iCar

About the project:

This was my final year engineering project and objective of this project was to reduce road accidents by assisting drivers in various aspects of driving by using modules such as lane detection, pedestrian & car detection, driver drowsiness detection and rear view parking assistance.

This project was selected as one of the “Top 10 projects in India” by Quest Ingenium 2013. It won the “Best Project – Quests Employees Choice” award in the same event. The project was funded by Karnataka State Council for Science & Technology. We published our research in the Science, Technology and Arts Research Journal from Wollega University.

The implementation combines computer vision techniques with pattern recognition, feature extraction, machine learning, object recognition, human computer interaction and parallel processing. This system provides robust extraction of lane markings in various types of roads and alerts the driver attempting to drift away from the lane. It also detects pedestrians & cars vulnerable to be hit by the vehicle and alerts the driver in time. The system uses eye closure based decision algorithm to detect driver drowsiness in all conditions and also warns using an interactive voice. It also assists the driver while reversing the vehicle, by providing a clear view of his blind spot areas. Computer vision algorithms like Hough’s Transform, Canny Edge detection and HAAR classifiers were applied to meet the objectives. The integrated module was analysed and tested in different terrains and under various lighting condition to produce an accurate and robust real-time assistance system. iCar is an innovative prototype with minimum hardware like low cost webcams and speakers.

Motivation

Despite safety advancements such as seat belts and airbags, cars remain the most dangerous mode of transportation, compared to aeroplanes, buses or trains. According to the annual statistics by our Ministry of Road Transport and Highways , nearly 5 lakh people die due to car crashes in India. The analysis of road accidents in terms of casual factors reveal that the driver’s fault, (79%) is the single most important factor responsible for accidents, fatalities and injuries.

These statistics are related to Indian roads, but we have similar statistics all around the world. Lack of assistance in the field of lane detection, driver drowsiness, pedestrian detection and night vision are the main causes of these accidents. Due to alcohol/drugs consumption, a driver tends to loose control and go off-lane, which can corrected by integrating a lane detector in the car. The accidents occurring at night can be prevented by the use night vision assistance and driver drowsiness recognition system. Sometimes the driver is not able to judge a pedestrian/animal crossing the road due to speeding or violation of traffic rules. This can be prevented by using a pedestrian detection system.

Team

Ms. Anusha Shetty, Mr. Zarif Ahmed, Mr. Nissar and me under the guidance of Mr. Hemanth Kumar

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