Obstacle Detection and Track Detection in Autonomous Cars

Abstract

This chapter illustrates the history and recent advancements in the field of Autonomous Vehicles with regard to two important concerns that play the most vital role in successful implementation and working of an Autonomous Car: (1) Obstacle Detection and (2) Track Detection. The car should be able to detect the obstacles for smooth and efficient working in order to avoid accident and collision. It should also be able to calculate the distance of the obstacle from the car. Similarly, Track Detection is also important as the autonomous car should stay within a predefined track and has to keep itself within the yellow lines on both sides of the road. This chapter elaborates the technologies and advancements that have been presented in the literature till date that deal with Obstacle Detection and Track Detection in Autonomous Cars/Vehicles.

Sharing the Road: Challenges and Strategies

“…Autonomous vehicles use a wide range of sensors to "see" the environment around them, collect the information and feed this collected data to the control system so that decisions can be made and required action can be taken. Cameras help to view objects; LiDAR (Light Detection and Ranging) sensors use light in the form of a laser to measure the distance between the object and the vehicle; RADAR (Radio Detection and Ranging) sensors detect the objects, measures their speed and the direction of their movement [17][18][19][20]. Ultrasonic sensors are also used that help to measure short distances at low speeds.…”

Protall (An Intelligent, multi-sensor, comprehensive obstacle avoidance system for automobiles and UAVs)

“…This system is designed to be robust and flexible as to work in any conditions and provide safety. The method as proposed in [3] illustrates recent advancements in Autonomous Vehicles regarding two critical concerns that play the most vital role in successfully implementing and working an Autonomous Car like Obstacle Detection and Track Detection. The work in [4] demonstrates the performance of LIDAR, RADAR, vision cameras, ultrasonic sensors and IR.…”

MuSLi: A multi sensor LiDAR detection for C-V2X networks

“…In the context of Internet of Vehicles (IoV) paradigm, as part of the Intelligent Transport System (ITS) and with the advent of autonomous vehicles, one of the most important functionality to be developed is the obstacle detection [6,7]. In order to develop advanced control systems for detecting obstacles, a combination of advanced sensors, radar and camera need to be considered for building an accurate environment perception.…”