Showing papers on "Intelligent transportation system published in 2005"

Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach

Abstract: Short-term forecasting of traffic parameters such as flow and occupancy is an essential element of modern Intelligent Transportation Systems research and practice. Although many different methodologies have been used for short-term predictions, literature suggests neural networks as one of the best alternatives for modeling and predicting traffic parameters. However, because of limited knowledge regarding a network’s optimal structure given a specific dataset, researchers have to rely on time consuming and questionably efficient rules-of-thumb when developing them. This paper extends past research by providing an advanced, genetic algorithm based, multilayered structural optimization strategy that can assist both in the proper representation of traffic flow data with temporal and spatial characteristics as well as in the selection of the appropriate neural network structure. Further, it evaluates the performance of the developed network by applying it to both univariate and multivariate traffic flow data from an urban signalized arterial. The results show that the capabilities of a simple static neural network, with genetically optimized step size, momentum and number of hidden units, are very satisfactory when modeling both univariate and multivariate traffic data.

Dynamic Wavelet Neural Network Model for Traffic Flow Forecasting

Abstract: Accurate and timely forecasting of traffic flow is of paramount importance for effective management of traffic congestion in intelligent transportation systems. In this paper, a novel nonparametric dynamic time-delay recurrent wavelet neural network model is presented for forecasting traffic flow. The model incorporates the self-similar, singular, and fractal properties discovered in the traffic flow. The concept of wavelet frame is introduced and exploited in the model to provide flexibility in the design of wavelets and to add extra features such as adaptable translation parameters desirable in traffic flow forecasting. The statistical autocorrelation function is used for selection of the optimum input dimension of traffic flow time series. The model incorporates both the time of the day and the day of the week of the prediction time. As such, it can be used for long-term traffic flow forecasting in addition to short-term forecasting. The model has been validated using actual freeway traffic flow data. The model can assist traffic engineers and highway agencies to create effective traffic management plans for alleviating freeway congestions.

Lane detection using color-based segmentation

Abstract: Lane boundary detection is the problem of estimating the geometric structure of the lane boundaries of a road on the images captured by a camera. To be an intelligent vehicle, lane boundary is necessary information, so the system and the algorithm should be as simple and fast as possible. In this paper, we propose a new method based on color information and this method is applicable in complex environment. In this system, we first choose a region of interest to find out a threshold using statistical method in a color image. The threshold then will be used to distinguish possible lane boundary from the road. We use color-based segmentation to find out the lane boundary and use a quadratic function to approach it. This system demands low computational power and memory requirements, and is robust in the presence of noise, shadows, pavement, and obstacles such like cars, motorcycles and pedestrians conditions. The result images can be used as pre-processed images for lane tracking, road following or obstacle detection.

Agent-based control for networked traffic management systems

Abstract: Agent or multiagent systems have evolved and diversified rapidly since their inception around the mid 1980s as the key concept and method in distributed artificial intelligence. They have become an established, promising research and application field drawing on and bringing together results and concepts from many disciplines, including AI, computer science, sociology, economics, organization and management science, and philosophy. However, multiagent systems have yet to achieve widespread use for controlling traffic management systems. Most research focuses on developing hierarchical structures, analytical modeling, and optimized algorithms that are effective for real-time traffic applications, as you can see from well-known traffic control systems such as CRONOS, OPAC, SCOOT, SCAT, PRODYN, and RHODES. Although those functional-decomposition-based systems are useful and successful for many traffic management problems, costs and difficulties associated with their development, operation, maintenance, expansion, and upgrading are often prohibitive and sometimes unnecessary, especially in the rapidly arriving age of connectivity. We need to rethink control systems and reinvestigate the use of simple task-oriented agents for traffic control and management of transportation systems.

Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

Abstract: In this paper we demonstrate a driver intent inference system (DIIS) based on lane positional information, vehicle parameters, and driver head motion We present robust computer vision methods for identifying and tracking freeway lanes and driver head motion These algorithms are then applied and evaluated on real-world data collected in a modular intelligent vehicle test-bed Analysis of the data for lane change intent is performed using a sparse Bayesian learning methodology Finally, the system as a whole is evaluated using a novel metric and real-world data of vehicle parameters, lane position, and driver head motion

Using Support Vector Machines for Lane-Change Detection

Abstract: Driving is a complex task that requires constant attention, and intelligent transportation systems that support drivers in this task must continually infer driver intentions to produce reasonable, ...

