A New System for Road Traffic Optimisation Using the Virtual Traffic Light Technology

Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge.Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms,sensors and cameras.However,they also face some challenges,such as high-cost installation,operation,and maintenance issues.This paper develops a new system based on the Virtual Traffic Light(VTL)technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’travel time.Additionally,it reduces the costs of installation,maintenance and operation over various conventional traffic light systems.Consequently,the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID,priority and time of arrival.To evaluate the system,four scenarios were presented where each scenario uses a different number of vehicles consisting of three types(emergency vehicles,public buses and private vehicles),each given a different priority.The proposed system is evaluated by integrating two simulators,namely,(OMNeT++)and(SUMO),and two frameworks,namely,(VEINS)and(INET)to prepare an appropriate working environment.the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76%compared with conventional traffic lights.Further,it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%,while the average waiting time for public buses is improved by 94.81%–97.23%.On the other hand,the waiting time for private vehicles‘improved by 87.14%to 89.71%’.

Intelligent 3-Way Priority-Driven Traffic Light Control System for Emergency Vehicles

The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in instances where emergency situations occur at traffic light intersections that are consistently congested with a high volume of vehicles. This implementation of a traffic light controller system is designed with the intention of addressing this problem. The purpose of the system was to facilitate the operation of a 3-way traffic control light and provide priority to emergency vehicles using a Radio Frequency Identification (RFID) sensor and Reduced Instruction Set Computing (RISC) Architecture Based Microcontroller. This research work involved designing a system to mitigate the occurrence of accidents commonly observed at traffic light intersections, where vehicles often need to maneuver in order to make way for emergency vehicles following a designated route. The research effectively achieved the analysis, simulation and implementation of wireless communication devices for traffic light control. The implemented prototype utilizes RFID transmission, operates in conjunction with the sequential mode of traffic lights to alter the traffic light sequence accordingly and reverts the traffic lights back to their normal sequence after the emergency vehicle has passed the traffic lights.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Traffic light detection and recognition in intersections based on intelligent vehicle

To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.

Design and Analysis of Traffic Information Transmission System Based on Visible Light Communication

Visible Light Communication( VLC) based on LED is a new wireless communication technology with high response rate and good modulation characteristics in the wavelengths of 380- 780 nm. Compared with conventional methods,the waveband of VLC is harmless to human and safe to communication because of no magnetism radiation. An audio information transmission system using LED traffic lights is presented based on VLC technology. The system is consisted of transmitting terminal,receiving terminal and communication channel. Some experiments were made under real communication environment. The experimental results showed that the traffic information transmission system works steadily with good communication quality and achieves the purpose of transmitting audio information through LED traffic lights,with a data transfer rate up to 250 kbps over a distance of 5 meters.

Simulation of traffic flow with traffic light strategies via a modified cellular automaton model

Traffic flows controlled by traffic light strategies were investigated via a cellular automaton model with anticipation, which is suitable for describing urban traffic. Three kinds of strategies, i. e., synchronized, green-wave and random switching lights, were designed, simulated and compared with each other. It is shown that the green-wave strategy is only valid at lower density and there is not an effective way with the three strategies to improve the efficiency of traffic flow at high density.

A Greedy Traffic Light and Queue Aware Routing Protocol for Urban VANETs

Vehicular Ad-hoc Networks(VANETs) require reliable data dissemination for time-sensitive public safety applications. An efficient routing protocol plays a vital role to achieve satisfactory network performance. It is well known that routing is a challenging problem in VANETs due to the fast-changing network typology caused by high mobility at both ends of transmission. Moreover, under urban environment, there are two non-negligible factors in routing protocol design, the non-uniform vehicle distribution caused by traffic lights, and the network congestion due to high traffic demand in rush hours. In this paper, we propose a greedy traffic light and queue aware routing protocol(GTLQR) which jointly considers the street connectivity, channel quality, relative distance, and queuing delay to alleviate the packet loss caused by vehicle clustering at the intersection and balance the traffic load among vehicles. Through performance evaluation, we show that our proposed protocol outperforms both TLRC and GLSR-L in terms of packet delivery ratio and end-to-end delay.

Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control

This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.

Advanced Leader Election for Virtual Traffic Lights

We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless network- ing between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light （VTL） system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an inter- section and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic ve- hicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We in- vestigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.

