• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.113-118
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• 2016

The walking speed of handicapped people generally is slower than that of normal people. So it is difficult for them to cross at crosswalks within the allotted time provided by the traffic light. This problem can be solved by expanding the time of the traffic light. However, if the latency of the traffic light is increased without distinguishing the handicapped among all other pedestrians, the efficiency of traffic signal lights will decrease. In this paper, we propose a smart traffic signal connecting mechanism between the previous pedestrian traffic signal and a pedestrian's device (smartphone). This Smart pedestrian traffic light, through this mechanism, minimizes traffic congestion by providing additional walking time only to the handicapped among pedestrians. This crosswalk traffic light recognizes the handicapped using a technique called Internet of things (IOT). In this paper, we extract the data necessary to build an effective smart crosswalk traffic light mechanism through simulation techniques. We have extracted different kinds of traffic signal times with our virtual simulation environment to verify the efficiency of the smart crosswalk pedestrian traffic light system. This approach can validate the effective delay time of the traffic signal time through a comparison based on number of pedestrians.

• Journal of KIBIM
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• v.12 no.2
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• pp.1-11
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• 2022

Road traffic accidents (RTAs) are the leading cause of accidental death among children. RTA reduction is becoming an increasingly important social issue among children. Municipalities aim to resolve this issue by introducing "Smart Pedestrian Crosswalks" that help prevent traffic accidents near children's facilities. Nonetheless such facilities tend to be installed in relatively limited number of areas, such as the school zone. In order for budget allocation to be efficient and policy effects maximized, optimal location selection based on machine learning is needed. In this paper, we employ machine learning models to select the optimal locations for smart pedestrian crosswalks to reduce the RTAs of children. This study develops an optimal location index using variable importance measures. By using k-means clustering method, the authors classified the crosswalks into three types after the optimal location selection. This study has broadened the scope of research in relation to smart crosswalks and traffic safety. Also, the study serves as a unique contribution by integrating policy design decisions based on public and open data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.137-143
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• 2017

Facilities for pedestrian safety of the visually impaired are scarce on the walkway and crosswalk. Braille blocks are installed on the walkways and RF controlled signal lights and sound generators are installed on the crosswalk at the main intersection for the visually impaired. An RF remote control system using one frequency has a problem of simultaneously operating nearby signal lamps and sound generators at an intersection. In this paper, we develop the smart cane that uses a beacon to identify the signal lamp and sound generators installed on the crosswalk at intersections and to operate the signal lamps and sound generators in the direction of the walk by IR communication. The developed smart cane is able to provide the pedestrian navigation for the blind by interworking with mobile apps through Bluetooth communication.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.576-582
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• 2016

Currently, every person possesses a smart phone due to the development of the IT industry. However, crosswalk pedestrian accidents have been sharply increasing due to smart phone use. If a traffic light can recognize smart phones when a smart-phone user approaches and arrives at a given sign, many accidents could be reduced by using beacon signals. Before the era of smart phones, the accident rate involving cell phone use was relatively low. Nevertheless, when considering the development of IT equipment that produces a threat to human life, government cannot regulate smart phone use outside. The purpose of this paper is to indirectly warn a smart phone user in order to reduce the accident rates.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.223-234
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• 2017

The audible pedestrian signal (APS) is an add-on device which connects to the pedestrian signaling device and informs the contents and changes of the signaling by sound. It provides walking direction information of the pedestrian crossing so that the blind people can safely cross the pedestrian crossing. In an intersection where a plurality of audible pedestrian signal (APS) are installed at an intersection crosswalk, existing audible pedestrian signal (APS) operate simultaneously in the communication radius of a wireless remote controller, which may cause confusion for the blind people and the public may complain about the noise. In this paper, we developed a BLE (Bluetooth Low Energy)-based audible pedestrian signal (APS) system capable of supporting two-way communications with a smart-phone that can cross the intersection safely and improve the walking comfort and traffic safety for the blind people. The proposed method is a method in which the BLE beacon communication based audible pedestrian signal (APS) presents active service to the blind people, and the existing audible pedestrian signal (APS) is a way of requesting the passive service by the blind people with the wireless remote control by the unidirectional communication based on 358Mhz. The developed system is installed in the crossroad of Doma-dong, Seo-gu, Daejeon, and it is tested and operated by the blind people. The satisfaction evaluation and analysis of the audible pedestrian signal (APS) for the blind people have good results and are planned to be expanded in the future.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.51-59
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• 2024

In this paper, we propose a novel traffic safety system designed to reduce pedestrian traffic accidents and enhance safety on university campuses. The system involves real-time detection of vehicle speeds in designated areas and the interaction between vehicles and pedestrians at crosswalks. Utilizing the YOLOv5s model and Deep SORT method, the system performs speed measurement and object tracking within specified zones. Second, a condition-based output system is developed for crosswalk areas using the YOLOv5s object detection model to differentiate between pedestrians and vehicles. The functionality of the system was validated in real-time operation. Our system is cost-effective, allowing installation using ordinary smartphones or surveillance cameras. It is anticipated that the system, applicable not only on university campuses but also in similar problem areas, will serve as a solution to enhance safety for both vehicles and pedestrians.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.251-259
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• 2013

This paper is aimed to introduce to a moving bollard (i.e., smart bollard) to improve the pedestrian safety along the crosswalk in the school zone as a means to physically separate pedestrians and approaching vehicles, to propose the appropriate criteria for its installation and implementation from the traffic engineering perspective, and to evaluate its effectiveness with the microscopic simulation model. The simulation results indicate that implementing the smart bollard results in the decrease of average approaching speed and traffic throughput and the most critical factors affecting its effectiveness are yellow time of the traffic signal directly associated with the location of the advance warning sign and its operation time, 5~6 seconds and 2~3 seconds, respectively.