Autonomous Vehicles - KPIT

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I. Introduction Are you still pondering about a car which has an autopilot option to drive and has an independent braking system with zero tolerance over the road accidents? Are you thinking of a car like Bat mobile in Batman which drives itself from parking lot with just a message like “Please come and pick me up at Gate-4”? And are you thinking of a system which helps to keep your car in a particular lane, pick your navigation, and help you to park your car without troubling you? If it is so, then “Please wake up from dreaming and see the reality”. Artificial Intelligence Laboratory all over the world has been working and some of them even proved operation of the dreamed autonomous systems in cars. In May 2012, Google driverless car became the first autonomous car to get a licence and hence became the first to register this successful story in the history. Google's unmanned car is proved to run as good as a skilled driver and has travelled around 50000 Kms from the day of inception to August 2012 without any accidents [1]. Similarly, Chinese military has also claimed to have an autonomous car that was tested for over 100 kms [14]. Despite disadvantages like high purchase and maintenance cost, it has too many advantages to emphasis its impact on the future car market and an ability to create tough competition for the conventional cars. With this brief other set of questions come in mind like “How does an unmanned car work?” and “Can an autonomous system make driving as reliable as the one by a human driver?” This article is intended to provide some clarity on different types of sensors deployed on the unmanned vehicles. In addition to giving clarity, a brief introduction about the autonomous car is given in the article. An unmanned vehicle is a vehicle controlled remotely or capable of sensing their environment and navigating on their own. World's first modern driverless car (63 Km/hr) has been developed by Mercedes-Benz and Bundeswehr University Munich in 1980 and since then, more advances have been made in robotic car technologies [2]. As of 2013, major companies such as Mercedes-Benz, General Motors, Google, Continental Automotive Systems, Autoliv Inc., Bosch, Nissan, Toyota, and Audi have developed working prototype of autonomous vehicles and are currently competing to commercialise their models of fully autonomous vehicles. Currently, different systems such as Autonomous Cruise Control, In-vehicle Navigation, Blind Spot Monitoring, Automatic Parking and Traffic Sign Recognition have been incorporated into the robotic cars and used significantly. Each of the mentioned systems has its own application and utilises different types of sensors to disable human interface in the autonomous cars. Autonomous Cruise Control (ACC) generally uses LIDAR or Radar to derive distance of vehicles ahead and automatically adjust its speed or enable brake support to maintain a safe distance. In-vehicle navigation system utilises Global Positioning System (GPS) for providing up-to-date information about traffic and automatically finds optimum way to commute. Blind Spot Monitoring (BSM) system uses cameras to check for any impending collision in the blind spots while changing lanes. Automatic Parking System (APS) uses sensors installed on front and back bumpers to automatically park the car within the available space. Traffic Sign Recognition (TSR) system utilises cameras to identify traffic signs which are on the road and helps the car to automatically adjust its speed accordingly. Thus, these sensors act analogous to eyes and ears of the driver. Control system of autonomous car acts similar to driver's brain which is required to operate different sub-systems of autonomous car. This tells us that there will not be any unmanned vehicles without any sensors and control system. Knowing its importance, a brief introduction about various sensors like Camera, LIDAR, Radar, Ultrasonic, and Infrared sensors are presented along with a very short description about GPS and Carputer, a mobile computer designed to run in cars. 22 TechTalk@KPIT, Volume 6, Issue 4, 2013
