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Journal articles on the topic 'Traffic signs and signals Australia'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Rash-ha Wahi, Rabbani, Narelle Haworth, Ashim Kumar Debnath, and Mark King. "Influence of Type of Traffic Control on Injury Severity in Bicycle–Motor Vehicle Crashes at Intersections." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 38 (2018): 199–209. http://dx.doi.org/10.1177/0361198118773576.

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Many studies have identified factors that contribute to bicycle–motor vehicle (BMV) crashes, but little is known about determinants of cyclist injury severity under different traffic control measures at intersections. Preliminary analyses of 5,388 police-reported BMV crashes from 2002 to 2014 from Queensland, Australia revealed that cyclist injury severity differed according to whether the intersection had a Stop/Give-way sign, traffic signals or no traffic control. Therefore, separate mixed logit models of cyclist injury severity (fatal/hospitalized, medically treated, and minor injury) were

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Inagaki, Joji. "Traffic message signals and signs." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 76, no. 1 (1992): 21–24. http://dx.doi.org/10.2150/jieij1980.76.1_21.

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Raj, Kumar Shrivastava, and Yadav Rakesh. "Automated Traffic Signals using Real-Time Traffic Densities." Journal of Information Technology and Sciences 4, no. 3 (2018): 28–36. https://doi.org/10.5281/zenodo.1693994.

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The ever-increasing problem of traffic is taking a toll on the commuters’ daily routine wherein a significant amount of time of the day is consumed in travelling itself. With expanding movement, the suburbanites are required to stop for longer lengths at activity intersections sitting tight for the green signs bringing about loss of time and fuel. To check this issue, this paper proposes a brilliant activity control framework which powerfully changes the signs continuously by breaking down and looking at the movement at different intersections. The proposed methodology utilizes Hadoop to

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C, Bharanidharan, Jeevan Chandra, Hitesh Kumar, Jayasurya s, and Stella A. "GLOBAL IMAGE IDENTIFIER." International Research Journal of Computer Science 9, no. 8 (2022): 195–200. http://dx.doi.org/10.26562/irjcs.2022.v0908.08.

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Many of the things, signs, and symbols we encounter when exploring the world might not be familiar to us. A global image identifier must be created to minimize confusion and misunderstanding. We shall use the less-than-universal traffic signs as an example. Road signs are strategically positioned to safeguard drivers’ and tourists' safety. Additionally, they offer instructions on when and where cars should turn or not turn. The traffic signs on the road express several cautions. In India, there are 400 traffic accidents per day, according to official statistics. Road signs ensure the safety of

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Gaurav Singh and Prof. Sonam Singh. "Traffic Object Detection and Recognition Systems." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 4 (2024): 81–86. http://dx.doi.org/10.32628/cseit24104110.

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You are already known about automatic vehicles in which the car can control itself. Cars must clearly understand and recognize all traffic signals. Many organizations named Uber, Google, Tesla, Toyota, Mercedes-Benz, Ford, Audi and others are getting involved on this technology to enhance their experience by adding features like autonomous driving and putting efforts in maximum innovation in this field. As a result, if we want to work with this technology accurately it depends on how the vehicle can distinguish between different signs such as no entry, height limit, turning signs, school signs

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Snehal Chaudhary, Et al. "Use of Convolutional Neural Network and SVM Classifiers for Traffic Signals Detection." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 490–93. http://dx.doi.org/10.17762/ijritcc.v11i9.8834.

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Road signals are crucial for preserving a safe and effective flow of traffic. They give directions to cars, warn them of potential dangers, and notify them of the conditions of the road ahead. Road signs make roadways safer for both vehicles and pedestrians by regulating traffic and reducing accidents. Failure to obey traffic signals can be harmful and result in collisions. Drivers must always be conscious of their surroundings and pay attention to traffic signs. If a driver misses a signal, they should proceed with caution and safety to prevent injuring themselves or others, and they should s

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Cui, Naizhong. "Optimization Strategies for Traffic Signal and Identification Design." Frontiers in Science and Engineering 5, no. 2 (2025): 92–98. https://doi.org/10.54691/nvmq1d61.

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This article deeply studies how to improve the effectiveness of traffic signal and roadway signage design, pointing out some shortcomings in current design, including the lack of rationality in signal configuration, low recognition, and ineffective coordination with the surrounding road environment. In response to these issues, scientific layout and planning of traffic signals, enhancing the recognizability of signals and signs, improving the compatibility between signals and roads, and promoting the development and application of intelligent traffic signal systems have been proposed. Intended

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Gore, Shubham, Manan Bhasin, and Suchitra S. "Traffic Sign Detection using Yolo v5." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 2679–83. http://dx.doi.org/10.22214/ijraset.2023.51591.

