Showing papers on "Intelligent transportation system published in 2006"

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

Abstract: Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles

A License Plate-Recognition Algorithm for Intelligent Transportation System Applications

Abstract: In this paper, a new algorithm for vehicle license plate identification is proposed, on the basis of a novel adaptive image segmentation technique (sliding concentric windows) and connected component analysis in conjunction with a character recognition neural network. The algorithm was tested with 1334 natural-scene gray-level vehicle images of different backgrounds and ambient illumination. The camera focused in the plate, while the angle of view and the distance from the vehicle varied according to the experimental setup. The license plates properly segmented were 1287 over 1334 input images (96.5%). The optical character recognition system is a two-layer probabilistic neural network (PNN) with topology 108-180-36, whose performance for entire plate recognition reached 89.1%. The PNN is trained to identify alphanumeric characters from car license plates based on data obtained from algorithmic image processing. Combining the above two rates, the overall rate of success for the license-plate-recognition algorithm is 86.0%. A review in the related literature presented in this paper reveals that better performance (90% up to 95%) has been reported, when limitations in distance, angle of view, illumination conditions are set, and background complexity is low

Vehicular Ad Hoc Networks (VANETs): Challenges and Perspectives

Abstract: Vehicular Ad hoc Network (VANET), a subclass of mobile Ad Hoc networks (MANETs), is a promising approach for future intelligent transportation system (ITS). These networks have no fixed infrastructure and instead rely on the vehicles themselves to provide network functionality. However, due to mobility constraints, driver behavior, and high mobility, VANETs exhibit characteristics that are dramatically different from many generic MANETs. This article provides a comprehensive study of challenges in these networks, which we concentrate on the problems and proposed solutions. Then we outline current state of the research and future perspectives. With this article, readers can have a more thorough understanding of vehicle ad hoc networking and the research trends in this area.

Automatic traffic surveillance system for vehicle tracking and classification

Abstract: This paper presents an automatic traffic surveillance system to estimate important traffic parameters from video sequences using only one camera. Different from traditional methods that can classify vehicles to only cars and noncars, the proposed method has a good ability to categorize vehicles into more specific classes by introducing a new "linearity" feature in vehicle representation. In addition, the proposed system can well tackle the problem of vehicle occlusions caused by shadows, which often lead to the failure of further vehicle counting and classification. This problem is solved by a novel line-based shadow algorithm that uses a set of lines to eliminate all unwanted shadows. The used lines are devised from the information of lane-dividing lines. Therefore, an automatic scheme to detect lane-dividing lines is also proposed. The found lane-dividing lines can also provide important information for feature normalization, which can make the vehicle size more invariant, and thus much enhance the accuracy of vehicle classification. Once all features are extracted, an optimal classifier is then designed to robustly categorize vehicles into different classes. When recognizing a vehicle, the designed classifier can collect different evidences from its trajectories and the database to make an optimal decision for vehicle classification. Since more evidences are used, more robustness of classification can be achieved. Experimental results show that the proposed method is more robust, accurate, and powerful than other traditional methods, which utilize only the vehicle size and a single frame for vehicle classification.

Intelligent Transportation Systems

Abstract: This issues Works in Progress department features 10 interesting ongoing intelligent transportation systems projects. The first five projects (TIME, Sentient Transport, EVT, DynaCHINA, TrafficView) focus on traffic and vehicular data collection, transmission, and analysis. The sixth projects aims to provide intelligent-copilot services for driven, while the seventh focuses on asset identification and data collection for railroad environments. The eighth and ninth projects are budding application development environments for automobiles, and the tenth project is designing a multimodal biometric identification system for travel documents

Enhancing Security and Privacy in Traffic-Monitoring Systems

Abstract: Intelligent transportation systems increasingly depend on probe vehicles to monitor traffic: they can automatically report position, travel time, traffic incidents, and road surface problems to a telematics service provider. This kind of traffic-monitoring system could provide good coverage and timely information on many more roadways than is possible with a fixed infrastructure such as cameras and loop detectors. This approach also promises significant reductions in infrastructure cost because the system can exploit the sensing, computing, and communications devices already installed in many modern vehicles. This architecture separates data from identities by splitting communication from data analysis. Data suppression techniques can help prevent data mining algorithms from reconstructing private information from anonymous database samples

Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations

Abstract: This paper presents a new method for the design and validation of advanced driver assistance systems (ADASs). With vehicle hardware-in-the-loop (VEHIL) simulations, the development process, and more specifically the validation phase, of intelligent vehicles is carried out safer, cheaper, and is more manageable. In the VEHIL laboratory, a full-scale ADAS-equipped vehicle is set up in a hardware-in-the-loop simulation environment, where a chassis dynamometer is used to emulate the road interaction and robot vehicles to represent other traffic. In this controlled environment, the performance and dependability of an ADAS is tested to great accuracy and reliability. The working principle and the added value of VEHIL are demonstrated with test results of an adaptive cruise control and a forward collision warning system. On the basis of the 'V' diagram, the position of VEHIL in the development process of ADASs is illustrated.

