Self-driving cars are useless without specialized maps—this invention could free them
New software could make robotic vehicles much better at handling long drives into countryside.
Some background: Autonomous cars currently undergoing testing drive only on streets with meticulously labeled maps that take up huge amounts of storage space. “Maps for even a small city tend to be gigabytes; to scale to the whole country, you’d need incredibly high-speed connections and massive servers,” says Teddy Ort, a grad student at MIT’s computer science and artificial intelligence lab (CSAIL).
The solution: A new, more adaptable approach by the CSAIL team, called MapLite, uses simple GPS data to plot a path to the vehicle’s destination, and lidar sensors to navigate along the way. The sensors estimate curb distances and the road conditions more than 100 feet ahead of the vehicle.
Why it matters: Labor-intensive mapping systems are not a scalable solution. Autonomous cars will need to function in areas with poor-quality or unlit roads on which they don’t have detailed data. While MapLite has only been tested in rural Massachusetts so far, it could make robotic cars more capable drivers.
Keep Reading
Most Popular
DeepMind’s cofounder: Generative AI is just a phase. What’s next is interactive AI.
“This is a profound moment in the history of technology,” says Mustafa Suleyman.
What to know about this autumn’s covid vaccines
New variants will pose a challenge, but early signs suggest the shots will still boost antibody responses.
Human-plus-AI solutions mitigate security threats
With the right human oversight, emerging technologies like artificial intelligence can help keep business and customer data secure
Next slide, please: A brief history of the corporate presentation
From million-dollar slide shows to Steve Jobs’s introduction of the iPhone, a bit of show business never hurt plain old business.
Stay connected
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.