Design of Traffic Light Based on Field Programmable Gate Array

The use of fixed-time traffic lights for road traffic control has the disadvantage of low traffic efficiency. In order to optimize the vehicle traffic at the intersection, this paper proposes a design scheme of a real-time control system for road intelligent traffic lights based on FPGA. The system adopts the polling control model, the vehicle detector detects the arrival rate of vehicles, and obtains the corresponding traffic light green time length according to the traffic rules and polling model theory. Using Altera’s Cyclone IV series EP4CE15E22C8 chip as the development platform, a specific design plan is given. The circuit mainly includes program-controlled amplifier module, AD acquisition module, cross-correlation calculation module, serial port transmission and Lab-VIEW module. The system can realize the intelligent adjustment of traffic lights. Different vehicle arrival rates are detected at different times, so that the corresponding traffic light configuration time length changes accordingly. This intelligent adjustment controls road traffic and makes the main and branch roads coordinate and cooperate, thereby improving the traffic efficiency of the intersection.

Effectiveness of traffic light system on Brazilian consumers perception of food healthfulness

Front-of-package(FOP)nutrition labelling schemes were developed to improve consumer’s comprehension about the food nutrients associated with non-communicable diseases(NCDs).Several FOPs have already been developed,and Brazil is in the process of evaluating a scheme to introduce in the products.The aim of this study was to investigate the impact of TLS,the scheme proposed by the food industry,on the product healthfulness perception.A study with 141 participants was carried out.A conjoint task was designed considering three categories and levels:types of dairy products(light yogurt,prato cheese,and chocolate flavoured milk),Traffic Light System(yes vs.no)and brand(well-known vs.unknown).The effect of TLS on perceived healthfulness was evaluated using a 9-point scales(1:not healthy;9:very healthy).Results showed that the inclusion of TLS did not influence the perceived healthfulness of the products by consumers,even among consumers with higher interest in healthy eating.These findings suggest that the proposal supported by the food industry does not seem to be the most appropriate,being recommended the development of further studies to compare the efficacy of TLS and other FOP schemes.

Optimal traffic light control method for a single intersecti on basedon hybrid systems

A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.

Basic Limit Theorems for Light Traffic Queues &Their Applications

In this paper, we study some basic limit theorems characterizing the stationary behavior of light traffic queuing systems. Beginning with limit theorems for the simple M/M/1 queuing system, we demonstrate the methodology for applying these theorems for the benefit of service systems. The limit theorems studied here are dominant in the literature. Our contribution is primarily on the analysis leading to the application of these theorems in various problem situations for better operations. Relevant Examples are included to aid the application of the results studied in this work.

Anthropogenic activity,hydrological regime,and light level jointly influence temporal patterns in biosonar activity of the Yangtze finless porpoise at the junction of the Yangtze River and Poyang Lake,China

Under increasing anthropogenic pressure,species with a previously contiguous distribution across their ranges have been reduced to small fragmented populations.The critically endangered Yangtze finless porpoise(Neophocaena asiaeorientalis asiaeorientalis),once commonly observed in the Yangtze River-Poyang Lake junction,is now rarely seen in the river-lake corridor.In this study,static passive acoustic monitoring techniques were used to detect the biosonar activities of the Yangtze finless porpoise in this unique corridor.Generalized linear models were used to examine the correlation between these activities and anthropogenic impacts from the COVID-19 pandemic lockdown and boat navigation,as well as environmental variables,including hydrological conditions and light levels.Over approximately three consecutive years of monitoring(2020–2022),porpoise biosonar was detected during 93%of logged days,indicating the key role of the corridor for finless porpoise conservation.In addition,porpoise clicks were recorded in 3.80%of minutes,while feeding correlated buzzes were detected in 1.23%of minutes,suggesting the potential existence of localized,small-scale migration.Furthermore,both anthropogenic and environmental variables were significantly correlated with the diel,lunar,monthly,seasonal,and annual variations in porpoise biosonar activities.During the pandemic lockdown period,porpoise sonar detection showed a significant increase.Furthermore,a significant negative correlation was identified between the detection of porpoise click trains and buzzes and boat traffic intensity.In addition to water level and flux,daylight and moonlight exhibited significant correlations with porpoise biosonar activities,with markedly higher detections at night and quarter moon periods.Ensuring the spatiotemporal reduction of anthropogenic activities,implementing vessel speed restrictions(e.g.,during porpoise migration and feeding),and maintaining local natural hydrological regimes are critical factors for sustaining porpoise population viability.

