LANE DETECTION USING COMPUTER VISION FOR SELF-DRIVING CARS

Self-Driving Cars

“Real-Time Lane Detection for Driving System Using Image Processing”

In the past decade a lot of research has been done on vision based real-time advanced driver safety system (ADAS). Many OEM car manufacturing companies have stressed their research on ADAS so as to increase the vehicle and driver safety. This work is aimed at developing an algorithm for on road lane departure warning (LDW) system. LDW can be successfully used for dropping the on road accidents ...

Computer Vision Based Object Detection and Recognition for Vehicle Driving

Applying computer technology to vehicle driving has been studied for many years. Most of the studies focused on autonomous vehicle driving in a simplified environment like freeways, or life independent systems like GPS. A general case where kind of unexpectedly fatal conditions may occur which we are driving in an urban area, however, has not been considered. In this paper, we proposed a system...

Responsibility and the Moral Phenomenology of Using Self-Driving Cars

This paper explores how the phenomenology of using selfdriving cars influences conditions for exercising and ascribing responsibility. First, a working account of responsibility is presented, which identifies two classic Aristotelian conditions for responsibility and adds a relational one, and which makes a distinction between responsibility for (what one does) and responsibility to (others). T...

Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information. This paper presents a deep neural network approach that unlocks the potential of event cameras on a challenging motion-estimation task: prediction of a vehicle’s steering angle. To make the best out of this sensor–algorithm combination, we adapt state-of-the-art con...