scholarly journals A two‐step abnormal data analysis and processing method for millimetre‐wave radar in traffic flow detection applications

2021 ◽  
Author(s):  
Haiqing Liu ◽  
Kunmin Teng ◽  
Laxmisha Rai ◽  
Yu Zhang ◽  
Shengli Wang
Keyword(s):  
Data Analysis ◽  
Traffic Flow ◽  
Processing Method ◽  
Millimetre Wave ◽  
Wave Radar ◽  
Flow Detection

scholarly journals Data Feature Analysis of Non-Scanning Multi Target Millimeter-Wave Radar in Traffic Flow Detection Applications

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2756 ◽  
Author(s):  
Haiqing Liu ◽  
Na Li ◽  
Deyong Guan ◽  
Laxmisha Rai
Keyword(s):  
Traffic Flow ◽  
Millimeter Wave ◽  
Road Traffic ◽  
Event Identification ◽  
Millimeter Wave Radar ◽  
Wave Radar ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Vehicle Trajectory ◽  
Flow Detection

The millimeter-wave radar has been widely used in traffic applications. However, little research has been done to install the millimeter-wave radar on the top of a road for detecting road traffic flow at a downward looking direction. In this paper, the vehicle parameters, including the distance, angle and radar cross-section energy, are collected by practical experiments in the aforementioned application scenario. The data features are analyzed from the dimensions of single parameter sampling characteristics and multi-parameter relationships. Further, the correlations of different parameter series are given using the grey correlation analysis method. For millimeter-wave radar used in the traffic flow detection, our work can definitely provide significant support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification.

Implementation and vehicle tests of a vehicle stop-and-go cruise control system

2002 ◽  
Vol 216 (7) ◽  
pp. 537-544 ◽  
Author(s):  
K Yi ◽  
N Ryu ◽  
H J Yoon ◽  
K Huh ◽  
D Cho ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Speed Control ◽  
Step Motor ◽  
Cruise Control ◽  
Longitudinal Control ◽  
Linear Quadratic Optimal Control ◽  
Millimetre Wave ◽  
Stop And Go ◽  
Wave Radar

Implementation and vehicle tests of a vehicle longitudinal control algorithm for stop-and-go cruise control have been performed. The vehicle longitudinal control scheme consists of a set-speed control algorithm, a speed control algorithm, and a distance control algorithm. A desired acceleration for the vehicle for the control of vehicle-to-vehicle relative speed and clearance has been designed using linear quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. Vehicle tests have been conducted using two test vehicles. A 2000 cm3 passenger car equipped with a radar distance sensor, throttle/brake actuators and a controller has been used as a subject vehicle in the vehicle tests. A millimetre wave radar sensor has been used for distance measurement. A step motor and an electronic vacuum booster have been used for throttle/brake actuators. It has been shown that the implemented vehicle longitudinal control system can provide satisfactory performance in vehicle set-speed control and vehicle clearance control at lower speeds.

INFLUENCE OF TRUCK TRAFFIC ON ACOUSTIC POLLUTION IN KAUNAS DISTRICTS CROSSED BY HIGHWAYS/KROVININIO AUTOTRANSPORTO ĮTAKA AKUSTINEI TARŠAI RESPUBLIKINĖS REIKŠMĖS MAGISTRALIŲ KERTAMUOSE KAUNO MIKRORAJONUOSE/ ВЛИЯНИЕ ГРУЗОВОГО АВТОТРАНСПОРТА НА АКУСТИЧЕСКОЕ ЗАГРЯЗНЕНИЕ В МИКРОРАЙОНАX ГОРОДА KАУНАСА С ТРАССАМИ ГОСУДАРСТВЕННОГО ЗНАЧЕНИЯ

2009 ◽  
Vol 17 (4) ◽  
pp. 198-204 ◽  
Author(s):  
Regina Gražulevičienė ◽  
Inga Bendokienė
Keyword(s):  
Data Analysis ◽  
Traffic Flow ◽  
Noise Level ◽  
Traffic Noise ◽  
Heavy Vehicles ◽  
Truck Traffic ◽  
Statistical Software ◽  
Study Results ◽  
Noise Measurements ◽  
Main Streets

