Intelligent vehicles and road transportation systems (ITS) Week 1 : - PowerPoint PPT Presentation

Brainstorming Brainstorming Open questions and introductory discussion Why is road transportation important to you and society? D Gingras – ME470 IV course CalPoly Week 1 14 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What do like and dislike about current cars ? D Gingras – ME470 IV course CalPoly Week 1 15 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What are the three main components of a road transportation system (automotive)? D Gingras – ME470 IV course CalPoly Week 1 16 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What is the main source of road accidents ? Give some examples. D Gingras – ME470 IV course CalPoly Week 1 17 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What are the main variables affecting or influencing safety ? D Gingras – ME470 IV course CalPoly Week 1 18 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion Give some examples of current safety systems in cars. D Gingras – ME470 IV course CalPoly Week 1 19 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion Why making vehicles more intelligent? D Gingras – ME470 IV course CalPoly Week 1 20 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion Define “intelligence” from an engineering point of view? D Gingras – ME470 IV course CalPoly Week 1 21 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion Define the following words: Imagining Thinking Reasoning Knowledge Meaning Perception Planning Cognition Attention Awareness Consciousness D Gingras – ME470 IV course CalPoly Week 1 22 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What are the main capabilities/features of an “intelligent” vehicle? D Gingras – ME470 IV course CalPoly Week 1 23 11-juin-15

Brainstorming Brainstorming Open questions and introductory discussion What are the main constraints/challenges to mass produce and sell intelligent vehicles ? D Gingras – ME470 IV course CalPoly Week 1 24 11-juin-15

History History of road transportation  4000 BC- 3500 BC – invention of wheels on carts Mesopotamia  2000 BC - horses domesticated  Roads (Trails) to satisfy pedestrians and horses  Big civilizations Egypt: 3000 years B.C.  Babylon, Greece, Creta: 1000 years B.C.  Rome: 1000 years 600 BC to 400 AD.   Via Appia (312 BC) structure of 1 m to 1,50 m wide  1790 – bicycle  1862 – automobile  1867 – motorcycle  1908 – assembly line (Ford) Roman Via Appia D Gingras – ME470 IV course CalPoly Week 1 25 11-juin-15

History History of road transportation  The automobile as we know it was not invented in a single day by a single inventor.  It is estimated that over 100,000 patents created the modern automobile.  First theoretical plans for a motor vehicle have been drawn up by both Leonardo da Vinci and Isaac Newton. D Gingras – ME470 IV course CalPoly Week 1 26 11-juin-15

History History of road transportation First automobile at 2mph ! The horse had been humanity's primary form of transportation for more than two millennia …it seemed ridiculous that anything would ever replace horses. 27 D Gingras – ME470 IV course CalPoly Week 1 11-juin-15

History History of road transportation Etymology: origin of the word automobile "The new mechanical wagon with the awful name automobile has come to stay..." New York Times (1897) The credit for the name automobile goes to a 14 th Century Italian painter and engineer named Martini. Martini did draw plans for a man-powered carriage with four wheels. Automobile comes from the Greek word, "auto" (meaning self) and the Latin word, "mobils" (meaning moving). The word car is derived from Celtic word "carrus," (meaning cart or wagon). Other names for motor vehicles used in patent applications: • Oliver Evans applied for a U.S. patent in Philadelphia in 1792 for a "oruktor amphibolos" • George Selden received a patent for a "road machine" in 1879. • The Duryea brothers patented their "motor wagons" in 1895. • Henry Ford called his 1896 car a “quadricycle." Other early media references to motor vehicles included names such as: autobaine, autokenetic, autometon, automotor horse, buggyaut, diamote, horseless carriage, mocole, motor carriage, motorig, motor-vique, and the oleo locomotive. D Gingras – ME470 IV course CalPoly Week 1 28 11-juin-15

History History of road transportation Nicolas Joseph Cugnot: the first inventor 2.5 mph on only three wheels. The vehicle had to stop every ten to fifteen minutes to build up steam power Old engraving depicting the 1771 crash of Nicolas Joseph Cugnot's steam-powered car into a stone wall (first motor vehicle accident ever). D Gingras – ME470 IV course CalPoly Week 1 29 11-juin-15

