Autonomous Vehicles - KPIT

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per image at a range of 100 meters. The car was able to recognize road markings, its relative position in the road and the presence of other vehicles. Later in a test drive, with simulated traffic near Paris, the car drove with a speed of 130 km/h (81 mph), even judging whether it was safe to change lanes. This was considered as an important milestone in the evolution of autonomous vehicles. Dickmann's team drove a Mercedes S-Class car from Munich to Odense. It was 1,600 kms trip that was completed with a speed of 180 km/h (112 mph). The car travelled about 95% of the total distance fully automatically [7]. The main attraction of the above two projects are the cameras used. The camera configuration used for the above two projects is MarVEye (Multi-focal active / reactive Vehicle Eye) [6]. A pan-tilt camera head (TaCC) is used in the cars in both the projects and the MarVEye camera is mounted on that. The viewing direction of the TaCC can be controlled in pan by turning plus/minus 70° and a good horizontal coverage can be obtained. Figure 3 and 4 show the TaCCs of the test vehicles VaMoRs and VAMP [6]. Figure 3: TaCC of VaMoRs[6] C. EUREKA Prometheus Project Figure4: TaCC of VaMP[6] One of the largest research happened in the area of implementing driverless cars, is Prometheus (PROgraMme for a European Tr a ff i c o f H i g h e s t E ff i c i e n c y a n d Unprecedented Safety) project by the European Commission named EUREKA [16]. They offered more than 1 billion dollars to the participants. Ernst Dickmanns and his team were the key participants. The race started with twin robot vehicles, VaMP and VITA-2 and could travel around 600 miles in Paris multilane highway during heavy traffic condition. This project really encouraged further research in area of development of driverless cars. Figure 5 shows the inner view of the car used for the project. Figure 5: Inner view of vehicle used for Prometheus project [16] D. NavLab 5 Navlab 5, shown in Fig. 6, used for on-road navigation experiments was introduced in 1990 [2]. Navlab 5 is a Pontiac Trans Sport model. It has a PANS (Portable Advanced Navigation Support) platform, which provides a computing base and input/output environment for users. The power source for PANS platform is vehicle's cigarette lighter, which is completely portable. In addition, the PANS platform supports steering wheel control, position estimation and safety monitoring. Some of the researchers from Carnegie Mellon University drove NavLab 5 in 1995 from Pittsburgh to Los Angeles [7]. The car supported lane keeping for more than 600 miles because of the availability of PANS platform. NavLab 5 could complete almost 98% of the total distance fully automatically with a negligible help for obstacle avoidance. Figure 6 : NavLab 5 [2] Figure7: PANS inside the Navlab 5 [2] E. Grand Challenges by DARPA (Defence Advanced Research Projects Agency) A great milestone in the evolvement of autonomous vehicles is the first long-distance competition organized by DARPA for 8 TechTalk@<strong>KPIT</strong>, Volume 6, Issue 4, 2013
autonomous vehicles in 2004. The Grand Challenge inaugural race was a 150-mile course through Mojave. Out of the 15 vehicles competed in the race, Carnegie Mellon's Red Team Racing – 'Sandstorm', shown in Fig. 8, completed 7.3 miles [7]. Sandstorm was introduced as a 1986 model 998 HMMWV (High Mobility Multi-purpose Wheeled Vehicle) [8]. Sandstorm has a fresh engine and suspension. In addition, the shock isolation capability of Sandstorm softens the ride for computers and sensors. Acceleration control, braking and shifting of the vehicle are handled by drive-by-wire modifications. The inter module communication is accomplished through TTP (Time Triggered Protocol).The vital sensors of Sandstorm are vision, radar, laser, and GPS sensors. Later in 2005, DARPA organized a Grand Challenge with doubled prize money ($2 million). Around 23 teams participated for the 132miles race through Mojave. Five of them could reach the finishing point. On the race path, there were 3 tunnels and more than 100 turns. In addition, the vehicle had to navigate a steep pass with sharp drop-offs. It was really a challenging run. An autonomous Volkswagen Tourareg, named 'Stanley', shown in Fig. 9, by Stanford University won first place in the race and completed course in 6 hours and 54 minutes [7]. The special sensors present in Stanley, which help it to see road, include radar, lasers, and a camera system. Advanced computer system and artificial intelligence helped Stanley to have sense of its environment and avoid obstacles [9]. DARPA made things a little tougher in the grand challenge organized as a 60miles race in an urban environment in 2007. Eighty-nine teams entered for the race, and 11 made it to the start. The race path had 4 miles of k-rail enclosed streets, where entrants had to handle manned-vehicle traffic at the former George Air Force Base. Tartan racing team of Carnegie Mellon's university completed the race in 4 hours and 10 minutes with a Chevrolet Tahoe 'Boss', shown in Fig. 10 [7]. 'Boss' was developed by the Tartan Racing with the help of General Motors and other partners. The computer controls with radar and GPS systems help Boss to map the surrounding environment and detect potential obstacles. Boss determines safe driving routes by making use of lasers, intelligent algorithms, and computer software. Larry Burns, the GM Vice President of Research and Design, explains, "Not only can we use electricity in place of gasoline to propel the next generation of vehicles, the electronic technology in vehicles such as Boss can provide society with a world in which there are no car crashes, more productive commutes and very little traffic congestion" [12]. Figure 8: Sandstorm [7] Figure 9: Stanley [15] Figure 10: Boss [7] We can have a look in to some of the other researches happened during the same decade in all over the world. In ‘AHS (Automated Highway System) Demo'97' organized by San Diego, California, more than 20 fully automated vehicles traveled on a highway in San Diego. Another outstanding project was CARSENSE, which concentrated on slow driving in some hectic situations like traffic jam. Japan had also organized a demo race named 'AHSRA (Advanced Cruise-Assist Highway System Research Association) Demo 2000' around the same time, where the race showed how we can reduce road accidents by autonomous vehicles with limited driver intervention. During 2001 – 2004, a project ARCOS (Research Action for Secure Driving) is introduced by France, which was aimed to reduce road accidents by 30%. INVENT (Intelligent traffic and user-oriented technology) is another important research project in the area of introducing self-driving cars on road, by Germany. The main goal of the project was to reduce the traffic congestion and improve people's safety by using intelligent systems available in the autonomous vehicle. TechTalk@<strong>KPIT</strong>, Volume 6, Issue 4, 2013 59
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: A. Stanford Cart - The First Smart
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 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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