AUTONOMOUS VEHICLE IN FUTURE TRANSPORTAION PRESENTED BY : JEEVAN ABRAHAM JOJI OUTLINE OF PRESENTATION INTRODUCTION OBJECTIVE BRIEF HISTORY TECHNOLOGY USED APPLICATIONS ADVANTAGE AND LIMITATIONS OF DRIVERLESS CAR FUTURE CONCLUSION REFERENCES WHY AUTONOMOUS ? DRIVER ERROR IS THE MOST COMMON CAUSE OF TRAFFIC ACCIDENTS BREAKING LAWS AND FAILURE IN TAKEING SUDDEN DECISIOINS ADDS UP TO THE FACTORS CELL PHONES IN CARS ,CARELESS DRIVES,LACK OF SKILL,EXHAUSTED DRIVERS MAKES IT MORE FREQUENT THE FULLY AUTONOMOUS CARS POSSES THE TECHNOLOGY WHICH DRIVES IT THE SAFEST WAY POSSIBLE AND HAVE BEEN PROVED SUCCESSFUL IN THIS CONTEXT TILL NOW The fully autonomous cars posses the technology which drives it the safest way possible and have been proved successful in this context till now . AUTONOMOUS VEHICLE An autonomous vehicle (AV) is a vehicle that is capable of sensing its environment and operating without human input. AVs use a combination of sensors, cameras, and advanced algorithms to perceive their surroundings and make decisions about how to move and respond to different situations. These vehicles can navigate, accelerate, brake, and steer on their own, and can also make decisions about when to change lanes, merge onto a highway, or avoid obstacles. AVs have the potential to improve safety on the roads, reduce traffic congestion, and increase mobility for people who are unable to drive. We cannot compare this with the “Autopilot” system we are familiar of . The difference here is that , the autopilot system just make the vehicle move in a predefined path or a straight path , but this system drives the vehicle through any roads of varying traffic density and topography , in the safest way . The passenger just has to feed in the destinations he want to reach and the car will take him to the destination . HISTORY OF AV The history of autonomous vehicles can be traced back to the early 20th century when inventors and engineers began experimenting with the idea of self-driving vehicles. However, it wasn't until the late 20th century that significant advancements in technology and research began to pave the way for the development of fully autonomous cars. In the early 2000s, car manufacturers such as MercedesBenz and Volvo began to develop and test autonomous cars, with features such as lane keeping assistance and adaptive cruise control. In the 1980s and 1990s, researchers at universities and government agencies began experimenting with autonomous cars, using sensors and cameras to allow the vehicles to perceive their surroundings and make decisions. In recent years, more companies and organizations have been investing in the development of autonomous cars, and several cities and countries have started testing these vehicles on public roads. In the 2010s, companies such as Google and Tesla began to develop fully autonomous cars, using advanced algorithms and machine learning to allow the vehicles to navigate and operate without human input. While the technology is still developing, it is expected that fully autonomous cars will become more widely available for purchase in the coming years, with the potential to transform the way we move and transport goods. Working of autonomous vehicles Autonomous vehicles use a combination of sensors and software to navigate and drive without human input. These sensors include lidar, radar, cameras, and ultrasonic sensors, which gather data about the vehicle's surroundings. This data is then processed by the vehicle's on-board computer, which uses advanced algorithms to make decisions about how to navigate and control the vehicle. The vehicle's software also includes a mapping system, which allows the vehicle to understand its location and navigate to its destination. autonomous vehicles can communicate with other vehicles and infrastructure, such as traffic lights and road signs, to improve their understanding of the environment and make better driving decisions. The systems used in the car are LIDAR( Light Detection And Ranging) . Inertial Measurement Unit Position Estimators GPS( Global Positioning System) Long range Radar System Ultrasonic Sensors Video Cameras How do they look like WHY TOO MUCH CAMERA AND SENSORS ? Long range radar system Long-range radar is a key sensor used in autonomous vehicles to detect and track objects at a distance. It works by emitting a radio frequency (RF) signal and measuring the time it takes for the signal to bounce back after it hits an object. The radar can then use this information to calculate the distance and relative velocity of the object. Long-range radar typically has a range of several hundred meters and can detect objects in a wide field of view, making it useful for detecting and tracking vehicles, and other objects on the road. It can detect objects even in bad weather conditions like fog, rain or snow. In addition to