Autonomous Vehicles - KPIT

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on road. The technology that is developed in making ADAS, directly or indirectly, contributing to the development of a driverless car and importantly further development of ADAS will create an autonomous environment. I V . W o r k d o n e a t K P I T Technologies KPIT, as a technology provider, is making efforts in developing technology required for ADAS. In last 5 years, KPIT has developed multiple ADAS features, published 28 technical papers and filed for 9 patents. Research at KPIT has advanced to deal with multiple hurdles such as sensor variability, real life challenges, and performance issues. It has led to the development of new technology, sensor know-how, object detection algorithms, hardware optimization, control algorithms, multicore expertise, critical test methodologies and vehicle integration. Figure 6: Major Challenges while developing Camera Based Driver Assist System Features such as Pedestrian Detection, Forward Collision Warning, Lane Departure Warning, Blind Spot Monitoring, Traffic Sign Recognition, Advanced Beam Control and Driver Status Monitoring constitute major portion of a complete ADAS system. Our focus has been on development of all these features. These algorithms are configurable for different vision sensors and are independent of the hardware platforms. Different countries have different traffic patterns, road and lighting conditions. Therefore, rigorous testing under multiple scenarios and tuning of algorithms is very important in order to ensure stable behavior of the algorithms. ADAS Collision Avoidance Light Control FCW LDW TSR ACC LKA NVPD ABC Vision Systems under development lFCW - Forword Collision Warning lLDWS - Lane Departure Warning System lTSR - Traffic / Road Sign Recognition Successfully Integrated complex systems lACC - Adaptive Cruise Control lLKA - Lane Keep Assist System Successfully developed and delivered complex vision systems lNVPD - Night Visison with Pedestrian Detection lABC - Advance Beam Control Camera based Solution Figure 7: ADAS Development at KPIT KPIT has setup a vehicle that is used to collect data in India. It has also collected test data in other countries. This data is being used to carry out the lab tests of the algorithms, understand and handle peculiar use cases. A dedicated team of engineers has successfully handled multiple challenges in implementing these systems on a passenger car in a real time environment and is working towards making these systems operational under different lighting, weather, road and traffic conditions. KPIT's advanced research team is also keeping an eye on future challenges and has developed technologies for Rain Drop Removal, Video Stabilization, Noise Handling, Image Enhancements and multicore migration tool. KPIT has also developed configurable software algorithms for Vehicle Control. These algorithms are compliant with AUTOSAR and they are used in ACC (Adaptive Cruise Control), LKA (Lane Keep Assist) and BSD (Blind Spot Detection). The Architecture and Verification strategies of these algorithms are in compliance with the ISO 26262 Functional Safety Standards and also support future sensor fusion applications. Leveraging on its spread and success in areas of automotive, KPIT is also providing integrated solutions of ADAS with infotainment, chassis and brakes. V. Patents filed by KPIT Keeping its focus on research, innovation and frugal engineering, KPIT has filed number of patents and publications in this area. 30 TechTalk@KPIT, Volume 6, Issue 4, 2013
Sr. No. Table 1: List of patents filed by KPIT on ADAS Patent Title 1 Method and System for pedestrian detection using Wigner Distribution 2 Method and system for image enhancement using Wigner distribution 3 A System for Real-Time Image Correction for Curvilinear Surfaces 4 Pedestrian Detection and Tracking System 5 An Image Enhancement and Pedestrian Detection System 6 A System For Detecting, Locating And Tracking A Vehicle 7 System and Method for Depth Imaging 8 A System and Method for Performance Characterization 9 Straight Line Detection Apparatus and Method KPIT has gained valuable experience while developing these systems from concept level to the production level and has proved a right partner for many OEMs and Tier-1s in the area of ADAS. VI. Into the future The journey into the world of autonomous vehicle through ADAS will continue to challenge the industry, transport and safety administrative bodies, researchers and engineers in many ways. It would be interesting to see how it will attract consumers and the shareholders. From the fusion of sensors to the control of multiple ECUs, from development of platform to the optimization of various critical resources, the technology is advancing very fast. Many technology providers are in the process of developing and expanding their ADAS technologies for a driverless car. Media is also upbeat about the technology. Whether it's news from Google about launching of Robo-Taxis [3] or announcement of Singapore's first electric autonomous vehicle NAVIA [4], we have seen the glimpses of future transportation. ADAS will continue to grow and will act as a stepping stone for future cars. Very soon we will see Advanced 'Driver' Assist Systems, no longer be assisting the drivers but driverless cars! References [1] Paul Stenquist, “Nissan Announces Plans to Release Driverless Cars by 2020”, August 29, 2013. Available: http://wheels.blogs.nytimes.com/ [2] http://www.navigantresearch.com/newsroom 2013/08/29/nissan-announces-plansto-release-driverless-cars-by-2020/?_r=0 /autonomous-vehicles-will-surpass-95-million-inannual-sales-by-2035 [3] http://www.indiatimes.com/boyz-toyz/cars-and- bikes/a-fleet-of-robotaxis-to-drive-you-into-the- future-97607.html [4] http://www.asianscientist.com/tech-pharma/ntujtc-navia-first-electric-autonomous-vehicle-2013/ TechTalk@KPIT, Volume 6, Issue 4, 2013 531
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 and 24: Seeing Through Sensors About the Au
Page 25 and 26: Figure 1: A robotic Volkswagen Pass
Page 27 and 28: Figure 4: Infrared image of a stree
Page 29 and 30: Bringing Vision to Life About the A
Page 31: Radar needs an attention, there exi
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

Autonomous Vehicles - KPIT

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