Arvind Thiagarajan, Lenin S. Ravindranath, Katrina LaCurts, Sivan Toledo, Jakob Eriksson, Samuel Madden, Hari Balakrishnan
7th ACM Conference on Embedded Networked Sensor Systems (SenSys), Berkeley, CA, November 2009
Traffic delays and congestion are a major source of inefficiency,
wasted fuel, and commuter frustration. Measuring and
localizing these delays, and routing users around them, is an
important step towards reducing the time people spend stuck
in traffic. As others have noted, the proliferation of commodity
smartphones that can provide location estimates using a
variety of sensors — GPS,WiFi, and/or cellular triangulation—
opens up the attractive possibility of using position samples
from drivers’ phones to monitor traffic delays at a fine spatiotemporal
granularity. This paper presents VTrack, a system
for travel time estimation using this sensor data that addresses
two key challenges: energy consumption and sensor unreliability.
While GPS provides highly accurate location estimates,
it has several limitations: some phones don’t have GPS at
all, the GPS sensor doesn’t work in “urban canyons” (tall
buildings and tunnels) or when the phone is inside a pocket,
and the GPS on many phones is power-hungry and drains
the battery quickly. In these cases, VTrack can use alternative,
less energy-hungry but noisier sensors like WiFi to
estimate both a user’s trajectory and travel time along the
route. VTrack uses a hidden Markov model (HMM)-based
map matching scheme and travel time estimation method that
interpolates sparse data to identify the most probable road
segments driven by the user and to attribute travel times to
those segments. We present experimental results from real
drive data and WiFi access point sightings gathered from a deployment
on several cars. We show that VTrack can tolerate
significant noise and outages in these location estimates, and
still successfully identify delay-prone segments, and provide
accurate enough delays for delay-aware routing algorithms.
We also study the best sampling strategies for WiFi and GPS
sensors for different energy cost regimes.
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Bibtex Entry:
@inproceedings{thiagarajan2009vtrack, author = "Arvind Thiagarajan and Lenin S. Ravindranath and Katrina LaCurts and Sivan Toledo and Jakob Eriksson and Samuel Madden and Hari Balakrishnan", title = "{VTrack: Accurate, Energy-Aware Traffic Delay Estimation Using Mobile Phones}", booktitle = {7th ACM Conference on Embedded Networked Sensor Systems (SenSys)}, year = {2009}, month = {November}, address = {Berkeley, CA} }