"Making Existing Cars Smart Via Embedded Vision and Deep Learning," a Presentation from NAUTO

Copyright © 2016 NAUTO 1

Making Existing Cars Smart Via

Embedded Vision and Deep Learning Dr. Stefan Heck, CEO, NAUTO, Inc.

May 2, 2016


Transport Today: 99% Waste of $3/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

More than 33,000 road

fatalities in US

$300B annually in cost

>95%

Caused

by human

error

Road at peak throughput only 5% of the time…

...and then only 10% covered with cars


The Fix: Part 1

Autonomous: 90% accident reduction

Connected: Time, route, and fleet

& mode optimization

Shared: 50% utilization

(70% if used for

delivery at night?)

Electric: 85% efficient

drivetrain


The Fix Part 2:

Autonomous: 90% accident reduction

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 Connected:

Time, route, and fleet

& mode optimization

8 Cents per Mile!


A Fork in

the Road to

Autonomy


• 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

What if there were a third way?

60-80% of

benefits

in

2 years


Fleet App Driver App Insurance API

The Quick Fix: the NAUTO upgrade path!


NAUTO captures driver behavior in context

Driver Vehicle Context

Speed

Location

Acceleration/braking

Intent – glimpse of the future

Distraction

Traffic and road risk

Data on all vehicles visible


-

1

2

3

4

5

6

7

8

1 2 3 4 5 6 7 8 9 10Index o

f Loss / C

olli

sio

ns

Coach

or fire Prevent

#1 cause of

accidents:

distraction

Build their

driving into

autonomy

20%

Safe Drivers

20%

Bad Drivers

60%

Average Drivers

With vision and context, predictive power grows 5x

Current

usage based

insurance

models

NAUTO

machine

vision &

context



NAUTO developed lightweight detection algorithms

1

1

Large cloud algorithm accuracy

exceeds best published academic

results and can be trained to

detect many other types of objects

and events

Small algorithm can be run on

mobile chipset with 35msec

forward pass time


Directly detect #1 cause of crashes


NAUTO: all-weather, any environment


Where?

“The early bird stays alive”

Shifting commute earlier

reduces risk

When?

NAUTO Enables Real Time Awareness

What?

Who?

• Forward-

facing

camera

• Collision

warning /

ADAS

“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

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


Solution to billion dollar problems

Traffic Congestion: Waze on Steroids

• Avoid $300B time lost — 5.5B hours, 4x pollution

• Real time lane by lane traffic not 5 min delayed

• No turking while driving

• Real time parking: 30% of urban traffic circling for parking

Reinvent insurance:

Accidents ->

preventing crashes

• Save 20K lives, 1M

injuries, $300B damage

• Detect when distraction

matters and what good driving is in crowded cities

• 40x data from near misses

• Assess actual driver behavior BEFORE accidents

Public Safety & Safe Sharing

• Recover 1.2 million stolen cars, amber alerts

• Achieve Vision Zero: 2/5 pedestrian fatalities are hit and run today

• Easier to share any car since you know who/how it is driven

Infrastructure & Maps

• Prioritize $155B spent on cities and highways

• Dynamic maps for autonomy

• Make cities easier and safer for humans


Contact:

Stefan Heck

CEO, NAUTO, Inc.

[email protected]

mailto:[email protected]

Technology

"Making Existing Cars Smart Via Embedded Vision and Deep Learning," a Presentation from NAUTO