Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

An AI that makes road maps from aerial images

18.04.2018

Map apps may have changed our world, but they still haven't mapped all of it yet. In particular, mapping roads can be tedious: even after taking aerial images, companies like Google still have to spend many hours manually tracing out roads. As a result, they haven't yet gotten around to mapping the vast majority of the more than 20 million miles of roads across the globe.

Gaps in maps are a problem, particularly for systems being developed for self-driving cars. To address the issue, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have created RoadTracer, an automated method to build road maps that's 45 percent more accurate than existing approaches.


This is the RoadTracer map process.

Credit: MIT CSAIL

Using data from aerial images, the team says that RoadTracer is not just more accurate, but more cost-effective than current approaches. MIT professor Mohammad Alizadeh says that this work will be useful both for tech giants like Google and for smaller organizations without the resources to curate and correct large amounts of errors in maps.

"RoadTracer is well-suited to map areas of the world where maps are frequently out of date, which includes both places with lower population and areas where there's frequent construction," says Alizadeh, one of the co-authors of a new paper about the system. "For example, existing maps for remote areas like rural Thailand are missing many roads. RoadTracer could help make them more accurate."

In tests looking at aerial images of New York City, RoadTracer could correctly map 44 percent of its road junctions, which is more than twice as effective as traditional approaches based on image segmentation that could map only 19 percent.

The paper, which will be presented in June at the Conference on Computer Vision and Pattern Recognition (CVPR) in Salt Lake City, Utah, is a collaboration between MIT CSAIL and the Qatar Computing Research Institute (QCRI).

Alizadeh's MIT co-authors include graduate students Fayven Bastani and Songtao He, and professors Hari Balakrishnan,Sam Madden, and David DeWitt. QCRI co-authors include senior software engineer Sofiane Abbar and Sanjay Chawla, who is the research director of QCRI's Data Analytics Group.

How it works

Current efforts to automate maps involve training neural networks to look at aerial images and identify individual pixels as either "road" or "not road." Because aerial images can often be ambiguous and incomplete, such systems also require a post-processing step that's aimed at trying to fill in some of the gaps.

Unfortunately, these so-called "segmentation" approaches are often imprecise: if the model mislabels a pixel, that error will get amplified in the final road map. Errors are particularly likely if the aerial images have trees, buildings or shadows that obscure where roads begin and end. (The post-processing step also requires making decisions based on assumptions that may not always hold up, like connecting two road segments simply because they are next to each other.)

Meanwhile, RoadTracer creates maps step-by-step. It starts at a known location on the road, and uses a neural network to examine the surrounding area to determine which point is most likely to be the next part on the road. It then adds that point and repeats the process to gradually trace out the road one step at a time.

"Rather than making thousands of different decisions at once about whether various pixels represent parts of a road, RoadTracer focuses on the simpler problem of figuring out which direction to follow when starting from a particular spot that we know is a road," says Bastani. "This is in many ways actually a lot closer to how we as humans construct mental models of the world around us."

The team trained RoadTracer on aerial images of 25 cities across six countries in North America and Europe, and then evaluated its mapping abilities on 15 other cities.

"It's important for a mapping system to be able to perform well on cities it hasn't trained on, because regions where automatic mapping holds the most promise are ones where existing maps are non-existent or inaccurate," says Balakrishnan.

Bastani says that the fact that RoadTracer had an error rate that is 45 percent lower is essential to making automatic mapping systems more practical for companies like Google.

"If the error rate is too high, then it is more efficient to map the roads manually from scratch versus removing incorrect segments from the inferred map," says Bastani.

Still, implementing something like RoadTracer wouldn't take people completely out of the loop: The team says that they could imagine the system proposing road maps for a large region and then having a human expert come in to double-check the design.

"That said, what's clear is that with a system like ours you could dramatically decrease the amount of tedious work that humans would have to do," Alizadeh says.

