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Open AccessJournal ArticleDOI

An Intelligent Driver Assistance System (I-DAS) for Vehicle Safety Modelling using Ontology Approach

TLDR
An ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation is proposed and the presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.
Abstract
This paper proposes an ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation. Intelligent Driver Assistance System (I-DAS) is a major component of InVANET[12], which focuses on generating the alert messages based on the context aware parameters such as driving situations, vehicle dynamics, driver activity and environment. I-DAS manages the parameter representation, consistent update /maintenance in XML format while the interpretation of a critical situation is done using ontology modeling. Related safety technologies such as Adaptive Cruise Control, Collision Avoidance System, Lane Departure Warning System, Driver Drowsiness detection system, Parking Assistance System, which generate warnings and alerts to driver continuously, for assistance according to context which is integrated in Vehicle and Vehicle 2 Driver (V2D) communications by DVI(Driver Vehicle Interface) had been applied. The simulation test bed developed using Java framework[21] to generate safety alerts in various driving situations shows the usefulness of this approach. The response time graph for the simulation of context IDAS is depicted and analysed. The effective performance of the driving scenarios in various modes like day and night for single, 2-way and 4-way road scenario for the best, worst and average cases of simulation had been studied. The system works in VANET scenario, which needs to be adaptive for environment changes and to vary according to the context. The presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.

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Patent

Driver assistance system for vehicle

TL;DR: In this paper, an adaptive speed control system for controlling the speed of a vehicle is proposed to detect a curve in the road ahead of the vehicle via processing by the image processor of image data captured by the imaging device.
Journal ArticleDOI

An Adaptive Longitudinal Driving Assistance System Based on Driver Characteristics

TL;DR: A prototype of a longitudinal driving-assistance system, which is adaptive to driver behavior, is developed, and results show that the self-learning algorithm is effective and that the system can, to some extent, adapt to individual characteristics.
Proceedings ArticleDOI

Advanced Driver Assistance Systems

TL;DR: Demand for advanced driver-assistance systems, especially those that help with monitoring, warning, braking, and steering task is expected to increase over the next decade, fueled largely by regulatory and consumer interest in safety applications that protect drivers and reduce accidents.
Journal ArticleDOI

Development of a simulation platform for safety impact analysis considering vehicle dynamics, sensor errors, and communication latencies: Assessing cooperative adaptive cruise control under cyber attack

TL;DR: A simulation platform is proposed which can evaluate the safety performance of CACC controllers of interest under various paroxysmal or extreme events and is validated against data collected from real field tests and tested under various cyber-attack scenarios.
Proceedings ArticleDOI

The automotive ontology: managing knowledge inside the vehicle and sharing it between cars

TL;DR: The Automotive Ontology is described, which is located at the core of such an open platform, which gives an overview of design areas relevant to automotive applications, as well as meta aspects that facilitate inference and reasoning.
References
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Traffic Engineering

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TL;DR: This paper presents a conceptual framework and software infrastructure that together address known software engineering challenges, and enable further practical exploration of social and usability issues by facilitating the prototyping and fine-tuning of context-aware applications.
Proceedings ArticleDOI

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TL;DR: In this article, the analysis of a rear-end collision warning/avoidance (CW/CA) system algorithm is presented, which is designed to meet several criteria: 1. System warnings should result in a minimum load on driver attention. 2. Automatic control of the brakes should not interfere with normal driving operation.
Proceedings ArticleDOI

CARS: Context-Aware Rate Selection for vehicular networks

TL;DR: CARS, a novel context-aware rate selection algorithm that makes use of context information to systematically address the above challenges, while maximizing the link throughput, is designed, implemented and evaluated.
Journal ArticleDOI

Interactive Road Situation Analysis for Driver Assistance and Safety Warning Systems: Framework and Algorithms

TL;DR: A development framework and novel algorithms for road situation analysis based on driving action behavior, where the safety situation is analyzed by simulating real driving action behaviors and the experimental results show that the approach is efficient forRoad situation evaluation and prediction.
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