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Using vehicles as probes is a flexible and low-cost way to obtain real-time traffic information. This paper addresses the sampling issues of using probe vehicles for detecting traffic information in a road network. A spatial and temporal analysis model based on signal processing theory is established and used to derive bounds on the sampling period, transmitting period and sample sizes of probe vehicles...
We address the problem of determining the path of a vehicle on a given vector map of roads, based on tracking data such as that obtained from onboard GPS receivers. We describe a method that is based on a piecewise matching of track segments to map features. A notable feature of our method is that it is applicable to a large class of existing methods. We discuss metrics for evaluating the output of...
In this paper, we present a model of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as quadrotor aircraft. And we explained its control architecture including vision based control. Quadrotors have generated considerable interest in both the control community due to their complex dynamics and military because of their advantages over regular air vehicles. The proposed...
This paper discusses the profile framework of CANopen protocol for a hybrid electric vehicle (HEV). Based on the analysis of the CANopen protocol and the HEV system structure, a preliminary version of CANopen profiles for the HEV is firstly drafted out. Then the object dictionary for each HEV module and communication mechanism of the vehicle network is described in detail. Finally the CANopen profile's...
This paper discusses a new receiving system for visible light communication applied to intelligent transport systems (ITS). We use a light emitting diode (LED) traffic signal as a transmitter that sends information to vehicles that feature a receiver. There are, however, several problems associated with applying visible light communication to the field of ITS. First, we have to transmit information...
We propose a new video analysis method for counting vehicles, where we use an adaptive bounding box size to detect and track vehicles according to their estimated distance from the camera given the scene-camera geometry. We employ adaptive background subtraction and Kalman filtering for road/vehicle detection and tracking, respectively. Effectiveness of the proposed method for vehicle counting is...
Data from vehicles approaching an intersection during a red-light phase has been recorded by measuring real traffic in urban areas. Using a laser scanner based tracking system, vehicle velocities during approaches to the red light have been estimated and various metadata (such as object class, distance to the intersection when the traffic light turned from green to orange and weather data) has been...
The issue of collision avoidance in road vehicles has been investigated for years from very different points of view. A very interesting approach consists of the creation and interpretation of a scene of the vehicles that can be involved in a conflictive situation. In order to determine the role of the vehicle in the scene, having information of its position, orientation and velocity, as well as its...
Most of the common lane recognition systems are designed to work on well structured roads and rely on the existence of markings. In this paper we present a lane recognition scheme for country roads. Our novel approach works even in the absence of markings. The parameter estimation is formulated as a maximum-a-posteriori estimation task fusing color, texture, and edges. The framework can easily be...
Much work was carried out recently for emergency braking based on radar signals. The key step for emergency braking is the reliable detection of obstacles. Moving objects are verified as such by tracking the radar signal. However, discarding so-called phantom objects remains a challenge for stationary objects. This leads to the question of sensor fusion for more reliable verification of obstacles...
In this paper, we present a method for estimating road shape using on-vehicle millimeter-wave radar. The radar detects not only the backscatter from vehicles but also from stationary objects such as crash barriers and sound barrier walls that are generally installed along roads. This indicates that we can estimate road shape by collecting information on the distribution of these objects. We adopt...
Localization is a critical problem in the research of intelligent vehicles. Traditional vision based methods suffer from reliable problems in outdoor environment, especially in complicated urban areas. This paper proposes a novel approach to localize the position of a vehicle with respect to a global map, based on the texture of the ground where the vehicle moves. Images of the ground texture are...
Improvements on pedestrian classification reliability applying a Bayesian approach to multisensor data fusion is described in this paper. The proposed approach fuses information provided by a laser scanner and a monocular gray-level camera. The key is to combine in a probabilistic framework, the detecting capabilities of these sensors to classify pedestrians located along the vehicle trajectory. The...
We show how to determine the time to contact from time varying images using only accumulated sums of suitable products of image brightness derivatives. There is no need for feature or object detection, tracking of features, estimation of optical flow, or any "higher level" processing. This so-called "direct" method for determining the time to contact is based on analysis of the...
The purpose of this paper is to demonstrate the application of a combination of neural network and an oscillating model facility as an approach in identification of aerodynamic coefficients of ground vehicle. In literature study, a method for estimating transient aerodynamic data has been introduced and the aerodynamic coefficients are extracted from the measured time response by means of conventional...
Recently driving support techniques using in-vehicle sensors have attracted much attention and have been applied to practical systems. We focus on supporting drivers in poor visibility conditions. Fog is one of the causes that lead to lack of visibility. In this paper, we propose a method of judging fog density using in-vehicle camera images and millimeter-wave (mm-W) radar data. This method determines...
Vehicular safety research activities have been active in recent years with a focus on the developments of driver assistance systems. Intersection collision is a primary category of roadway safety concerns that can benefit from vehicle-based as well as infrastructure-based solutions. This paper provides a discussion of traffic characteristics and their effects on driver behaviors in intersection across-path...
The goal of this project is to develop a Webcam-based system for monitoring the activities of automobile drivers. As in any system deployed for monitoring driver activities, the primary goal is to distinguish between safe and unsafe driving actions. There is no fixed list of actions that qualifies the unsafe driving behaviors. In general, an activity or an action that reduces a driver's alertness...
Driving a car in urban areas autonomously requires the ability of an in-depth analysis of the current situation. For understanding the current situation and deducing consequences for the execution of behaviors (maneuvers), higher-level reasoning about the situation has to take place. In this paper, an approach for situation interpretation for cognitive automobiles is presented. The approach relies...
This paper presents an integrated system to prevent driver from taking a curve with a dangerous speed. The integrated system underlines three functions developed as follows : the first function consists in knowing the geometry characteristics of the coming road; the second function has to compute a safe speed according to the road section, the vehicle and the driver; the last function must impose...
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