Autonomous vehicle technology has been a major research and development 
topic in the automotive industry during the last decade.The Second generation of driver
assistance systems was introduced around the 1990s based on sensors that measure the 
external state of the vehicle with the focus of providing information and warnings to the 
driver.Figure 1: Evolution of Advanced Driver Assist Systems
The following sensors that measure conditions outside the vehicle, and vehicle 
position relative to its environment are essential in driving assist systems and 
autonomous vehicle technologies: Vision, LIDAR, RADAR, ultrasonic range, GPS, and 
inter-vehicle communication.Prominent sensors such as LIDAR, GPS, radar, 
vision, ultrasonic and inertial measurement unit, their working principle and usage are 
discussed in the following sections.LIDAR transmits a beam of light pulse from a rotating mirror, part of that light 
will reflect back to the sensor to detect any non-absorbing object or surface (Figure 4).Using the calculated distance, the sensor constructs a 3D map of the world 
including the objects around it. LIDAR uses infrared (IR), visible or ultraviolet (UV) 
waves of the electromagnetic spectrum for different applications and comes in various
1D, 2D and 3D configurations.Active safety and driver assistance system that intervene to avoid and/or 
mitigate an emergency situation and then immediately disengage are also not included 
for the various levels of automation.The short-term goal is to automate driving in select well-defined situations as 
implemented by some of the technology companies, for example testing of self-driving 
taxi cabs in well-defined suburbs.The technologies developed in 
the automotive industry also has direct applications in construction, mining, agricultural 
equipment, seaborne shipping vessels, and unmanned aerial vehicles (UAVs).The latest generation of Driver Assist Systems (DAS), 
also called Advanced Driver Assist Systems (ADAS), defines and controls trajectories
beyond the current request of the driver, i.e. overriding driver commands to avoid a 
collision.The embedded control software development (that includes data fusion
from sensors, inter-vehicular communication, real-time cloud computing support) is the 
key technical challenge.A high-end LIDAR sensor can measure multiple distances per 
laser pulse which is helpful to see through dust, rain and mostly transparent surfaces 
such as glass windows and porous object like wire fences.Despite the heavy
intensity of investment in technology development, it will still take a few decades before 
an entirely autonomous self-driving vehicle navigates itself through national highways 
and congested urban cities [1].Some current ADAS examples include traffic jam 
assist, collision avoidance assist, pedestrian and oncoming traffic detection systems.Data 
fusion strategies that combine real-time information from these multiple sensors is an 
important part of the embedded control software.Actuation technologies, i.e. computer 
control steering, throttle, transmission, and braking, are mature and do not present any 
R&D challenges.Echoes sensed vary in frequency depending on the speed of the object.30), 
medium (?2.2.3.