"a vision of safety," a presentation from nauto
Post on 13-Apr-2017
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A Vision of Safety
Dr. Stefan Heck
CEO
Nauto, Inc.
1
Transport today: 99% waste of $2/mile Productive use
2.6% driving
0.8% looking for parking
0.5% sitting in congestion
The typical American car
spends 96% of its time parked
86% of
fuel never
reaches
the wheels
Rolling resistance
1% Energy used to move the person
Aerodynamics
Transmission
losses
Idling
Engine losses
Inertia
Auxiliary power Road at peak throughput only 5% of the time…
...and then only 10% covered with cars
More than 33,000 road
fatalities in US
$300B annually in cost
>95%
Caused
by human
error
2
More than 33,000 road
fatalities in US
$300B annually in cost
>95%
Caused
by human
error
Productive use
2.6% driving
0.8% looking for parking
0.5% sitting in congestion
The typical American car
spends 96% of its time parked
86% of
fuel never
reaches
the wheels
Rolling resistance
1% Energy used to move the person
Aerodynamics
Transmission
losses
Idling
Engine losses
Inertia
Auxiliary power Road at peak throughput only 5% of the time…
...and then only 10% covered with cars
Autonomous: 90% accident reduction
Connected: Time &
route shift & transit
integration
Shared: 50% utilization
(70% with
delivery at night?)
Electric: 85% efficient
drivetrain
Transport today: 99% waste of $2/mile
3
8 cents per mile!
Autonomous: 90% accident reduction
Connected: Time &
route shift & transit
integration
Shared: 50% utilization
(70% with
delivery at night?)
Electric: 85% efficient
drivetrain
Autonomous
maintenance
& charging
Peloton or 8x
capacity
autonomous
HOV lanes
Smart Autoroute
No up
front cost for
batteries
Use only
size car &
battery you
need
Match open trips & 2 minute service
Intermodal hub connections
ACES
4
Billon dollar challenges as the world urbanizes Traffic Congestion
• $300B time lost – 5.5B hours, 4x pollution
• Together with housing biggest economic pain point
for wealthy cities
• 30% of urban traffic circling for parking
• 2-4% asset productivity of cars
Accidents
• 33K lives, 250K disabilities, 2M injuries
• $300B damage
• 95% human error mostly phone and passenger
distraction and traffic/road/environmental conditions
realized too late
• 12 US cities and dozens globally embrace Vision Zero
Public Safety
• 1.2 million cars stolen every year
• 800K missing people, 65K kidnappings per year
• 2/5 pedestrian fatalities are hit and run
• $100B parking revenue
Infrastructure & Maps
• $155B spent on highways – prioritization is
critical
• Autonomy requires precise, up to date data
• $2B mapping market growing 55% CAGR
5
Real time public space data network solves system problems Traffic Congestion: Waze on Steroids
• Data by lane
• Real time visual brake lights and speeds vs GPS averaging
with 3-7 min delay
• Data generated automatically – no turking while driving
• Find parking in real time
Accidents: Causes not proxies to reinvent insurance
• 10x data from near misses not just actual accidents
• See 10-12 cars per vehicle equipped with sensors
• Assess actual driver behavior BEFORE accidents
• Ability to warn and coach to PREVENT rather than PROTECT loss
• Instant upload of telemetry for accidents
Public Safety: Robocop writes tickets
• Focus police on serious/repeat offenders
• Car tracks its surroundings – alarm with self-reporting
• Parking without pucks or wiring
Infrastructure & Maps: Crowd sourced 4D
• Near real time coverage
• SLAM allows construction of high resolution
dynamic overlay maps
• Prioritization of city resources to usage
AI computer
vision on vehicles • Detect and classify vehicles, signs, road
conditions
• Detect pedestrians and occupants
• Monitor driver attention
• Real time bi-directional link to cloud
• Machine learning in car and in cloud
6
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1 2 3 4 5 6 7 8 9 10 Cra
sh &
Near
Cra
sh F
requency Index
Lo
ss R
atio
In
de
x
Early UBI Current UBI Near Misses + Crashes + Visual Data
With vision context, predictive power grows 5x
Sources: ^“Early UBI”: Progressive July 2012 Snapshot Study; “Current UBI”: Towers Watson April
2015;
“Near Misses + Crashes + Visual Data”: NHTSA / VTTI 100 Car Naturalistic Driving Study
Best Risk
Decile Over-priced risks:
Loss ratio ~75%
better than average
Under-priced risks:
Loss ratio ~150%
worse than average
Average drivers:
Benefit from dynamic
network data services
such as traffic flow
Worst Risk Decile
5x better risk
segmentation than
OBDII/Dongle/Mobile
phone UBI
7
Where?
“The early bird stays alive”
Shifting commute earlier
reduces risk
When?
NAUTO enables real time awareness
Safe
drivers
Average
drivers
Unsafe
drivers
Cra
sh
ra
te
What?
Who?
• Forward-
facing
camera
• Collision
warning /
ADAS
Distractions:
- mobile phone
- passengers
6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11
“Geek” late AM commuter has very high danger at night
• Inward-
facing
camera
• Driver
history
• Mapping
On the left: 4x
danger of right
turn
On the right:
pedestrians
& bicycles
In front: danger of
running a red light
Backing up: potential
property damage
Aggressive driving
style - tailgating,
hard/late braking
Low situational
awareness
Targeted
services more
compelling
than coaching
Car / pedestrian crashes along
Market street
Dangerous on-ramp: Potrero /
César Chávez & Hwy 101
Dangerous intersection:
Bayshore Blvd. & Silver Ave.
Polk St. car / bike crash
corridor: from residential
areas to Mission / startups
Detailed map of
San Francisco
high-incident areas
Monday-Thursday
Cra
sh
ra
te
Early AM commuter avoids crash danger
Standard AM commuter has high danger
• Data science
Drunk driving at night
8
A fork in
the road to
Autonomy
9
What if there was a third way?
• A: Augment human
perception for safety
• C: Each car learns
from every other car
• E: Solve parking,
braking, congestion
• S: Sharing easier if
you know who is
driving and how
10
NAUTO retrofit device
11
In-Vehicle Block Diagram
Main SoC
DRAM Flash Forward Cam
4K
Driver Cam
1080
Audio In/Out
GPS
Acceleromete
r/Compass
Gyro
Wifi +
BT4.0LE
LTE Module
uC PMIC
Battery
Micro
SD
slot
Wish list:
• Low-power SoC
with more than 8
cores, fast GPU
• Neural network
co-processor
• CUDA-like
capabilities on
ARM
• 4K, HDR, wide
angle, high
framerate
12
13
Driver distraction identification
14
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