Traffic Control Information Research Articles

TrafficPro: A road speed prediction framework for urban signal-controlled road networks

In view of the problem that traditional deep learning models do not consider the active time-varying characteristics of traffic flow (signal control information) when predicting the speed of urban road networks, and have low prediction accuracy, this paper proposes a speed prediction framework based on generative adversarial networks and graph neural networks. In this framework, the generator network simultaneously encodes the road network traffic flow and signal control information through active and passive prediction modules to generate prediction results, and then uses the discriminator network to improve the generalization of the prediction results. This framework can obtain higher prediction accuracy than traditional time series models and deep learning models. In the real road network speed prediction scenario, this framework can reduce the prediction error compared to the best benchmark model 3%-4%.

Bayesian Network-Based Correlation Bias Analysis for Air Traffic Control Information Extraction

Bayesian Network-Based Correlation Bias Analysis for Air Traffic Control Information Extraction

TRAFFIC CONTROL RECOGNITION WITH AN ATTENTION MECHANISM USING SPEED-PROFILE AND SATELLITE IMAGERY DATA

Abstract. Traffic regulators at intersections act as an essential factor that influences traffic flow and, subsequently, the route choices of commuters. A digital map that provides up-to-date traffic control information is beneficial not only for facilitating the commuters’ trips, but also for energy-saving and environmental protection. In this paper, instead of using expensive surveying methods, we propose an automatic way based on a Conditional Variational Autoencoder (CVAE) to recognize traffic regulators, i. e., arm rules at intersections, by leveraging the GPS data collected from vehicles and the satellite imagery retrieved from digital maps, i. e., Google Maps. We apply a Long Short-Term Memory to extract the motion dynamics over a GPS sequence traversed through the intersection. Simultaneously, we build a Convolutional Neural Network (CNN) to extract the grid-based local imagery information associated with each step of the GPS positions. Moreover, a self-attention mechanism is adopted to extract the spatial and temporal features over both the GPS and grid sequences. The extracted temporal and spatial features are then combined for detecting the traffic arm rules. To analyze the performance of our method, we tested it on a GPS dataset collected by driving vehicles in Hannover, a medium-sized German city. Compared to a Random Forest model and an Encoder-Decoder model, our proposed model achieved better results with both accuracy and F1-score of 0.90 for the three-class (arm rules of uncontrolled, traffic light, and priority sign) task. We also carried out ablation studies to further investigate the effectiveness of the GPS input branch, the image input branch, and the self-attention mechanism in our model.

Security Challenges of Location Privacy in VANETs and State-of-the-Art Solutions: A Survey

A Vehicular Ad-hoc Network (VANET) comprises a group of moving or stationary vehicles connected by a wireless network. VANETs play a vital role in providing safety and comfort to drivers in vehicular environments. They provide smart traffic control and real-time information, event allocation. VANETs have received attention in support of safe driving, intelligent navigation, emergency and entertainment applications in vehicles. Nevertheless, these increasingly linked vehicles pose a range of new safety and security risks to both the host and its associated properties and may even have fatal consequences. Violations of national privacy and vehicle identities are a major obstacle to introducing forced contact protocols in vehicles. Location privacy refers to the privacy of the vehicle (driver) and the location of the vehicle. Whenever a vehicle sends a message, no one but authorized entities should know their real identity and location of the vehicle. All the messages sent by the vehicle must be authenticated before processing, hence location privacy is an important design aspect to be considered in VANETs operations. The novelty of this paper is that it specifically reviews location privacy in VANETs in terms of operational and safety concerns. Furthermore, it presents a critical analysis of various attacks, identity thefts, manipulation and other techniques in vogue for location privacy protection available in state-of-the-art solutions for VANETs. The efforts in this paper will help researchers to develop a great breadth of understanding pertaining to location privacy issues and various security threats encountered by VANETs and present the critical analysis of the available state-of-the- art solutions to maintain location privacy in VANETs.

Create a Traffic Control Information Space in the Logistics Environment

The research describes the competitive environment in the market of transport-logistics services of Kazakhstan. Logistics networks are represented by two transport systems: JSC ‘National Company Kazakhstan Temirzholy’ hereinafter Operator, as well as other railway administrations and access routes of the Customer (LLP ‘KM Tranko). The experience of TRANKO JSC, where marketing systems in the railway services market of Kazakhstan occupy an important place, is of interest. This format of services in the Republic is not common, therefore the services of JSC ‘TRANKO’ are unique and the specifics of these services, including planning and management of the logistics process with a system of response to failures, can be provided only for large business.

