Real Time Eye Detection and Tracking Method for Driver Assistance System

Autonomous vehicles and advanced driver assistance systems are predicted to provide higher safety and reduce fuel and energy consumption and road traffic emissions. Lane detection and tracking are the advanced key features of the advanced driver assistance system. Lane detection is the process of detecting white lines on the roads. Lane tracking is the process of assisting the vehicle to remain in the desired path, and it controls the motion model by using previously detected lane markers. There are limited studies in the literature that provide state-of-art findings in this area. This study reviews previous studies on lane detection and tracking algorithms by performing a comparative qualitative analysis of algorithms to identify gaps in knowledge. It also summarizes some of the key data sets used for testing algorithms and metrics used to evaluate the algorithms. It is found that complex road geometries such as clothoid roads are less investigated, with many studies focused on straight roads. The complexity of lane detection and tracking is compounded by the challenging weather conditions, vision (camera) quality, unclear line-markings and unpaved roads. Further, occlusion due to overtaking vehicles, high-speed and high illumination effects also pose a challenge. The majority of the studies have used custom based data sets for model testing. As this field continues to grow, especially with the development of fully autonomous vehicles in the near future, it is expected that in future, more reliable and robust lane detection and tracking algorithms will be developed and tested with real-time data sets.

Download Full-text

Hardware Simulation of Active Lane Keeping Assist Based on Fuzzy Logic

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v5.i2.pp321-326 ◽

2017 ◽

Vol 5 (2) ◽

pp. 321 ◽

Cited By ~ 3

Author(s):

Noor Cholis Basjaruddin ◽

Kuspriyanto Kuspriyanto ◽

Didin Saefudin ◽

Alditama Rachman

Keyword(s):

Fuzzy Logic ◽

Real Time ◽

Driver Assistance System ◽

Assistance System ◽

Advanced Driver Assistance System ◽

Toll Roads ◽

Test Results ◽

Driver Assistance ◽

Lane Departure ◽

Lane Keeping

Accidents due to cross the lane (lane departure crash) of achieving 19% of all accidents. These accidents mostly caused because the driver is not concentrating or dozing. A device that can help the driver so that the vehicle does not exit lanes known as Active Lane Keeping Assist (ALKA). ALKA is a subsystem of Advanced Driver Assistance System (ADAS) and is now used in several brands of cars namely Audi, BMW, and Ford. ALKA useful to help the driver, especially on roads with monotonous situations such as toll roads. This paper presents the development of fuzzy logic-based algorithm for ALKA. A battery toy car is used as a hardware simulation to test the algorithm in real time situation. The test results at three different speeds are slow, medium, and high indicate that the algorithm can work according to design.

Download Full-text

Reconfigurable HW/SW Architecture of a Real-Time Driver Assistance System

Lecture Notes in Computer Science - Reconfigurable Computing: Architectures, Tools and Applications ◽

10.1007/978-3-540-78610-8_16 ◽

2008 ◽

pp. 149-159 ◽

Cited By ~ 2

Author(s):

Josef Angermeier ◽

Ulrich Batzer ◽

Mateusz Majer ◽

Jürgen Teich ◽

Christopher Claus ◽

...

Keyword(s):

Real Time ◽

Driver Assistance System ◽

Assistance System ◽

Driver Assistance

Download Full-text

A Centralized Real-Time Driver Assistance System for Road Safety Based on Smartphone

Advanced Microsystems for Automotive Applications 2012 ◽

10.1007/978-3-642-29673-4_20 ◽

2012 ◽

pp. 221-230 ◽

Cited By ~ 7

Author(s):

Andrea Corti ◽

Vincenzo Manzoni ◽

Sergio M. Savaresi ◽

Mario D. Santucci ◽

Onorino Di Tanna

Keyword(s):

Real Time ◽

Road Safety ◽

Driver Assistance System ◽

Assistance System ◽

Driver Assistance

Download Full-text