IEEE Communications Magazine - June 2017 - page 128

IEEE Communications Magazine • June 2017
126
0163-6804/17/$25.00 © 2017 IEEE
A
bstract
Map services and applications have been
studied extensively within the mobile comput-
ing community in the past two decades, starting
from standalone GPS receivers and then mov-
ing toward connected smart terminals with live
digital maps of transportation networks and even
real-time traffic. More recently, with the deep
penetration of modern 3G/4G networking and
social networking, the crowd intelligence from
the social community has been explored toward
crowdsourced navigation. In this article, we first
provide an overview of the past and present road
navigation technologies. We then discuss very
recent advances in crowd intelligence, identifying
the unique challenges and opportunities therein.
We further present a case study that utilizes the
crowdsourced driving information to combat the
last mile puzzle for road navigation.
I
ntroduction
With the advances of outdoor positioning services
(GPS in particular), automated road navigation
has quickly risen to become a killer application
over the past two decades. Earlier generations
of navigation services rely on dedicated GPS
devices from such major companies as TomTom,
Garmin, and Magellan. Given the deep penetra-
tion of third/fourth generation (3G/4G) mobile
networking and social networking, drivers are
now well connected anytime and anywhere; they
can readily access information from the Internet
and share the information with their communi-
ty. Online digital map services such as Google
Maps are experiencing an explosion in use and
serving billions of users on a daily basis.
1
Real-
time driving information such as live traffic or
construction locations has been incorporated as
well. On the macro-scale of a transportation net-
work, the quality of the recommended routes is
generally acceptable with state-of-the-art naviga-
tion services. However, it is known [1] that the
routes from the map-based services often fail to
be agreed on by local drivers, who have detailed
knowledge of local/dynamic driving conditions.
There is great potential in exploring the crowd
intelligence toward
crowdsourced navigation
.
In this article, we first provide an overview of
past and present road navigation technologies.
We then discuss the very recent advances in
crowd intelligence, identifying the unique chal-
lenges and opportunities therein. Following in
chronological order, we summarize the key activi-
ties in two stages (Fig. 1):,
1.
Standalone devices
, starting from GPS receiv-
ers and then smart devices (smartphones
in particular) that seamlessly integrate such
positioning technologies as assisted GPS
(A-GPS), WiFi positioning, motion sensors,
and cellular network positioning
2.
Crowd intelligence
, which has been popular
in map building, navigation, and localization,
particularly with the advancement of smart-
phones with social networking
We further present a crowdsourced navigation
application as a case study,
CrowdNavi
[2], which
incorporates a complete set of algorithms to auto-
matically cluster the landmarks from drivers’ tra-
jectories and locate the best route. We highlight
the key design and implementation issues therein
and demonstrate its superiority with a real-world
example for last mile navigation.
The remainder of this article is organized as
follows. We present representative works from
the early stages of research on standalone devices
from GPS to smartphones. We focus on the use
of crowdsourced human intelligence in naviga-
tion. We then present the case study of Crowd-
Navi. Finally, we conclude the article.
N
avigation with
S
tandalone
D
evices
:
F
rom
GPS
to
S
martphones
The cornerstone of any navigation service is a reli-
able positioning technology, and GPS is no doubt
the dominating one. The GPS project, launched
by the United States in 1973, provides geoloca-
tion and time information to a receiver anywhere
on Earth where there is an unobstructed line of
sight to four or more GPS satellites. It operates
independent of any telephonic or Internet recep-
tion. Other similar systems (e.g., Galileo in the
European Union and Beidou in China) have been
or are being deployed.
For civilian use, GPS can reach a 3.5 m hor-
izontal accuracy. While high-sensitivity GPS
chipsets have been adopted in recent years,
standalone GPS still does not work well in urban
and indoor environments. As a result, comple-
mentary positioning systems are employed in
smartphones (e.g., cellular network and WiFi posi-
tioning techniques).
Assisted GPS:
Most smartphones are GPS-en-
abled and further employ a technology known as
A-GPS, where an assistance server provides satel-
Crowdsourced Road Navigation:
Concept, Design, and Implementation
Xiaoyi Fan, Jiangchuan Liu, Zhi Wang, Yong Jiang, and Xue Liu
S
ustainable
I
ncentive
M
echanisms
for
M
obile
C
rowdsensing
The authors provide an
overview of past and
present road navigation
technologies. They
discuss recent advances
in crowd intelligence,
identifying the unique
challenges and opportuni-
ties therein. They present
a case study that utilizes
the crowdsourced driving
information to combat
the last mile puzzle for
road navigation.
Xiaoyi Fan and Jiangchuan Liu are with Simon Fraser University; Zhi Wang and Yong Jiang are with Tsinghua University; Xue Liu is with McGill University.
1
Google I/O 2013 session
(Google Maps: Into the
Digital Object Identifier:
10.1109/MCOM.2017.1600738
1...,118,119,120,121,122,123,124,125,126,127 129,130,131,132,133,134,135,136,137,138,...228
Powered by FlippingBook