Channels ▼

Web Development

Cars as Mobile Traffic Sensors

Data about road and traffic conditions can come from radio stations' helicopters, the Department of Transportation's roadside sensors, or even, these days, updates from ordinary people with cell phones. But all of these approaches have limitations: Helicopters are costly to deploy and can observe only so many roads at once, and it could take a while for the effects of congestion to spread far enough that a road sensor will detect them.

MIT's CarTel project is investigating how cars themselves could be used as ubiquitous, highly reliable mobile sensors. To that end, members of the CarTel team have developed a new algorithm that would optimize the dissemination of data through a network of cars with wireless connections. Researchers at Ford are already testing the new algorithm for possible inclusion in future versions of Sync, the in-car communications and entertainment system developed by Ford and Microsoft.


Calvin Newport, a postdoc in Balakrishnan's group, who developed the new algorithm together with Alejandro Cornejo, a grad student in Nancy Lynch's Theory of Distributed Systems Group, says that previous work on diffusing information through networks of cars tended to assume that, over time, the network would always provide a sequence of connections that could relay data from any one car to any other. The problem is that the CarTel experiment suggests that that isn't the case. On the other hand, it also demonstrates that two cars that do come within wireless-transmission range of each other will frequently remain near each other for long stretches of time -- repeatedly hitting the same lights on the same stretch of road, for instance.

A good information-dissemination algorithm should thus ensure that two cars passing each other in opposite directions, with only a fleeting wireless connection, will exchange high-priority data -- say, that a tractor trailer has jackknifed across three lanes of traffic on the nearby interstate. On the other hand, it should also ensure that two cars stuck at a light together, with plenty of time on their hands, exchange lower-priority data as well -- like the location of a particularly nasty pothole.


The crucial feature of the series is that the smaller the number, the more frequently it occurs; but over long enough spans of time, higher numbers will occur at least once. If the smallness of a number represents its priority -- jackknifed trucks are 0, bad potholes are, say, 8 -- then using the binary carry sequence to order data transmissions will ensure that high-priority data is broadcast more frequently, but not to the exclusion of low-priority data. Newport and Cornejo were able to mathematically prove that using the binary carry sequence optimizes the diffusion of information throughout the network.

T. J. Giuli, the technical expert on mobile computing at Ford Research and Advanced Engineering who's testing Newport and Cornejo's algorithm, says that disseminating data through networks of cars will be particularly useful in urban areas. The alternative, he explains, would be to download traffic data over the cellular network, as anyone with an iPhone might do today. "If more people are associated with the same cell base station, you kind of have to split the bandwidth among more and more people, so your effective bandwidth decreases," Giuli says. With a network of wirelessly connected vehicles, on the other hand, "as the density of mobile-networking consumers increases, the bandwidth also increases." At the same time, however, Giuli says that networked vehicles could also help propagate traffic information in rural areas where cell towers -- and, for that matter, hovering helicopters and DOT sensors -- are sparse.

Related Reading

More Insights

Currently we allow the following HTML tags in comments:

Single tags


<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags


<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text


Dr. Dobb's TV