History of road transportation History Early history of the combustion engine  1680 - Dutch physicist, Christian Huygens, designed (but never built) an internal combustion engine that was to be fuelled with gunpowder.  1807 - Francois I saac de Rivaz of Switzerland invented an internal combustion engine that used a mixture of hydrogen and oxygen for fuel. Rivaz designed a car for his engine - the first internal combustion powered automobile. However, his was a very unsuccessful design.  1824 - English engineer, Samuel Brown, adapted an old Newcomen steam engine to burn gas, and he used it to briefly power a vehicle up Shooter's Hill in London.  1858 - Belgian-born engineer, Jean Joseph Étienne Lenoir, invented and patented (1860) a double-acting, electric spark-ignition internal combustion engine fuelled by coal gas. In 1863, Lenoir attached an improved engine (using petroleum and a primitive carburetor) to a three-wheeled wagon that managed to complete an historic fifty-mile road trip.  1862 - Alphonse Beau de Rochas , a French civil engineer, patented but did not build a four-stroke engine (French patent # 52,593, January 16, 1862).  1864 - Austrian engineer, Siegfried Marcus * , built a one-cylinder engine with a crude carburetor, and attached his engine to a cart for a rocky 500-foot drive. Several years later, Marcus designed a vehicle that briefly ran at 10 mph that a few historians have considered as the forerunner of the modern automobile by being the world's first gasoline- powered vehicle. D Gingras – ME470 IV course CalPoly Week 1 30 11-juin-15

History of road transportation History Early history of the combustion engine  1866 - German engineers, Eugen Langen and Nikolaus August Otto, improved on Lenoir's and de Rochas' designs and invented a more efficient gas engine.  1873 - George Brayton , an American engineer, developed an unsuccessful two-stroke kerosene engine (it used two external pumping cylinders). However, it was considered the first safe and practical oil engine.  1876 - Nikolaus August Otto invented and later patented a successful four-stroke engine, known as the "Otto cycle".  1876 - The first successful two-stroke engine was invented by Sir Dougald Clerk .  1883 - French engineer, Edouard Delamare-Debouteville , built a single-cylinder four-stroke engine that ran on stove gas. It is not certain if he did indeed build a car, however, Delamare- Debouteville's designs were very advanced for the time - ahead of both Daimler and Benz in some ways at least on paper.  1885 - Gottlieb Daimler invented what is often recognized as the prototype of the modern gas engine - with a vertical cylinder, and with gasoline injected through a carburetor (patented in 1887). Daimler first built a two-wheeled vehicle the "Reitwagen" (Riding Carriage) with this engine and a year later built the world's first four-wheeled motor vehicle.  1886 - On January 29, Karl Benz received the first patent (DRP No. 37435) for a gas-fuelled car.  1889 - Daimler built an improved four-stroke engine with mushroom-shaped valves and two V-slant cylinders.  1890 - Wilhelm Maybach built the first four-cylinder, four-stroke engine. D Gingras – ME470 IV course CalPoly Week 1 31 11-juin-15

History of road transportation History America's first gasoline- powered commercial car manufacturers were Charles and Frank Duryea . The brothers were bicycle makers who became interested in gasoline engines and automobiles and built their first motor vehicle in 1893, in Springfield, Ma. By 1896, the Duryea Motor Wagon Company had sold thirteen models of the Duryea, an expensive Duryea: the first mass producers of limousine, which remained in cars - assembly line in parallel. production into the 1920s. D Gingras – ME470 IV course CalPoly Week 1 32 11-juin-15

History of road transportation History Henry Ford (1863-1947) invented an improved assembly line (production in series) and installed the first conveyor belt-based assembly line in his car factory in Ford's Highland Park Michigan plant, around 1913-14. The assembly line reduced production costs for cars by reducing assembly time. Ford's famous Model T was assembled in ninety-three minutes. Ford made his first car, called the “quadricycle“, in June 1896. Success came after he founded the Ford Motor Company in 1903. This was the third car manufacturing company created to produce the cars he designed. He introduced the Model T in 1908 and it was a success. After installing the moving assembly lines in his factory in 1913, Ford became the world's biggest car manufacturer. By 1927, 15 million Model Ts had been manufactured. D Gingras – ME470 IV course CalPoly Week 1 33 11-juin-15

History of road transportation History The rise of computing power 1969: Apollo 11 computer 2.048 MHz CPU, Memory 74 kB, RAM 4kB Exponential Growth in Computer Processing Power (Moore’s law) and Computer Aided Engineering (CAE) Capability Year Model Size (No. of Elements) 1980 500 - 5000 1985 1,000 – 10,000 1990 3,000 – 20,000 1995 5,000 – 60,000 2000 10,000 – 500,000 Today Larger than 5,000,000 http://www.aprosys.com/img/06.pdf D Gingras – ME470 IV course CalPoly Week 1 34 11-juin-15