An Efficient Security Scheme for Vehicular Communication Using a Quantum Secret Sharing Method

Potential adversary and maliciously-behaved vehicles may cause traffic chaos or even lead to traffic accidents (particularly on traffic congestion crossroads). To address this issue, a novel security scheme is proposed for facilitating an efficient vehicular communication by employing a quantum secret sharing method. In the proposed scheme, the traffic control information is broadcasted regularly and shared among vehicles to reduce traffic congestion, and thus avoiding traffic accidents. Finally, we also demonstrate the superiority performance of our proposed scheme through theoretical and numerical simulation analysis.

Impact of Green Light Optimized Speed Advisory on Unsignalized Side-Street Traffic

In recent years, rapid technological breakthroughs in infrastructure-to-vehicle, vehicle-to-vehicle, and vehicle-to-infrastructure wireless communications have created the possibility of new concepts for traffic signal control. The green light optimized speed advisory (GLOSA) approach uses traffic signal control information and the current position of a vehicle to recommend an appropriate speed for each vehicle, reducing the number of stops at traffic signals. Previous research mainly focused on the impact of GLOSA on the performance of movements on major streets. The purpose of this paper is to examine the effects of GLOSA on delay, capacity, and surrogate safety measures for vehicles that arrive from unsignalized side driveways and access roads. A highly calibrated and validated Vissim simulation model of a five-intersection segment of 3500 South, an urban corridor in Salt Lake City, Utah, was used as a test environment. Scenarios of various traffic loads and GLOSA activations have been defined and simulated. Outputs from Vissim were used to measure the impact of GLOSA. Vehicular trajectory files were postprocessed in the FHWA Surrogate Safety Assessment Model to analyze vehicular conflict data and thereby evaluate the traffic safety effects of GLOSA. The findings show that GLOSA often significantly affects delay of the side-street traffic. However, in general, GLOSA has only a minor impact on the number of conflicts. Regarding the impact of type of traffic control on GLOSA’s operations, the findings show that the fixed-time signals work better than actuated–coordinated signals, and road geometry and proximity of the signalized intersections affect the impact of GLOSA on the side-street traffic.

Solutions to the problem of inconsistent plans in railway traffic operation

The demands on modern railway traffic systems are high. Higher efficiency is required, meaning better utilisation of infrastructure capacity and reduced energy consumption. Timeliness has a high priority and safety has to be unconditional. The operation of railway traffic includes many actors in different roles and separate organisations. Our studies of train traffic control have shown that improved collaboration between the actors and advanced control systems are needed to meet the high demands. Instead, many actors are following their own plans based on their own goals and insufficient information. This paper explores the concept of a real-time traffic plan (RTTP) to coordinate collaboration between the different actors, and demonstrates how it can be implemented in systems for train traffic control and driver information. We present the traffic control system STEG and the driver advisory system CATO. Both systems are in use, allowing re-planning and sharing of such an RTTP. Based on these systems, we discuss general and specific design solutions, in accordance with human factors and explain a way of introducing automation that supports the traffic controllers without interfering with their planning. With these systems, we are able to show that a more holistic approach to train traffic control, based on an RTTP, is technically feasible and that sharing this plan with the train drivers substantially improves qualities in train traffic control.

Virtual track: applications and challenges of the RFID system on roads

The RFID System on Roads (RSR), which includes RFID tags deployed on roads and RFID readers installed on vehicles, is an essential platform for future transportation systems. It can provide unique features that are missing from the current systems, including lane level position, road traffic control information, vehicle distance estimation, real time driving behavior analysis, and so on. Based on these features, several novel vehicular applications can be implemented, which can significantly improve the transportation safety and efficiency. Specifically, the proposed applications on RSR include Assisted Navigation Systems, Electrical Traffic Control, Unmanned Patrol Systems, Vehicle Distance Estimation, Parking Assistant System, Route Tracing and Access Control, Unmanned Ground Vehicles. We also investigate the corresponding engineering/system and research challenges for implementing RSR and its applications in this article.

