacity and low measurement accuracy are overcome. In this system the data of the frequency change caused by the vehicles through the coil is collected, and the function of vehicles type classification in real-time is added, which is a great improvement compared to traditional induction loop detection system of vehicles.

scholarly journals Leak Detection Systems for Short Pipelines

2000 ◽  
Author(s):  
Renan Martins Baptista
Keyword(s):  
Detection System ◽  
Leak Detection ◽  
Low Complexity ◽  
Transient Model ◽  
Service Companies ◽  
Detection Systems ◽  
Volume Balance ◽  
Pipeline Networks ◽  
Phase Liquid ◽  
Flow Detection

This paper describes procedures developed by PETROBRAS Research & Development Center to assess a software-based leak detection system (LDS) for short pipelines. These so-called “Low Complexity Pipelines” are short pipeline segments with single-phase liquid flow. Detection solutions offered by service companies are frequently designed for large pipeline networks, with batches and multiple injections and deliveries. Such solutions are sometimes impractical for short pipelines, due to high cost, long tuning procedures, complex instrumentation and substantial computing requirements. The approach outlined here is a corporate approach that optimizes a LDS for shorter lines. The two most popular implemented techniques are the Compensated Volume Balance (CVB), and the Real Time Transient Model (RTTM). The first approach is less accurate, reliable and robust when compared to the second. However, it can be cheaper, simpler, faster to install and very effective, being marginally behind the second one, and very cost-efective. This paper describes a procedure to determine whether one can use a CVB in a short pipeline.

scholarly journals Pengaruh Pelican Crossing terhadap Panjang Antrian dan Tundaan Kendaraan di Ruas Jalan Asia Afrika Kota Bandung (Hal. 18-27)

2018 ◽  
Vol 4 (2) ◽  
pp. 18
Author(s):  
Muhammad Reza Nugraha ◽  
Dwi Prasetyanto ◽  
Andrean Maulana
Keyword(s):  
Traffic Flow ◽  
Multiple Regression ◽  
Queue Length ◽  
Vehicle Traffic ◽  
Maximum Queue Length

ABSTRAKPelican crossing merupakan jenis penyeberangan yang dioperasikan oleh penyeberang jalan yang bertujuan memberikan keselamatan kepada penyeberang. Tujuan dari penelitian ini adalah menentukan jenis penyeberangan dan mencari pemodelan tundaan dan panjang antrian akibat pelican crossing di jalan Asia Afrika Bandung. Data penelitian ini adalah frekuensi penyeberangan, jumlah penyeberang, jumlah kendaraan terhenti, arus lalu lintas, tundaan dan panjang antrian kendaraan. Analisis penentuan jenis penyeberangan menggunakan perhitungan PV2  dan analisis pemodelan tundaan dan panjang antrian menggunakan regresi linier berganda. Dari perhitungan PV2 didapatkan hasil PV2=2,49*109 yang berarti termasuk kepada jenis penyeberangan pelikan dengan lapak tunggu. Model yang mewakili hubungan antara panjang antrian (Y) dengan jumlah kendaraan terhenti (X1) dan frekuensi penyeberangan (X2) adalah Y=2,201 + 3,203X1 + 3,510X2. Model yang mewakili hubungan antara tundaan  (Y) dengan variabel bebas yang sama adalah Y=0,709 + 2,656X1 + 7,645. Panjang antrian maksimum sebesar 78,072 meter dan tundaan maksimum sebesar 89,826 detik.Kata kunci: pelican crossing, panjang antrian, tundaanABSTRACTPelican crossing is a type of pedestrian cross which is operated by pedestrian with purpose is to give safety for the crosser. The aim of this study are to determine the type of crossing and find the model of delay and queue length because of pelican crossing at Asia Afrika Street Bandung. The data of this study are crossing frequency, amount of crossers, amount of stopped vehicle, traffic flow, delay and queue length vehicle. Analysis for the type of the crossing obtained by calculation of and analysis of model delay and queue length are use multiple regression. The result from the calculation of PV2  is PV2=2,49*109 which is the type of the crossing is pelican with protector. The represent model of relation between the queue length (Y) with amount of stopped vehicle  and crossing frequency (X2) is  Y=2,201 + 3,203X1 + 3,510X2.The represent model of relation between delay (Y) with same dependent variable is Y=0,709 + 2,656X1 + 7,645. The maximum queue length is 78,072 meters and the delay maximum is 89,826 seconds.Keyword: pelican crossing, the queue length, delay

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