History of road transportation History Over 100 years of electricity/electronics in cars: ADAS Microprocessor Drive ICs and by wire Transistor microcontroller Telematics Increased complexity Solid Electronic First state transmission radio in radio Cruise control car Hybrid control Transistor AC ABS DC controlled generator Spark Closed- generator ignition Airbags plugs loop air- coiled Selenium fuel ratio 4 V battery 1 million rectifier 3 phase control Low T-Ford current voltage sold in 12 V High generator 1915 ignition battery voltage system ignition system 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Source: BOSCH GmbH D Gingras – ME470 IV course CalPoly Week 1 35 11-juin-15

History of road transportation History The car (light blue line) is closely following the mobility long term trend. D Gingras – ME470 IV course CalPoly Week 1 36 11-juin-15

History of road transportation History Historic View on Driver Assistance • Turn signal reset – eliminates manual reset • Synchronized manual transmission – eliminates throttle application • Servo for breaking and steering – reduced force required from the driver • Centralized door locking (incl. remote control) – enables opening and locking without access to respective door • Automatic transmission – eliminates manual gear shifting • Oil level indicator – eliminates dirty hands • Anti ‐ lock Breaking System (ABS) – increased stability during braking D Gingras – ME470 IV course CalPoly Week 1 37 11-juin-15

History of road transportation History Historic View on Driver Assistance • Park Assist – parking without bumps and scratches • Electronic Stability Program (ESC, ESP, DSC, ...) – improved stability within physical limits • Brake Assist – reduced braking distance in emergency in braking situations • Navigational Systems – eliminates map in driver‘s hands • Climate Control – controls interior temperature to comfortable level • Night vision – enhances driver‘s perception range in darkness • Cruise Control – maintains vehicle velocity D Gingras – ME470 IV course CalPoly Week 1 38 11-juin-15

History of road transportation History Historic View on Driver Assistance • General remarks on the previous list of DAs – none of the previous examples is required for mobility – nevertheless driver assistance is an indispensable part of vehicle equipment – advanced driver assistance systems also take over primary driving tasks • Main success factor of DAs – Relief of inconvenient tasks – Increase of safety – Complement or supplement of human skills D Gingras – ME470 IV course CalPoly Week 1 39 11-juin-15

History of road transportation History First electrical vehicles in 1880s Taxi in New-York, 1898, with docking station for recharging batteries D Gingras – ME470 IV course CalPoly Week 1 40 11-juin-15

History of road transportation History 1940s Milwaukee Machine Tools ad 1940s Cannon Electric ad proclaiming the proclaiming that air-conditioning will be availability of in-car "pagers" after WWII. available for automobiles after WWII. D Gingras – ME470 IV course CalPoly Week 1 41 11-juin-15

History Vision of future driving 1958 Source: Science Digest, Electronic Highway of the Future (Apr, 1958) D Gingras – ME470 IV course CalPoly Week 1 42 11-juin-15

Context Automotive context Automobile safety is the study and practice of design, construction, equipment and regulation to minimize the occurrence and consequences of automobile accidents. Road traffic safety more broadly includes roadway design. Active safety is used to refer to technology assisting in the prevention of a crash. Passive safety is used to refer to technology to protect occupants during and/or after a crash. Active safety examples Passive safety examples brake assist seat belts traction control airbags chassis assist passenger safety cell good grip deformation zones head up displays loadspace barrier-nets good visibility from driver's seat laminated glass low noise level in interior correctly positioned fuel tanks legibility of instrumentation, warning symbols fuel pump kill switches early warning of severe braking ahead (automatic) emergency call good chassis balance and handling emergency medical services anti-lock braking system electronic stability control intelligent speed adaptation collision warning/avoidance D Gingras – ME470 IV course CalPoly Week 1 43 11-juin-15

Context Automotive context Decomposing a imminent collision scenario Typically, driver response time is in the order of a second or more, whereas active safety systems can be in the order of tens of ms. D Gingras – ME470 IV course CalPoly Week 1 44 11-juin-15