Multi-Objective Optimization of Traffic Signal Timing at Typical Junctions Based on Genetic Algorithms

With the rapid development of urban road traffic and the increasing number of vehicles,how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities.Therefore,in this paper,a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed.Specifically,a typical urban intersection was selected as the research object,and drivers’acceleration habits were taken into account.What’s more,the shortest average delay time,the least average number of stops,and the maximum capacity of the intersection were regarded as the optimization objectives.The optimization results show that compared with the Webster method when the vehicle speed is 60 km/h and the acceleration is 2.5 m/s^(2),the signal intersection timing scheme based on the proposed Genetic Algorithm multi-objective optimization reduces the intersection signal cycle time by 14.6%,the average vehicle delay time by 12.9%,the capacity by 16.2%,and the average number of vehicles stop by 0.4%.To verify the simulation results,the authors imported the optimized timing scheme into the constructed Simulation of the Urban Mobility model.The experimental results show that the authors optimized timing scheme is superior to Webster’s in terms of vehicle average loss time reduction,carbon monoxide emission,particulate matter emission,and vehicle fuel consumption.The research in this paper provides a basis for Genetic algorithms in traffic signal control.

TWO-DIMENSIONAL CELLULAR AUTOMATON TRAFFIC MODELWITH RANDOMLY SWITCHING TRAFFIC LIGHTS

Cellular automation traffic models can include various factors in traffic systems and the corresponding computational simulations are rather simple and effective. The Biham-Middleton-Levine model (BML model) facilitates the simulation of two-dimensional traffic flow problems via the cellular automaton models. In this paper, the BML model is improved by removing its limitation of synchronized change of traffic lights. In the new model, the traffic light at each crossing could arbitrarily change its starting time and tempo of variation, and hence the model could more realistically describe the influence of traffic lights on the performance of traffic systems. Some new effects appearing in the new model are also elucidated.

基于轨迹数据的非机动车左转信号灯安全效应评估

【目的】对城市交叉口采用的左转非机动车信号灯设施进行交通安全性量化评估。【方法】提出一种基于拓展碰撞时间(extended time to collision,ETTC)指标的左转非机动车信号灯安全效应评估方法。针对现有的碰撞时间(time to collision,TTC)指标不适于评估交叉口左转非机动车冲突的问题,考虑非机动车车辆尺寸与加速度对交通冲突的影响,采用拓展碰撞时间指标,评估交叉口非机动车交通冲突。收集长沙市4个信号交叉口的视频大数据,利用视频软件Tracker提取车辆微观轨迹后,开展案例分析。【结果】左转非机动车信号灯在时间上明确了非机动车的通行权,其设置能显著降低非机动车冲突率,在平峰、高峰时段非机动车冲突率分别降低了40.11%、25.27%。在直行相位末期、左转相位即将启亮时,设置组的左转非机动车在待行区等待,冲突率降为0;而对比组近50%的非机动车违规左转,冲突严重。设置左转非机动车信号灯的改善效果随非机动车流量的增大呈先增加后降低趋势,而随机动车流量的增大呈逐步波动下降趋势。【结论】本研究揭示了非机动车左转信号灯的设置对减少交叉口交通冲突的影响,可为城市交叉口非机动车交通安全管控提供有益参考。

大咖揭秘系列科普——车祸为什么会发生

道路交通事故频发,使儿童和青少年面临着巨大威胁。现通过解答公众关心的交通事故相关问题,科普专业的交通知识,揭开车祸发生的神秘面纱。首先深入剖析了涵盖人、车、路、环境四方面的车祸频发原因,其中的人为因素占比高达93%。针对红绿灯问题,强调了按其指示出行的重要性,但红绿灯并非绝对保障,同时也需要多观察周围环境。此外,还探讨了车速与安全的相对性,提出适宜的车速应依据道路条件而定,并警示感冒及服药后驾驶的潜在风险。最后讨论了无人驾驶技术的影响,其虽有望减少人为失误,但仍尚存挑战。通过科普的形式,旨在提高公众对交通事故的科学认知,增强公众的交通安全意识,减少交通事故的发生。

规范资本发展的核心要义与实践方案

在社会主义市场经济条件下如何规范和引导资本健康发展,是新时代马克思主义政治经济学必须研究解决的重大理论和实践问题。与马克思主义政治经济学一脉相承,党的最新理论成果深刻揭示了社会主义市场经济条件下的资本特性和行为规律,阐释了规范资本发展的核心要义,包括规范资本发展的根本立场、本质要求、目标遵循、治理形态和实践路径。创造性地提出了通过设置“红绿灯”,规范资本发展的实践方案,包括坚持两个毫不动摇,引导资本行为转向“绿灯区”;明确规则底线,禁止资本行为转向“红灯区”;施加限制条件,增设“黄灯区”规范资本防“红”转“绿”。