Microscopic traffic simulation: A tool for the design, analysis and evaluation of intelligent transport systems

Abstract: This paper summarises some of the main modelling and interface developments made recently in the AIMSUN microscopic traffic simulator to provide a better response to the requirements for the assessment of ITS systems, advanced transport analysis and ATMS. The description addresses two main areas: improvements on the dynamic assignment capabilities, and the embedding of the simulator in the AIMSUN/ISM (Intermodal Strategy Manager) a versatile graphic environment for model manipulation and simulation based traffic analysis and evaluation of advanced traffic management strategies. AIMSUN/ISM includes two specific tools, the Scenario Analysis Module to generate and simulate the traffic management strategies, and the (ODTool) to generate and manipulate the Origin-Destination matrices describing the mobility patterns required by the dynamic analysis of traffic conditions. The matrix calculation procedures have been implemented on basis to a flexible interface with the EMME/2 transport planning software.

Perspectives on Intelligent Transportation Systems (ITS)

Abstract: -SECTION I. Introduction to Intelligent Transportation Systems (ITS) -ITS: A Short History and a Perspective on the Future -SECTION II. ITS Organizational Issues, Regionalism and the Transportation / Information Infrastructure -Transportation Operations: An Organizational and Institutional Perspective -Deploying the Transportation / Information Infrastructure -ITS Deployment and the 'Competitive Region' -SECTION III. ITS: Implications for the Transportation Profession and Transportation Education -Educating the 'New Transportation Professional' -The New Transportation Faculty: The Evolution to Engineering Systems -SECTION IV. 'Thoughts on ITS', ITS Quarterly: Five Years of Columns on ITS Issues -Beyond Technology - Local Organizational Readiness for ITS Deployment -Co-Opetition: A Framework for Analyzing ITS Relationships -Teaching about ITS - A Moving Target -ITS and Safety: A Worst Case Scenario -AHS, ITS and Awareness -The ITS Role at the Millennium -ITS and the Federal Transportation Science and Technology Strategy -ITS and 'Rescuing Prometheus' -ITS and Congestion -Regional ITS Architecture Consistency: What Should It Mean? -A Cautionary Note -It Happened in Boston -Considering ITS as a Complex Adaptive System -Mega-Cities in Developing Countries - a Major ITS Market for the Future -SECTION V. Where We Are Today in ITS and Issues for the Future -Intelligent Transportation Systems at the Turning Point: Preparing for Integrated, Regional and Market-Driven Deployment -Transitions in the World of Transportation: A Systems View -ITS: What We Know Now That We Wish We Knew Then: A Retrospective on the ITS 1992 Strategic Plan

Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety

Abstract: This paper explores the technical feasibility of five Advanced Driver Assistance System (ADAS) functions to contribute to road traffic safety, to reach stated European (EU) and national road traffic safety targets. These functions – enhanced navigation, speed assistance, collision avoidance, intersection support and lane keeping – were selected from previous research as adequate substitutes for infrastructure related measures. State-of-the-art enabling technologies (like positioning, radar, laser, vision and communication) and their potential are analysed from a technical perspective, and possible obstacles for large-scale dedicated ADAS implementation for road traffic safety are discussed.

A realtime dynamic traffic control system based on wireless sensor network

Abstract: One disadvantage of most conventional vehicle detection methods in a traffic control system is that they can only detect the vehicle in a fixed position. This paper proposed a new vehicle detection method using the wireless sensor network (WSN) technology. The striking feature of the proposed WSN-based method is that it can monitor the vehicles dynamically. This paper also developed a new signal control algorithm to control the state of the signal light in a road intersection. Simulations of the real-life intersection traffic control system are conducted in the paper. The simulation results show that the proposed method is effective for the traffic control in a real road intersection.

A collaborative driving system based on multiagent modelling and simulations

Abstract: Collaborative driving is a growing domain of intelligent transportation systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an automated highway system (AHS). In this paper, we address this issue by using a platoon of cars considered as more or less autonomous software agents. To achieve this, we propose a hierarchical driving agent architecture based on three layers (guidance layer, management layer and traffic control layer). This architecture has been used to develop centralized platoons, where the driving agent of the head vehicle coordinates other driving agents by applying strict rules, and decentralized platoons, where the platoon is considered as a group of driving agents with a similar degree of autonomy, trying to maintain a stable platoon. The latter decentralized model mainly considers an agent teamwork model based on a multiagent architecture, known as STEAM. The centralized and decentralized coordination models are finally compared using results from simulation scenarios that highlight safety, time efficiency and communication efficiency aspects for each model.