Context Automotive context Typical specs for a vehicle today New purchase price: $30,000 Engine output: 180 hp Fuel economy: 23.3 mpg and 19.8 mpg (truck) Occupancy: 1.95 (car) – 2.35 (van) New-car buyer trade-in: after 4 years at 55,000 miles New-car leases trade-in: after 3 years at 36,000 miles Life span: just over 13 years Final mileage: 145,000 miles Source: http://www.safecarguide.com/gui/new/neworused.htm, http://www1.eere.energy.gov/vehiclesandfuels/facts/ printable_versions/2010_fotw613.html, http://www.sacbee.com/2012/10/09/4894505/average-fuel-economy-for-new-cars.html, http://www.nhtsa.gov/Laws+ &+ Regulations/CAFE+ -+ Fuel+ Economy/2004+ Automotive+ Fuel+ Economy+ Program D Gingras – ME470 IV course CalPoly Week 1 45 11-juin-15

Context Automotive context Annual U.S. traffic volumes - 1982 & 2007 ***Per stats pulled from the government DOT http://jagadees.files.wordpress.com/2008/08/dotapril2.png D Gingras – ME470 IV course CalPoly Week 1 46 11-juin-15

Context Automotive context Annual U.S. hours delayed while traveling during peak hours http://ops.fhwa.dot.gov/aboutus/one_pagers/perf_measurement.htm D Gingras – ME470 IV course CalPoly Week 1 47 11-juin-15

Context Automotive context An automobile needs to be:  operational at -40 to + 80 (120) deg C  operational at 0 to 100% humidity  operational at 0 to 3000m altitude  shock resistant  work without frequent adjustment, preferably self adjusting  maintenance free (no pre-flight check…)  can be sold at all markets, very different regions w/ varying regulation  self explanatory, intuitive (no one reads handbook)  12 years of operation, no maintenance, wear needs to be "obvious"  low cost  mass producible  recyclable  non-toxic  sell it and never see it again (especially no recall) D Gingras – ME470 IV course CalPoly Week 1 48 11-juin-15

Context Automotive context body motion: yaw rate, lateral / Vehicle complexity location, destination, longitudinal / vertical speed, VIN acceleration transmission speed(s), torque, gear, pressure, windows, maintenance data doors status engine speed, torque, load, temperatures, ambient, pressures, pressure, mainten- temperature, ance lighting, rain data driver steering, brake, throttle, nearby gear selection, turn signal, lights vehicles: distance, seats, restraint systems status, speed, number heating / ventilation, infotainment settings brakes / steering / vehicle dynamics control / driver assistance system status More than 4200 signals, 10M lines of code, 35% system cost Source: Driving Cars Toward Complexity , I. Krueger (UC San Diego), NPR Interview, April 30, 2010 D Gingras – ME470 IV course CalPoly Week 1 49 11-juin-15

Context Automotive context Vehicle complexity Up to 80 controllers 1 - Powertrain: ignition, injection, transmission, 4WD… - Safety: airbag, seatbelts, pre-tensioners… - Chassis: steering, brakes, dampers… - Driving Aid:parking aid, night vision… - Entertainment: MP3, CD, radio… Source: 1. “Driving Cars Toward Complexity”, I. - HVAC: air conditioning… Krueger (UC San - Body: seats, doors, roof… Diego), NPR - Vision: lights, wipers, mirrors… Interview, April 30, 2010 - Information: displays, navigation… Up to 20 Communications Networks 2 -MOST: Entertainment and information - CAN: Powertrain, safety, chassis, driving aid - LIN: Body, vision, HVAC Source 2. “Software-Technologie in der Automobilindustrie”, K. Grimm, Daimler AG,2009 D Gingras – ME470 IV course CalPoly Week 1 50 11-juin-15

Motivations Context Motivation for intelligent vehicles The roads are not used efficiently. IVs can improve  Traffic density  Flexibility in road segments allocation D Gingras – ME470 IV course CalPoly Week 1 51 11-juin-15

Context Automotive context Use case of ADAS: Harsh operating conditions: A Canadian example…;-) Parking would be much more comfortable/safer for this driver if his car was equipped with a parking assist system, a rear-view camera and pedestrian detection. Would they work properly? Source Roland Berger Insights, Automotive Competence Center Client Magazine Issue 01.2013 D Gingras – ME470 IV course CalPoly Week 1 52 11-juin-15

Context Automotive context Typical driving scene: Where is Charlie? Source: D Langer, Volkswagen Electronics Research Laboratory, 2012 D Gingras – ME470 IV course CalPoly Week 1 53 11-juin-15

Context Automotive context Typical driving scene analysis This type of scene analysis must be done in real-time, typically every 50 to 100 ms. (blue: pedestrian, red: moving cars, yellow: non-moving cars, green: lanes) Source: D Langer, Volkswagen Electronics Research Laboratory, 2012 D Gingras – ME470 IV course CalPoly Week 1 54 11-juin-15