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Abstract: One of the crucial areas of research in the field of advanced driver assistance systems (ADAS) is the detection and recognition of traffic signals in a real-time environment. These are specifically developed to work in real-time to improve road safety by informing the driver of various traffic signals such as speed limits, priorities, restrictions, and so on. This research paper proposes a traffic sign identification system on an Indian dataset utilizing the YOLOv5 model. This study suggests a method for detecting a particular set of 10 traffic signs. You Only Look Once (YOLO) v5 is

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J, Sanjay, Sandesh Saidapur, Sanjay CR, and Shamanth Reddy. "Traffic Sign Detection using Convolutional Neural Networks." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 4269–73. http://dx.doi.org/10.22214/ijraset.2023.51261.

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Abstract: Signs on the road are crucial making sure the flow of traffic is smooth. Disregard whilst watching the traffic sign board is one of the main causes of traffic accidents. Traffic signs are essential for controlling traffic, preventing accidents, and assuring safety.No entry, speed limit, traffic lights, left or right turn, children crossing, etc. are just a few examples of various sorts of signs. The human observation of traffic control signals under the current approaches could lead to a re-entry collision of cars. The fast-moving traffic may be delayed as a result. Additionally, the

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Almusawi, Husam A., Mohammed Al-Jabali, Amro M. Khaled, Korondi Péter, and Husi Géza. "Self-Driving robotic car utilizing image processing and machine learning." IOP Conference Series: Materials Science and Engineering 1256, no. 1 (2022): 012024. http://dx.doi.org/10.1088/1757-899x/1256/1/012024.

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Abstract The major goal of this paper is to build and represent a prototype of a fully autonomous car that employs computer vision to detect lanes and traffic signs without human intervention using limited computing capacity. The project contains an embedded system represented by a Raspberry Pi 3 which serves as the image processing and machine learning unit. This method requires a stream of images as input for the computer vision using OpenCV2 library with C++ programming language along with Haar Cascade Classifier for the detection of traffic signs. The Raspberry Pi will send binary signals

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Ms.Reshma D.Vartak Koli and Dr. Avinash Sharma. "A Systematic Study Traffic Sign Detection System, Different Types of Road Traffic Sign and Various Techniques of Road Traffic Sign Recognition." International Research Journal on Advanced Engineering and Management (IRJAEM) 6, no. 07 (2024): 2457–69. http://dx.doi.org/10.47392/irjaem.2024.0354.

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By giving real-time information on road conditions and regulatory signage, traffic sign detecting systems enable autonomous driving technologies and contribute significantly to traffic flow and safety. To make choices and navigate safely, these systems depend on precise awareness of their surroundings, including traffic signs. Autonomous vehicles can perceive and react to road conditions more effectively by recognizing and understanding traffic signs, which eventually results in safer and more effective transportation. When stop signs or traffic signals are about to appear, when a vehicle is a

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Sreenivas, Dr M. "Traffic Sign Recognition Using CNN." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 3522–34. http://dx.doi.org/10.22214/ijraset.2022.44532.

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Abstract: You've probably heard about self-driving automobiles, in which the passenger can completely rely on the vehicle for transportation. Cars must, however, understand and follow all traffic rules in order to achieve level 5 autonomy. Many researchers and large organisations, including as Tesla, Uber, Google, Mercedes-Benz, Toyota, Ford, Audi, and others, are working on autonomous vehicles and self-driving automobiles in the world of artificial intelligence and technological innovation. As a result, in order for this technology to be accurate, the vehicles must be able to understand traff

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Xiong, Jun Yu, Xiao Hui Du, Jia Qi Wang, and Hui Li Zhai. "A Optimized Design of One Traffic Circle." Advanced Materials Research 588-589 (November 2012): 1632–35. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1632.

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In this paper we use queuing theory to analysis the incoming traffic, developed an effective way to control the traffic of a circle by using stop signs and yield signs,and calculated the traffic capacity and average waiting time of this method. Then, we use signals to control the traffic and improve the original method by a analysis the ways the car can pass through the circle crossing. Taking into account of the traffic flow in the different time of a day, we got the light's signal period to adapt to the features of the traffic flow.