Figure 1: A robotic Volkswagen Passat with cameras and other sensors [3] II. Cameras and stereo vision Cameras are the optoelectronic device used to capture a real 3D scene into a 2D image plane. While acquiring an image, the continuous real scene is discretised into pixels and hence provides information about the scene in discretised format. Cameras are widely used in unmanned vehicles to acquire information about the scene and the captured data is processed to help self-driven robotic cars. Cameras can replicate driver's eyes in autonomous cars. By keeping more cameras, it can be used to identify the objects in blind spot region (which is handled by Blind Spot Monitoring) while changing lane as well as in parking (which is handled by Automatic Parking System). Some of the applications of cameras in autonomous cars include detecting lanes, obstacles, neighboring vehicles, and traffic signals. Usage of cameras provides flexibility for autonomous vehicles because it can be used in adverse climate. The images acquired in hazy environment can be converted to similar images taken in normal condition using postprocessing technique called “De-weathering”. Similarly, there are many post processing techniques which can convert corrupted image into an image taken at normal condition. Some of the post-image processing techniques are fog, smoke and rain drop removal, image de-blurring and low light image enhancement. The ability to postprocess the image acquired makes the cameras inevitable for unmanned vehicles. A low cost scientific camera with 400 frames/second and 1.5 megapixels resolution is available for 350 USD in the market [12]. Stereo vision is a computer vision technique which utilises two cameras facing the same direction to produce 3D view of the real 3D scene by just acquiring images. This technique helps to recreate the 3D view of the scene and facilitate the system to recognise objects and analysis motions [4]. Hence computer vision technique along with image processing techniques are utilised in o autonomous car to generate 360 view of the actual scene. This recreation of 3D view enables the car to see everything around it and make decisions about every aspect of driving. As the cost of cameras is driving down, m o s t o f c o m p a n i e s i n t e r e s t e d i n manufacturing autonomous cars are trying to adopt vision based system for sensing the surroundings. As mentioned, stereo vision setup requires two cameras mounted on a flat plate or fixture and hence it cost depends on the cameras opted. III. Laser interferometry detection and ranging technology (LIDAR) LIDAR uses spinning lasers and photoelectric diodes to create a virtual model of its surrounding. It works by illuminating the scene with laser and detecting the reflected ray using photoelectric diode. The time taken by the laser is determined and used to measure distance of the object from the laser. The same principal is followed while using the spinning lasers and diodes to recreate the 3-D surface of the scene (see Fig. 2). The resolution of the reconstructed scene can be improved by increasing the frequency of spinning lasers and the number of lasers. The ability of the laser to reflect back from wide range of objects is due to high energy and shorter wavelength. But due to its harmful effects on human eye and high cost, this technique becomes less preferable than camera based vision. In market, LIDAR capable of producing 6000 points per second can be purchased for $6000 USD while 1.3 million data points per second for $75,000 USD [8]. TechTalk@KPIT, Volume 6, Issue 4, 2013 523
Page 1 and 2: TechTalk@KPIT a quarterly journal o
Page 3 and 4: Contents Editorial Guest Editorial
Page 5 and 6: Dr. Vinay G. Vaidya CTO KPIT Techno
Page 7 and 8: Journey Without Driver About the Au
Page 9 and 10: A. Stanford Cart - The First Smart
Page 11 and 12: autonomous vehicles in 2004. The Gr
Page 13 and 14: obtained by laser range finder. The
Page 15 and 16: To Be or Not To Be... A Driver Abou
Page 17 and 18: When the autonomous vehicle complet
Page 19 and 20: ultrasonic sensors, etc. provide vi
Page 21 and 22: Scientist Profile Sebastian Thrun S
Page 23: Seeing Through Sensors About the Au
Page 27 and 28: Figure 4: Infrared image of a stree
Page 29 and 30: Bringing Vision to Life About the A
Page 31 and 32: Radar needs an attention, there exi
Page 33 and 34: Sr. No. Table 1: List of patents fi
Page 35 and 36: Drive-By-Wire : A KPIT Case Study A
Page 37 and 38: the operational accuracy, it is har
Page 39 and 40: DRIVERS BRAKE HYDRAULIC MOTOR Manua
Page 41 and 42: Wired Through Wireless About the Au
Page 43 and 44: FORWARD OBSTACLE DETECTION AND AVOI
Page 45 and 46: Microcontroller Abstraction Layer (
Page 47 and 48: Autonomous Intelligent Vehicles Aut
Page 49 and 50: Inside Connected Vehicle About the
Page 51 and 52: D. Communications security (COMSEC)
Page 53 and 54: security built-in from the very beg
Page 55 and 56: Gazing Through a Crystal Ball About
Page 57 and 58: Thus, from a passenger acceptance a
Page 59 and 60: About KPIT Technologies Limited KPI

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