Calling all cars:
cell phone
networks and the
future of traffic
Presentation by Scott Corey
Article written by Haomiao
Huang
The Future of Cars
 Self-driving
cars?
 Boosting the brainpower of the
environment cars drive in
 Traffic monitoring has been revolutionized
An intelligent highway
 Reducing
the effect of traffic jams and
accidents
 Traffic control schemes to react to real
time data
 Aid in planning for the future
Sensors
 Monitor
traffic
 Parking availability
 Air pollution
 Have traditionally been static sensors



Inductive Loop Detectors
Traffic Cameras
RFID tags
Problems
 Expensive
to deploy, operate, repair
 Placed only at key locations
 Mobile
sensors are a necessity
Mobile Phones
 Equipped
with GPS and Internet access
 Smartphones enable more widespread
source of data
 Worldwide,
there are more cell phones in
use than toothbrushes
Mobile Millennium
 One
of the first large-scale phone-based
traffic monitoring projects in the US
 Run by Nokia, NAVTEQ, and UC Berkeley
Gathering data, but privately
 User
privacy is key for user acceptance
 Two main needs:


Preventing the path of a vehicle to be
reconstructed
Separating the identification of the phone
from the data
Anonymity
 Data
from phones is tagged with user
information
 The data packet is encrypted at
transmission
 Proxy server cannot decrypt packet, but
can strip identifying information
 Sent to traffic servers after information
stripped
Reconstructing paths
 Uses
virtual trip lines instead of constant
reporting
 VTL spacing varies based on speed to
maximize number of cars
 Randomizing measurements
Making sense of it all





UC Berkeley tasked to fuse all the data
together
GPS from phones
GPS data from dedicated vehicles
Static sensors
Given all of the measurements being
gathered and a stretch of road of interest,
what is the best estimate of the number of
cars on that road, and how fast they're
going?
Combining data with maps
 GPS
tracks are useless alone – need to
combine with maps to know what road
network you are monitoring
 Measurements have to use machinelearning methods to correct for people
walking with phones, parked cars
The flow of traffic
 Tracking
thousands of cars individually is
difficult and expensive
 Traffic researchers treat movement of cars
as liquid flowing through tubes
Fluid Dynamics
 Requires
initial conditions and rate of cars
entering/leaving roadway
 Fluid dynamics model works well with
fixed sensors
 Cameras can determine initial conditions
 Sensors attached to on and off ramps
Disruptions
 Drivers


are not perfect
Accidents
Unnecessary slow-downs
 Adding
GPS dramatically increases the
versatility of the fluid model
 GPS incorporated as internal conditions
for the flow to satisfy
Mobile Century
 Proof
of concept test
 100 cars with mobile phones mixed into
traffic
 Ran for 10 hours with 150 student drivers
 Despite accounting for 2-5% of cars on
the highway, speed and density of cars
measured at a high resolution
 Accident was detected and reported in
less than a minute
Till all are one
 Concepts
and technology are now
widespread
 Mobile sensors used to identify potholes in
roads
 Connections to vehicle sensors
 Mobile sensing is the future