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Sensors

[Due to the increasing size of the archives, each topic page now contains only the prior 365 days of content. Access to older stories is now solely through the Monthly Archive pages or the site search function.]

Pisa, Deutsche Telekom and Kiunsys launch smart city pilot project to optimize inner city parking as part of ITS; POSSE

June 26, 2014

The Italian city of Pisa and Deutsche Telekom have launched a smart city pilot project to test an intelligent parking system and to analyze historical traffic data via a “big data” service. The system, which will integrate into Pisa’s intelligent transport system (ITS), will help motorists in Pisa find a free parking space more easily and quickly, as well as pay for it via their smart phone.

The city of Pisa worked with Deutsche Telekom and its partner firm Kiunsys to install the new smart city service on Piazza Carrara, located directly on the banks of the river Arno. Wireless Parking Spots Sensors (PSS) on the floor of each parking spot detect whether the spaces are free or occupied. Several data units collect the information and send it over the mobile network to the city’s server infrastructure. The information is then displayed on indication panels which guide drivers to a free space. The solution is also integrated in Pisa’s existing Tap&Park app which drivers can choose to download to take them directly to a free parking space and even pay for it via the app.

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CMU demo’ing Autonomous SRX in Washington this week

June 25, 2014

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Sample images of urban driving and screen-captures of the Autonomoous SRX’s tracking system’s results. The images in the first row show detection and tracking results from an arriving area of Pittsburgh international airport. The other two images in the second row show those of an urban street. Cho et al. (2014) Click to enlarge.

Researchers from Carnegie Mellon University (CMU) this week will demonstrate the CMU advanced Autonomous Cadillac SRX in Washington, DC. The car was brought to Washington at the request of Congressman Bill Shuster of Pennsylvania, who participated in a 33-mile drive in the autonomous vehicle between a Pittsburgh suburb and the city’s airport last September. Scheduled over two days, the demonstration will show how autonomous technology will eventually be fully integrated into vehicles that are currently on the market.

Developed with support from the National Science Foundation (NSF), the US Department of Transportation, DARPA and General Motors, the car is the result of more than a decade of research and development by scientists and engineers at CMU and elsewhere. Their work has advanced the underlying technologies—sensors, software, wireless communications and network integration—required to make sure a vehicle on the road is as safe—and ultimately safer—without a driver than with one. (In the case of the Washington, DC, demonstration, an engineer will be on hand to take the wheel if required.)

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Google focusing autonomous driving development on mastering city street driving; patents piling up

April 29, 2014

Over the past year, Google has shifted the focus of its autonomous vehicle project onto mastering city street driving, according to Chris Urmson, Director, Google Self-Driving Car Project. (Urmson was the technical team leader of the CMU team that won the DARPA 2007 Urban Challenge, an autonomous vehicle race.)

Google’s autonomous cars use video cameras; 4 radar sensors (front, back, left, right); a laser range finder (Velodyne HDL-64E LiDAR) to “see” other traffic; and a GPS as well as a wheel encoder and very detailed road maps to determine the precise location of the vehicle. Google says that its autonomous vehicles have logged nearly 700,000 autonomous miles (1.13 million km) over the four years they have been on the road. Since its last pubic update in 2012, Google said that it has logged thousands of miles on the streets of Mountain View, California, Google’s home.

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Volvo Cars developing systems for Driver State Estimation; driver sensors

March 17, 2014

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A sensor that is able to monitor in which direction the driver is looking, how open the eyes are, as well as head position and angle is part of Volvo Cars’ work on developing systems that can detect if a driver is tired or inattentive. The technology is based on a sensor installed in the dashboard and small LEDs that illuminate the driver with infrared light.The information can be used to adjust the action of safety systems to the driver’s condition. Click to enlarge.

Volvo Cars is researching systems that can recognize and distinguish whether a driver is tired or inattentive. By placing a sensor on the dashboard to monitor aspects such as in which direction drivers are looking, how open their eyes are, as well as their head position and angle, it is possible to develop precise safety systems that detect a driver’s state and are able to adjust the car accordingly.

The analysis of the driver’s state, known as Driver State Estimation, in which driver sensors play an important role, is a field that may be key to self-driving cars in the future, Volvo suggests. The car will need to be able to determine for itself whether the driver is capable of taking control when the conditions for driving autonomously are no longer present. A driver sensor could be of assistance in this.

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Volvo Car Group tests road-embedded magnets for accurate positioning of self-driving cars

March 11, 2014

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Volvo Car Group has completed a research project using magnets in the roadway to help the car determine its position. A pattern of round ferrite magnets (40x15 mm) was located 200 mm below the road surface. The test car was equipped with several magnetic field sensors. Click to enlarge.

Volvo Car Group has completed a research project using magnets embedded in the roadway to help the car determine its position. The research, which has been financed in strategic co-operation with the Swedish Transport Administration (Trafikverket), is a potential means of implementing self-driving vehicles.

Reliable and highly accurate positioning is one of the crucial issues in the development of self-driving cars. While established positioning technologies such as GPS and cameras have limitations in certain conditions, road-integrated magnets remain unaffected by physical obstacles and poor weather conditions. Accordingly, the use of road magnets has attracted some academic research, as well as a number of patents filed on different approaches.

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Subaru debuts next-generation EyeSight system; three new ADAS technologies coming this year

January 24, 2014

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The EyeSight system. Click to enlarge.

Subaru of America, Inc. has introduced a new and improved version of its EyeSight driver assistance system. The new system now features color stereo cameras which deliver an approximately 40% longer and wider detection range; brake light detection; and full functionality when the speed differential between the Eyesight-equipped car and another vehicle is up to 30 mph (48 km/h), up from 19 mph (31 km/h) previously.

Also debuting in Subaru models later this year are three additional advanced driver assistance (ADAS) technologies: blind spot detection; lane change assist; and rear cross traffic alert. These new systems will be introduced on Subaru’s product line-up starting in 2014.

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Ford kicks off new automated driving research projects with MIT and Stanford University

January 22, 2014

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Ford Fusion Hybrid automated research vehicle with four LiDAR sensors. Click to enlarge.

Building on the capabilities of the automated Ford Fusion Hybrid research vehicle unveiled last month (earlier post), Ford is working with the Massachusetts Institute of Technology (MIT) and Stanford University to research and to develop solutions to some of the technical challenges surrounding automated driving.

The MIT research focuses on scenario planning to predict actions of other vehicles and pedestrians, while Stanford is exploring how a vehicle might maneuver to allow its sensors to peek around obstructions. Put another way, the purpose of the MIT project is enhance the utilization of the line-of-sight data already acquired by the Fusion’s sensors to provide augmented predictive capability, especially for pedestrians. The purpose of the Stanford work is to enhance the acquisition of non-line-of-sight data.

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TU München team develops new technique for accurate distance measurement by advanced driver assistance systems using cooperative transponders

January 21, 2014

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Basic concept for range detection using cooperative transponders. Click to enlarge.

As part of the “cooperative transponder” research project Ko-TAG (earlier post), researchers at the Technische Universität München (TUM) developed a new approach to distance measurement to enable advanced driver assistance systems (ADAS) in cars to pinpoint the location of pedestrians and cyclists even in non-line-of-sight situations—i.e., when they are hidden from the driver’s view.

In this scheme, pedestrian’s and cyclist’s cell phones serve as transponders. On-board positioning systems compute the projected trajectory of the transponders and initiate an emergency braking sequence in case a pedestrian or cyclist moves into the path of a car.

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