Signal Timing Changes Research Articles

Proposed Design and Modeling of Smart Traffic Light System using Arduino

The most benefit from using traffic light signals were they reduced the number of accidents on roads and also helped with the movement of traffic securely without collision. In Libya we use traditional traffic lights which causes collisions in some places. Therefore, this paper proposed a smart system to solve the traffic problem by using dynamic traffic light control. In this system if there is no traffic on the other signal then one should not wait for this signal. The system which includes light traffic will control this signal and move to the next signal. The signal timing changes automatically when traffic intensity is sensed at the intersection. The microcontroller used in this project is "ARDUINO", also there are other devices such as ultrasound sensors (transmitter and receiver) that are mounted on both sides of the road on poles, the aim of this research is to solve and develop the problem of the road traffic, by using C++ language, electric wires, resistance, electronic board and ultrasonic sensors. In the end, fortunately the results were very accurate.

Density Based Traffic Control Using Machine Learning

Abstract: “Density Based Traffic Control Using Machine Learning” is a project that is designed to develop a density based dynamic traffic signal system. The signal timing changes automatically on sensing the traffic density at the junction. Traffic congestion is a severe problem in many major cities across the world. Conventional traffic light system is based on the fixed time concept allotted to each side of the junction which cannot be varied as per varying traffic density

Smart Traffic Light Control System with Automatic Vehicle Speed Breaker

The aim of the project is to design a smart traffic light control system interfaced with a barrier gate and an LDR based traffic light control system. When the signal timing changes a delay is provided with the help of a microcontroller, pop up barrier before the zebra crossing will open or close to allow vehicles to pass. When the signal is red the interfaced barrier gate closes and a buzzer notifies the closing of gate, thereby blocking the traffic but when the signal is green the same barrier opens and allows a proper flow of vehicles to avoid traffic congestion. We provide a time delay for all signals to change and buzzer action by using ESP32 microcontroller. ESP32 microcontroller is used for signal timing change as well as street light control according to LDR. Smart Street light which operates with the help of sensors Microcontrollers are programmed in such a way to adjust their timing and phasing to meet changing traffic conditions. The circuit, besides being reliable and compact, is also cost effective. This project presents the way of conservation of energy by reducing electricity wastage as well as to reduce the man power. The project uses light emitting diodes (LED) that do not consume an enormous amount of electricity. LDR is used as a sensor for the functioning of street lights effectively.

Advanced Traffic Control System for Emergency Vehicle

Abstract: Traffic congestion is a severe problem in most of the cities across the world and it has become a nightmare for the citizens. It is caused by delay in signal, inappropriate timing of traffic signal ling etc. The delay of traffic light is hard coded and it does not depends on traffic. Therefore for optimizing traffic control, there is an increasing demand in systematic quick automatic system. This paper is designed to develop a density based dynamic traffic signal control. The signal timing changes automatically on sensing the traffic density at the junction. The microcontroller used in this project is Raspberry Pi. The system contains IR sensors (transmitter and receiver) which will be mounted on the either side of the road on poles. It gets activated and receives the signal as the vehicles passes close by it

Multimodal Intersection Signal Timing Considerations Framework, Performance Measures, and Case Study

Signal retiming is a cost-effective practice to improve intersection operations through periodic updating of the timing plans. Traditionally, signal retiming has focused on vehicular-based performance (e.g., reducing vehicle delay or number of stops), while often unintentionally ignoring the needs of other users, such as pedestrians, cyclists, and transit vehicle passengers. This unintended omission is further exacerbated by the signal timing tools used in the industry, which tend to primarily report vehicular metrics. To address these challenges, this research developed a multimodal signal timing framework along with easy-to-use performance measures. These performance measures include (1) vehicle delay, (2) crosswalk delay, (3) crossing stress, and (4) bus delay. To assess the approach effectiveness, the proposed framework and the developed tools were applied to 12 intersections along the North Glebe Corridor, in Arlington, VA, for the weekday a.m. peak. Analysis results showed that the proposed framework and tools can incorporate most multimodal considerations and address the limitations of the traditional vehicle-based approaches by quantifying multimodal tradeoffs at signals. With the proposed tools, the alternative timing plan developed for the a.m. peak yielded a 4.5% improvement in performance along the corridor, versus a degradation of 3.7% if only vehicle delay was considered in the analysis. Additional sensitivity analysis conducted along the corridor using various timing plan scenarios showed that the calculated values of the measures are accurately reflecting the anticipated effects of signal timing changes that aim to improve crossing stress for non-motorized users and/or reduce their delay at the intersection crosswalks.

