Researchers testing frugal autonomous car system, aim for $150 price tag
Google certainly has pockets deep enough to trick out self-driving cars with any kind of pricey gear, but researchers at the University of Oxford have begun testing a solution that aims to keep things affordable. Currently, the system leverages an array of low-profile stereo cameras and lasers that rings up at about £5,000 (approximately $7,750), but the next goal is to knock the price down to £500, and eventually to a cool £100 (roughly $150). “Really, we do need to solve the engineering challenges of not relying on expensive sensors, but relying on cheap sensors,” Professor Paul Newman told the Telegraph. “But doing some really smart things with those cheap sensor feeds.”
Rather than a vehicle that acts as a chauffeur at all times, Newman’s vision for the modified Nissan Leaf, dubbed RobotCar, is for it to take control on select occasions. While drivers go about their commute, the system composes a 3D map of the car’s environs and commits it to memory. When the auto identifies a familiar setting and feels confident about its ability to take the reigns, it could let the driver know it’s ready to assume control. Right now, the automobile’s been tested on private roads, but the team behind it is working with the UK’s Department of Transportation to roll it onto public streets.

Researchers testing frugal autonomous car system, aim for $150 price tag

Google certainly has pockets deep enough to trick out self-driving cars with any kind of pricey gear, but researchers at the University of Oxford have begun testing a solution that aims to keep things affordable. Currently, the system leverages an array of low-profile stereo cameras and lasers that rings up at about £5,000 (approximately $7,750), but the next goal is to knock the price down to £500, and eventually to a cool £100 (roughly $150). “Really, we do need to solve the engineering challenges of not relying on expensive sensors, but relying on cheap sensors,” Professor Paul Newman told the Telegraph. “But doing some really smart things with those cheap sensor feeds.”

Rather than a vehicle that acts as a chauffeur at all times, Newman’s vision for the modified Nissan Leaf, dubbed RobotCar, is for it to take control on select occasions. While drivers go about their commute, the system composes a 3D map of the car’s environs and commits it to memory. When the auto identifies a familiar setting and feels confident about its ability to take the reigns, it could let the driver know it’s ready to assume control. Right now, the automobile’s been tested on private roads, but the team behind it is working with the UK’s Department of Transportation to roll it onto public streets.

emergentfutures:

No More Car Crashes by 2020?
The leading cause of car accidents is pretty obvious – its human error. Whether its drunk driving, distracted driving, or aggressive driving, it all comes back to the person behind the wheel. Less than 20% of accidents are caused by road or mechanical failure, so the only way to truly make driving safer for everyone is to give the person behind the wheel more tools to drive safely – or even remove the human element altogether.
Here are five things that can put us on a path to ZERO human error car crashes by 2020:
Full Story: Innovaro

emergentfutures:

No More Car Crashes by 2020?

The leading cause of car accidents is pretty obvious – its human error. Whether its drunk driving, distracted driving, or aggressive driving, it all comes back to the person behind the wheel. Less than 20% of accidents are caused by road or mechanical failure, so the only way to truly make driving safer for everyone is to give the person behind the wheel more tools to drive safely – or even remove the human element altogether.

Here are five things that can put us on a path to ZERO human error car crashes by 2020:

Full Story: Innovaro

Observation Deck: What Happens When Cars Start Talking to Each Other? | Underwire | Wired.com

The cars: They will drive themselves. That’s pretty much a given at this point, thanks to artificial intelligence research at Stanford and elsewhere. And they’ll talk to each other, too — the processes that let our cars go fast and get to where we tell them won’t be centralized. There won’t be a control tower. Software will sort it out among itself.

poptech:

Autonomous robotic plane flies indoors at MIT

For decades, academic and industry researchers have been working on control algorithms for autonomous helicopters — robotic helicopters that pilot themselves, rather than requiring remote human guidance. Dozens of research teams have competed in a series of autonomous-helicopter challenges posed by the Association for Unmanned Vehicle Systems International (AUVSI); progress has been so rapid that the last two challenges have involved indoor navigation without the use of GPS.