PRISMATICA: toward ambient intelligence in public transport environments

Abstract: On-line surveillance to improve safety and security is a major requirement for the management of public transport networks and other public places. The surveillance task is a complex one involving people, management procedures, and technology. This work describes an architecture that takes into account the distributed nature of the detection processes and the need to allow for different types of devices and actuators. This was part of a major European initiative on intelligent transport systems. Because of the dominant nature of closed circuit television in surveillance, This work describes in detail a computer-vision module used in the system and its particular ability to detect situations of interest in busy conditions. The system components have been implemented, integrated, and tested in real metropolitan railway environments and are considered to be the first step toward providing ambient intelligence in such complex scenarios. Results are presented that not only deal with detection performance, but also on the perception of people who used the system on its effectiveness and potential impact.

RHODES to intelligent transportation systems

Abstract: To help fulfill the promises of ITS (intelligent transportation system), the ATLAS (Advanced Traffic and Logistics Algorithms and Systems) research center is developing and testing the RHODES (real-time hierarchical optimized distributed effective system) traffic control system. We believe that RHODES play a major role in the realization of future Advanced Traffic Management Systems, a major component of ITS.

Intelligent transportation system

Abstract: A node for communications in a transportation network comprises a processor, a memory, a communication device, and a set of instructions executable by the processor for: extracting information from a first message, making a first determination based at least in part on the information; and making a second determination as to whether a second message should be sent based on the first determination.

Power-steering control architecture for automatic driving

Abstract: The unmanned control of the steering wheel is, at present, one of the most important challenges facing researchers in autonomous vehicles within the field of intelligent transportation systems (ITSs). In this paper, we present a two-layer control architecture for automatically moving the steering wheel of a mass-produced vehicle. The first layer is designed to calculate the target position of the steering wheel at any time and is based on fuzzy logic. The second is a classic control layer that moves the steering bar by means of an actuator to achieve the position targeted by the first layer. Real-time kinematic differential global positioning system (RTK-DGPS) equipment is the main sensor input for positioning. It is accurate to about 1 cm and can finely locate the vehicle trajectory. The developed systems are installed on a Citroe/spl uml/n Berlingo van, which is used as a testbed vehicle. Once this control architecture has been implemented, installed, and tuned, the resulting steering maneuvering is very similar to human driving, and the trajectory errors from the reference route are reduced to a minimum. The experimental results show that the combination of GPS and artificial-intelligence-based techniques behaves outstandingly. We can also draw other important conclusions regarding the design of a control system derived from human driving experience, providing an alternative mathematical formalism for computation, human reasoning, and integration of qualitative and quantitative information.

An error model for inter-vehicle communications in highway scenarios at 5.9GHz

Abstract: The design and evaluation of Inter-Vehicle Communication (IVC) protocols rely much on the accurate and efficient computational simulations. For simulations of Medium Access Control (MAC) and higher layers, the modeling work of underlying Physical layer (PHY) and wireless channel has impacts both on the computational efficiency of simulations and on the correctness of results. In this contribution, we discuss the modeling issues of the inter-vehicle wireless channel in highway scenarios and the packet error performance of Dedicated Short Range Communications (DSRC) PHY, which works at the newly allocated 5.9GHz Intelligent Transportation System (ITS) frequency band. A computationally efficient yet accurate enough error modeling approach used in our MAC layer simulator WARP2 is presented in this paper, together with simulation results. Both weaknesses and potential improvements of the proposed approach are discussed also in this work.

Advanced traveler information system for Hyderabad City

Abstract: The advanced traveler information system (ATIS) is a type of intelligent transportation system application areas that implements emerging computer, communication, and information technologies to provide vital information to the users of a system regarding traffic regulation, route and location guidance, hazardous situations and safety advisory, and warning messages. ATIS requires a large amount of data for processing, analysis, and storage for effective dissemination of traveler information to users. A geographical information system (GIS) allows large data to be effectively processed, stored, analyzed, logically associated, and graphical displayed. Thus, GIS-based ATIS provides a convenient and powerful tool for storage and graphical representation of information, which can be useful users. Further, by availing the powerful GIS functionalities, a user can conceive a problem and allow the appropriate software to assist him in the decision-making process regarding optimum route selection and trip planning. In this paper, the authors present a GIS-based ATIS for Hyderabad City, India. Development of this GIS-based ATIS has been carried under the ArcView GIS environment. This user-friendly system provides comprehensive information about Hyderabad City, such as road networks, hospitals, government and private offices, stadiums, bus and railway stations, and tourist places within the city limits. This system can be used effectively in bus stations, railway stations, airports, and tourist information centers, as well as in personal computers to provide information to travelers and to facilitate travel.