Human Sensor Vehicle Traffic Control System with In-Vehicle Notification

The Human Sensor Vehicle Traffic Control with In-vehicle Notification is a vehicle traffic preemption system that employs the Microsoft's Kinect technology to implement a real-time human controlled traffic override system through use of body gestures to control traffic light systems by a traffic warden and at the same time, broadcasts traffic control data right into vehicles equipped with appropriate receiving devices. This system is designed for use in both Fixed-Time and Dynamic controlled traffic systems. Basically, the present technology serves three purposes to wit: Emergency Vehicle Traffic Preemption for Fire engines and Ambulances Alteration of traffic light systems based on varying traffic conditions such as time of day or for special circumstances such as major events or any other circumstances causing unusual traffic demands. Broadcast of traffic conditions to drivers right inside the vehicles. In most urban locations, traffic is usually unpredictable and pre-programmed traffic light system always fail to cater for the demand of adjustability based on prevailing traffic situation per time per intersection. This system allows for human intervention in controlling the electronic traffic system using hand and other body gestures. Furthermore, this system extends the functionality of prior arts by broadcasting traffic control information right into the vehicle dashboard thereby aiding people with poor eye-sights, color blindness or drivers in smaller vehicles queued behind large ones. Also in situations where visibility is low possibly due to hog, humidity or smoke, this system ensures the driver is adequately notified of the traffic directions per time. For data reception, appropriate software applications are developed for the following popular mobile platforms: Apple iOS, Android, Windows Phone, Symbian and Blackberry which are placed inside a vehicle, preferably hung to the dashboard or windscreen. Language: en

Cognitive multicast with partially overlapped channels in vehicular ad hoc networks

Vehicle to many vehicles (V2MV) multicast is an attractive application to provide vehicle safety and traffic control information, urban sensing and multimedia content sharing in vehicular ad hoc networks. Due to the limitation of DSRC channels, Wi-Fi channels can be alternative to realize the multicast in the vehicular networks. However, the deployment using the Wi-Fi in ISM bands is challenging due to the interference from increasing residential Wi-Fi users as well as inter-vehicle interference. In this study, we propose a cognitive multi-channel, multi-radio multicast protocol, CoCast, borrowing concept of recently developed cognitive radio techniques, which can help overcome such interference, with spectrum sensing and multi-channel assignment. Unfortunately, number of orthogonal channels is very limited in the ISM band to avoid interference in urban Wi-Fi cloud. Therefore, we apply two additional features to use partially overlapped channels: parallel frame transmission over OFDM subchannels to exploit spectral diversity, and network coding for the subchannel frames. Our evaluation results show that the reliability of multicast communication among vehicles in a dense urban environment can be significantly improved with these protocol extensions.

Quantifying Loop Detector Sensitivity and Correcting Detection Problems on Freeways

Loop detectors are the most commonly used vehicle detector for freeway management. A loop detector consists of a physical loop of wire embedded in the pavement connected to a sensor located in a nearby cabinet. The sensor detects the presence or absence of vehicles over the loop and typically allows a user to manually select the sensitivity level of operation to accommodate for a wide range of responsiveness from the physical loop. In conventional practice, however, it is difficult to know the physical loop’s responsiveness, which makes selecting the appropriate sensitivity level difficult. If the sensitivity and responsiveness are poorly matched it will degrade the detector’s data and the performance of applications that use the data, including: traffic management, control, and traveler information. To resolve this often overlooked problem, this paper presents an algorithm to assess how well a loop detector’s sensitivity is set by calculating the daily median on-time from the data reported by the loop detector. The algorithm can be incorporated into conventional controller software or run off-line. The result can be used both to correct the detector on-times for an inappropriate sensitivity setting in software (e.g., through a multiplicative correction factor) and to trigger an alarm to dispatch a technician to adjust the hardware sensitivity. Plotting the daily median on-time over months or years can show how the detector performance evolves. The approach is then transposed to dual-loop detectors to identify and correct for inaccurate spacing between the paired detectors. Finally, the methodology is evaluated by comparing the loop detector speeds against the concurrent velocities from a GPS-equipped probe vehicle. Although the focus of this paper is on loop detectors, with only minor modification the algorithm should also be applicable to other detector technologies that emulate loop detector operation, e.g., side-fire microwave radar.