But MIT’s Robust Robotics Group — which fielded the team that won the last AUVSI contest — has set itself an even tougher challenge: developing autonomous-control algorithms for the indoor flight of GPS-denied airplanes. At the 2011 International Conference on Robotics and Automation (ICRA), a team of researchers from the group described an algorithm for calculating a plane’s trajectory; in 2012, at the same conference, they presented an algorithm for determining its “state” — its location, physical orientation, velocity and acceleration. Now, the MIT researchers have completed a series of flight tests in which an autonomous robotic plane running their state-estimation algorithm successfully threaded its way among pillars in the parking garage under MIT’s Stata Center.

MIT’s Semi-Autonomous Car Balances Human, Computer Control | Autopia | Wired.com
There are autonomous cars, and there are drivers’ cars. Now we have something in the middle. Sterling Anderson and Karl Iagnemma of MIT have created a semi-autonomous driving system that gives drivers full control of the vehicle, but kicks when the car gets too close to another object. This sounds like the adaptive cruise control found in expensive Mercedes-Benzes, but this software is much more nuanced and ambitious than anything on the road.

MIT’s Semi-Autonomous Car Balances Human, Computer Control | Autopia | Wired.com

There are autonomous cars, and there are drivers’ cars. Now we have something in the middle. Sterling Anderson and Karl Iagnemma of MIT have created a semi-autonomous driving system that gives drivers full control of the vehicle, but kicks when the car gets too close to another object. This sounds like the adaptive cruise control found in expensive Mercedes-Benzes, but this software is much more nuanced and ambitious than anything on the road.

Let the Robot Drive: The Autonomous Car of the Future Is Here | Wired
…
Google isn’t the only company with driverless cars on the road. Indeed, just about every traditional automaker is developing its own self-driving model, peppering Silicon Valley with new R&D labs to work on the challenge. Last year, a BMW drove itself down the Autobahn, from Munich to Ingolstadt (“the home of Audi,” as BMW’s Dirk Rossberg told me at the company’s outpost in Mountain View, California). Audi sent an autonomous vehicle up Pikes Peak, while VW, in conjunction with Stanford, is building a successor to Junior. At the Tokyo Auto Show in November, Toyota unveiled its Prius AVOS (Automatic Vehicle Operation System), which can be summoned remotely. GM’s Alan Taub predicts that self-driving cars will be on the road by the decade’s end. Groups like the Society of Automotive Engineers have formed special committees to draft autonomous-vehicle standards.

Let the Robot Drive: The Autonomous Car of the Future Is Here | Wired

Google isn’t the only company with driverless cars on the road. Indeed, just about every traditional automaker is developing its own self-driving model, peppering Silicon Valley with new R&D labs to work on the challenge. Last year, a BMW drove itself down the Autobahn, from Munich to Ingolstadt (“the home of Audi,” as BMW’s Dirk Rossberg told me at the company’s outpost in Mountain View, California). Audi sent an autonomous vehicle up Pikes Peak, while VW, in conjunction with Stanford, is building a successor to Junior. At the Tokyo Auto Show in November, Toyota unveiled its Prius AVOS (Automatic Vehicle Operation System), which can be summoned remotely. GM’s Alan Taub predicts that self-driving cars will be on the road by the decade’s end. Groups like the Society of Automotive Engineers have formed special committees to draft autonomous-vehicle standards.


A startup called Liquid Robotics has a growing fleet of autonomous vehicles that rove the ocean collecting data from a variety of onboard sensors.
(via I’ve moved again : On a New Road)

via 2020:

A startup called Liquid Robotics has a growing fleet of autonomous vehicles that rove the ocean collecting data from a variety of onboard sensors.