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Satpute, Ms Bhumika Vasant, Ms Dhanlaxmi Balavant Don, Ms Rakhi Ajaykumar Salave, Ms Abrar Zameer Shaikh, and Prof Akash K. Gunjal. "Intelligent Transportation System." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 4560–69. http://dx.doi.org/10.22214/ijraset.2022.43354.

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Abstract: People have experienced frequent communication and information exchange in recent years as a result of the proliferation of mobile devices. For example, when people go on vacations, it is common for each person to bring a smart phone with them to get information about nearby attractions. When a user visits a location, the application will provide useful information based on the user's current location preferences and previous visits to locations and their traffic signs. This new feature of map will learn your preferences and will display traffic signs in the area this system would di

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Neelima, Vaka, Cherukuri Nayomi, Arla Prasanna Kumari, Munnangi Ravi Teja, Mr K. Sivakrishna, and Dr M. Sreenivasulu. "Traffic Signs Recognization using Machine Learning." International Journal of Innovative Research in Engineering and Management 9, no. 2 (2022): 665–60. http://dx.doi.org/10.55524/ijirem.2022.9.2.105.

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The expansive road network in India is responsible for the movement of the vast majority of the country's products as well as its population. Intelligent transit systems are one example of the cutting-edge technology that has been developed and implemented over the course of the past three decades to enhance the safety of public transportation and reduce emissions. Other examples of this cutting-edge technology include autonomous vehicles and magnetic levitation. (ITS). In spite of the difficulties, there is still a sizeable scholarly community that is interested in researching methods that ar

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Wani, Gulzar Ahmad, and Dr Gurinder Kaur Sodhi. "Implementation of Bootstrap Technique in Detection of Road Sign using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 2299–304. http://dx.doi.org/10.22214/ijraset.2022.48460.

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Abstract: Traffic sign recognition is a driver assistance tool that can alert and warn the driver by showing any applicable limitations on the current stretch of road. Such limitations include signs such as 'traffic light approaching' or 'walking crossing.' The present research focuses on identifying Indian road and traffic signs in real time. Real-time footage from a moving automobile is captured by a computerized camera, and genuine traffic signs are retrieved using vision data. The network is divided into three stages: one for identification and the other for classification. The first stage

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Alawaji, Khaldaa, Ramdane Hedjar, and Mansour Zuair. "Traffic Sign Recognition Using Multi-Task Deep Learning for Self-Driving Vehicles." Sensors 24, no. 11 (2024): 3282. http://dx.doi.org/10.3390/s24113282.

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Over the coming years, the advancement of driverless transport systems for people and goods that are designed to be used on fixed routes will revolutionize the transportation system. Therefore, for a safe transportation system, detecting and recognizing traffic signals based on computer vision has become increasingly important. Deep learning approaches, particularly convolutional neural networks, have shown exceptional performance in various computer vision applications. The goal of this research is to precisely detect and recognize traffic signs that are present on the streets using computer

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Mohammed, Mohammed. "Golden Jackal Optimization with Neutrosophic Rule-Based Classification System for Enhanced Traffic Sign Detection." International Journal of Neutrosophic Science 23, no. 4 (2024): 29–40. http://dx.doi.org/10.54216/ijns.230403.

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Traffic signs detection is a critical function of automatic driving and assisted driving is a significant part of Cooperative Intelligent Transport Systems (CITS). The drivers can obtain the data attained via automated traffic sign detection to improve the comfort and security of motor vehicle driving and regulate the behaviors of drivers. Recently, deep learning (DL) has been utilized in the fields of traffic sign detection and achieve better results. But there are two major problems in traffic sign recognition to be immediately resolved. Some false sign is always detected due to the interfer

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Ford, Garry L., and Dale L. Picha. "Teenage Drivers’ Understanding of Traffic Control Devices." Transportation Research Record: Journal of the Transportation Research Board 1708, no. 1 (2000): 1–11. http://dx.doi.org/10.3141/1708-01.

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Teenage drivers are involved in traffic crashes more often than any other driver group, and their fundamental knowledge of traffic control devices and rules of the road is extremely important in safe driving. Only limited data exist, however, on teenage drivers’ understanding of traffic control devices, and little research has been done on determining their comprehension thereof. Research was performed to document teenage drivers’ ability to understand 53 traffic control devices. These traffic control devices included 6 combinations of sign shape and color; 8 regulatory signs; 14 warning signs

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Dang, Xiaochao, Wenze Ke, Zhanjun Hao, Peng Jin, Han Deng, and Ying Sheng. "mm-TPG: Traffic Policemen Gesture Recognition Based on Millimeter Wave Radar Point Cloud." Sensors 23, no. 15 (2023): 6816. http://dx.doi.org/10.3390/s23156816.