IVs Basic technologies of IVs basics Current invasive intelligence D Gingras – ME470 IV course CalPoly Week 1 55 11-juin-15

IVs Basic technologies of IVs basics To develop a vehicle « counciousness », we need to get information on:  Its own internal states  Its immediate surrounding  Its remote/extended surrounding  Its level of risk in perception/decision/action making Develop a vehicular « innate survival instinct » D Gingras – ME470 IV course CalPoly Week 1 56 11-juin-15

IVs Basic technologies of IVs basics Automatic driving systems Integrated information systems Learning faulty- Complexity « Networked vehicle » tolerant autonomous implementation 5.9 GHz DSRC systems difficulty Bluetooth, 802.11 hierarchical multilevel « wireless » architectures Recognition – scene analysis « Drive by-wire » Cell phones Ex. road signs multivariable adaptive « Total awareness » control systems Enhanced night vision Systems PID and lanes/pedestrian detection Driver’s vigilence monitoring Active anti-collision External Oral man-machine dialog sensors Side mirrors modules Internal Man- machine interfaces modules Sensors voice command systems - haptic systems Driver ID Keys, board fingerprint Distributed network sensors and buttons « Smart dust » MEMS, SOC Nano Discrete sensors and actuators 2025 Source: Siemens VDO 2000 Intelligence penetration in cars D Gingras – ME470 IV course CalPoly Week 1 57 11-juin-15

Context Automotive context IVs basics 2009: …and then came the Google car… D Gingras – ME470 IV course CalPoly Week 1 58 11-juin-15

IVs Basic technologies of IVs basics Some advanced technical functions in IVs  Estimation position and heading of ego-vehicle  Estimating and tracking position of other vehicles  Detecting, classifying and positioning obstacles  Control vehicle stability and dynamics  Estimating and controlling braking performance  Navigation  Communication with other vehicles and outside world

IVs Basic technologies of IVs basics Infotainment: not safety related. D Gingras – ME470 IV course CalPoly Week 1 60 11-juin-15

IVs Main tasks of IVs basics "Position" Cognition Localization Global Map Environment Model Path Local Map Real World Perception Motion Control Environment D Gingras – ME470 IV course CalPoly Week 1 61 11-juin-15

IVs Basic technologies of IVs basics An intelligent vehicle consists basically of four fundamental technologies: environment perception and modeling, localization and map building, path planning and decision-making, and motion control. Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 62 11-juin-15

IVs Basic architecture of IVs basics Vision Perception Positioning Navigation Communication Collaboration Artificial intelligence Control Actuation Source: Vermaas L L G et al., Intelligent Vehicle Survey and Applications, Advances in Technological Applications of Logical and Intelligent Systems, G. Lambert-Torres et al. (Eds.), IOS Press, 2009 D Gingras – ME470 IV course CalPoly Week 1 63 11-juin-15

IVs basics Basic technologies of IVs Challenge: from the tons of data coming out of the sensors, how to extract and compress the useful information to insure reliable real-time reasoning. Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 64 11-juin-15

IVs Basic technologies in IVs basics The AI part: Basic brain model in IVs D Gingras – ME470 IV course CalPoly Week 1 65 11-juin-15

IVs Basic technologies in IVs basics Basic driver model Source: E. DONGES, “A two-level model of driver steering behavior", Human Factors, vol. 20, No 6, 1978. D Gingras – ME470 IV course CalPoly Week 1 66 11-juin-15

IVs Basic technologies in IVs basics A very basic vehicular motion control Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 67 11-juin-15

IVs Basic technologies in IVs basics Interactive road situation analysis framework Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 68 11-juin-15

IVs basics Basic technologies of IVs Dead reckoning positioning system Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 69 11-juin-15

IVs IVs basic architecture basics Another example from VW Source: D Langer, Volkswagen Electronics Research Laboratory, 2012 D Gingras – ME470 IV course CalPoly Week 1 70 11-juin-15

IVs Basic technologies in IVs basics Toward integration of automotive control systems: Software « Intelligence » Smart sensor Smart actuator Sensors Controllers Actuators MEMs D Gingras – ME470 IV course CalPoly Week 1 71 11-juin-15

IVs Basic technologies of IVs basics Typical framework of a vehicle control system Source: H. Cheng, Autonomous intelligent vehicles: theory, algorithms, and implementation, Springer, 2011 D Gingras – ME470 IV course CalPoly Week 1 72 11-juin-15