AUTOMATIC TRAFFIC SIGNAL CONTROLLER USING ARDUINO

Traffic congestion and accidents caused by more than speeding vehicles have been a major cause for anxiety in societies due to their negative effects such as stress to commuters, release of more toxic fumes into the atmosphere, accidents and loss of productive hours.The enhancement of Traffic Light Controller utilizing ultrasonic sensor and microcontroller. The Paper is designed for structuring a thickness based dynamic traffic signal framework where the planning of signal will change as a result on detecting the traffic density at any road junction. This paper offers an move toward for handling traffic congestion and over speeding offenders. This system uses infrared sensors as counters to measure the traffic density in each lane. The infrared sensors are also for speed detection with a Bluetooth module and Bluetooth serial monitor. These sensors are interfaced with the traffic light through a micro controller. The signal timing changes automatically on sensing the traffic density at the junction. The microcontroller used in this project is ARDUINO. In instance of any vehicle in emergency condition or on the other hand in emergency like VVIPs, a SMS is send to Traffic Control Authority, who has the control of microcontroller empowers microcontroller. The implementation of the prototype design show that traffic control and speed detection using infrared sensors and Arduino Atmega 2560 give a better performance and the time taken to clear traffic at an intersection reduced significantly with 60% time saved

Density based traffic control system implementation using Arduino micro-controller board

This paper gives the design of the density-based traffic control system implementation using Arduino micro-controller board. Traffic congestion is a severe problem in most of the cities across the world and it has become a nightmare for the citizens. It is caused by delay in signal, inappropriate timing of traffic signaling etc. The delay of traffic light is hard coded and it does not depend on traffic. Therefore, for optimizing traffic control, there is an increasing demand in systematic quick automatic system. This paper is designed to develop a density based dynamic traffic signal control. The signal timing changes automatically on sensing the traffic density at the junction. The microcontroller used in this project is ARDUINO. The system contains Ultrasonic sensors (trigger and echo) which will be mounted on the either side of the road on poles. It gets activated and receives the signal as the vehicles passes close by it. The work presented here is the mini-project work of the second sem students of electronics & communication engineering department of Dayananda Sagar College of Engg., Bangalore.

Design of On-line Simulation System for Signal Control of Urban Intersections Based on Visual Sensing Technology

Intersection area is the area with the most serious conflicts and accidents in the whole urban traffic system. Therefore, it is of great significance to combine modern computer technology, sensing technology and communication technology to intelligently control intersections, improve the efficiency of traffic signal control and reduce the delay time in conflict areas. Starting with video detection and using deep learning in the detection module, a video detection mechanism based on restricted Boltzmann machine network is proposed. Based on C # programming language, the intersection traffic signal simulation module is designed through COM interface provided by traffic simulation software VISSIM, which realizes road network import, parameter setting, signal timing change, simulation operation and simulation result output. Numerical experiments show that fuzzy control method with self-correcting factor is superior to timing control method and classical fuzzy control method in average delay time of vehicles.

Density Based Traffic Control System Using Arduino

Traffic congestion is a severe problem in most of the cities across the world and it has become a nightmare for the citizens. It is caused by delay in signal, inappropriate timing of traffic signaling etc. The delay of traffic light is hard coded and it does not depend on traffic. Therefore, for optimizing traffic control, there is an increasing demand in systematic quick automatic system. This paper is designed to develop a Density based traffic controller system using ARDUINO. The signal timing changes automatically on sensing the traffic density at the junction. The microcontroller used in this project is ARDUINO. The system contains IR sensors (transmitter and receiver) which will be mounted on the either side of the road on poles. It gets activated and receives the signal as the vehicles passes close by it. In this system, we will use IR sensors to measure the traffic density. We have to arrange one IR sensor for each road; these sensors always sense the traffic on that particular road. All these sensors are interfaced to the microcontroller. Based on these sensors, controller detects the traffic and controls the traffic system.