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Automatic driving technology refers to equipment such as vehicle-mounted sensors and computers that are used to navigate and control vehicles autonomously by acquiring external environmental information. To achieve automatic driving, vehicles must be able to perceive the surrounding environment and recognize and understand traffic signs, traffic signals, pedestrians, and other traffic participants, as well as accurately plan and control their path. Recognition of traffic signs and signals is an essential part of automatic driving technology, and gesture recognition is a crucial aspect of traff

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Balázs, Viktor, László Szilágyi, Antal Apagyi, and Timotei István Erdei. "The Implementation of an Opencv-Based Traffic Sign Identifier Videoanalyst Software." Műszaki Tudományos Közlemények 9, no. 1 (2018): 39–42. http://dx.doi.org/10.33894/mtk-2018.09.05.

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Abstract Nowdays, accidents tend to happen because our attention is being split up by the ever-growing influx of information, losing the focus from the driving, traffic signs, and other signals. The consequences of these minor or major accidents weight down on our shoulders. During our project, we tried to eliminate, or help this issue, using present technology, improving upon that, trying to avoid these accidents. Our task consisted on implementing a software, that could identify traffic signs from any video streams.

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Allen, R. Wade, Zareh Parseghian, and Theodore J. Rosenthal. "Simulator Evaluation of Road Signs and Signals." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 14 (1994): 903–6. http://dx.doi.org/10.1177/154193129403801423.

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This paper describes a accuracy versus speed paradigm for evaluating signing and traffic signal conditions using low cost simulation technology. Two research examples are reviewed. One study involved the use of an interactive driving simulator that included the presentation of high resolution signs over the apparent viewing range from 500 to 50 feet. Drivers had to control vehicle speed and lane position while identifying the meaning of symbol signs as rapidly as possible. Subjects were scored in terms of correctness and the distance at which signs were identified. A second study involved a co

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Lee, Suzanne E., Sarah B. Brown, Miguel A. Perez, Zachary R. Doerzaph, and Vicki L. Neale. "Normal and Hard Braking Behavior at Stop Signs and Traffic Signals." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 22 (2005): 1897–901. http://dx.doi.org/10.1177/154193120504902203.

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A testbed intersection violation warning system was developed to address the problem of intersection crashes. The effectiveness of such systems is fundamentally dependent on the driver-braking model used to decide if a warning should be issued to the driver. If the model is unrealistic, drivers can either be annoyed due to assumed braking levels that are too low, or can be warned too late if braking expectations are too high. Initial algorithm development relied on data from the Collision Avoidance Metrics Partnership (CAMP) Forward Collision Warning (FCW) project. However, it was unknown whet

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Kharchenko, I. K., I. G. Borovskoy, and E. А. Shelmina. "Modular Architecture of Advanced Driver Assistance Systems for Effective Traffic Sign Recognition." Vestnik NSU. Series: Information Technologies 21, no. 3 (2023): 56–71. http://dx.doi.org/10.25205/1818-7900-2023-21-3-56-71.

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Analysis of modern approaches to the implementation of driver assistance systems, as well as the implementation of the architecture of the driver assistance system, aimed at recognizing traffic signs at the maximum distance from it under difficult weather conditions, for early feedback to the driver. The paper considers the main signals used in the implementation and operation of the driver assistance system: data from the car's CAN bus, information from a GPS receiver, video fragments from a digital camera. The presented modular architecture uses the listed data sources for estimating the tra

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Lengyel, Henrietta, and Zsolt Szalay. "Classification of traffic signal system anomalies for environment tests of autonomous vehicles." Production Engineering Archives 19, no. 19 (2018): 43–47. http://dx.doi.org/10.30657/pea.2018.19.09.