DGPS-Based Vehicle-to-Vehicle Cooperative Collision Warning: Engineering Feasibility Viewpoints

Abstract: The vehicle collision warning system (CWS) is an important research and application subject for vehicle safety. Most of this topic's research focuses on autonomous CWSs, where each vehicle detects potential collisions based entirely on the information measured by itself. Recently, an alternative scenario has arisen. This scenario is known as cooperative driving, where either the vehicle or the infrastructure can communicate its location, intention, or other information to surrounding vehicles or nearby infrastructure. Since installing a low-cost global-positioning-system (GPS) unit is becoming a common practice in vehicle applications, its implications in cooperative driving and vehicle safety deserve closer investigation. Furthermore, the future trajectory prediction may lead to a straightforward approach to detect potential collisions, yet its effectiveness has not been studied. This paper explores the engineering feasibility of a future-trajectory-prediction-based cooperative CWS when vehicles are equipped with a relatively simple differential GPS unit and relatively basic motion sensors. The goals of this paper are twofold: providing an engineering argument of possible functional architectures of such systems and presenting a plausible example of the proposed future-trajectory-based design, which estimates and communicates vehicle positions and predicts and processes future trajectories for collision decision making. In this paper, common GPS problems such as blockage and multipath, as well as common communication problems such as dropout and delays, are assumed. However, specific choices of GPS devices and communication protocol or systems are not the focus of this paper

A feature-based tracking algorithm for vehicles in intersections

Abstract: Intelligent Transportation Systems need methods to automatically monitor the road traffic, and especially track vehicles. Most research has concentrated on highways. Traffic in intersections is more variable, with multiple entrance and exit regions. This paper describes an extension to intersections of the feature-tracking algorithm described in [1]. Vehicle features are rarely tracked from their entrance in the field of view to their exit. Our algorithm can accommodate the problem caused by the disruption of feature tracks. It is evaluated on video sequences recorded on four different intersections.

A Comparative Study of Data Dissemination Models for VANETs

Abstract: VANETs (vehicular ad hoc networks) are emerging as a new network environment for intelligent transportation systems. Many of the applications built for VANETs will depend on the data push communication model, where information is disseminated to a group of vehicles. In this paper, we present a formal model of data dissemination in VANETs and study how VANET characteristics, specifically the bidirectional mobility on well defined paths, affects the performance of data dissemination. We study the data push model in the context of TrafficView, a system we have implemented to disseminate information about the vehicles on the road. Traffic data could be disseminated using vehicles moving on the same direction, vehicles moving in the opposite direction, or vehicles moving in both directions. Our analysis as well as simulation results show that dissemination using only vehicles in the opposite direction increases the data dissemination performance significantly.

ACC+Stop&go maneuvers with throttle and brake fuzzy control

Abstract: Research on adaptive cruise control (ACC) with Stop&Go maneuvers is presently one of the most important topics in the field of intelligent transportation systems. The main feature of such controllers is that there is adaptation to a user-preset speed and, if necessary, speed reduction to keep a safe distance from the vehicle ahead in the same lane of the road, whatever the speed. The extreme case is the stop and go operation in which the lead car stops and the vehicle at the rear must also do so. This paper presents the development of an ACC system and related experiments. The system input information is acquired by a real-time kinematic phase differential global positioning system (GPS) (i.e., centimetric GPS) and wireless local area network links. The outputs are the variables that control the pressure on the throttle and brake pedals, which is calculated by an onboard computer. In addition, the car control is based on fuzzy logic. The system has been installed in two mass-produced Citroe/spl uml/n Berlingo electric vans, in which all the actuators have been automated to achieve humanlike driving. The results from real experiments show that the unmanned vehicles behave very similarly to human-driven cars and are very adaptive to any kind of situation at a broad range of speeds, thus raising the safety of the driving and allowing cooperation with manually driven cars.

