• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.719-724
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• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.92-98
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• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.53-59
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• 2011

This paper proposes a new method of traffic signal detection and recognition in an RGB color model. The proposed method firstly processes RGB-filtering in order to detect traffic signal candidates. Secondly, it performs adaptive threshold processing and then analyzes connected components of the binary image. The connected component of a traffic signal has to be satisfied with both a bounding box rate and an area rate that are defined in this paper. The traffic signal recognition system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.133-151
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• 1995

The collective of highly reliable traffic data is necessary for traffic signal control. This study is to test application of RTMS sensor to traffic signal control. In order to find out the possibility of its application th traffic signal control, 5 types of experiments were performed. The major findings are as follows ; -The detection are a has been changing according to degree and gain. -At the results of experiments for interference are a measure, Degree 60 is stable condition. -At the results of reliability test for volume and speed. the error rate decreases as speed increases and that of Zone 1 is lower than that of Zone 3. -Two modes are set up for reliability test of traffic volume. It founds that the detection reliability of the stopped vehicles are higher than that of the passing vehicles at sidefire-intersection mode. It founds that the results are vice-versa at sidefire-highway mode. Conclusively, this sensor cannot directly apply to colection of traffic data for traffic signal control. However, this sensor can be substituted for a loop detector which is used popularly for signal control, and freeway traffic control if above faults are made up.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.141-143
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• 2022

This paper presented a new technology to identify traffic violations of motorbike riders by detecting the traffic signal using You Only Look Once (YOLO) object detection. The hardware module that is mounted on the front of the motorbike consists of Raspberry Pi with a camera to run the YOLO object detection, a GPS module to acquire the motorcycle's coordinate, and a LoRa communication module to send the data to a cloud DB. The main goal of the software is to determine whether a motorbike has violated a traffic signal. This paper proposes a function to recognize the red traffic signal colour with its movement inside the camera angle and determine that the traffic signal violation happens if the traffic signal is moving to the right direction (the rider turns left) or moving to the top direction (the riders goes straight). Furthermore, if a motorbike rider is violated the signal, the rider's personal information (name, mobile phone number, etc), the snapshot of the violation situation, rider's location, and date/time will be sent to a cloud DB. The violation information will be delivered to the driver's smartphone as a push notification and the local police station to be used for issuing violation tickets, which is expected to prevent motorbike riders from violating traffic signals.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1051-1058
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• 2008

The advancement of technology for image processing and communications makes it possible for current traffic signal controllers and vehicle detection technology to make both emergency vehicle preemption and transit priority strategies as a part of integrated system. Present]y traffic signal control in crosswalk is controlled by fixed signals. The signal control keeps regular signals traffic even with no traffic, when there is traffic, should wait until the signal is given. Waiting time causes the risk of traffic accidents and traffic congestion in accordance with signal violation. To help reduce the risk of accidents and congestion, this paper explains traffic signal control system for the adaptive priority order so that signal may be preferentially given in accordance with the situation of site through the object detect images.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.153-160
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• 2018

Purpose: A traffic signal controller needs to control and coordinate to ensure that traffic and pedestrians move as smoothly as possible. Since a traffic signal controller has a significant impact on the safety of vehicles and pedestrians, it is important to monitor the failure and deterioration of the traffic signal controller. The purpose of this paper is to propose an IoT (Internet of Things)-based monitoring system for a traffic signal controller. Methods: Every traffic signal controller has a nominal system trajectory specified when it is deployed. The proposed IoT-based monitoring system collects the system trajectory information through real-time monitoring. By comparing the nominal system trajectory and the monitored system trajectory, we are able to detect the failure and deterioration of the traffic signal controller. Conclusion: The proposed IoT-based monitoring system can contribute to the safety of vehicles and pedestrians by maximizing the availability of a traffic signal controller.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.31-43
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• 2006

As of March 2005, the standard of traffic signal controllers became effective. The standard presents specifications and functions of a traffic signal controller which collects traffic information, sends it to the traffic control center, and controls traffic signal with adequate traffic signal timing provided by the traffic control center. Since the controllers by the previous standard lack parts compatibility and have different control functions and communication protocol, the maintenance cost has been increased. Also, some important functions like conflict detection have not worked out perfectly. To overcome these disadvantages, first of all, this standard secures hardware compatibility. Conflict detection method has been enhanced. Communication protocol to the traffic control center was included in the standard. With this standard, independent maintenance system and prompt treatment of hardware malfunctions becomes possible. Also, the unified intersection traffic control method will increase traffic safety.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1122-1129
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• 2015

This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.