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Abstract In the future there will be a lot of changes and development concerning autonomous transport that will affect all participants of transport. There are still difficulties in organizing transport, but with the introduction of autonomous vehicles more challenges can be expected. Recognizing and tracking horizontal and vertical signs can cause a difficulties for drivers and, later, for autonomous systems. Environmental conditions, deformity and quality affect the perception of signals. The correct recognition results in safe travelling for everyone on the roads. Traffic signs are designed

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Saadi Abdullah, Ahmed, Majida Ali Abed, and Ahmed Naser Ismael. "Traffic signs recognitionusing cuckoo search algorithm and Curvelettransform with image processing methods." Journal of Al-Qadisiyah for computer science and mathematics 11, no. 2 (2019): 74–81. http://dx.doi.org/10.29304/jqcm.2019.11.2.591.

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Compliance with traffic signs is one of the most important things to follow to avoid traffic accidents as well as compliance with traffic rules in terms of parking, speed control, and other traffic sings. Progress in different areas, such as self-propelled car manufacturing or the production of devices that help the visually impaired, require values to find a way to determine traffic signals with high precision in this research, The first step is to take a picture of the traffic sign and apply some digital image processing techniques to increase image contrast and eliminate noise in the image,

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Joseph, Sheemona C., Ganesh S., Kannadhasan Suriyan, and Selvi Priya K. "Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning." Journal of Informatics and Web Engineering 4, no. 2 (2025): 225–35. https://doi.org/10.33093/jiwe.2025.4.2.14.

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Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial task for autonomous vehicles (AVs) and advanced driver assistance systems (ADAS). These technologies' ability to accurately recognize traffic signs enables them to make informed decisions in real time, thereby elevating the standard for overall driving safety. The study uses a large, annotated dataset of images of traffic signs to train and assess the CNN mode

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Koh, Dong-Woo, Jin-Kook Kwon, and Sang-Goog Lee. "Traffic Sign Recognition Evaluation for Senior Adults Using EEG Signals." Sensors 21, no. 13 (2021): 4607. http://dx.doi.org/10.3390/s21134607.

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Elderly people are not likely to recognize road signs due to low cognitive ability and presbyopia. In our study, three shapes of traffic symbols (circles, squares, and triangles) which are most commonly used in road driving were used to evaluate the elderly drivers’ recognition. When traffic signs are randomly shown in HUD (head-up display), subjects compare them with the symbol displayed outside of the vehicle. In this test, we conducted a Go/Nogo test and determined the differences in ERP (event-related potential) data between correct and incorrect answers of EEG signals. As a result, the wr

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Jain, Vaibhav, Tanay ., Saransh Gangele, and K. Kalimuthu. "Driver Assistance System using in-vehicle Traffic Lights and Signs." International Journal of Engineering & Technology 7, no. 2.24 (2018): 527. http://dx.doi.org/10.14419/ijet.v7i2.24.12151.

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In recent years, with the advancement of vehicular communication, it is possible to detect various road signs and provide traffic light information to the driver inside the vehicle with the application of heads-up display (HUD). It detects road signs, does basic classifications and accordingly directs the driver to slow down or stop the vehicle. The vehicle’s heads-up display keeps the driver focused by providing road warnings, speed limit, traffic signals and some vital navigation information in the driver’s line of sight(LOS). This system has 4 phases, Image recognition, wireless communicati

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Paavani, R. Krishna, V. Indraja, V. Neelimajyothi, S. Sai, and Mr M. Sriramulu. "Traffic Sign Board Detection Using Single Shot Detection (SSD)." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 4095–97. http://dx.doi.org/10.22214/ijraset.2022.43336.

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Abstract: Traffic sign board detection (TSBD) is a significant portion of intelligent transportation system (ITS). Being able to identify traffic signals more accurately and effectively can improve safe driving .Due to increase in technology there are autonomous vehicles . The traffic sign recognition process includes two parts: detection and classification. In this paper, we use an object detection algorithm called SSD to detect the traffic signs. This convolutional neural network uses multiple feature maps to detect objects. For the traffic sign is very small to the whole picture, the SSD mo

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Chowdhury, Abdullahi, Gour Karmakar, Joarder Kamruzzaman, Rajkumar Das, and S. H. Shah Newaz. "An Evidence Theoretic Approach for Traffic Signal Intrusion Detection." Sensors 23, no. 10 (2023): 4646. http://dx.doi.org/10.3390/s23104646.

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The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can only detect intrusions created by spoofed vehicles. However, these approaches fail to detect intrusion from attacks on in-road sensors, traffic controllers, and signals. In this paper, we proposed an IDS based on detecting anomalies associated with flow rate, phase time, and vehicle speed, which is a significant extension of our previous work using addition

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Domínguez, Hugo, Alberto Morcillo, Mario Soilán, and Diego González-Aguilera. "Automatic Recognition and Geolocation of Vertical Traffic Signs Based on Artificial Intelligence Using a Low-Cost Mapping Mobile System." Infrastructures 7, no. 10 (2022): 133. http://dx.doi.org/10.3390/infrastructures7100133.

