Smart Traffic Light Research Articles

Smart traffic lights for people with visual impairments: A literature overview and a proposed implementation

Attempting to establish aids for individuals who are visually impaired has urged many cities to seek solutions for improving their quality of life. Namely, cities have installed sound-emitting devices into traffic lights as well as sidewalks that assist their navigation. Moreover, as cities are always striving to move forward and achieve innovations concerning navigation for disabled individuals, smart traffic lights, capable of synchronizing in real-time according to traffic and individual mobility conditions, are already being installed around the world. This is in line with the adoption of the smart city concept, which involves a set of methodologies and indicators that regulate how cities perform regarding the promotion of citizens’ quality of life. Another important principle is the techno-economic aspect indicating the need for low-cost careful planning to produce cost-efficient solutions, while additional important issues are maintenance, power efficiency, and the means to coordinate numerous devices to facilitate operation in a timely and reliable manner. In this article, we present an overview of the existing solutions for the navigation of people who are blind and visually impaired along with a requirement analysis performed on the feedback received from interviews with members of the Lighthouse for the Blind of Greece both of which lead to the proposal of a new implementation that pushes the state of the art.

Cycling Infrastructure for All EPACs Included?

A modal shift to electric pedal-assisted cycles (EPACs) can help with reaching the transport emission goals of the European Green Deal. With the rising sales of EPACs in Europe, a lack of appropriate (electric) cycling infrastructure remains a major barrier for many potential users. This paper discusses the results of a survey about the requirements of (potential) cyclists to design a better cycling infrastructure. The differences in requirements for non-cyclists vs. cyclists and electric cyclists vs. conventional cyclists are discussed using statistical analysis. The key findings are that cyclists and non-cyclists both require wide quality cycling infrastructure with safe crossing points, secure bicycle parking and smart traffic lights. Non-cyclists’ requirements significantly differ from cyclists’ on 12 items, of which rain cover while cycling and parking spots for the car are the most noteworthy. There is (but) one significant difference between the requirements of EPAC users and conventional cyclists: the need for charging points for EPACs along the cycle route.

Pedestrian Traffic Light Control with Crosswalk FMCW Radar and Group Tracking Algorithm.

The increased mobility requirements of modern lifestyles put more stress on existing traffic infrastructure, which causes reduced traffic flow, especially in peak traffic hours. This calls for new and advanced solutions in traffic flow regulation and management. One approach towards optimisation is a transition from static to dynamic traffic light intervals, especially in spots where pedestrian crossing cause stops in road traffic flow. In this paper, we propose a smart pedestrian traffic light triggering mechanism that uses a Frequency-modulated continuous-wave (FMCW) radar for pedestrian detection. Compared to, for example, camera-surveillance systems, radars have advantages in the ability to reliably detect pedestrians in low-visibility conditions and in maintaining privacy. Objects within a radar’s detection range are represented in a point cloud structure, in which pedestrians form clusters where they lose all identifiable features. Pedestrian detection and tracking are completed with a group tracking (GTRACK) algorithm that we modified to run on an external processor and not integrated into the used FMCW radar itself. The proposed prototype has been tested in multiple scenarios, where we focused on removing the call button from a conventional pedestrian traffic light. The prototype responded correctly in practically all cases by triggering the change in traffic signalization only when pedestrians were standing in the pavement area directly in front of the zebra crossing.

Traffic Flow Prediction for Smart Traffic Lights Using Machine Learning Algorithms

Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces more pollution, noise and stress for citizens. Neural networks (NN) and machine-learning (ML) approaches are increasingly used to solve real-world problems, overcoming analytical and statistical methods, due to their ability to deal with dynamic behavior over time and with a large number of parameters in massive data. In this paper, machine-learning (ML) and deep-learning (DL) algorithms are proposed for predicting traffic flow at an intersection, thus laying the groundwork for adaptive traffic control, either by remote control of traffic lights or by applying an algorithm that adjusts the timing according to the predicted flow. Therefore, this work only focuses on traffic flow prediction. Two public datasets are used to train, validate and test the proposed ML and DL models. The first one contains the number of vehicles sampled every five minutes at six intersections for 56 days using different sensors. For this research, four of the six intersections are used to train the ML and DL models. The Multilayer Perceptron Neural Network (MLP-NN) obtained better results (R-Squared and EV score of 0.93) and took less training time, followed closely by Gradient Boosting then Recurrent Neural Networks (RNNs), with good metrics results but the longer training time, and finally Random Forest, Linear Regression and Stochastic Gradient. All ML and DL algorithms scored good performance metrics, indicating that they are feasible for implementation on smart traffic light controllers.