The aim of the study was to assess the influence of truck traffic on acoustic pollution in two Kaunas districts crossed by highways‐ Eiguliai and Šilainiai. Composition of traffic flow and noise measurements were conducted near the main streets and national highways that cross the districts. GIS and statistical software SPSS 12.01 were used for the data analysis. The study results showed that mean noise level near the main streets was 70 dB(A) in the daytime,‐ 68.6 dB(A) in the evening and at night it was 61.1 dB(A) in Eiguliai, and in Šilainiai it was 67 dB(A), 65 dB(A) and 58 dB(A), correspondingly. On the highways, crossing the districts, heavy vehicles compose about 3 times higher part of total traffic flow during the day and about 2 times in the evening compared to other main streets. The noise level depended on the traffic flow and correlation coefficient fluctuated from 0.77 to 0.85. The modelling of traffic flow showed, that the increase of trucks proportion by 2 percent would increase the traffic noise by 1.1 dB(A) in the streets with traffic flow of 300 veh./hour or more, and by 1.8 dB(A) with traffic flow of 200 veh./hour or less. Our findings suggest that the influence of heavy vehicles on acoustic pollution is higher in the districts with lower traffic flow. Santrauka Tyrimo tikslas – nustatyti krovininio autotransporto įtaką akustinei taršai Kauno mikrorajonuose, kuriuos kerta respublikinės reikšmės magistralės – Islandijos plentas ir vakarinis lankstas. Aplinkos triukšmo lygis ir transporto srautų intensyvumas Eigulių ir Šilainių seniūnijoje buvo matuotas 34 taškuose – dieną, vakare ir naktį. Duomenims apdoroti taikyta geografinių informacinių (GIS) sistemų technologijos, SPSS 12.0.1 ir Statistica 15 statistinės analizės paketai. Tyrimų rezultatai: vidutinis ekvivalentinis triukšmo lygis Eigulių seniūnijoje dieną prie pagrindinių gatvių siekė 70 dBA, vakare – 68,6 dBA, o naktį – 61,1 dBA ir iš esmės nesiskyrė nuo Šilainių seniūnijos, atitinkamai 67 dBA, 65 dBA ir 58 dBA. Magistraliniuose keliuose, kertančiuose Eigulių ir Šilainių seniūnijas, vidutinis transporto srautų intensyvumas dieną ir vakare buvo 5 kartus, naktį 6 kartus didesnis nei vidutinis srautų intensyvumas pagrindinėse gatvėse tuo pačiu metu, o krovininio autotransporto dalis dieną 3 kartus, o vakare 2 kartus viršijo vidutinius pagrindinių gatvių srautus. Nustatyta sąsaja tarp transporto srautų intensyvumo ir triukšmo lygio: Eigulių seniūnijos dienos koreliacijos koeficientas buvo 0,85, vakaro ir nakties – 0,83, o Šilainių seniūnijos – atitinkamai 0,78, 0,77 ir 0,80. Transporto srautų sudėties modeliavimo duomenimis, padidėjus krovininio transporto proporcijai 2 %, gatvėse, kuriose transporto srautas didesnis nei 300 aut./val., triukšmo lygis padidėtų 1,1 dBA, o kur transporto srautas mažesnis nei 200 aut./val., triukšmo lygis padidėtų 1,8 dBA (koreliacijos koeficientas – 0,63). Krovininio transporto įtaka akustinei taršai didesnė mikrorajonuose, kuriuose transporto srautai nedideli. Резюме Целью данной работы было изучить влияние грузового автотранспорта на акустическое загрязнение в микрорайонах города Каунаса, которые пересекают трассы государственного значения. Это шоссе Исландиос и объезд Вакаринис. Состав транспортного потока определялся и уровень шума измерялся около главных улиц микрорайонов. Результаты исследования показали, что средний уровень шума днем был 70 dBA, вечером – 68,6 dBA, ночью – 61,1 dBA. На трассах государственного значения, пересекающих микрорайоны, по сравнению с другими улицами потоки грузовых автомобилей были в 3 раза больше днем и 2 раза больше вечером. Установлена зaвисимость между величиной транспортного потока и шума (r = 0,77–0,85). Моделирование состава транспортного потока показало, что при увеличении на улицах грузового транспорта на 2% с 300 авт./час и больше шум увеличивается на 1,1 dBA, а при количестве грузового транспорта, составляющем 200 авт./час и меньше, шум возрастает на 1,8 dBA. Влияние грузового автотранспорта на акустическое загрязнение больше в микрорайонах с небольшим транспортным потоком.

Robot Self Position based on Asynchronous Millimetre Wave Radar Interference

2019 ◽  
Author(s):  
Daniel F. Albuquerque ◽  
Edgar S. Goncalves ◽  
Eurico F. Pedrosa ◽  
Francisco C. Teixeira ◽  
Jose N. Vieira
Keyword(s):  
Millimetre Wave ◽  
Wave Radar
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