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Road maintenance is a key aspect of road safety and resilience. Traffic signs are an important asset of the road network, providing information that enhances safety and driver awareness. This paper presents a method for the recognition and geolocation of vertical traffic signs based on artificial intelligence and the use of a low-cost mobile mapping system. The approach developed includes three steps: First, traffic signals are detected and recognized from imagery using a deep learning architecture with YOLOV3 and ResNet-152. Next, LiDAR point clouds are used to provide metric capabilities and

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A, Jayaprakash, and C. Kezi Selva Vijila. "Detection and Recognition of Traffic Sign using FCM with SVM." JOURNAL OF ADVANCES IN CHEMISTRY 13, no. 6 (2017): 6285–89. http://dx.doi.org/10.24297/jac.v13i6.5773.

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This paper mainly focuses on Traffic Sign and board Detection systems that have been placed on roads and highway. This system aims to deal with real-time traffic sign and traffic board recognition, i.e. localizing what type of traffic sign and traffic board are appears in which area of an input image at a fast processing time. Our detection module is based on proposed extraction and classification of traffic signs built upon a color probability model using HAAR feature Extraction and color Histogram of Orientated Gradients (HOG).HOG technique is used to convert original image into gray color t

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Mitroshin, Dmitriy V. "On the Improvement of the International Statutory Regulation in Road Traffic." Administrative law and procedure 2 (February 11, 2021): 25–28. http://dx.doi.org/10.18572/2071-1166-2021-2-25-28.

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The article describes the role of the Russian Federation in the development of an international legal framework for road traffic, and its implementation at the global and regional levels. The content of the amendments implemented in the relevant basic international legal acts — the 1968 Conventions on Road Traffic and on Road Signs and Signals was specified. An assessment is given to the contribution of LL.D, Professor Alexander Yuryevich Yakimov to this activity.

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Pavani, Korada Bala. "Traffic Sign Detection and Recognition System using CNN." International Journal for Research in Applied Science and Engineering Technology 12, no. 8 (2024): 213–19. http://dx.doi.org/10.22214/ijraset.2024.63889.

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Abstract: Traffic signs play a crucial role in providing drivers with critical information. Therefore, motorists must possess the ability to read and understand traffic signals in order to drive safely. There has been a lot of research on traffic sign detection during the past many decades. There is a severe lack of real-time and precise detections in the present state of the art of traffic sign detection, which is preventing it from being really useful. This study details an approach to traffic sign recognition that operates in real-time and provides drivers with voice assistance. This system

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Venkatramulu, S., Bairy Yugasri, Triveni Mohan Sadala, Garidepalli Revathi, and V. Chandra Shekhar Rao. "Violation of Traffic Rules and Detection of Sign Boards." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8s (2023): 249–55. http://dx.doi.org/10.17762/ijritcc.v11i8s.7204.

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Today's society has seen a sharp rise in the number of accidents caused by drivers failing to pay attention to traffic signals and regulations. Road accidents are increasing daily as the number of automobiles rises. By using synthesis data for training, which are produced from photos of road traffic signs, we are able to overcome the challenges of traffic sign identification and decrease violations of traffic laws by identifying triple-riding, no-helmet, and accidents, which vary for different nations and locations. This technique is used to create a database of synthetic images that may be us

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Et. al., Nikhil S. Rajguru,. "Implementation paper of Traffic Signal Detection and Recognition using deep learning." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 1S (2021): 212–19. http://dx.doi.org/10.17762/turcomat.v12i1s.1760.

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Traffic boards and traffic signals are used to maintain proper traffic through busy roads. They help to recognize the rules to follow when driving the vehicle. These signs warn the distracted driver, and prevent his/her actions which could lead to an accident. We have proposed a system which can help recognize these boards and signals at real time thus avoiding major mishap. A real-time automatic sign detection and recognition can help the driver, significantly increasing his/her safety. Lately traffic sign recognition has got an immense interest lately by large scale companies such as Google,

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Balado, Jesús, Elena González, Pedro Arias, and David Castro. "Novel Approach to Automatic Traffic Sign Inventory Based on Mobile Mapping System Data and Deep Learning." Remote Sensing 12, no. 3 (2020): 442. http://dx.doi.org/10.3390/rs12030442.

