Intelligent Vehicle Navigation System Research Articles

A Security and Privacy Preserved Intelligent Vehicle Navigation System

With emergence of smart city concept, intelligent transportation becomes one of its key enablers, with navigation as an indispensable component. Vehicular ad hoc network (VANET) based systems emerge to provide navigation services to vehicle users, which is characterized by employing Roadside Units (RSUs) to collect road condition information from nearby vehicles. The querying vehicle exploits the information retrieved through the RSUs to determine an optimal route. We focus on addressing two key issues in such system. First, while querying, the destination of the vehicle user should not be leaked to the queried RSU and trusted authority (TA), which is likely to be misused. Second, the navigation process should be independent of participation of the centralized TA, which can be a single point of failure. To address these issues, this article proposes a security and privacy preserved intelligent vehicle navigation system, adopting a distributed approach, to retrieve navigation without revealing the destination. The security of the system has been thoroughly evaluated using an adversary model, BAN Logic and AVISPA tool. In addition, the performance of the proposed system has been evaluated, and compared with the existing systems. The comparison illustrates that the proposed system is computationally efficient than the existing systems.

Intelligent Vehicle Navigation System Based on Visual Detection and Positioning

This design is a set of intelligent vehicle navigation system which relies on visual detection and positioning. The image is processed and the coordinates of beacon and car body are extracted by the camera hanging above. The coordinate information is transmitted to the intelligent vehicle and fused with the intelligent vehicle data to determine its own environment and running state. The system integrates image processing, wireless communication and intelligent path planning to realize the task of accurate recognition and automatic tracing.

Road obstacles positional and dynamic features extraction combining object detection, stereo disparity maps and optical flow data

One of the most relevant tasks in an intelligent vehicle navigation system is the detection of obstacles. It is important that a visual perception system for navigation purposes identifies obstacles, and it is also important that this system can extract essential information that may influence the vehicle's behavior, whether it will be generating an alert for a human driver or guide an autonomous vehicle in order to be able to make its driving decisions. In this paper we present an approach for the identification of obstacles and extraction of class, position, depth and motion information from these objects that employs data gained exclusively from passive vision. We performed our experiments on two different data-sets and the results obtained shown a good efficacy from the use of depth and motion patterns to assess the obstacles' potential threat status.

Intelligent vehicle navigation system with assistance and alerting capabilities

SummaryNavigation assistance systems are aiming to improve safety and provide traffic optimization and have become more and more popular in a modern vehicular technology. The reason is given by the significant traffic increase and numerous congestion events in large cities, large complexity of road infrastructure, and unexpected or hazardous conditions that can be found on roads. This paper proposes an innovative navigation system solution that intelligently gathers traffic data provided by integrated car sensors and/or onboard security systems and uses it to warn other participants. System concepts, architecture, design, implementation, and performance evaluation aspects are presented, and tasks organization for an embedded cost‐effective implementation using a real‐time kernel is illustrated.

Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS). In the GOS, there is bank of extended Kalman filters (EKFs), each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

Intelligent Vehicle Navigation System Based on Multi-Visual Cognition Information

Visual cognition system is an important research content of intelligent vehicle control system. This paper researched traffic lights recognition, lane line identification and traffic sign recognition which consist of vehicle intelligent multi-visual cognition system. The intelligent vehicle navigation system based on multi-visual cognition information fusion was also built and some algorithms had been tested on the real unmanned vehicle which led a good result.

The Intelligent Vehicle Navigation System Based on Photoelectric Sensor

This paper describes the intelligent vehicle navigation system based on 16 bits MCU MC9S12XS128. The system uses MC9S12XS128 as control core, realizing path recognition through the laser sensor, using PWM signals to control the actuator steering and motor speed, making the intelligent vehicle tracing along the black line of 25mm wide placidly. This technology can be widely used in automatic warehouse, robot vehicle and unmanned factory, etc. In this case, we designed and developed this intelligent vehicle navigation system, among it the PID algorithm is applied to the control structure. And the photoelectric sensing technology is also applied into the system. This system is of important reference significance for the research on unpiloted system.

Event classification for vehicle navigation system by regional optical flow analysis

We address the problem of event classification for intelligent vehicle navigation system from video sequences acquired by a front mounted camera in complex urban scenes. Although in normal driving condition, large variety of events could be found and be preferably attached to an alerting system in a vehicle, there have been relatively narrow research activities on driving scene analysis, for example, finding local information such as lanes, pedestrians, traffic signs or light detections. Yet, the above-mentioned methods only provide limited performance due to many challenges in normal urban driving conditions, i.e. complex background, inhomogeneous illumination, occlusion, etc. In this paper, we tackle the problem of classification of various events by learning regional optical flows to detect some important events (very frequent occurring and involving riskiness on driving) using low cost front mounted camera equipment. We approached the problem as follows: First, we present an optical flow-based event detection method by regional significance analysis with the introduction of a novel significance map based on regional histograms of flow vectors; Second, we present a global and a local method to robustly detect ego-motion-based events and target-motion-based events. In our experiments, we achieved classification accuracy about 91% on average tested with two classifiers (Bayesian and SVM). We also show the performance of the method in terms of computational complexity achieving about 14.3 fps on a laptop computer with Intel Pentium 1.2 Ghz.

Design of Intelligent Vehicles Control System based on Photoelectric Detector

Given the characteristics of the road information, an intelligent vehicle navigation system based on infrared sensors is developed. Signal collection and processing method are outlined. This paper describes a method cleverly exploiting principles of optics to improve the lane-keeping ability of infrared photoelectric sensors. Considering that the conventional PID can not meet the requirement of motor controls for their real-time character and table lookup based on fuzzy control cannot meet the requirement of steady precision, an improved PID with fuzzy control algorithm is proposed, As a result of test, navigation accuracy is increased by double; dynamic performance and steady precision of the system are both obviously improved by the control algorithm proposed.

DEVELOPMENT OF AN EVENT-REPORTING INTELLIGENT VEHICLE NAVIGATION SYSTEM FOR AREAS WITH URBAN CANYONS

Common vehicle navigation systems employ mostly GPS satellite positioning to track the vehicle's position and velocity. The tracked position can be dynamically shown on a digital map or automatic route guidance can be performed. So-called “Intelligent GPS Vehicle Navigation Systems”, simply speaking, are extensions of common GPS vehicle navigation systems. It can be said, that they are GPS vehicle positioning systems with embedded intelligence. From the authors' point of view, an intelligent system should be able to detect the changes of the real-world situation and to give an appropriate response to the changes. Therefore, an Intelligent GPS Navigation System should have all the basic functionality of a common GPS navigation system, and be able to detect and react to the conditions that are of concern of the driver or the vehicle manager. To achieve this, an intelligent GPS navigation system should be integrated with different types of sensors and communication devices that are able to monitor and perform event reporting to the vehicle's real-word situation. Hence, event reporting is an essential component of an Intelligent Vehicle Navigation System (IVNS). With regard to the navigation part of the system, it is essential that the vehicle's trajectory can be continuously tracked to provide necessary guidance for the driver. However, for GPS-alone systems a reliable position determination in urban canyons may not always be possible, therefore it is necessary to investigate the integration of other vehicle tracking devices and methods.After the discussion of the potential applications of an event reporting IVNS, a more detailed description of a prototype system will be given. Such a system is being developed in a research project at the Department of Land Surveying and Geoinformatics of the Hong Kong Polytechnic University. Finally, field test results of the prototype IVNS conducted in Hong Kong are presented and the integration of wireless location services for positioning and a new GPS-alone position tracking method for urban canyons are briefly discussed.