IVs Basic technologies of IVs basics Computer systemic view of IV main components Source:Nan-Ning Zheng, “Toward Intelligent Driver-Assistance and Safety Warning Systems”, IEEE Intelligent systems magazine, 2004. D Gingras – ME470 IV course CalPoly Week 1 73 11-juin-15

Basic technologies of IVs IVs basics Architecture for a driver assistance and safety warning system Source:Nan-Ning Zheng, “Toward Intelligent Driver-Assistance and Safety Warning Systems”, IEEE Intelligent systems magazine, 2004. D Gingras – ME470 IV course CalPoly Week 1 74 11-juin-15

IVs Basic technologies of IVs basics DOT’s vision of intelligent vehicles Source: US DOT NHTSA ACAS Program, final report, 2000 D Gingras – ME470 IV course CalPoly Week 1 75 11-juin-15

IVs Basic technologies of IVs basics Levels of automation in intelligent vehicle applications IV apps areas can roughly be divided into three groups depending on the level of support to the driver (Note the DOT IHVS has set 5 levels):  Advisory systems: These systems provide an advisory/warning to the driver. No action is taken by the vehicle. Exemples are collision warning systems, animal warning at night, side object warning (blind spot), and driver impairment monitoring.  Semi-autonomous systems : These systems take partial control of the vehicle, either for driver assistance or for an emergency intervention to prevent a collision These systems often use haptic measures, i.e. based on the sense of touch, to assist the driver. Semi-autonomous systems include functions such as CMBS (Collision Mitigation Braking System), lane-keeping, Adaptive Cruise Control (ACC), parking assist and precise docking.  Fully autonomous systems . This kind of systems take full control of the vehicle Current examples are low speed automated driving (for congested traffic) or platooning on highways. D Gingras – ME470 IV course CalPoly Week 1 76 11-juin-15

IVs Basic technologies in IVs basics Smart sensors and actuators into IVs  Actual state-of-the-art: transducers linked together with a microprocessors through a common bus.  Smart sensors are now made of multiple chips.  Micromachining and VLSI circuitry is merging.  Smart sensors do more than just picking up and sending a signal, they have embedded algorithms that process and interpret data, communicate and self-calibrate over time.  Integrating bus interface circuitry is also coming , starting at the module level and spreading to the chip level. D Gingras – ME470 IV course CalPoly Week 1 77 11-juin-15

Basic technologies in IVs IVs basics MEMS Micro-Electro-Mechanical Systems  Miniature systems for sensing and actuating  Batch fabrication approach  Utilizes microelectronics manufacturing base  Common technology for sensors, actuators, and systems  MEMS manufacturing of automotive sensors began in 1981 with pressure sensors for engine control  Continued in the early 1990s with accelerometers to detect crash events for air bag safety systems  In recent years has further developed with angular-rate inertial sensors for vehicle-stability chassis systems and navigation. D Gingras – ME470 IV course CalPoly Week 1 78 11-juin-15

IVs Basic technologies in IVs basics Applications for MEMs in cars D Gingras – ME470 IV course CalPoly Week 1 79 11-juin-15

IVs Basic technologies in IVs basics Why using MEMS  Utilizes the economy of batch processing, together with miniaturization and integration of on-chip electronic intelligence  MEMS makes high-performance sensors available for automotive applications, at the same cost as the traditional types of limited- function sensors they replace.  In other words, sensors would have to be several times more expensive than MEMS if they were still made by traditional electromechanical/discrete electronics approaches. D Gingras – ME470 IV course CalPoly Week 1 80 11-juin-15

IVs Basic technologies in IVs basics Advanced Driver Assistance Systems Advanced Driver Assistance Systems, or ADAS , are systems to help the driver in the driving process. When designed with a safe Human-Machine Interface it should increase car safety and more generally road safety. It takes over some of the primary driving tasks from the driver. Examples:  Stop-n-go ACC for congested traffic (~ 2003)  Lane keeping on freeways (~ 2004)  Automated throttle, brakes, steering in tedious stop-n-go traffic D Gingras – ME470 IV course CalPoly Week 1 81 11-juin-15

IVs Basic technologies in IVs basics Advanced Driver Assistance Systems Primary Driving Tasks – are required to get from current position to destination – Navigation – Maneuver (e.g. lane change) – Trajectory (e.g. velocity, steering, stabilization) See e.g.: Wuhong Wang, Fuguo Hou, Huachun Tan & Heiner Bubb (2010): A Framework for Function Allocations in Intelligent Driver Interface Design for Comfort and Safety, Int. Journal of Computational Intelligence Systems, 3:5, 531- ‐ 541 D Gingras – ME470 IV course CalPoly Week 1 82 11-juin-15