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Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the one hand, images are faster to process and artificial intelligence techniques, specifically Convolutional Neural Networks, are more optimized than in point clouds. On the other hand, point clouds allow a more exact positioning than the exclusive use of image

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Hashim, Rabia, Ravinder Pal Singh, and Monika Mehra. "Road Sign Detection System using Neural Networks and Tensor Flow." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (2022): 548–56. http://dx.doi.org/10.22214/ijraset.2022.40672.

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Abstract: Automated tasks have simplified almost everything we perform in today's environment. Due to a desire to focus only on driving, drivers regularly ignore signs placed on the side of the road, which can be harmful to themselves and others. To address this issue, the motorist should be informed in a method that does not require them to divert their concentration. Traffic Sign Detection and Recognition (TSDR) is critical in this case since it alerts the motorist of approaching signals. Not only are roads safer because of this, but motorists also feel more at ease when driving unfamiliar o

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Kozłowska, Małgorzata Klaudia. "Consistency and certainty of the road marking system as a subject of protection based on the offence law. Analysis of the characteristics of the offence from article 85 § 1 of offence code." Transportation Overview - Przeglad Komunikacyjny 2017, no. 1 (2017): 17–23. http://dx.doi.org/10.35117/a_eng_17_01_03.

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Nowadays when the road infrastructure rapidly expands as well as the traffic, the correct road markings are of a vital importance in ensuring safety and efficiency of this traffic. Negligible number of road incidents caused by incorrect road markings results in treating quality and certainty of those markings as being of less importance. Thus, such an important issue is to ensure effective, criminal law protection of the legal interests which is a stable and reliable system of road markings. Polish legislator adopted as a subject of individual protection on the basis of code of offence inviola

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Sarebni, Ahmad Viky Furqon, Bagus Hario Setiadji, and Alfa Narendra. "Accident Analysis on the Arteri Yos Sudarso street." Eduvest - Journal of Universal Studies 5, no. 5 (2025): 5013–22. https://doi.org/10.59188/eduvest.v5i5.50082.

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The Yos Sudarso arterial road, a critical ring road connecting industrial zones and ports in Central Java, experiences high accident rates (averaging 6 accidents/month from 2019 to 2022). Despite its economic significance, inadequate traffic signage and complex topography contribute to recurring accidents, necessitating a targeted safety analysis. This study investigates (1) the correlation between road complementary devices (e.g., traffic signs) and accident rates, and (2) the relationship between traffic volume and accident frequency, with a focus on high-risk vehicle groups. Field surveys a

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Özarpa, C., İ. Avcı, B. F. Kınacı, S. Arapoğlu, and S. A. Kara. "CYBER ATTACKS ON SCADA BASED TRAFFIC LIGHT CONTROL SYSTEMS IN THE SMART CITIES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W5-2021 (December 23, 2021): 411–15. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w5-2021-411-2021.

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Abstract. There are regular developments and changes in cities. Developments in cities have affected transportation, and traffic control tools have changed. Traffic signs and traffic lights have been used to direct pedestrians and vehicles correctly. Traffic light control systems are used to ensure the safety of vehicles and pedestrians, increase the fluency in traffic, guide them in transportation, warn pedestrians and drivers, and regulate and control transportation disruptions. In order to facilitate people's lives, it is desired to control the traffic components autonomously with the devel

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Long, Richard G., David A. Guth, Daniel H. Ashmead, Robert Wall Emerson, and Paul E. Ponchillia. "Modern Roundabouts: Access by Pedestrians who are Blind." Journal of Visual Impairment & Blindness 99, no. 10 (2005): 611–21. http://dx.doi.org/10.1177/0145482x0509901005.

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This article describes the key differences between roundabouts and traditional intersections that have traffic signals or stop signs and discusses how these differences may affect the mobility of pedestrians who are visually impaired. It also provides a brief summary of the authors’ research on this topic and suggests strategies for addressing the access issues that roundabouts sometimes create.

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Kim, Eunjee, Hyorim Kim, Yujin Kwon, and Gwanseob Shin. "Visibility of an in-ground signal when texting while walking." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1933–37. http://dx.doi.org/10.1177/1071181320641466.