Roadway traffic monitoring from an unmanned aerial vehicle

Abstract: Roadway networks span large distances and can be difficult to monitor. Most efforts to collect roadway usage data either require a large fixed infrastructure or are labor intensive. Technological advances in electronics and communication have recently enabled an alternative, unmanned aerial vehicles (UAVs). UAVs capable of carrying sensors and communications hardware to relay data to the ground are becoming available on the commercial market. UAVs can cover large areas and focus resources. They can travel at higher speeds than ground vehicles and are not restricted to travelling on the road network. We investigate the use of a UAV to monitor roadway traffic and develop and demonstrate several applications using data collected from a UAV flying in an urban environment. We describe our use of the data to determine level of service, average annual daily traffic, intersection operations, origin–destination flows on a small network, and parking lot utilization. Our ability to determine these measures illustrates the feasibility of extracting useful information from images sampled from a UAV for both off-line planning and real-time management applications, and our discussion of the methods indicates the challenges and opportunities images obtained from such a platform pose and entail.

Vehicle Positioning System Using Location Codes in Passive Tags

Abstract: Vehicles driving on a roadway interrogate passive tags in or on lanes of the roadway. Codes in the tags represent locations along the highway and which lane the vehicle is traveling in. Units in the vehicles communicate longitudinal and lane positions derived from the codes among each other or with infrastructure units for purposes such as traffic management, alerts concerning other vehicles, alerts concerning external conditions, or traffic control. The units may also communicate vehicle lengths or other parameters or characteristics. Vehicle units may communicate with sensors and actuators in the vehicles for purposes such as updating the vehicles' positions between adjacent tags. Specific applications for intelligent transportation systems are described.

Application of the ARIMA Models to Urban Roadway Travel Time Prediction - A Case Study

Abstract: Travel time is the time required to traverse a route between any two points of interest and it is an important parameter that can be used to measure the effectiveness of transportation systems. The ability to accurately predict freeway and arterial travel times in transportation networks is a critical component for many Intelligent Transportation Systems (ITS) applications. In this paper, we focus on the application of using time series models to study the arterial travel time prediction problem for urban roadways and a section of Minnesota State Highway 194 is chosen as our case study. We use the Global Positioning System (GPS) probe vehicle method to collect data. The time series modeling is then developed, in particular, we focus on the autoregressive integrated moving average (ARIMA) model due to the non-stationary property of the data collected. The section models established for the corridor are verified via both the residual analysis and portmanteau lack-of-fit test. Finally, based on the models developed we present our prediction results. Our study indicates the potential and effectiveness of using the ARIMA modeling in the prediction of travel time. The method presented in this paper can be easily modified and applied to short-term arterial travel time prediction for other urban areas.

Real time Rome

Abstract: In today's world, wireless mobile communications devices an creating new dimensions of interconnectedness between people, places, and urban infrastructure. This ubiquitous connectivity within the environment can be observed and interpreted in real-time through aggregate records collected from communication and transportation networks. The real-time acquisition can regard traces of information and communication networks, mavement patterns of people and transportation systems, spatial and social usage of streets and neigbbourboods. This paper reports on the Real Time Rome project, exhibited at the 10th Internationl Architecture Exhibition in Venice, Italy. The Real Time Rome project is the first example of an urban-wide real-time monitoring system that collects and processes data provided by telecommunications networks and transportation systems in order to understand patterns of daily life in Rome. Obseriwg the real-time city becomes a means to understanding the present and anticipating the future urban environement 1 .

On-Road Evaluation of Intelligent Speed Adaptation, Following Distance Warning and Seatbelt Reminder Systems: Final Results of the TAC SafeCar Project

Abstract: The project had several aims: to evaluate the technical operation of a number of ITS technologies with high estimated safety potential; to assess the acceptability to drivers of these technologies; and to evaluate, in an on-road setting, the impact of these technologies, alone and in combination, on driver performance and safety. The project also involved a study that examined, in an advanced driving simulator, the effects on driving performance of two variants of Intelligent Speed Adaptation (ISA). This report documents the design, methodology and final outcomes of Phase 4 of the project, which involved the deployment and on-road evaluation of four ITS technologies equipped to 15 Ford passenger cars (referred to as SafeCars). The four technologies were: Intelligent Speed Adaptation (ISA); Following Distance Warning (FDW); Seatbelt Reminder (SBR) and Reverse Collision Warning (RCW). During the trial, the treatment drivers were exposed to all four ITS technologies, while the control drivers were exposed to the SBR and RCW systems only. Each SafeCar was equipped with a data logging system which automatically recorded a range of driving performance measures. This report presents the findings that derived from the logged driving data and from the subjective data on drivers perceived acceptability and usability of the SafeCar systems. (a)

Smart Cars on Smart Roads: An IEEE Intelligent Transportation Systems Society Update

Abstract: To promote tighter collaboration between the IEEE Intelligent Transportation Systems Society and the pervasive computing research community, the authors introduce the ITS Society and present several pervasive computing-related research topics that ITS Society researchers are working on. This department is part of a special issue on Intelligent Transportation.