Density Based Traffic System via IR Sensor

This paper presents an inventive prototype design of a traffic light which is purposely used at junctioned road since traffic light is the best way to supervise and manage traffic at any busy junction or intersection. This project is designed to develop a density based traffic signal system where its signal timing changes automatically after sensing the traffic density at the intersection. Traffic density is define as the amount of vehicle congested at a certain place, in this case an intersection. The more vehicles available, the higher the traffic density is. This increasing number of vehicles on the road will produce many problems such as traffic jammed thus will also drive to road accidents. Conventional traffic light uses fixed time which cause difficulties in controlling the traffic itself. In order to resolve this problem, design of this traffic light will help to reduce traffic jammed at a particular location. This traffic light uses an Arduino UNO microcontroller to create an automation function together with an Infrared sensor (IR sensor) to detect the density of the traffic. Each vehicle is set to 3 seconds. All vehicles pass through the traffic light is measured and processed accordingly to delays. If there is no vehicle on the road for at least 1 second, then it will change to another traffic light. By using this, all vehicles will be counted and interacted with the system thus increase delay period for the green light at each traffic light which may have high density of traffic. Thus, it will reduce problems which might rooted from traffic congestion at the intersection.

Intelligent Traffic Control System with Priority to Emergency Vehicles

Traffic is the most critical problem in metropolitan cities. Traffic control becomes more necessary to provide problem-less, peaceful driving and pollution-less life to people. The work is designed to develop a density based dynamic traffic signal system. The signal timing changes automatically on sensing the traffic density at the junction. The traffic system is structured with a camera. The image captured by the camera is processed in order to calculate the number of vehicles present in the image. The camera also identifies the siren and allows the green light for emergency vehicles like ambulance, fire engine etc. In this paper, masking algorithm is used to process the image and find the vehicle count on the road. This algorithm shows only the required portion of the image and masks the unnecessary details. The visual basic programming is used to control the glowing time of traffic light based on the vehicle count on the road. The Arduino controller is a single board microcontroller used for instructing the LED to glow. This method can be used to detect road accidents and identify violations of the spiral movements of cars. The whole system when installed on road, provides a way for easy traffic clearance for emergency vehicles without a need of sergeant.

Grouping by feature of cross-modal flankers in temporal ventriloquism

Signals in one sensory modality can influence perception of another, for example the bias of visual timing by audition: temporal ventriloquism. Strong accounts of temporal ventriloquism hold that the sensory representation of visual signal timing changes to that of the nearby sound. Alternatively, underlying sensory representations do not change. Rather, perceptual grouping processes based on spatial, temporal, and featural information produce best-estimates of global event properties. In support of this interpretation, when feature-based perceptual grouping conflicts with temporal information-based in scenarios that reveal temporal ventriloquism, the effect is abolished. However, previous demonstrations of this disruption used long-range visual apparent-motion stimuli. We investigated whether similar manipulations of feature grouping could also disrupt the classical temporal ventriloquism demonstration, which occurs over a short temporal range. We estimated the precision of participants’ reports of which of two visual bars occurred first. The bars were accompanied by different cross-modal signals that onset synchronously or asynchronously with each bar. Participants’ performance improved with asynchronous presentation relative to synchronous - temporal ventriloquism - however, unlike the long-range apparent motion paradigm, this was unaffected by different combinations of cross-modal feature, suggesting that featural similarity of cross-modal signals may not modulate cross-modal temporal influences in short time scales.