Dual-lanthanide urea metal-organic framework based fluorescent traffic light microsensor for solvent decoding and visual trace water assay

A rapid and sensitive sensor for organic solvent decoding and water assay is crucial for human health and chemical industry. Herein, a dual-lanthanide metal-organic framework (Ln-MOF) Eu0.2Tb0.8-UL (UL: urea-containing ligand) was fabricated for 3-dimensional solvent decoding and ratiometric on-off water assay in organic solvents. According to innovative multiple response mechanisms including ligand protonation and -OH oscillation, the energy transfer of ligand to Ln3+ and Tb3+ to Eu3+ is precisely regulated by water content. Ultra-low limit of detection (0.004% v/v), broad response range (0–100%) and high-efficacy fluorescence color changing from red to green are achieved. A one-to-two logic device with single input (water content) and dual outputs (Eu3+ and Tb3+ emissions) was designed for the facile intelligent water detection, which is realized by 3 output results: YES (1, 0), PASS (0, 0) and NOT (0, 1), just like a smart traffic light sensor (red-yellow-green). The MOF-loaded paper microsensor was constructed for real-time and sensitive detection of trace water in organic solvents, coupled with a smartphone-assisted visual portable device. To our knowledge, this is the first case of Ln-MOF-based 3-dimensional solvent decoder, and traffic light-like logic analytical device and paper microsensor for real-time visual water assay in organic solvents.

A review on piezoelectric energy for smart street and traffic lights

There’s a need to look for alternate sources of energy due to increasing population. The utilization of energy from the vibrations created by the vehicles and the activity by people is relevant for the energy deficient countries. This review incorporates various research papers that deal with piezoelectric materials to generate energy. Along with different techniques to increase energy efficiency, papers dealing with integration of piezoelectric sensors with smart street and traffic lights have also been reviewed. However, the authors believe that with further research into piezoelectric material, a model can be proposed which is both time and energy efficient.

Cooperative Navigation Strategy for Connected Autonomous Vehicle Operating at Smart Intersection

This paper focuses on the cooperative navigation strategy for connected autonomous vehicles operating at smart intersections. The goal of this work is a cooperative navigation system to achieve cooperative collision avoidance for enhancing the safety and capacity of the intersection. This work considers cooperative connected autonomous vehicles operating simultaneously with non-cooperative autonomous vehicles. This work uses beyond visual range scenarios to reduce the vulnerable situations. Beyond visual range, information is implemented by using the data from the roadside units, autonomous intersection management system, smart traffic lights, and onboard units. The efficacy of this work is validated in MATLAB/Simulink environment. The simulation results show the separation time within the set upper and lower bounds. That ensures that the ego vehicle does not collide with others at the intersection. The cooperative collision avoidance algorithm guides the ego vehicle as soon as the ego vehicle comes in the range of the intersection service area, which increases the safety and capacity of the intersection. This strategy is comfortably used for both an unsignalized and signalized intersection. In an unsignalized intersection scenario, the ego vehicle uses an onboard unit. In signalized intersection scenario, the ego vehicle uses a roadside unit, onboard unit, autonomous intersection management system, and smart traffic lights. As no such framework is found in the literature. The proposed framework is the near-future requirement where the connected autonomous vehicle utilizes the information from smart infrastructure devices.

Security Concerns for 5G/6G Mobile Network Technology and Quantum Communication

5G is the new generation of mobile communication that is taking over the 3G and 4G generations. As our generation has expanded and continues to work faster and more adapt to the electronics of today, we are faced with the ever-improving technologies to keep us moving forward. 5G has the possibility of faster upload and download speeds. The possibility of more and improved smart products to advance our lives, from autonomous cars, smart traffic lights, improved city Wi-Fi availability, and gaming improvements with no lag time, just to name a few. It is expected that 5G/6G will make it wide open for new frequency ranges which will result in many connections and huge data transfer maintaining high network efficiency. With 6G on the horizon, Quantum Computing and networking are playing a key role. We anticipate that Quantum Information Technologies will enable and support future 6G systems in both communication and computing. Quantum computing networks boast a few potential security and performance advantages compared to incumbent network technology. The security and energy efficiency of quantum networks is superior to present solutions because quantum networks can theoretically work with single photons whose quantum states remain undisclosed in transmission from origin to destination. Quantum computing networks and associated technology may begin to be implemented in 5G networks and could become fully implemented with the advent of 6G networking technology. In this work, we are focusing on the security risks that can be involved with the new 5G and their proposed solutions. We will study the role of Quantum Key Distribution as leverage to improve 6G security.