Sequential Modeling Framework for Optimal Sensor Placement for Multiple Intelligent Transportation System Applications

Traffic sensors have been deployed for decades to freeways to meet the requirements of various traffic/transportation applications, most noticeably traffic control and traveler information applications. A unique feature of traffic sensor deployment is that it is a continuous and evolving process. That is, with new applications that emerge, additional sensors are usually required to be deployed to meet new requirements. This process is also sequential in nature and the new deployment has to consider existing sensors. In this paper, we propose a modeling framework to capture this sequential decision-making process for traffic sensor deployment. The framework is based on our recent findings that (1) optimal sensor deployment for a single application can be determined by a staged process or, more formally, a dynamic programming (DP) method and (2) new sensor locations for new applications can be optimally solved by the DP method via considering existing sensors. We illustrate the framework using two applications: ramp metering control and travel time estimation. It is found that the proposed scheme can appropriately capture the decision-making process of traffic sensor deployment and can generate optimal sensor placement at any stage by considering sensors that have already been deployed. The model is tested using global positioning system enabled cell phone data and traffic simulation on a real-world freeway route in the San Francisco Bay Area.

Developing a road traffic control system with GIS

Since the onset of rapid urbanisation and the growth in vehicular transport in China, the cycle time for supplying urban road demand has become shorter, requiring urban road traffic control information such as signal controls, traffic marks and signs to change dramatically. This has led to a much greater focus on how to collect, manage and update dynamic traffic control information and to analyse traffic resources with this information. The present study aimed to develop a system to manage road traffic control information and analyse traffic resources using visual techniques. In this system road traffic control information is represented as objects such as points, lines or regions in a geographic information system (GIS) and their specifications are stored in an attribute table of the objects. Moreover, graphic user interfaces were developed to process, edit, query, display and print the information. A road traffic resource analysis system has been developed based on the road network and the relevant traffic control information. This system has been implemented by the city police and is being used by the urban traffic police to manage and disseminate the information.

An intelligent traffic management expert system with RFID technology

This paper presents an intelligent traffic management expert system with RFID technology. The system provides both practically important traffic data collection and control information and can trace criminal or illegal vehicles such as stolen cars or vehicles that evade tickets, tolls or vehicle taxes. The system architecture consists of an RFID reader, a passive tag, a personal computer, a pair of infrared sensors, and a high-speed server with a database system. Based on RFID technology, the system collects and calculates average speed and average flow information on each road of a district area in a city. It then transmits the messages from all the congested roads in a district area to the server in the district center via a communication program. Through a flooding algorithm, each server in a district center exchanges and updates information with all neighbor servers in other district centers so all that the servers in various district centers can get all the latest congestion messages in a city. Therefore, a dynamic navigation system can find the shortest path that avoids congested roads. Meanwhile, we compare three types of tags for choosing a better solution for e-plates in the future. We also adopt infrared sensors for detecting cars that do not have a tag.

Collection and use of environmental data for transport management: a view from local authorities

Research undertaken by the Transportation Research Group at the University of Southampton is discussed, which studies the views, needs and requirements of local authorities as users of sensor grids for environmental monitoring. The study was undertaken through a combination of literature review and workshop activity. Representatives from local authorities were invited to participate in a workshop discussion. It was agreed that more detailed and comprehensive environmental data will be useful for transport planning, network management and traveller information provision. The detailed data can be used to provide a sound understanding of local environmental situations and to identify specific problem areas and times. For local authorities, monitoring noise level and air pollutants which have direct impact on human health such as PM10, PM2.5 and NOx is more important than monitoring green house emission. Historic data on air pollution will be essential for local transport plans focusing on reduction of road-transport-related pollution. Real time environmental data will be needed to be integrated with existing traffic control and traveller information systems. Information on areas surrounding schools and hospitals are most desirable. However, there was a concern regarding negative information disseminated to the public.

Determination of Pedestrian Push-Button Activation Duration at Typical Signalized Intersections