providing range and velocity information, long-range radar can also be used to detect the shape, size and material of an object, which can be used for object classification and identification. LIDAR SYSTEM The Light Detection And Ranging system can be considered as the eye of the car . It is a remote sensing technology which measures distance by illuminating a target with a light beam and analyses the reflected light . It uses Laser beams , ultra violet , visible light or near infrared light to image objects . It can target a wide range of materials . Here , a narrow laser beam is used , which maps physical structures with a high resolution . The system uses Laser beams of wavelength 1550 nm which are “ eye-safe”. The basic LIDAR system consists of a Laser range finder beam reflected using a rotating The laser beam is scanned around the scene to be digitized , in 3 Dimensions using an array of similar systems , gathering distance measures at specified angle intervals . The detector part uses two main technologies , Solid State Photo detectors and Photomultipliers. The LIDAR sensors require info about their orientation and position , which they obtain from the GPS and the Inertial Measurement Unit . CAMERA The camera in an autonomous vehicle is used for visual perception and navigation. It captures images of the surrounding environment and uses computer vision algorithms to interpret and understand the information. The camera is typically mounted on the exterior of the vehicle and can be positioned in various locations, such as the front, rear, sides, or top. It can also be equipped with different types of lenses and sensors, such as infrared or lidar, to improve its performance in different lighting and weather conditions. The camera plays a critical role in the vehicle's ability to detect and respond to obstacles, pedestrians, and other vehicles on the road. It also helps the vehicle understand traffic signs, signals, and lane markings, allowing it to make informed decisions about its path and speed. The camera data is also used for mapping and localization, allowing the vehicle to accurately track its location and navigate to its destination. In addition to its role in navigation, the camera can also be used for other purposes such as monitoring the vehicle's cabin and identifying passengers. MEDIUM RANGE RADAR Medium range radar can provide detailed information about the environment around an autonomous vehicle, including the location and movement of other vehicles, pedestrians, and obstacles. This type of radar can detect objects at a distance of up to several hundred meters, which is useful for navigation in busy urban environments. Medium range radar can also be used to detect and track moving objects, such as other vehicles on the road, which can help the autonomous vehicle make decisions about its own movement and trajectory. In addition to providing information about the environment, medium range radar can also be used for collision avoidance and safety systems, such as automatic emergency braking. Medium range radar can also be integrated with other sensor systems, such as cameras and lidar, to provide a more complete and accurate picture of the environment. The use of medium range radar in autonomous vehicles can also improve traffic flow and reduce the risk of accidents by allowing the vehicle to make more informed decisions about its movement and trajectory. ULTRASONIC RADAR Ultrasonic radar is a type of sensor that uses high-frequency sound waves to detect and measure the distance of objects. It is commonly used in autonomous vehicles to detect and avoid obstacles in the vehicle's path. Ultrasonic radar is a low-cost alternative to lidar and other types of radar, making it an attractive option for use in autonomous vehicles. It is able to detect objects in close proximity to the vehicle, making it useful for detecting pedestrians, bicycles, and other small objects that may be difficult to see with traditional sensors. Ultrasonic radar can also be used to measure the distance to a nearby object, which can be used to determine the vehicle's speed and distance from other objects. The ultrasonic radar sensor can be integrated into the vehicle's existing sensor suite, allowing for a more comprehensive understanding of the vehicle's surroundings. . The technology is also more durable and can withstand harsh weather conditions and extreme temperatures. Ultrasonic radar can help autonomous vehicles to navigate in low visibility conditions such as fog, rain, and snow. With ultrasonic radar, autonomous vehicles can detect obstacles even in the dark which can greatly increase the vehicle's safety. The use of ultrasonic radar in autonomous vehicles can help to improve the overall safety and reliability of the vehicle, making it a valuable addition to any autonomous vehicle sensor suite.