Cluster-based multi-channel communications protocols in vehicle ad hoc networks

Abstract: The dedicated short range communications (DSRC) standard equipped with seven channels is designated for intelligent transportation system (ITS) applications to improve the driving safety and support networking services among moving vehicles. Making best use of the DSRC multichannel architecture, we propose a cluster-based multichannel communications scheme, which integrates the clustering with contention-free/contention-based MAC protocols. In our proposed scheme, the elected cluster-head (CH) vehicle functions as the coordinator (like WLAN's basestation) to collect/deliver the real-time safety messages within its own cluster and forward the consolidated safety messages to the neighboring CHs. Also, the CH vehicle controls channel-assignments for cluster-member vehicles transmitting/receiving the non-real-time traffics, which makes the wireless channels more efficiently utilized for the non-real-time data transmissions. Our scheme uses the contention-free MAC (TDMA/broadcast) within a cluster and the IEEE 802.11 MAC among CH vehicles such that the real-time delivery of safety messages can be guaranteed. The simulation results show that our proposed scheme can significantly improve the throughputs of vehicle data communications while guaranteeing the real-time delivery of safety messages

WITS: A Wireless Sensor Network for Intelligent Transportation System

Abstract: Transportation information collection and communication plays a key role in Intelligent Transportation System (ITS). Unfortunately, most conventional ITSs can only detect the vehicle in a fixed position, and their communication cables and power cables elevate the cost of construction and maintenance. Because of the advantages of the wireless sensor network (WSN) such as low power consumption, wireless distribution, and flexibility without cable restrictions., the usage of WSN in ITSs is expected to be able to overcome the above difficulties. This paper proposes an WSN-based transportation information collection and communication system. Hardware and software WSN modules are designed and prototyped.

Bi-level Programming Formulation and Heuristic Solution Approach for Dynamic Traffic Signal Optimization

Abstract: : Although dynamic traffic control and traffic assignment are intimately connected in the framework of Intelligent Transportation Systems (ITS), they have been developed independent of one another by most existing research. Conventional methods of signal timing optimization assume given traffic flow pattern, whereas traffic assignment is performed with the assumption of fixed signal timing. This study develops a bi-level programming formulation and heuristic solution approach (HSA) for dynamic traffic signal optimization in networks with time-dependent demand and stochastic route choice. In the bi-level programming model, the upper level problem represents the decision-making behavior (signal control) of the system manager, while the user travel behavior is represented at the lower level. The HSA consists of a Genetic Algorithm (GA) and a Cell Transmission Simulation (CTS) based Incremental Logit Assignment (ILA) procedure. GA is used to seek the upper level signal control variables. ILA is developed to find user optimal flow pattern at the lower level, and CTS is implemented to propagate traffic and collect real-time traffic information. The performance of the HSA is investigated in numerical applications in a sample network. These applications compare the efficiency and quality of the global optima achieved by Elitist GA and Micro GA. Furthermore, the impact of different frequencies of updating information and different population sizes of GA on system performance is analyzed.

Reliable Real-Time Framework for Short-Term Freeway Travel Time Prediction

Abstract: It is widely acknowledged that traffic information has the potential of increasing the reliability in road networks and in alleviating congestion and its negative environmental and societal side effects. However, for these beneficial collective effects to occur, reliable and accurate traffic information is a prerequisite. Building on previous research, this article presents a reliable framework for online travel time prediction for freeways, which could, for example, be used to generate traffic information messages on so-called dynamic route information panels on freeways. Central in this framework is a so-called state-space neural network (SSNN) model, which learns to predict travel times directly from data obtained from real time traffic data collection systems. In this article we show that by using an ensemble of SSNN models also a measure for the reliability of each prediction can be produced. This enables traffic managers to monitor in real time the reliability of this system without actually measuring travel times.

A Survey of Research in Inter-Vehicle Communications

Abstract: As a component of the intelligent transportation system (ITS) and one of the concrete applications of mobile ad hoc networks, inter-vehicle communication (IVC) has attracted research attention from both academia and industry of, notably, US, EU, and Japan. The most important feature of IVC is its ability to extend the horizon of drivers and on-board devices (e.g., radar or sensors) and, thus, to improve road traffic safety and efficiency. This chapter surveys IVC with respect to key enabling technologies ranging from physical radio frequency to group communication primitives and security issues. The mobility models used to evaluate the feasibility of these technologies are also briefly described. We focus on the discussion of various MAC protocols that seem to be indispensable components in the network protocol stack of IVC. By analyzing the application requirements and the protocols built upon the MAC layer to meet these requirements, we also advocate our perspective that ad hoc routing protocols and group communication primitives migrated from wired networks might not be an efficient way to support the envisioned applications, and that new coordination algorithms directly based on MAC should be designed for this purpose.