A hybrid approach of symbolic aggregate approximation and bitmap: application to fault diagnosis of reciprocating compressor valve

Feature extraction plays an important role in machinery fault diagnosis and prognosis. The features extracted from time, frequency and time-frequency domains are widely investigated to describe the properties of overall signal from different perspectives (e.g. RMS, energy, etc.), seldom considering the sequential pattern of time-series signal in which the fault information may be embedded. This paper contributes a novel approach based on Symbolic Aggregate approXimation (SAX) framework and bitmap technology to extract fault information by analyzing sequential pattern in time-series signal for fault diagnosis. In the proposed method, SAX and bitmap are subtly combined. SAX technique reduces the dimensionality of raw data by transforming the original real valued time series into a discrete one. Fault features are extracted with bitmap representation by a simple histogram form summarizing the occurrence of the chosen symbols words, in which signal timing change character is investigated. Compared with the commonly used methods, the proposed approach has high computation efficiency and feature extraction accuracy. Experimental studies on reciprocating compressor valve demonstrate that the presented approach outperforms the methods of SAX-entropy and EMD-energy-entropy using support vector machine for classification.

충격파 이론을 이용한 대중교통 우선신호의 신호시간 산정모형

본 연구에서는 충격파 모형을 이용하여 능동식 우선신호의 최적 신호시간을 산정하기 위한 모형을 제시하였다. 본 신호 최적화 모형을 이용하여 능동형 우선신호 기법 중 Early green 및 Green extension이 적용되는 조건에서 충격파 면적을 산정할 수 있다. 본 연구에서는 평균통행시간 및 교차로 진출시각을 이용해 충격파의 발생 속도를 산정하기 위한 방법을 제시하였으며, 이를 이용해 우선신호로 인한 현시 변화량에 따라 충격파 면적 변화량을 산정할 수 있다. 또한 교차로 전체의 충격파 면적이 최소화되는 신호시간을 산정하여 우선신호로 인해 증가하는 일반차량의 지체를 최소화할 수 있도록 하였다. 우선신호 신호시간 산정 모형의 효과평가를 위해 VISSIM과 ComInterface를 이용한 미시적 시뮬레이션 분석을 시행하였으며, 이동류의 포화상태를 고려하여 지체 최소화를 위한 신호시간이 산정됨을 확인하였다. 독립교차로를 대상으로 하는 사례분석에서 우선신호를 위해 비우선현시를 균일하게 단축하는 전략 대비 본 모형에서 일반차량 지체가 10% 이상 개선됨을 확인하였다. 본 연구는 트램, BRT, 중앙버스 전용차로 등 대중교통 우선시설이 확산되고 있는 최근 국내 상황에서 신호교차로의 운영효율을 높이기 위한 새로운 우선신호 제어 방법을 제시하였다는데 의의가 있겠다. This research suggested the traffic signal calculation model of active transit signal priority using a shockwave model. Using this signal priority timing optimization model, the shockwave area is computed under the condition of Early Green and Green Extension among active transit signal priority techniques. This study suggested the speed estimation method of backward shockwave using average travel time and intersection passing time. A shockwave area change is calculated according to signal timing change of transit signal priority. Moreover, this signal timing calculation model could determine the optimal signal priority timings to minimize intersection delay of general vehicles. A micro simulation analysis using VISSIM and its user application model ComInterface was applied. This study checked that this model could calculate the signal timings to minimize intersection delay considering saturation condition of traffic flow. In case studies using an isolated intersection, this study checked that this model could improve general vehicle delay of more over ten percentage as compared with equality reduction strategy of non-priority phases. Recently, transit priority facilities are spreading such as tram, BRT and median bus lane in Korea. This research has an important significance in that the proposed priority model is a new methodology that improve operation efficiency of signal intersection.

Agent-Based Simulation of Ecospeed-Controlled Vehicles at Signalized Intersections

Ecospeed control systems attempt to reduce vehicle fuel consumption levels by optimization of vehicle trajectories in the vicinity of signalized intersections while these systems account for traffic signal timing constraints. The proposed algorithm uses dynamic programming to compute the vehicle trajectory needed to navigate through the intersection with the amount of minimum fuel subject to several constraints, including vehicular interactions, traffic signal timing changes, and vehicle and roadway constraints. The proposed application uses infrastructure-to-vehicle and vehicle-to-vehicle communication to receive traffic signal and vehicle data. The research presented in the paper developed an agent-based modeling tool to simulate and test the system under various traffic volume and market penetration levels. The simulation model used a variety of microscopic inputs, such as the roadway vertical profile, roadway surface condition, traffic volumes, and traffic signal timing information. The system was tested on a sample signalized intersection and produced fuel consumption reductions of 30% and travel speed increases of 200%, on average, within the vicinity of the intersection. Actual savings in total trip time, average speed, and the amount of fuel consumed depend on the trip profile, including the number of intersections and total trip length.