Advanced traveler information system for Hyderabad City

Abstract: The advanced traveler information system (ATIS) is a type of intelligent transportation system application areas that implements emerging computer, communication, and information technologies to provide vital information to the users of a system regarding traffic regulation, route and location guidance, hazardous situations and safety advisory, and warning messages. ATIS requires a large amount of data for processing, analysis, and storage for effective dissemination of traveler information to users. A geographical information system (GIS) allows large data to be effectively processed, stored, analyzed, logically associated, and graphical displayed. Thus, GIS-based ATIS provides a convenient and powerful tool for storage and graphical representation of information, which can be useful users. Further, by availing the powerful GIS functionalities, a user can conceive a problem and allow the appropriate software to assist him in the decision-making process regarding optimum route selection and trip planning. In this paper, the authors present a GIS-based ATIS for Hyderabad City, India. Development of this GIS-based ATIS has been carried under the ArcView GIS environment. This user-friendly system provides comprehensive information about Hyderabad City, such as road networks, hospitals, government and private offices, stadiums, bus and railway stations, and tourist places within the city limits. This system can be used effectively in bus stations, railway stations, airports, and tourist information centers, as well as in personal computers to provide information to travelers and to facilitate travel.

Advanced information feedback in intelligent traffic systems.

Abstract: The optimal information feedback is very important to many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. As to traffic flow, a reasonable real-time information feedback can improve the urban traffic condition by providing route guidance. In this paper, the influence of a feedback strategy named congestion coefficient feedback strategy is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other two information feedback strategies, i.e., travel time and mean velocity.

Land mobile GNSS availability and multipath evaluation tool

Abstract: Applications of global navigation satellite system (GNSS) in land transportation systems are already extensively deployed and will certainly continue to grow especially in the framework of intelligent transport systems. However, one of the best-known drawbacks of such a system is the lack of satellite visibility in dense urban areas as well as in some specific embedded railway environments. This restricts considerably GNSS use for extended safety related applications. In this paper, a new tool is proposed to predict the availability of a satellite constellation from the point of view of the land transportation user. Knowing the trajectory of a land vehicle, the tool predicts the number of satellites that will be received and produces a safety criterion able to qualify the GNSS localization result. A first version of the tool, already in operation, merges an image processing approach providing the knowledge of the land environment, and the output of a satellite tracking program predicting satellite positions in the sky. This allows us to determine, using a simple optical approach, the number of satellites received in line-of-sight or blocked, with regard to the nearby environment of the receiving antenna. Results obtained in railway as well as in road environments show that satellite signals received by multipath are often used by GNSS receivers in the localization process. Thus, propagation characteristics of the satellite signals in an urban canyon configuration were characterized to determine when a signal received by reflected ray is used by the receiver or not. A criterion related to the satellite elevation is defined to improve the overall performance of the predictive tool. Comparisons with real measurements are commented on. Both simulations and measurements are very similar.

Cluster-Based framework in vehicular ad-hoc networks

Abstract: The application of Mobile Ad Hoc Network (MANET) technologies in the service of Intelligent Transportation Systems (ITS) has brought new challenges in maintaining communication clusters of network members for long time durations. Stable clustering methods reduce the overhead of communication relay in MANETs and provide for a more efficient hierarchical network topology. During creation of VANET clusters, each vehicle chooses a head vehicle to follow. The average number of cluster head changes per vehicle measures cluster stability in these simulations during the simulation. In this paper we analyze the effect of weighting two well-known clustering methods with the vehicle-specific position and velocity clustering logic to improve cluster stability over the simulation time.

VGrid: vehicular adhoc networking and computing grid for intelligent traffic control

Abstract: We propose VGrid: an ad hoc networking and computing grid formed by leveraging inter-vehicle and vehicle-to-roadside wireless communications. In addition to exchanging data between vehicles, VGrid actively uses pertinent data to perform computations for solving traffic-related problems. The goal is to evolve intelligent transportation engineering from a centralized to a distributed approach, in which vehicle equipped with wireless networking and computers can cooperate and solve vehicular traffic-flow control problems autonomously. We present an example application: the merging of two lanes into one. We explore various algorithms to compute the optimal schedule for vehicle arrivals at the merge point using velocity/position information exchanged between vehicles. Our simulation results, using realistic vehicle mobility patterns, show that the proposed VGrid framework and algorithms can increase the system throughput and decrease the latency through the merge point.

