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Introducing a Sensor Network for Advanced Driver Assistance Systems Using Fuzzy Logic and Sensor Data Fusion Techniques

Mahdi Rezaei Ghahroudi, Mohammadreza Sarshar and Reza Sabzevari

Driving, one of our daily activities is a complex task involving a great amount of interaction between the driver, vehicle and environment. Drivers regularly share their attention among operating the vehicle, monitoring traffic and nearby obstacles, and performing secondary tasks such as conversing, adjusting comfort settings (e.g. temperature, radio). The complexity of the task and uncertainty of the driving environment points up the growing demand on automotive safety systems, which aim for a significant contribution to the overall road safety. In this paper we implement an applicable framework for advanced driver assistance systems based on fuzzy logic and multi-sensor data fusion techniques to reduce the driver’s workload and to help lessen the danger of road incidence. Therefore we introduced a novel deployment for a network of multi-sensors such as Radar, Laser, Ultrasound and Vision which are mounted on a host vehicle with a specific tendency to degree of driver’s vigilance. The proposed method is applied on some real driving tasks such as following and overtaking a vehicle with a safe speed and distance. The results are improved by a moving window filter and enriched by some MATLAB and Fuzzy TECH simulations.

Keywords: Sensor data fusion, sensor network, driver assistance system, adaptive cruise control.

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