Investigation on Control Methods and Development of Intelligent Vehicle Controller for Automated Highway Systems P.Suresh ME11D045 Guide Dr. P. V. Manivannan Precision Engineering and Instrumentation Laboratory Department of Mechanical Engineering Indian Institute of Technology Madras Chennai 600036 1/15
Contents Contents Introduction Intelligent Vehicles Objectives of Research Success Stories References 2/15
Introduction Introduction Challenges in Road Transportation: Traffic Congestion High accident rate High Accident mortality Increase in Vehicle Population Government initiatives to tackle surface transportation problems: Conversion of 2 lane highways to 4 lane highways Building high speed expressways Golden Quadrilateral project Strict enforcement of traffic regulations These Initiatives have not been able to solve the problems. 3/15
Introduction The Single Most Important Factor for Road Accidents is: Human Error Drivers tend to commit errors when driving at very high speeds due to the following reasons: Fatigue Poor Visibility Deteriorated Road Conditions Adverse Weather Very small available response times Intelligent vehicles and Automated Highway Systems (AHS) will help in reducing the number of accidents and thus minimise loss of life and property resulting from accidents. 4/15
History of AHS & Intelligent Vehicles 1939 New York World Fair GM Futurama first formal introduction to the idea of AHS and autonomous vehicles 1953 scale model of AHS developed by GM and Radio Corporation of America 1958 GM tests full size passenger car with in-built guidance system Introduction 1960s Development of road centralised control system (Dr. Valdamir Zworykin from RCA). Circuits buried in the road to magnetically sense vehicle speed and location. 1980s a vision-guided Mercedes-Benz robot van, designed by Ernst Dickmanns, Bundeswehr University Munich DARPA-funded Autonomous Land Vehicle (ALV) in the United States 1987-1995- EUREKA Prometheus Project on autonomous vehicles 1994- twin robot vehicles Vamp and Vita-2 of Daimler-Benz drove semi autonomously 1995-the Carnegie Mellon University Navlab project-semi-autonomous car 1996-Alberto Broggi of the University of Parma launched the ARGO Project lane following achieved 1997-DEMO 97- Fleet of over 20 vehicles guided on a 7 mile stretch of Interstate 15 Highway north of San Diego, USA 2000- US Army funded DARPA DEMO I,II and III projects for autonomous vehicles over difficult road terrain. 2000-AHSRA Demo 2000 (Japan) - 38 cars, buses and trucks illustrated the ideal system for reducing road traffic accidents using driver information and control assist systems. The automation system made use of magnetic sensors on the road. 2001--the Carnegie Mellon University Navlab project-semi-autonomous car 2001-2003-Chauffeur II development of truck platooning by DaimlerChrysler, Renault, IVECO and Fiat 2009- SARTRE project-uk, Spain & Sweden- Platooning system with lead vehicle controlled by a professional driver 2010 -VisLab ran VIAC, the VisLab Intercontinental Autonomous challenge, 13000 KM test run of autonomous vehicles. 2011- First successful trial of SARTRE project was in Jan2011 at Volvo Test Track in Sweden-single car was slaved behind a rigid truck. 5/15
Intelligent Vehicles (Driverless Cars) Intelligent vehicles Vehicles equipped with an autopilot system --- capable of driving without input from a human driver. Advantages of intelligent / autonomous vehicles are: Relief from driving and navigating task Accident prevention Increased roadway capacity Traffic congestion reduction Increased safety due to elimination of driver error 6/15
Intelligent Vehicle Sub-systems Intelligent vehicles Steering controller Braking controller Obstacle avoidance controller Master controller Engine controller (ECU) Lane following controller Transmission controller Fig. 1 Vehicle sub-systems 7/15
Sensors Intelligent vehicles Perception is an important aspect of any intelligent or autonomous system. Some of the sensors used in the Intelligent Vehicles are: GPS (Global Positioning System)- provides the absolute location and direction of the vehicle on the road data is received from satellites orbiting the earth Optical Camera - Eye of the vehicle. Provides it vision capability Infra red camera - Provides night vision capability Radar Measurement of distances (vehicles -vehicle and Vehicle obstacles) 8/15