Multiagent Meta-level Control for Adaptive Traffic Systems: A Case Study

As cities across the globe continue to grow, traffic congestion has become globally ubiquitous with great economic and environmental costs associated with it. The increasing prevalence of self-driving vehicles creates an opportunity to build smart, responsive traffic infrastructure of the future. Such an infrastructure consisting of connected and autonomous vehicles and smart traffic lights would have the potential to cope with congestion, weather phenomena and accidents, while maintaining safety and ensuring privacy of information. This paper introduces an approach to address the challenge of dynamically adjusting traffic to the changes in the environment. We argue that multiagent meta-level control (MMLC) is an effective way to non-myopically determine how and when this adaptation should be done. The approach highlights the role of dynamic meta-reasoning in a platooning scenario, in which collaboration contributes to improved travel time for vehicles in the network as well as a positive environmental impact as related to fuel consumption and emissions. Specifically, for the case study described in the paper, our MMLC-based approach leads to approximately 44% decrease in travel time, 7% increase in average speed, a 32% decrease in fuel consumption and a 35% drop in emissions. We also see performance advantages for a scaled-up mixed traffic simulation environment.

CYBER ATTACKS ON SCADA BASED TRAFFIC LIGHT CONTROL SYSTEMS IN THE SMART CITIES

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 developments in autonomous systems. Cyber threats arise due to the active use of the internet and signals or frequencies in the use of modules that will provide communication with traffic lights, traffic signs, and vehicles, which are traffic components at the inter-sections of many roads in the control of central systems. The study is limited to smart traffic lights, which are traffic components. If we examine the cyber-attacks, we can see that Malware Attacks, Buffer Overflow Attacks, DoS attacks, and Jamming Attacks can be made. Network-Based Intrusion Detection Systems and Host-Based Intrusion Detection Systems can be used to detect and stop Malware Attacks, Buffer Overflow Attacks, DoS attacks, and Jamming Attacks. Intrusion detection systems tell us whether the data poses a threat or does not pose after the data passing through the system is examined. In this way, system protection is ensured by controlling the data traffic in the system.

Development of a system for analyzing and unloading road traffic using artificial intelligence

Every year, the growth rate of cars in Russia will continue to grow, which makes it extremely difficult to organize road traffic. To solve this problem, innovations in the automotive industry, such as smart traffic lights, are needed to more effectively regulate traffic on public roads. Therefore, an urgent issue is the development of a system for analyzing and unloading road traffic to improve the situation at intersections and subsequent automation through the introduction of artificial intelligence. The Arduino Uno was chosen as the layout for the organization of a smart traffic light.

Design and implement a smart traffic light controlled by internet of things

The rise of the population produces an increase in the number of vehicles on the road, which creates heavy traffic in the roads and that causes many issues for the citizens and traffic cops an extra two emergency instances so it’s necessary with developing technology to solve this problem. in this research, we used the Arduino UNO microcontroller board to build a new smart traffic light controller (STLC). Signal lights produce traffic congestion, and the system makes every attempt to alleviate it. In this paper, we designed a smart traffic control system by using Arduino to solve the problem of congestion at the intersection of the Dor al Moalemen in Wasit city , working to prevent traffic jam and reduce time, Using Arduino mega, ultrasonic sensor, and a camera esp32, the suggested technique analyses and manages everyday traffic at a three-line intersection. Furthermore, the suggested system achieves three-line intersection sync and implements a balance between the number of vehicles on each side and the green light. when Traffic violation the camera will capture the car number and send it to the database by using telegram.

An Agent-Based Simulation to Explore Communication in a System to Control Urban Traffic with Smart Traffic Lights

Populational growth increases the number of cars and makes the transport infrastructure increasingly saturated. The control of traffic lights by intelligent software is a promising way to solve the problem caused by this situation. This article addresses this problem that occurs in urban traffic. An agent-based simulation of an urban traffic control system is proposed. The solution is offered as intelligent traffic lights as agents to alleviate traffic congestion at a given location. Each agent controls a crossing and maintains communication with agents from other corners. Thus, they can have greater control of a larger area and identify patterns that can help them to solve congestion problems. The results of our simulated experiments point to the improvement of the urban traffic when using the proposed Multiagent System, in comparison with an approach that uses crossing agents without communication and other that implements static traffic lights.