(via I’ve moved again : On a New Road)

via 2020:

Why the Future of Transportation Is All About Real-Time Data
In order to tackle urban transportation challenges in cities around the world, the Massachusetts Institute of Technology (MIT) and the National Research Foundation of Singapore launched a five-year cooperative project in 2009 — Future Urban Mobility (FM) — to look at new models and technology tools aimed at sustainability. The FM team is one of four interdisciplinary research groups that are part of the Singapore-MIT Alliance for Research and Technology Centre, or SMART Centre. FM is developing SimMobility, a simulation platform where researchers explore transportation, environmental impacts, energy and land use and the activities of individual travelers in the mix.
Some of the projects of FM include autonomous driving — as in, cars that drive themselves — and simultaneous research is being done in the areas of vehicle-to-vehicle communication and vehicle-to-infrastructure communication. Vehicle-to-vehicle communication looks at applications for both safety and information retrieval.
Applications are being developed so your car will get information about the location and intentions of vehicles in your vicinity, contributing to the process of autonomous driving. Vehicle-to-infrastructure projects are less safety-related and more focused on traffic operations, including the possibility of your car receiving information from traffic signals regarding data like when an upcoming stoplight will turn green. With this data, you can adjust your speed and slow down without having to stop at the signal, thus reducing stop-and-go traffic movement.

Why the Future of Transportation Is All About Real-Time Data

In order to tackle urban transportation challenges in cities around the world, the Massachusetts Institute of Technology (MIT) and the National Research Foundation of Singapore launched a five-year cooperative project in 2009 — Future Urban Mobility (FM) — to look at new models and technology tools aimed at sustainability. The FM team is one of four interdisciplinary research groups that are part of the Singapore-MIT Alliance for Research and Technology Centre, or SMART Centre. FM is developing SimMobility, a simulation platform where researchers explore transportation, environmental impacts, energy and land use and the activities of individual travelers in the mix.

Some of the projects of FM include autonomous driving — as in, cars that drive themselves — and simultaneous research is being done in the areas of vehicle-to-vehicle communication and vehicle-to-infrastructure communication. Vehicle-to-vehicle communication looks at applications for both safety and information retrieval.

Applications are being developed so your car will get information about the location and intentions of vehicles in your vicinity, contributing to the process of autonomous driving. Vehicle-to-infrastructure projects are less safety-related and more focused on traffic operations, including the possibility of your car receiving information from traffic signals regarding data like when an upcoming stoplight will turn green. With this data, you can adjust your speed and slow down without having to stop at the signal, thus reducing stop-and-go traffic movement.

 ‘Smart car’ model predicts the behavior of human drivers | KurzweilAI
The researchers test their algorithm using a miniature autonomous  vehicle traveling along a track that partially overlaps with a second  track for a human-controlled vehicle, observing incidences of collision  and collision avoidance	 (credit: Melanie Gonick)
MIT researchers have developed a software system for “smart cars” that predicts the behavior of other  human drivers, to prepare for a world where the road is shared by both  human and artificially intelligent drivers.
They tested their algorithms with toy-sized cars on a miniature track.
The key of their research is to create a system that carefully evaluates drivers based on their behavior and flags trouble cars.
Researchers  set up 100 potential collision scenarios on two overlapping circular  tracks, with some cars remote-controlled by human drivers and other cars  operating based on preset algorithms.

 ‘Smart car’ model predicts the behavior of human drivers | KurzweilAI

The researchers test their algorithm using a miniature autonomous vehicle traveling along a track that partially overlaps with a second track for a human-controlled vehicle, observing incidences of collision and collision avoidance (credit: Melanie Gonick)

MIT researchers have developed a software system for “smart cars” that predicts the behavior of other human drivers, to prepare for a world where the road is shared by both human and artificially intelligent drivers.

They tested their algorithms with toy-sized cars on a miniature track.

The key of their research is to create a system that carefully evaluates drivers based on their behavior and flags trouble cars.

Researchers set up 100 potential collision scenarios on two overlapping circular tracks, with some cars remote-controlled by human drivers and other cars operating based on preset algorithms.