Prediction Model of Bus Arrival Time for Real-Time Applications

Abstract: Advanced traveler information systems (ATIS) are one component of intelligent transportation systems (ITS), and a major component of ATIS is travel time information. Automatic vehicle location (AVL) systems, which are a part of ITS, have been adopted by many transit agencies to track their vehicles and to predict travel time in real time. Because of the complexity involved, there is no universally adopted approach for this latter application, and research is needed in this area. The objectives of the research in this paper are to develop a model to predict bus arrival time using AVL data and apply the model for real-time applications. The test bed was a bus route located in Houston, Texas, and the travel time prediction model considered schedule adherence, traffic congestion, and dwell times. A historical data-based model, regression models, and artificial neural network (ANN) models were used to predict bus arrival time. It was found that ANN models outperformed both the historical data-based model and the regression model in terms of prediction accuracy. It was also found that the ANN models can be used for real-time applications.

Issues and recent trends in vehicle safety communication systems

Abstract: This paper surveys the research on the applications of inter-vehicle communications, the issues of the deployment and technology, and the current status of inter-vehicle communications projects in Europe, the United States and Japan. The inter-vehicle communications, defined here as communications between on-board ITS computers, improve road traffic safety and efficiency by expanding the horizon of the drivers and on-board sensors. One of the earliest studies on inter-vehicle communications began in Japan in the early 1980s. The inter-vehicle communications play an essential role in automated platooning and cooperative driving systems developed since the 1990's by enabling vehicles to obtain data that would be difficult or impossible to measure with on-board sensors. During these years, interest in applications for inter-vehicle communications increased in the EU, the US and Japan, resulting in many national vehicle safety communications projects such as CarTALK2000 in the EU and VSCC in the US. The technological issues include protocol and communications media. Experiments employ various kinds of protocols and typically use infrared, microwave or millimeter wave media. The situation is ready for standardization. The deployment strategy is another issue. To be feasible, deployment should begin with multiple rather than single services that would work even at a low penetration rate of the communication equipment. In addition, non-technological, legal and institutional issues remained unsolved. Although inter-vehicle communications involve many issues, such applications should be promoted because they will lead to safer and more efficient automobile traffic.

MAC for Dedicated Short Range Communications in Intelligent Transport System

Abstract: In new intelligent transportation system of North American, the emphasis of the surface transportation infrastructure is based on vehicle-to-vehicle wireless communications,while 75 MHz dedicated short range communications may content to future delivery of rich media via vehicle-to-roadside links. This paper provides a tutorial overview of DSRC applications, assess IEEE 802.11 PHY and MAC layer characteristics, limitations of 802.11 in DSRC environments and state of DSRC. and anticipates that 802.11 specifications will need to be suitably altered to meet requirements for DSRC environments of multihop connectivity, high vehicle mobility and a variety of QOS requirements.

DartGrid II: a semantic grid platform for ITS

Abstract: Intelligent transportation systems offer an alternative approach to solving many problems by implementing advances in information, Internet, communication, and cybernetics technologies. Grid computing can support traffic data semantization, resource sharing, ITS subsystem cooperation, and global-scale distributed computing that connects all kinds of resources. We are currently using grid technology to build DartGrid II, a semantic ITS platform to support resource sharing, service flow management, and cross-domain cooperation.

Intelligent Mobile Robot Navigation

Abstract: Intelligent Mobile Robot Navigation builds upon the application of fuzzy logic to the area of intelligent control of mobile robots. Reactive, planned, and teleoperated techniques are considered, leading to the development of novel fuzzy control systems for perception and navigation of nonholonomic autonomous vehicles. The unique feature of this monograph lies in its comprehensive treatment of the problem, from the theoretical development of the various schemes down to the real-time implementation of algorithms on mobile robot prototypes. As such, the book spans different domains ranging from mobile robots to intelligent transportation systems, from automatic control to artificial intelligence.

Experience Implementing a User Service for Archived Intelligent Transportation Systems Data

Abstract: In cooperation with the Oregon Department of Transportation (ODOT) and other regional partners, the Portland regional intelligent transportation systems (ITSs) data archive was recently inaugurated via a direct fiber-optic connection between ODOT and Portland State University (PSU). In July 2004, the Portland Regional Transportation Archive Listing was activated; it received 20-s data from the 436 inductive loop detectors composing the Portland area's advanced traffic management system. PSU is designated as the region's official data archiving entity, consistent with the ITS architecture being developed. This paper discusses the steps taken for successful implementation of the Portland region's functional ITS data archive and plans for development and expansion. Included is a discussion of the archive structure, data storage, data processing, and user interface. An experiment involving Metro, the Portland region's metropolitan planning organization, demonstrates that archived loop detector data can be use...