Recent advances in pedestrian push-button design, led by the development of accessible pedestrian signals (APSs), have created a new method of communicating traffic control information to pedestrians. Some APS devices have beaconing features or verbal (speech) message capabilities obtained by pressing and holding the pedestrian push button for approximately 3 s. Other features, such as the extension of the walk interval, may also be activated with an extended press of the push button. Recent research has suggested that 3 s may be excessive because it is hard for some users to hold the push button for this long. Additionally, most pedestrians may not hold the push button for this length of time. The problem lies in determining how long the APS push button should be pressed for a push-button information message or special accessibility features to be obtained. The primary objective of the research described in this paper was to develop a time distribution of typical pedestrian push-button activation durations. Data were obtained by attaching a voltage recorder to the pedestrian push-button circuit inside traffic signal controllers at eight locations in three cities in Wisconsin and Massachusetts. This device recorded the amount of time, to the nearest 1/100 of a second, that each pedestrian push button was pressed. A total of 1,439 push-button presses were recorded. The average push-button press duration was 0.2 s. More than 95% of all push-button presses recorded were less than 1.0 s. Only four push-button presses exceeded 3.0 s. The results show that the duration of an extended push-button press needed to obtain additional crossing information can be reduced to approximately 1 s without a significant number of false calls. A 1-s press will minimize the effort required for pedestrians to actuate special accessible features, while it will minimize unnecessary noise and vehicular traffic disruption.

Determination of Pedestrian Push-Button Activation Duration at Typical Signalized Intersections

Recent advances in pedestrian push-button design, led by the development of accessible pedestrian signals (APSs), have created a new method of communicating traffic control information to pedestrians. Some APS devices have beaconing features or verbal (speech) message capabilities obtained by pressing and holding the pedestrian push button for approximately 3 s. Other features, such as the extension of the walk interval, may also be activated with an extended press of the push button. Recent research has suggested that 3 s may be excessive because it is hard for some users to hold the push button for this long. Additionally, most pedestrians may not hold the push button for this length of time. The problem lies in determining how long the APS push button should be pressed for a push-button information message or special accessibility features to be obtained. The primary objective of the research described in this paper was to develop a time distribution of typical pedestrian push-button activation durations. Data were obtained by attaching a voltage recorder to the pedestrian push-button circuit inside traffic signal controllers at eight locations in three cities in Wisconsin and Massachusetts. This device recorded the amount of time, to the nearest 1/100 of a second, that each pedestrian push button was pressed. A total of 1,439 push-button presses were recorded. The average push-button press duration was 0.2 s. More than 95% of all push-button presses recorded were less than 1.0 s. Only four push-button presses exceeded 3.0 s. The results show that the duration of an extended push-button press needed to obtain additional crossing information can be reduced to approximately 1 s without a significant number of false calls. A 1-s press will minimize the effort required for pedestrians to actuate special accessible features, while it will minimize unnecessary noise and vehicular traffic disruption.

Environmental Support for Older and Younger Pilots' Comprehension of Air Traffic Control Information

We investigated whether expertise mitigates age differences on pilot communication tasks when experts rely on environmental support. Pilots and nonpilots listened to air traffic control messages describing a route through an airspace, during which they referred to a chart of the airspace. The routes were high (waypoint routes anchored to navigational reference points on the chart) or low (vector routes that were not) in contextual support. Participants read back messages and answered questions about aircraft position (which required integration of message and chart information) or altitude (which did not). Pilots more accurately answered questions. The expertise advantage for position, but not altitude, questions was greater for waypoint routes, showing differential use of environmental support by experts. Age did not moderate these effects.

Effects of Data-Link Modality and Display Redundancy on Pilot Performance: An Attentional Perspective

The effectiveness of three different data link interfaces, involving auditory, visual, and redundant presentation of Air Traffic Control (ATC) information, was evaluated in a single pilot general aviation simulator. Fifteen certified flight instructor pilots flew a Frasca flight simulator with full visual display of the outside world, through a series of ATC-instructed maneuvers, while scanning outside for traffic. ATC instructions, of various lengths, were delivered through a text based data link display, through synthesized voice (similar to the current system), or through a redundant voice-text format. Pilots read back the instructions and then complied with whatever maneuver was instructed, while monitoring for traffic. Visual scanning was measured. The results revealed that the visual display provided greatest accuracy of communications readback, and was least disruptive of both traffic monitoring and flight path tracking. The auditory-only condition was most disruptive of these tasks, in part because the pilot's visual attention was drawn into the cockpit for longer periods while note taking, when compared with the visual text display. The redundant display condition provided many of the same benefits as the visual-only display, but was not associated with better performance than that display, and was sometimes inferior to it. This resulted, in part, because the arrival of the discrete auditory communications appeared to disrupt performance of the ongoing visual flight task. Across all conditions, the pilots allocated approximately 60% of their visual attention to monitoring the instrument panel and their communications accuracy was degraded by the longer ATC instructions. The results are interpreted in terms of mechanisms of attention and working memory in information processing, and in terms of the pilot's task priority hierarchy.