XPeng Motors focuses on developing intelligent electric vehicles with autonomous driving capabilities tailored for Chinese millennials. The company has a detailed roadmap for its autonomous driving solutions, including various levels of automation and advanced features optimized for the Chinese market. Their system architecture leverages high-performance computing platforms, like NVIDIA Xavier, to enhance perception and driving assistance technologies.

1. 0
Developing Autonomous Driving EVs for the
China Market XPENG Motors’ Approach
Junli Gu
VP of Autonomous Driving, XPENG
motors
March 18, 2019

2. 1
Agenda
1. XPENG Motors Introduction and Background
2. Roadmap for XPENG Motors’ Autonomous Driving Solution
3. System Architecture Design Powered by Xavier

3. 2
Who is XPENG?
We develop FUN, CONNECTED and INTELLIGENT EVs tailored for
the young and tech-savvy Chinese Millennials
2
• Aimed at young Internet users in China, with autonomous driving and
intelligent connection as the core differences
• 2014: Founded in Guangzhou, China
• Dec 2018: Mass production and official launch of G3 (electrical SUV)
• Q1 2019: Mass production of E28 (electrical sedan)

4. 3
Strong R&D capabilities and investments
Shanghai
Intelligent Connected
Vehicle
Navigation R&D
Silicon Valley &
San Diego
Machine Learning
Autonomous Driving
R&D
Guangzhou
Vehicle and VCU
R&D
V2X Testing
Trial and Production
Lead-in
Beijing
Artificial Intelligence
R&D
R&D footprint
Our R&D headcount accounts for over 70% of our total number of employees.

5. 4
Your Smart Driving Assistant
Connectivity
Xmart OS
X-pilot
Artificial
Intelligence

6. 5
X-center
XPENG Headquarter
5

7. 6
Agenda
1. XPENG Motors Introduction and Background
2. Roadmap for XPENG Motors’ Autonomous Driving Solution
3. System Architecture Design Powered by Xavier

8. 7
L3 Products: Highly-Autonomous Highway Features
L4 Products: Fully-Autonomous
Urban & Highway Features
- Driverless Robo Taxi
- Driverless Robo Bus
- Human Driver vehicles
L2+ Products: Semi-Autonomous Highway/Urban Features
- Human Driver vehicles
Self-Driving Two Separate Branches…

9. Comfort Driving with safety guarantees
Where are we heading…
• Key differentiation through XPENG’s intelligent EV strategy
• Focus on in-house software solutions running on leading
computer hardware platforms
• Focus on enhancing driver assistance features towards L3
capabilities in 2020
• Focus on feature optimization for Chinese market and
Chinese consumers
8

10. 9
Roadmap for XPENG Motors’ Autonomous Driving Solution XPilot
2018-2019 2020 2021-2022 2024-2025
CarModel
Autonomous
Driving
Achievement
&Goal
• Xpilot 2.0:
Full scenario auto
parking + LCC + ACC
• Xpilot 3.0:
Super Memory Parking
+ Highway Autopilot
• Xpilot 4.0:
AVP + Highway/Urban
Autopilot
• Xpilot x.0:
Full Automation in
limited scenarios
(highway, parking, etc.)
• First generation
solution for
commercialization
with partial self
developed IPs
• Fully self developed
end-to-end SW IP
• Next gen HW
platform with
optimized sensor cost
• First level-4 solution
in consumer vehicle
A Class SUV (G3) B Class Sedan (E28) B Class SUV

11. 10
XPENG G3
By AI,
irregular lots
By memory
Roadmap for XPENG Motors’ Autonomous Driving Solution-XPilot
parking functions
XPENG E28
Alleviate people’s parking anxiety in parallel, vertical, perpendicular, irregular lots…
parking functions
By voice
By Vision
By Ultrasonic

12. 11
Use Case Example: Super Memory Parking

13. 12
Use Case Example: Highway Auto-Pilot

14. 13
2km ahead
Xpilot’s Surrounding Reality
Ego
Traffic
Point of interest
Road side object
Lane condition

15. 14
Agenda
1. XPENG Motors introduction and background
2. Roadmap for XPENG Motors’ Autonomous Driving Solution
3. System architecture design powered by Xavier

16. 15
Driving
Big Data
AI and
Perception
High-perf
chips
Customized
Sensor
Structure
- -
Chinese Traffic Patterns
Local adaption is a must
- -
• Chinese style lane change and close cutting in
• Very large variety of obstacles
• Dense traffic
• Irregular Pattern

