Mobileye Vision Technologies Ltd.

Itai Ben Shalom

Amnon Shashua

Gideon Stein

Yoav Taieb

Eyal Bagon

Shai Shalev-Shwartz

Anna Clarke

David Huberman

Igor Tubis

Shai Shalev-Schwarz

A traffic light detection system for a vehicle is provided. The system may include at least one processing device programmed to receive, from at least one image capture device, a plurality of images representative of an area forward of the vehicle, the area including a traffic light fixture having at least one traffic light. The at least one processing device may also be programmed to analyze at least one of the plurality of images to determine a status of the at least one traffic light, and determine an estimated amount of time until the vehicle will reach an intersection associated with the traffic light fixture. The at least one processing device may further be programmed to cause a system response based on the status of at least one traffic light and the estimated amount of time until the vehicle will reach the intersection.

Systems and methods for causing a vehicle response based on traffic light detection

A navigation system may include a processor programmed to analyze a first image to identify a non-semantic road feature; identify a first image location, in the first image, of one point associated with the non-semantic road feature; analyze a second image to identify a representation of the non-semantic road feature in the second image; identify a second image location, in the second image, of the one point associated with the non-semantic road feature; determine, based on a difference between the first and second image locations and based on motion information for a vehicle between a capture of the first image and a capture of the second image, three-dimensional coordinates for the one point associated with the non-semantic road feature; and send the three-dimensional coordinates for the one point associated with the non-semantic road feature to a server for use in updating a road navigation model.

Updating road navigation model using non-semantic road feature points

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a traffic light detection system is provided for a vehicle. One or more processing devices associated with the system receive at least one image of an area forward of the vehicle via a data interface, with the area including at least one traffic lamp fixture having at least one traffic light. The processing device(s) determine, based on at least one indicator of vehicle position, whether the vehicle is in a turn lane. Also, the processing device(s) process the received image(s) to determine the status of the traffic light, including whether the traffic light includes an arrow. Further, the system may cause a system response based on the determination of the status of the traffic light, whether the traffic light includes an arrow, and whether the vehicle is in a turn lane.

Systems and methods for determining the status and details of a traffic light

Systems and methods for determining the status of a turn lane traffic light

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a system includes at least one image capture device configured to acquire at least one image of an area forward of the vehicle. The area includes a plurality of traffic lamp fixtures each including at least one traffic light. The system further includes at least one processing device configured to use at least one indicator of vehicle position, as determined from the at least one acquired image, to determine a relevance to the vehicle of each of the plurality of traffic lamp fixtures. The at least one processing device may determine, based on the at least one acquired image, a status of a traffic light included in at least one traffic lamp fixture determined to be relevant to the vehicle, and cause a system response based on the determined status.

Systems and methods for identifying relevant traffic lights

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a system includes at least one image capture device configured to acquire a plurality of images of a traffic light located in a region above the vehicle, outside of a sightline of a typical driver location in the vehicle. The system further includes a data interface, and at least one processing device. The at least one processing device may be configured to receive the plurality of images via the data interface, determine a status of the traffic light based on analysis of at least a first image from among the plurality of images, determine a change in status of the traffic light based on at least a second image from among the plurality of images, and cause a system response based on the determination of the change in status.

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Mazkaret Batya, Israel

Itai Ben Shalom