Impacts of Transit Priority on Signal Coordination: Case Study of Toronto, Ontario, Canada

This study introduces the current application of transit signal priority (TSP) in the City of Toronto, Ontario, Canada, and focuses on the following: traffic signal operations, constraints of the current signal control system and TSP technology, evaluation metrics, and models for simulating transit priority operation. In Toronto, 335 traffic signals have transit priority, 321 of which are under the control of the main traffic signal system (MTSS). Active transit priority unconditionally allows an extension of up to 30 s per cycle in addition to the normal signal green time on transit routes. The extension generates complaints about traffic delays for vehicles on side streets, long pedestrian wait times, and poor signal coordination. Field tests were conducted on a section of a downtown Toronto arterial bus route. Actual MTSS logs and signpost data obtained by the transit agency during field tests were used to investigate three scenarios along Bathurst Street at six signalized intersections. An analysis of signal timing changes that encompassed selection and determination of traffic operation performance measures was conducted on a per-cycle basis in the morning peak, afternoon peak, and off-peak periods. Green-band effectiveness was one of the evaluation measures used to assess signal progression. Subsequently, a performance assessment frame based on a model for the analytic hierarchy process was built to determine the best scenario and to help develop simulation models. The analysis shows that the TSP strategy of unconditional extension up to 30 s in signal green time is not recommended for use with the existing system of traffic signal control. The approaches described can apply to different transit routes with variable situations in Toronto.

Algorithm for Queue Estimation with Loop Detector of Time Occupancy in Off-Ramps on Signalized Motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.

Changes in crash risk following re-timing of traffic signal change intervals

More than 1 million motor vehicle crashes occur annually at signalized intersections in the USA. The principal method used to prevent crashes associated with routine changes in signal indications is employment of a traffic signal change interval — a brief yellow and all-red period that follows the green indication. No universal practice exists for selecting the duration of change intervals, and little is known about the influence of the duration of the change interval on crash risk. The purpose of this study was to estimate potential crash effects of modifying the duration of traffic signal change intervals to conform with values associated with a proposed recommended practice published by the Institute of Transportation Engineers. A sample of 122 intersections was identified and randomly assigned to experimental and control groups. Of 51 eligible experimental sites, 40 (78%) needed signal timing changes. For the 3-year period following implementation of signal timing changes, there was an 8% reduction in reportable crashes at experimental sites relative to those occurring at control sites ( P=0.08). For injury crashes, a 12% reduction at experimental sites relative to those occurring at control sites was found ( P=0.03). Pedestrian and bicycle crashes at experimental sites decreased 37% ( P=0.03) relative to controls. Given these results and the relatively low cost of re-timing traffic signals, modifying the duration of traffic signal change intervals to conform with values associated with the Institute of Transportation Engineers’ proposed recommended practice should be strongly considered by transportation agencies to reduce the frequency of urban motor vehicle crashes.

Phase Time Prediction for Traffic-Actuated Intersections

The Highway Capacity Manual (HCM) provides a methodology in Chapter 9 to estimate the capacity and level of service at a signalized intersection as a function of traffic characteristics and signal timing. At traffic-actuated intersections, the signal timing changes from cycle to cycle in response to traffic demand. An accurate prediction of average phase times and their corresponding cycle length is required to assess the performance of intersections controlled by traffic-actuated signals. The current technique suggested in Appendix II of HCM Chapter 9 for this purpose has not been well accepted. A more comprehensive methodology and a more satisfactory analytical model are described that predict traffic-actuated signal timing for both isolated and coordinated modes with actuated phases. The proposed methodology and model have been verified by simulation augmented by limited field studies. The results are encouraging with respect to their general reliability and their compatibility with the current HCM Cha...