Indeed, one advantage to RoadTracer's incremental approach is that it makes it much easier to correct errors - human supervisors can simply correct them and re-run the algorithm from where they left off, rather than continue to use imprecise information that trickles down to other parts of the map.

Of course, aerial images are just one piece of the puzzle. They don't give you information about roads that have overpasses and underpasses, since those are impossible to ascertain from above. As a result, the team is also separately developing algorithms that can create maps from GPS data, and working to merge these approaches into a single system for mapping.

###

This project was supported in part by the Qatar Computing Research Institute.

Media Contact

Adam Conner-Simons
aconner@mit.edu
617-324-9135

 @mit_csail

http://www.csail.mit.edu/ 

Adam Conner-Simons | EurekAlert!

More articles from Information Technology:

nachricht Reversing cause and effect is no trouble for quantum computers
20.07.2018 | Centre for Quantum Technologies at the National University of Singapore

nachricht Study suggests buried Internet infrastructure at risk as sea levels rise
18.07.2018 | University of Wisconsin-Madison

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Future electronic components to be printed like newspapers

A new manufacturing technique uses a process similar to newspaper printing to form smoother and more flexible metals for making ultrafast electronic devices.

The low-cost process, developed by Purdue University researchers, combines tools already used in industry for manufacturing metals on a large scale, but uses...

Im Focus: First evidence on the source of extragalactic particles

For the first time ever, scientists have determined the cosmic origin of highest-energy neutrinos. A research group led by IceCube scientist Elisa Resconi, spokesperson of the Collaborative Research Center SFB1258 at the Technical University of Munich (TUM), provides an important piece of evidence that the particles detected by the IceCube neutrino telescope at the South Pole originate from a galaxy four billion light-years away from Earth.

To rule out other origins with certainty, the team led by neutrino physicist Elisa Resconi from the Technical University of Munich and multi-wavelength...

Im Focus: Magnetic vortices: Two independent magnetic skyrmion phases discovered in a single material

For the first time a team of researchers have discovered two different phases of magnetic skyrmions in a single material. Physicists of the Technical Universities of Munich and Dresden and the University of Cologne can now better study and understand the properties of these magnetic structures, which are important for both basic research and applications.

Whirlpools are an everyday experience in a bath tub: When the water is drained a circular vortex is formed. Typically, such whirls are rather stable. Similar...

Im Focus: Breaking the bond: To take part or not?

Physicists working with Roland Wester at the University of Innsbruck have investigated if and how chemical reactions can be influenced by targeted vibrational excitation of the reactants. They were able to demonstrate that excitation with a laser beam does not affect the efficiency of a chemical exchange reaction and that the excited molecular group acts only as a spectator in the reaction.

A frequently used reaction in organic chemistry is nucleophilic substitution. It plays, for example, an important role in in the synthesis of new chemical...

Im Focus: New 2D Spectroscopy Methods

Optical spectroscopy allows investigating the energy structure and dynamic properties of complex quantum systems. Researchers from the University of Würzburg present two new approaches of coherent two-dimensional spectroscopy.

"Put an excitation into the system and observe how it evolves." According to physicist Professor Tobias Brixner, this is the credo of optical spectroscopy....

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

Leading experts in Diabetes, Metabolism and Biomedical Engineering discuss Precision Medicine

13.07.2018 | Event News

Conference on Laser Polishing – LaP: Fine Tuning for Surfaces

12.07.2018 | Event News

11th European Wood-based Panel Symposium 2018: Meeting point for the wood-based materials industry

03.07.2018 | Event News

 
Latest News

A smart safe rechargeable zinc ion battery based on sol-gel transition electrolytes

20.07.2018 | Power and Electrical Engineering

Reversing cause and effect is no trouble for quantum computers

20.07.2018 | Information Technology

Princeton-UPenn research team finds physics treasure hidden in a wallpaper pattern

20.07.2018 | Materials Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>