Sensors Intelligent vehicles Laser Scanner Known as LIDAR (Light Detection And Ranging) Sensor. Most popular sensor, used in most vehicles. Very expensive (a typical unit costs more than 3 lakh Rupees) Provides 2D and 3D data of the vehicle surrounding environment Odometry measurement of changes in position, velocity and acceleration using sensors located in moving parts. Inertial Measurement Systems Accelerometers and Gyroscopes Measures relative movement of robot in linear or angular direction. Compass Determines vehicle direction with respect to earth s poles. 9/15
Sensors Intelligent vehicles Sensor fusion Mechanism or algorithm that combines the data from different sensors into one perception of the environment Compass Optical camera LIDAR Microwave Radar GPS Sensor Fusion Mechanism/ Algorithm Perception Driving software Vehicle mechanics Gyroscope Infrared camera Wheel encoder Fig. 2 Vehicle sensor fusion mapping 10/15
Intelligent Vehicle Sensor Location Intelligent vehicles Autonomous Passat by Volkswagen, Germany Fig. 3 Autonomous Passat (Figure from Robotland Blog article Pickup an autonomous taxi cab in Berlin with ipad dated October 18 th,2011) 11/15
Vehicle Architecture Intelligent vehicles A general architecture of an intelligent vehicle. Perception Route map & destination information Sensor Path Planner Sensor Sensor Fusion Mechanism/ Algorithm Driver Behavior Model Navigator Driving software Sensor Driver / Pilot Physical Vehicle layer Steering controller Transmission Controller Engine controller Brake Controller Fig. 4 Vehicle Architecture 12/15
Objectives of Research Objectives Replace the Human Driver with an Equivalent Intelligent System: Develop a Supervisory / Master controller that will co-ordinate the functioning of the various sub-system controllers of the intelligent vehicle. Development of Vehicle and Driver behavior Models (Finite State Machine FSM) Development of control algorithms : Fuzzy, Neural and Genetic Algorithms Simulation and validation of developed control algorithms Development of Embedded controller Testing with scaled down vehicle model 13/15
Success Stories Actual Implementation Success Stories Google s Autonomous Car project Fleet of robotic Toyota Priuses have covered more than 1,90,000 miles (3 lakh kilometers) in all types of road conditions with minimal human input. University of Berlin s MadeinGermany VW Passat Autonomous taxis in Berlin VisLab (Italy) VisLab Intercontinental Autonomous Challenge (VIAC) Four driverless vehicles -15,000 KM trip - Parma in Italy to Shanghai China - July 26, 2010 - October 28, 2010 with virtually no driver intervention. 14/15
References References 1. Massimo Bertozzi, Alberto Broggi, Alessandra Fascioli, Vision-based intelligent vehicles: State of the art and perspectives, Robotics and Autonomous Systems 32 (2000) 1 16, 01/02/1999. 2. Nikhi M Chakravarthy and Lawrence B Holder Jr, Intelligent Cars, Intelligent Environments Presentation, Computer Science and Engineering Department, UTA, Spring 2003 3. Jameson M Wetmore, Driving the Dream: The History and Motivations Behind 60 Years of Automated Highway Systems in America, Automotive History Review, Summer 2003, pp. 4-19. 4. Sadayuki Tsugawa, A History of Automated Highway Systems in Japan and Future Issues, Proceedings of the 2008 IEEE International Conference on Vehicular Electronics and Safety, Columbus, OH, USA. September 22-24, 2008 5. Ola Ringdahl, Techniques and Algorithms for Autonomous Vehicles in Forest Environment, Dept. of Computing Sciences, Umea University, Sweden, ISSN-0348-0542, ISBN-978-91- 7264-373-4. 6. John Leonard, Jonathan How, Seth Teller, David Barrett, Chris Sanders, DARPA Urban Challenge: Team MIT Development Plan, October 27, 2006 7. Robotland blog, Pick up an autonomous taxi in Berlin with ipad,october 18,2011 8. Erico Guizzo, How Google s Self-Driving Car Works,IEEE Spectrum, October 18,2011 http://spectrum.ieee.org/automaton/green-tech/advanced-cars/how-google-self-driving-carworks THANK YOU 15/15