Truck route planning in nonstationary stochastic networks with time windows at customer locations

Abstract: Most existing methods for truck route planning assume known static data in an environment that is time varying and uncertain by nature, which limits their widespread applicability. The development of intelligent transportation systems such as the use of information technologies reduces the level of uncertainties and makes the use of more appropriate dynamic formulations and solutions feasible. In this paper, a truck route planning problem called stochastic traveling salesman problem with time windows (STSPTW) in which traveling times along roads and service times at customer locations are stochastic processes is investigated. A methodology is developed to estimate the truck arrival time at each customer location. Using estimated arrival times, an approximate solution method based on dynamic programming is proposed. The algorithm finds the best route with minimum expected cost while it guarantees certain levels of service are met. Simulation results are used to demonstrate the efficiency of the proposed algorithm

Survey of Routing Protocols for Inter-Vehicle Communications

Abstract: Inter-vehicle communications is a topic of growing interest, with a number of target applications under consideration. One significant application for inter-vehicle communications is dissemination of vehicle safety information such as road and traffic-related events and conditions. To support vehicle safety information, a reliable and efficient inter-vehicle communications system which can meet stringent safety application performance requirements is needed. This paper reviews developments in routing schemes targeted for ad hoc vehicle networks and considers them in the context of safety communications.

Effect of looking backward on traffic flow in a cooperative driving car following model

Abstract: An extended car following model is proposed by incorporating intelligent transportation system and the backward looking effect under certain condition in traffic flow The neutral stability condition of this model is obtained by using the linear stability theory The results show that anticipating the behavior of vehicles preceding and following one vehicle could lead to appreciable stabilization of traffic system From the simulation of space-time evolution of the vehicle headways, it is shown that the traffic jam could be suppressed efficiently via taking into account the information about the motion of two preceding vehicles and one following vehicle, and the analytical result is consistent with the simulation one

Performance of pheromone model for predicting traffic congestion

Abstract: Social insects perform complex tasks without top-down-style control, by sensing and depositing chemical markers called "pheromone". We have examined applications of this pheromone paradigm towards realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.

A PCA-Based Vehicle Classification Framework

Abstract: Due to its great practical importance, Intelligent Transportation System has been an active research area in recent years. In this paper, we present a framework that incorporates various aspects of an intelligent transportation system with its ultimate goal being vehicle classification. Given a traffic video sequence, the proposed system first proceeds to segment individual vehicles. Then the extracted vehicle objects are normalized so that all vehicles are aligned along the same direction and measured at the same scale. Following the preprocessing step, two classification algorithms - Eigenvehicle and PCA-SVM, are proposed and implemented to classify vehicle objects into trucks, passenger cars, vans, and pick-ups. These two methods exploit the distinguishing power of Principal Component Analysis (PCA) at different granularities with different learning mechanisms. Experiments are conducted to compare these two methods and the results demonstrate the effectiveness of the proposed framework.

CoSIGN: A Parallel Algorithm for Coordinated Traffic Signal Control

Abstract: The problem of finding optimal coordinated signal timing plans for a large number of traffic signals is a challenging problem because of the exponential growth in the number of joint timing plans that need to be explored as the network size grows. In this paper, the game-theoretic paradigm of fictitious play to iteratively search for a coordinated signal timing plan is employed, which improves a system-wide performance criterion for a traffic network. The algorithm is robustly scalable to realistic-size networks modeled with high-fidelity simulations. Results of a case study for the city of Troy, MI, where there are 75 signalized intersections, are reported. Under normal traffic conditions, savings in average travel time of more than 20% are experienced against a static timing plan, and even against an aggressively tuned automatic-signal-retiming algorithm, savings of more than 10% are achieved. The efficiency of the algorithm stems from its parallel nature. With a thousand parallel CPUs available, the algorithm finds the plan above under 10 min, while a version of a hill-climbing algorithm makes virtually no progress in the same amount of wall-clock computational time

TrafficAnalyzer - the integrated video image processing system for traffic flow analysis

Abstract: This paper presents the overview of an integrated video image processing system which can count traffic volumes, track moving objects such as vehicles and pedestrians, and recognize license plates number automatically by using image processing technology without any special hardware. Case studies are carried out by applying this system to the actual road traffic scene, and its performance and accuracy are evaluated. Experimental results of the image processing show that each analysis function has sufficiently satisfactory performance for practical use. For the covering abstract see ITRD E134653.