An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

A traffic signal recognition method and a traffic signal recognition device estimate whether or not a vehicle can be decelerated at a predetermined deceleration acceleration and can stop before a stop line based on a position of the stop line corresponding to a traffic signal located in a traveling direction of the vehicle, select the traffic signal corresponding to the stop line as a target traffic signal in a case where it is estimated that the vehicle cannot stop before the stop line, set detection area corresponding to the target traffic signal on an image obtained by capturing the traveling direction of the vehicle, and determine a display state of the target traffic signal by executing image processing on the detection area.

Vehicle guidance with systemic optimization may include traversing, by a current vehicle, a vehicle transportation network, by obtaining, by the current vehicle, systemic-utility vehicle guidance data for a current portion of the vehicle transportation network and traversing, by the current vehicle, the current portion of the vehicle transportation network in accordance with the systemic-utility vehicle guidance data. Obtaining the systemic-utility vehicle guidance data may include obtaining vehicle operational data for a region of a vehicle transportation network, wherein the vehicle operational data includes current operational data for a plurality of vehicles operating in the region, operating a systemic-utility vehicle guidance model for the region, obtaining systemic-utility vehicle guidance data for the region from the systemic-utility vehicle guidance model in response to the vehicle operational data, and outputting the systemic-utility vehicle guidance data to the current vehicle.

In one embodiment, a method includes receiving an image of an object captured in a geographic location. The method includes determining the geographic location associated with the image. The geographic location is represented in a map that includes one or more ambient light measurements corresponding to one or more geographic locations. The method includes using the one or more ambient light measurements corresponding to the geographic location in the map associated with the image to generate a color corrected image. The method includes determining a classification of the object using the color corrected image.

Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.

System, method, and device for controlling a vehicle. In one example, the system includes an electronic processor configured to capture, via a camera, a first image, determine, within the first image, a road traffic factor, and generate, based on sensor information from one or more sensors of the vehicle, a second image depicting an environment surrounding the vehicle. The second image includes the road traffic factor. The electronic processor is also configured to, determine, based on the detected road traffic factor and the second image, a predicted trajectory of a traffic participant proximate to the vehicle, and generate a steering command for the vehicle based on the predicted trajectory.

A driving support system includes: an acquisition portion configured to acquire visual-recognition position information on a position where a driver of a vehicle visually recognizes a traffic light; an image acquisition portion configured to acquire a forward image ahead of the vehicle; a traffic-light recognition portion configured to recognize a traffic light included in a forward image; and a notification portion configured to notify the driver of warning when the traffic light is not recognized from the forward image, in a case where the vehicle is present at a position based on the visual-recognition position information.

A navigation system includes a processing unit connected to a storage device for fetching and executing a navigation program to: determine a planned route; obtain a real-time image and real-time positioning data indicating a current location of the system; perform image recognition on the image, and determine whether a specific object exists in the image; determine whether a route adjustment condition is met based on the planned route, the positioning data and result of the determination; and adjust the planned route when the route adjustment condition is met. The route adjustment condition includes that a meaning conveyed by the specific object is in conflict with the planned route.

The invention relates to a method for an automated starting of a means of transport (80) at a light-signal system (70), comprising: recording an image of the light-signal system (70) by means of a first optical sensor (30) of the means of transport (80), determining a signaling state of the light-signal system (70) by means of the recorded image, executing an automated starting process of the means of transport (80) in response to a signaling state representing and/or announcing a travel clearance, determining a user action of a driver of the means of transport (80) for plausibility checking of the starting process, and depending on a result of the plausibility check, automatically continuing or terminating of the starting process.

Systems, apparatus and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may include a light emitter positioned external to a surface of the autonomous vehicle and being configured to implement a visual alert by emitting light from the light emitter. Data representing a light pattern may be received by the light emitter and the light emitted by the display may be indicative of the light pattern. The light pattern may be selected to gain the attention of the object (e.g., a pedestrian, a driver of a car, a bicyclists, etc.) in order to avoid the potential collision or to alert the object to the presence of the autonomous vehicle.