IVs Basic technologies in IVs basics Advanced Driver Assistance Systems Primary Driving Tasks  are required to get from current position to destination  Navigation  Maneuver (e.g. lane change)  Trajectory (e.g. velocity, steering, stabilization) Secondary Driving Tasks – control operation point of vehicle (throttle, brake, gears) – turn signal , wiper, light, … Tertiary Driving Tasks – control ambience – radio, phone D Gingras – ME470 IV course CalPoly Week 1 83 11-juin-15

IVs Basic technologies in IVs basics Driving automation requires a detailed understanding of how human drivers operate. Value Judgment Sensor World Behavior Processing Model Generation Planning Behavior Coordination World Model Sensors Structure Actuators Behavior Sensor Generation Processing Sensors Structure Actuators World World D Gingras – ME470 IV course CalPoly Week 1 84 11-juin-15

IVs Basic technologies in IVs basics Advanced Driver Assistance Systems D Gingras – ME470 IV course CalPoly Week 1 85 11-juin-15

IVs Basic technologies in IVs basics Advanced Driver Assistance Systems D Gingras – ME470 IV course CalPoly Week 1 86 11-juin-15

IVs Basic technologies in IVs basics Vehicle Communication Ad-hoc Networks: VANETS Source: R Berger, Automotive insight, Automotive Competence Center Client Magazine, Issue 01.2013 D Gingras – ME470 IV course CalPoly Week 1 87 11-juin-15

IVs Basic technologies in IVs basics Vehicle Communication Ad-hoc Networks: VANETS D Gingras – ME470 IV course CalPoly Week 1 88 11-juin-15

IVs Basic technologies in IVs basics DSRC:Dedicated Short Range Communications U.S. Federal Communications Commission (1999): “ … services are expected to improve traveler safety, decrease traffic congestion, facilitate the reduction of air pollution, …” D Gingras – ME470 IV course CalPoly Week 1 89 11-juin-15

IVs Basic technologies in IVs basics DSRC:Dedicated Short Range Communications Two basic types for safety:  Vehicle-to-Vehicle communication (V2V):  Information is transmitted between vehicles. It enables vehicles to know where the vehicles in its vicinity are and what they are doing. Applications include:  Forward Collision Warning  Emergency Electronic Brake Light  Blind Spot/Lane Change Warning  Intersection Movement Assist  Do Not Pass Warning  Control Loss Warning  Vehicle-to-Infrastructure communication (V2I) Applications include:  Automatic tolling  Traffic jam/construction site ahead warning Systems use absolute positioning and relative positioning. Maps are sent from the infrastructure to the vehicle Positioning based on GPS and dead reckoning D Gingras – ME470 IV course CalPoly Week 1 90 11-juin-15

IVs Basic technologies in IVs basics Embedded vehicle networks Controller Area Network (CAN)  Bus connecting microcontrollers and devices  Powertrain, chassis, safety, driving aid Media Oriented Systems Transport (MOST)  Low cost fiber optics for transport of high data volumes  Entertainment and information Local I nterconnect Network (LI N)  Small, slow, and cheap solution to integrate intelligent sensors  Vision, Body, HVAC D Gingras – ME470 IV course CalPoly Week 1 91 11-juin-15

IVs Basic technologies in IVs basics Embedded vehicle networks A high level comparison of the characteristics of LIN, CAN, and FlexRay/TTP . Source: P . E. Lanigan et al., Diagnosis in Automotive Systems: A Survey, Carnegie Mellon University, 2011 D Gingras – ME470 IV course CalPoly Week 1 92 11-juin-15

IVs Basic technologies in IVs basics Electronic Controller Unit (ECU)  Powertrain  ignition, injection, transmission, 4WD  Safety  airbag, seatbelts, pre-tensioners  Vision  lights, wipers, mirrors  Chassis  steering, brakes, suspension  Driving aids  parking aid, night vision  Entertainment  Body generic automotive  Seats, doors, roof computing and  HVAC communication  air conditioning topology Source: P . E. Lanigan et al., Diagnosis in Automotive Systems: A Survey, Carnegie Mellon University, 2011 D Gingras – ME470 IV course CalPoly Week 1 93 11-juin-15

