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2021 | OriginalPaper | Chapter

Infrastructure Enabled Autonomy—Autonomy as a Service

Author : Swaminathan Gopalswamy

Published in: Autonomous Vehicles

Publisher: Springer Nature Singapore

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Abstract

Multiple studies have established the potential for significant societal, environmental and economic benefits from autonomous vehicles. However, all the current approaches to autonomous driving require the automotive manufacturers to shoulder the primary responsibility and liability associated with replacing human perception and decision making with automation, slowing the penetration of autonomous vehicles, and consequently slowing the realization of the benefits of autonomous vehicles. We propose a new approach to autonomous driving that will re-balance the responsibility and liabilities associated with autonomous driving between traditional automotive manufacturers, private infrastructure players, and third-party players. The proposed distributed intelligence architecture leverages recent advances in connectivityand edge computing. The resulting Infrastructure Enabled Autonomy (IEA) leads to the new business model of “autonomy as a service”.

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Footnotes
1
Fagnant and Kockelman (2015).
 
2
US Department of Transportation (2018).
 
3
US Department of Transportation (2008).
 
4
Fenn and Blosch (2018).
 
5
US Department of Transportation (1997).
 
6
Thorpe et al. (1997).
 
7
Defense Advanced Research Projects Agency (2004).
 
8
Waymo (2020).
 
9
See, e.g., US Department of Transportation (2017).
 
10
JD Power Article (2016).
 
11
Quigley et al. (2008).
 
12
See, e.g., Koopman and Wagner (2016).
 
13
Society of Automotive Engineers (2018).
 
14
Yurtsever et al. (2020).
 
15
Accenture (2018).
 
16
Pizzuto et al. (2019)
 
17
To help readability, we capture a table of acronyms and symbols used in this chapter:
OEM
Original Equipment Manufacturer (car maker)
ADAS
Advanced Driver Assistance Systems
DBW
Drive-by-wire
API
Application Programming (Software) Interface
IEA
Infrastructure Enabled Autonomy
ITC
Infrastructure Enabled Autonomy Traffic Corridor
SA
Situational Awareness
DM
Decision Making
RSU
Road Side Unit (that carries the MSSPs)
SmartInfra
“Edge” computers that reside in the MSSP to generate SA from the sensors
MSSP
Multi-Sensor Smart Pack (carries sensors, SmartInfra, and comm)
SC
SmartConnect
 
18
The original technical paper, see Gopalswamy and Rathinam (2018).
 
19
See, e.g., Shalev-Shwartz et al. (2017).
 
20
For the mathematical derivation of the analysis and the numerical example details, see Gopalswamy and Rathinam (2018).
 
21
Nayak et al.(2018).
 
22
Ravipati et al. (2019).
 
23
Marr (2019).
 
24
Nayak (2019).
 
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Metadata
Title
Infrastructure Enabled Autonomy—Autonomy as a Service
Author
Swaminathan Gopalswamy
Copyright Year
2021
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-15-9255-3_8