Robocar

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Robocar

  1. 1. RobocarsSolving Personal and Small Transport
  2. 2. Wish List• End wasted driving time• Greatly reduced traffic fatalities• End parking hell• Conduit for much cheaper personal and package transportation• Conduit for switch to all electric transportation• Vehicles that drive themselves• Pooled by use vehicles• Drives itself (safely and efficiently) – You can spend the travel time more productively or not – No parking – Comes to you
  3. 3. A Few Reasons Why• Driving yourself is very dangerous.. – 35,000 deaths and over 1,000,000 injuries/yr US – $230 billion/yr in accident costs (over 2% US GDP)• Is very costly.. – 5 billion hours (est $1 trillion value) of people’s time (8% of US GDP)• Geopolitical, environmental – 50 billion gallon of imported gasoline • Replace with 5 billion gallon equivalents produced domestically • Eliminates 12-15% of US CO2 pollution• ~600 million urban parking places, up to 10% of urban land in many cities• Multiply by 10 for rough world wide impact
  4. 4. Bits already on the street• Computerized steering and braking• Automatic parallel parking• Active relative distance cruise control• Lane drift warnings• Built in lidar, radar, cameras• Crash avoidance• Real time traffic data incorporation• 15 years of (mostly) self driving cars – VaMP 1994 – heavy city driving with little human intervention – Mercedes 1995 – 1600km on autoban, 95% computer only
  5. 5. Coming Helpful Tech (near)• Crash avoidance – 80% of crashes are from inattention – Warn today, soon active crash avoidance – Way out of some legal roadblocks – The cars talk with one another in local mesh grid• Navigation improvements – System incorporates weather, road conditions, traffic reports, sensors along route, flow of local, google maps, etc for most efficient route – Networking with other vehicles for best over all traffic network flow
  6. 6. More Helpful Tech• Delivery bots – Military uses these, including all terrain models like Big Dog – Imagine them instead of UPS trucks and other human driven vans. Agile fleets with smaller loads• Other “sense” – Tied into traffic lights and other systems. • Light is always green if there is no relevant cross traffic • Can know the timing of the others ahead also – 30% better mileage in city – Tied to your “cloud” via 3/4G or other means – Tied to entire internet
  7. 7. More near term tech• Self-parking valet service – Parking in human driver impossible spaces – Instead of parking could rent itself out when you don’t need it• Mini-car robotic personal transport grids – Non-personal units – Automatic routing by wire for first units
  8. 8. Medium range tech• Autopilot – Human assisted• Urban delivery bot – By wire at first – Then free roving light slow moving bots• Whistle car – Comes on demand – Moves more slowly and perhaps in special lanes• Robotic Convoy – Drafting gives up to 45% mileage boost – Automatic convoys of vehicles doing follow the leader – Driver or vehicle joins and leaves convoy freely
  9. 9. Longer Term Tech• School of fish test – Successful avoidance of determined intention to crash] • Better information, much faster reaction times – Need fish like cooperative movements• Learning from human drivers – Autopilot mode watches and learns even when often • Multiple units share and correlate data • Test suite generation
  10. 10. When• Moore’s law gives 256 fold increase in computational power this decade• While we need algorithmic improvements there are no large conceptual missing parts• No big money invested yet but the payoff potential is larger than the Manhattan project• Blockers are – Legal – Perception – Current cost – Some algorithms
  11. 11. How Expensive?• Today’s fully autonomous cares are very expensive – Moore’s law is our friend – Much better algorithms including through simulations• More cheaper specialized cars• How expensive are ordinary cars – $240/mo + 1,000 miles gas + 40/mo insurance ~= $280/mo• Robocar (on demand) ~= 1000 miles * per mile cost – For muture tech this can be as low as $0.07 / mi = $70, and $0.01 for light urban vehicles• Savings on materials

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