IVs Basic technologies in IVs basics On-Board Diagnostics: OBD-II: OBD stands for “On-Board Diagnostics.” It is a computer- based system originally designed to reduce emissions by monitoring the performance of major engine components. A basic OBD system consists of an ECU (Electronic Control Unit), which uses input from various sensors (e.g., oxygen sensors) to control the actuators (e.g., fuel injectors) to get the desired performance. The “Check Engine” light, also known as the MIL (Malfunction Indicator Light), provides an early warning of malfunctions to the vehicle owner. A modern vehicle can support hundreds of parameters, which can be accessed via the DLC (Diagnostic Link Connector) using a device called a scan tool. D Gingras – ME470 IV course CalPoly Week 1 94 11-juin-15

IVs Basic technologies in IVs basics Electronic Stability Control 1. ESP-hydraulic unit with integrated ECU 2. Wheel speed sensors 3. Steering angle sensor 4. Yaw rate and acceleration sensor 5. ECU for engine management D Gingras – ME470 IV course CalPoly Week 1 95 11-juin-15

Traffic modeling Traffic modeling and analysis and analysis Let us consider vehicles crossing a certain point on a road. The time that a 0 t vehicle n reaches that point is denoted by and the time that the vehicle n 1 t has completely passed the measurement point, is denoted by . The time n headway of vehicle n is calculated by :    0 1 / v = speed of vehicle n T t t s v  1 n H n n n D Gingras – ME470 IV course CalPoly Week 1 96 11-juin-15

Traffic modeling Traffic modeling and analysis and analysis If N vehicles are counted that cross that point on the road during a time interval Δ T , then the traffic flow is defined as: N  q  T The arithmetic average speed v is given by, 1 N   v v n N  1 n The traffic density expressed in number of vehicles per km is given by,   / q v Thus to increase traffic flow, we can either increase the vehicle density or increase the average speed. This is not easy to achieve due to safety reasons. D Gingras – ME470 IV course CalPoly Week 1 97 11-juin-15

Traffic modeling Traffic modeling and analysis and analysis The previous formulas does not display the peculiar feature of traffic flow that the aggregate traffic speed decreases with increasing traffic density. Two functional relations between the traffic flow q , the average speed v , and the vehicle density are illustrated below. This common used flow-density relation is the fundamental diagram. The vehicle speed is maximum at low densities and almost zero at high densities Source: D. Helbing. Traffic and related self-driven many-particle systems. Reviews of Modern Physics, 73(4):1067–1141, December 2001. D Gingras – ME470 IV course CalPoly Week 1 98 11-juin-15

Traffic modeling Traffic modeling and analysis and analysis The fundamental diagram is usually expressed mathematically by:   a    1       ( ) exp   q V v  free     a   critical  v Where is the free flow speed and is the critical density. And a is a critical free parameter model depending on the road infrastructure (ex. number of lanes). NB: The formula above is not unique. Several other models have been proposed to describe traffic behavior, but this model is a common one. The slope of the fundamental diagram (last slide) starts almost linearly and corresponds to the free-flow speed. In this region the density can increase while the average speed stays the same, thus increasing the traffic flow. With increasing density, the traffic flow increases up to a maximum, i.e. the capacity flow, which is referred to as a critical point. The corresponding density and vehicle speed are the critical density and the critical speed. At higher densities than the critical density, the average vehicle speed is significantly lower than in free-flow traffic. D Gingras – ME470 IV course CalPoly Week 1 99 11-juin-15

Traffic modeling Traffic modeling and analysis and analysis Free flow: drivers can drive their desired speed, when traffic is unobstructed. In free-flow, drivers can maintain their desired speed, because their time headway is very large. Car-following mode: when the traffic density increases, drivers will adjust their speed such that they can follow the vehicle directly in front, while maintaining a safe time headway. Congested traffic: the vehicle density has passed a certain critical density such that the traffic flow and vehicle speed decrease significantly. If the vehicle speed drops to almost zero, the density has become too large and a traffic jam will occur. Traffic jams: Traffic jams typically move upstream, thus against traffic direction. If more vehicles leave the traffic jam at the downstream front than vehicles entering the traffic jam at the upstream front, then the traffic jam will reduce in length. The outflow of a traffic jam is more or less a fixed quantity. If the fixed quantity is denoted by q L , the traffic jam will thus reduce in width if q inflow < q L , where q inflow is the traffic flow that enters the traffic jam at the upstream front. D Gingras – ME470 IV course CalPoly Week 1 100 11-juin-15