Integrated Fog and Cloud Computing Issues and Challenges

Due to the exponential growth in the number of internet-of-things (IoT) devices like smartphones and smart traffic lights, the data generated by the devices and the service requirements are increasing. The biggest issue in accessing the cloud computing is that all processing is done on cloud resources. For cloud-based services, it is utmost required to send all data to cloud resources which leads to many issues and challenges. The important issues are large volume of data, low latency rate, low bandwidth. In order to resolve such issues, there is an essential need of a smart computing paradigm which works as a moderator between cloud computing and IoT devices to improve the performances of the services, maximizing utilization of computing resources, storage. This work presents an overview and description of fog computing in the context of cloud computing and internet of things (IoT) and also sheds light on the key differences between cloud computing and fog computing. This work also presents various issues and challenges in the context of fog computing with its various applications.

Smart Traffic Light System

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

Prototype Self-Adaptive Traffic Light Control System Using Cameras

Cambodia is a developing country with rapid development. More vehicle usage on the road increased, this leads to more traffic problems. The traditional traffic light and traffic police officer help solve the problem at a level and limited conditions. For a better improvement, the smart traffic light is a good solution that can adapt to the real-world environment. There are four cameras are used to capture and analyze the vehicle traffic to control the modes of the traffic light. This method gives the improvement over the limited time of the traditional traffic light. This smart traffic light comes with three-term mode conditions including normal mode, camera mode, and night mode.

Interaction of Adjacent Smart Traffic Lights During Traffic Jams at an Intersection

Interaction of Adjacent Smart Traffic Lights During Traffic Jams at an Intersection

DEVELOPMENT OF A SYSTEM FOR ANALYZING AND UNLOADING ROAD TRAFFIC USING ARTIFICIAL INTELLIGENCE

Every year the growth rate of cars in Russia will continue to grow, which will complicate the organization of road traffic. Therefore, innovations in the automotive industry, such as smart traffic lights, are needed to regulate traffic more efficiently.
 Purpose – development of a system for analyzing and unloading road traffic to improve the situation at intersections, automating road traffic by introducing artificial intelligence, assembling a working model of a traffic light based on Arduino.
 Method or methodology of work: the article considers a project to analyze and track and unload vehicles at an intersection.
 Results: a mock-up of a traffic light based on an Arduino UNO microcontroller was assembled and a neural network was developed for analyzing and unloading road traffic in real time in Python.
 Scope of the results: the results obtained should be applied to the most congested road sections.

Recent development of smart traffic lights

<span id="docs-internal-guid-288f4dcc-7fff-1e8c-0350-5032593b6e4f"><span>Increased traffic flow causes congestion, especially in large cities. Even though congestion is not unusual, traffic jams still result in very high economic and social losses. Several factors cause congestion, one of which is traffic lights. Therefore, a mechanism is needed so that traffic lights can intelligently and adaptively manage signal time allocation according to traffic flow conditions. A traffic light with this type of mechanism is known as a smart traffic light. Smart traffic light cycle settings can be grouped based on the traffic density, scenarios for emergency vehicles, and the interests of pedestrians. This paper analyzes the methods and technologies used in the development of smart traffic light technology from the perspective of these three situations as well as the development of smart traffic light technology in the future.</span></span>

Development of a Smart Traffic Light Control System Using IoT Technology

The development of a smart traffic light control system using IoT technology has become an essential topic in urban traffic management. This research paper focuses on the development of an IoT-based real-time traffic monitoring system for city governance. The system integrates traffic data from various sources, including cameras, sensors, and other data sources, to provide real-time traffic updates to city officials and drivers. The proposed system utilizes IoT technology to collect data from various traffic sources and processes it to determine the optimal time for traffic lights to switch between green, yellow, and red. The system uses a combination of machine learning algorithms and traffic models to predict traffic flow patterns and optimize traffic light timings. Additionally, the system can identify potential traffic accidents and send alerts to nearby emergency services. The proposed system is evaluated using simulation techniques and has shown a significant improvement in reducing traffic congestion and improving traffic flow in a simulated urban environment. Furthermore, the system provides real-time data analytics to city officials, allowing them to make informed decisions on traffic management and city planning. Overall, the development of a smart traffic light control system using IoT technology has significant potential in improving traffic management in urban areas. The proposed system can reduce traffic congestion, improve traffic flow, and enhance overall traffic safety. Therefore, it is essential to continue research and development in this area to implement the proposed system on a larger scale.