scholarly journals A Fuzzy Rules-Based Driver Assistance System

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Jong-Chih Chien ◽  
Jiann-Der Lee ◽  
Li-Chang Liu
Keyword(s):  
Driver Assistance System ◽  
Fuzzy Rules ◽  
Assistance System ◽  
Viewing Angle ◽  
Driver Assistance ◽  
The Road ◽  
Road Condition ◽  
Driving Condition ◽  
On The Road ◽  
Blind Spots

A vision-based driver assistance system using fuzzy rules to determine whether warnings are necessary is presented. This system is comprised of four cameras, one of which focuses on the driver for estimating the driver’s viewing angle, another focuses on the road ahead for the detection of road condition ahead, and the last two cameras are on both sides of the vehicle, facing backward, for the purpose of determining whether neighboring lanes are occupied by vehicles hidden in the blind-spots. The system uses fuzzy-rules for the analysis of interactions between the driver’s gaze, whether there are vehicles ahead, and in the neighboring lanes to determine whether the current driving condition should be of concern to the driver and issues one of three levels of warnings, from safe to dangerous.

scholarly journals User Preferences in the Design of Advanced Driver Assistance Systems

2021 ◽  
Vol 13 (7) ◽  
pp. 3932
Author(s):  
Sara Paiva ◽  
Xabiel García Pañeda ◽  
Victor Corcoba ◽  
Roberto García ◽  
Próspero Morán ◽  
...  
Keyword(s):  
Driver Assistance System ◽  
User Preferences ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Special Importance ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
On The Road ◽  
And Behavior

The transport network and mobility aspects are constantly changing, and major changes are expected in the coming years in terms of safety and sustainability purposes. In this paper, we present the main conclusions and analysis of data collected from a survey of drivers in Spain and Portugal regarding user preferences, highlighting the main functionalities and behavior that an advanced driver assistance system must have in order to grant it special importance on the road to prevent accidents and also to enable drivers to have a pleasant journey. Based on the results obtained from the survey, we developed and present a working prototype for an advanced driver assistance system (ADAS), its architecture and rules systems that allowed us to create and test some scenarios in a real environment.

Road Parameter-Based Driver Assistance System for Safe Driving

2019 ◽  
Vol 2 (4) ◽  
pp. 253-262
Author(s):  
Sai Charan Addanki ◽  
Keyword(s):  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
The Road ◽  
Lane Tracking ◽  
Road Type ◽  
Key Aspects ◽  
Type Classification

One of the key aspects of Advanced Driver Assistance Systems (ADAS) is ensuring the safety of the driver by maintaining a safe drivable speed. Overspeeding is one of the critical factors for accidents and vehicle rollovers, especially at road turns. This article aims to propose a driver assistance system for safe driving on Indian roads. In this regard, a camera-based classification of the road type combined with the road curvature estimation helps the driver to maintain a safe drivable speed primarily at road curves. Three Deep Convolutional Neural Network (CNN) models viz. Inception-v3, ResNet-50, and VGG-16 are being used for the task of road type classification. In this regard, the models are validated using a self-created dataset of Indian roads and an optimal performance of 83.2% correct classification is observed. For the calculation of road curvature, a lane tracking algorithm is used to estimate the curve radius of a structured road. The road type classification and the estimated road curvature values are given as inputs to a simulation-based model, CARSIM (vehicle road simulator to estimate the drivable speed). The recommended speed is then compared and analyzed with the actual speeds obtained from subjective tests.

scholarly journals Automobile Collision Detection and Avoidance System

2020 ◽  
Vol 9 (3) ◽  
pp. 1835-1840
Keyword(s):  
Collision Detection ◽  
Road Safety ◽  
Driver Assistance System ◽  
Driver Assistance ◽  
Safe Driving ◽  
The Road ◽  
Audible Sound ◽  
On The Road ◽  
Audio Output ◽  
Safety Systems

Maintaining road safety and safe driving are the challenges faced by the driver. To support the drive, there are on board safety systems mounted in the vehicles. However, these systems display visual messages that distract the driver’s attention from the road. There is a need for a system that can indicate the situations by keeping the attention of the driver on road. This paper is a proposal of a method that can be used to assist the drives while driving by generating the audio output based on the situation. According to research, driver assistance system is a solution for minimizing the time and frequency of drivers moving their eyes off traffic. Different approaches to assist the driver are discussed in this paper along with the challenges involved in executing them. The implementation is carried out using Arduino board and other hardware. The method is tested on samples to generate an audible sound that can be used by the drive to take suitable decision, by keeping eye on the road. This minimizes the need for the driver to look around while driving

scholarly journals Design and Implementation of Driver Assistance System using Machine Learning

2020 ◽  
Vol 994 ◽  
pp. 012006
Author(s):  
D. S. Bhargava ◽  
N. Shyam ◽  
K. Senthil Kumar ◽  
M. Wasim Raja ◽  
P Sivashankar.
Keyword(s):  
Machine Learning ◽  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance ◽  
Design And Implementation

Development of a Driver Assistance System

2003 ◽  
Author(s):  
Shinnosuke Ishida ◽  
Jun Tanaka ◽  
Satoshi Kondo ◽  
Masahito Shingyoji
Keyword(s):  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance

Car Drivers' Pattern of Eye Fixations on the Road and in the Laboratory

1981 ◽  
Vol 52 (2) ◽  
pp. 515-522 ◽  
Author(s):  
Amos S. Cohen
Keyword(s):  
Experimental Design ◽  
Traffic Situation ◽  
The Road ◽  
Eye Fixations ◽  
Driving Condition ◽  
On The Road ◽  
Task Oriented ◽  
As If

Car drivers' eye fixations were registered while driving a car on the road or when in the viewing a slide which showed the same traffic situation. Even when the subjects of the second group were instructed to observe the slide presented as if they were driving there, they fixated their eyes on well-defined targets with quite different frequencies than those motorists who actually drove the car on the road. Furthermore, prolonged fixation times were observed in the laboratory as compared to the road-driving condition. The magnitude of the obtained differences was rather great. The results suggest that the subjects on the road fixated more task-oriented targets and also picked up more information per time unit than their counterparts in the laboratory. The results are discussed in relation to the experimental design.

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