Autonomous Vehicles: advances, algorithms, and the road ahead

[2016-09-30 Fri 18:59:34] speaker: Benjamin Choi, DSO National Labs event: Friday Hacks

1950s - 1970s: smart roads

1980s: Autonomous Land Vehicle project

• road following

1990s: No hands across America

Early 2000s: PerceptOR

2004-2005: DARPA Grand Challenge

2007: DARPA Urban Challenge

2009-now:

• Google gets in the game
• Mining trucks are self driving
• nuTonomy and Uber
• George Hotz making a kit
• DSO working on autonomous armored vehicles

Why is it hard?

• roads are dynamic
• reading traffic lights
• driving in the rain
• offroad jungle paths
• no GPS signals

offroad challenges

• paths include soft objects which the vehicle can bash through
• LIDA can only detect surfaces, but not tell if it is hard or soft
• perhaps a camera can help, but computer vision is hard
  • illustrate with grid of numbers
• paths are not flat, need to determine if safe to drive over

subsystems for autonomy

• localisation
  • odometry by tracking points on images
  • LOAM algorithm
• perception
  • semantic labelling of image
    • Efficient graph-based image segmentation
  • transform coordinates and fuse with LIDA data
  • dynamic obstacle tracking for moving objects
  • using neural networks to analyze images
• planning
  • need to account for vehicle dynamics
  • A* search on state lattice
• control
  • open loop control, no feedback
  • feedback control

other issues

• missing planning
• individual and cooperative behaviours
• mapping
• visualization

engineering robustness

• health reporting
• supervisor daemons
• state machines for each module
• safeguards
• deterministic execution times
  • custom dafe data structures

the road ahead

• full autonomy
• deep neural networks
• solid state LIDAR
• toolkits

questions

• testing in the lab
  • with simulators
• AVs are getting bullied