Augmented Reality Surveillance System for Road Traffic Monitoring

2014 ◽  
pp. 310-317 ◽  
Author(s):  
Alexander Filonenko ◽  
Andrey Vavilin ◽  
Taeho Kim ◽  
Kang-Hyun Jo
Keyword(s):  
Augmented Reality ◽  
Surveillance System ◽  
Road Traffic ◽  
Traffic Monitoring

Road Traffic Monitoring

IEE Review ◽  
1989 ◽  
Vol 35 (5) ◽  
pp. 188
Author(s):  
P.L. Belcher
Keyword(s):  
Road Traffic ◽  
Traffic Monitoring

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.

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

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.

scholarly journals Development of a Road Condition Information System using Augmented Reality Technology on Smartphones

2020 ◽  
Vol 10 (2) ◽  
pp. 49-55
Keyword(s):  
Information System ◽  
Augmented Reality ◽  
High Speed ◽  
Human Error ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Data Conversion ◽  
The Road ◽  
Road Condition ◽  
Augmented Reality Technology

Recently, accidents involving ground transportations are getting worse and more serious. Indonesian State Police (Korlantas POLRI) recorded the number of accidents in 2018 as many as 109,215 accidents. The number has incresed 4.69 percent compared to 2017 as many as 104,327 events. Road traffic accidents are caused by human error, the driver in this case. The driver's mistake is influenced by several factors, one of them is they cannot expect the road condition when they drive a vehicle at high speed. To solve this problem, drivers need information that can show road conditions. So, we present a new approach for detecting damaged roads by applying augmented reality technology. This research produces a road condition information system to help drivers get information about road conditions via smartphone. This system uses augmented reality technology with a markerless GPS Based Tracking method. The development of this system requires several stages such as collecting the data, data conversion, data classification, and views road condition. The researchers gathered the road condition data from the Public Work Department Semarang. This department itself undertakes a task to control the road condition in Semarang The trial of this system includes all drivers in Semarang city. Based on the results of the questionnaire responded to by 93 respondents, this test obtained an average value of 68%. So this system gets a pretty good response from the driver. Through this system, all drivers can avoid the damaged road condition which can cause traffic-congested and accident.

scholarly journals Knowledge-Based Road Traffic Monitoring

2007 ◽  
pp. 182-191 ◽  
Author(s):  
Antonio Fernández-Caballero ◽  
Francisco J. Gómez ◽  
Juan López-López
Keyword(s):  
Road Traffic ◽  
Traffic Monitoring ◽  
Knowledge Based
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