17. 16
Challenge: Perception & Creating a Representative 3D Environmental Model
Compute (MP/s)
Quality raw sensor input with cost
constraints
2
1
Preponderance of training data
(especially corner cases)
3

18. 17
Challenge: Perception & Creating a Representative 3D Environmental Model
Real stream taken from E28 camera sets; ISP developed in house;

19. 18
Challenge: Extending to Day/Night, All Weather, All locations
1) Time (Location of Sun: Day/Night/NotDawn/NotDusk)
2) Select Weather Conditions
3) Availability of GNSS & RTK
4) Place (GeoFenced)
5) Select Speed Range
6) Road/Traffic Conditions
Sensing/Perception challenges (due
to insufficient quality of raw data
and/or compute power)
Mapping challenges
Driving policy
challenges

20. Ultrasonic Sensors
(6 in Front)
Tri-focal Cameras
(2M pixels, FOV 28,
52, 100, 60/15fps)
Surround-view
Camera (1 at Back)
Rear-view Camera
(2M pixels,FOV 52,
30fps)
In-Car Intelligent
Camera
Radars
(5 in Total)
Surround-view Camera
(1 in Front)
Ultrasonic Sensors
(6 at Back)
Surround-view
Camera (2 on Sides)
Cut-In Prevention
Camera
1M pixels, 60fps)Rear-view Camera
(1M pixels, 30fps)
Sensor System for E28 (Mass production in 2020)
19
Note: We use first vehicle G3’s picture as E28’s design is not revealed yet.

21. 20
XPilot Camera Coverage and Functions for E28
360 coverage; Designed to cover traffic scenarios in China
HFOV 100
HFOV 52

22. 21
System Differentiators

23. 22
1828x948@15fps
(for Highway Driving)
457x237@60fps
(for Urban Driving)
Long Range CNN
(Perception at > 200m)
Close Proximity CNN
(Responds x4 faster)
Cameras
Variable fps Network for China Specific Drive Conditions
(Close Vehicle Proximity and Abrupt Cut-ins)
1

24. 23
HighwayUrban Canyon
START POINT /
END POINT
55 Km route (Approx. 2.5hr)
2.5hrs x 3600 x 1Hz = 9,000 samples
GuangzhouRoute8
Absolute
Localization
Reference
Antenna +
GNSS/INS
2 GNSS / INS
20cm absolute-localization-accuracy at 95% (2 σ)
20cm absolute-localization-accuracy for at 95% (2 σ) of Highway route in white

25. 24
Front Radars
Right Front
Corner Radar
Left Front
Corner Radar
Left Rear
Corner Radar
Right Rear
Corner Radar
3 RADAR
Five Radars of High Angular Resolution: 2x improvement
5th Generation of Radar Technology

26. 25
Industry Leading Computing Platform
XPilot Unit (XPU) powered by NVIDIA Xavier
NVIDIA Xavier
Safety MCU
Camera Des
Camera Des
Camera Des
Memory
EMMC
Storage
CAN
Transceiver
Ethernet
Switch
Power
Management
CAN Ethernet
4

27. 26
Why NVIDIA Xavier?
0
5
10
15
20
25
30
35
Computing Power (TOPS)
Deep Learning Computing Throughput
NVIDIA Xavier FPGA NVIDIA Parker TI TDA2xx
TOPS

28. 27
XPU Software Stack
NVIDIA Xavier SoC Aurix MCU
Hypervisor
NVIDIA
Foundations
QNX OS and BSP/Drivers
NVIDIA System Software NvMeida/CUDA/CuDNN/TensorRT …
NVIDIA Drive Works
XPilot Frameworks
(Project Eagle)
NVIDIA
Tier-1
AUTOSAR
OTA Data
Camera
Service
CAN
Service
(Radar,
IMU/GNSS,
Vehicle IO)
XPilot
Autonomous
Driving
Applications
Perception,
Localization
Prediction, Path
Planning
Control, …
XPU HW NVIDIA/Tier- SW XPU Platform SW XPilot SW
Visualization Launcher
Monitor
Diagnostic
Service
Xpilot
Safety
App

29. 28
Driving hierarchy w/ safety intervention
AEB
Driver: Human Driver: XPilot
Collision
Warnings
5 SAFETY
Independent AEB System

30. 29
Summary
• XPENG Motors develop FUN, CONNECTED and INTELLIGENT EVs tailored for the
young and tech-savvy Chinese millennials
• Roadmap for XPENG Motors’ Autonomous Driving Solution
• System architecture design powered by Xavier

31. 30
E28 is coming…
To be revealed at Auto Shanghai April 16