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An increase in pedestrian accidents associated with smartphone use has been one of the main issues in road traffic safety research and administration. Recently, traffic lights and safety signs embedded in the ground have been introduced, but without sufficient scientific consideration. A laboratory experiment evaluated the visibility of an in-ground signal while varying its contrast and position. Twenty-three participants performed a signal detection task when conducting texting while walking on a treadmill. The signals were displayed randomly onto the ground one at a time at three different p

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Poku, Samuel, Delia Bandoh, Ernest Kenu, Emma Kploanyi, and Adolphina Addo- Lartey. "Factors contributing to road crashes among commercial vehicle drivers in the Kintampo North Municipality, Ghana in 2017." Ghana Medical Journal 54, no. 3 (2020): 132–39. http://dx.doi.org/10.4314/gmj.v54i3.2.

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Objective: The study assessed driver, vehicular and road-related factors associated with road crashes (RC) in the Kintampo North Municipality.Design: Cross-sectional studySetting: Kintampo North MunicipalityData source: Demographics, vehicular and road usage information on registered drivers at Ghana Private Road and Transport Union (GPRTU) and Progressive Transport Owners Association (PROTOA) in Kintampo North MunicipalityMain outcome: involvement in road crashes and related factorsResult: A total of 227 drivers were approached for this study. None of them declined participation. They were al

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Umid Ruzmatovich, Tajimuratov, Adilov Shukhrat Kayumovich, Tajimuratov Ruzmat Otajanovich, Tajimuratov Abdusami, and Umid Ugli. "A MODERN SOLUTION THAT HAS A POSITIVE IMPACT ON LOGISTICS SERVICES AND SIGNIFICANTLY REDUCES INTERSECTION FATALITIES." Journal Scientific and Applied Research 25, no. 1 (2023): 59–69. http://dx.doi.org/10.46687/jsar.v25i1.380.

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Year after year, the problems on the world's roads are getting worse. According to the UN Economic Commission for Europe (ECE) 2006 Report on the 1968 Geneva Convention "Road Signs and Signals", the rules are periodically updated to take into account the growing demands for human safety, environmental protection, and the rapid development of technological progress around the world (Report IEC UN, New York and Geneva, 2007). Unfortunately, for about a hundred years now, no drastic measures have been taken against the causes of road traffic accidents around the world. Our research is focused on

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Palande, Prapti. "StreetX: A Traffic Sign Detection System." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 3180–84. https://doi.org/10.22214/ijraset.2025.68043.

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Traffic sign recognition is a vital component of intelligent transport systems that enables automated vehicles and driver assistance systems to comprehend and respond properly to traffic signals. The current research introduces a real-time traffic sign recognition system developed through the integration of a machine learning algorithm with an Arduino-based system. The system implements convolutional neural networks for detection and recognition with high accuracy and varied lighting conditions, thereby keeping accuracy high regardless of the situation. The model is trained from a large corpus

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Azzam, Diya Mahmoud, and Craig C. Menzemer. "Numerical Study of Stiffened Socket Connections for Highway Signs, Traffic Signals, and Luminaire Structures." Journal of Structural Engineering 134, no. 2 (2008): 173–80. http://dx.doi.org/10.1061/(asce)0733-9445(2008)134:2(173).

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Kurmanova, A. "Frequency of Injuries and Deaths Due to Traffic Accidents Caused by the Driver, Bishkek." Bulletin of Science and Practice 10, no. 8 (2024): 212–19. http://dx.doi.org/10.33619/2414-2948/105/25.

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Road traffic injuries due to the severity of their adverse consequences are one of the priority health problems both in the Kyrgyz Republic and around the world. In Bishkek, the most common causes of traffic accidents caused by the driver were violations of the rules of maneuvering, violation of the rules for the passage of a pedestrian, crossing, non-observance of the rules of priority of travel, road signs, signals, speeding, driving into the oncoming lane, double overtaking, driving while intoxicated, non-observance of distance. However, it should be taken into account that for reasons such

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Jiang, Wei. "A traffic and road signal recognition method through deep learning." Applied and Computational Engineering 76, no. 1 (2024): 280–87. http://dx.doi.org/10.54254/2755-2721/76/20240617.

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Before deep learning became popular, some researchers used traditional computer vision algorithms, including support vector machines, decision trees, and random forests to deal with traffic and road signal recognition problems. These methods often require manual design of features and may not perform well when dealing with complex scenarios and changing conditions. Therefore, traffic and road signal recognition have witnessed a transformative shift with the advent of deep learning technologies. Convolutional neural networks (CNNs) developed from deep learning has shown prominent capabilities i

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