A method includes receiving, by a remote server, operating parameters regarding one or more components of a vehicle from a vehicle controller of the vehicle; retrieving, by the remote server, at least one of static information or dynamic information regarding one or more parameters ahead of the vehicle; determining, by the remote server, an adjustment for at least one of the one or more components of the vehicle based on (i) the operating parameters and (ii) the at least one of the static information or the dynamic information; and providing, by the remote server, an instruction to the vehicle controller regarding the adjustment.

Embodiments are directed towards controlling uncontrolled release of ammonia from an engine of a vehicle. An estimated status of the engine is determined prior to an event, such as an estimated load on the engine prior to the vehicle going up a hill. A predictive model of uncontrolled ammonia release is generated for the estimated status. At least one engine-related countermeasure is selected based on the predictive model. If the predictive model of uncontrolled ammonia release with the selected countermeasures satisfies a threshold condition, then the selected engine-related countermeasure is employed.

A method including determining a direct distance between the vehicle position and a position of the roadside unit and a planar distance between the vehicle position in a horizontal plane containing the vehicle position, and a projection of the position of the roadside unit onto the plane. The method further includes calculating a height of a roadside unit relative to the vehicle position using the direct distance and the planar distance determined for the vehicle position. The method also includes setting a value indicative of the height of the roadside unit relative to the vehicle position as a height correction value and storing the height correction value of the vehicle position in association with information indicative of the vehicle position as the height correction function.

An apparatus is obtained which provides, to a vehicle, information on a road-surface and that on an obstacle(s), and information on the degree of reliability, on the basis of information received from roadside units. The apparatus includes a communications circuitry to receive obstacle information from the roadside units where each unit includes a plurality of sensors to detect the obstacle(s) within a predetermined field of view. A reliability determinator determines the degree of reliability of information on an obstacle(s) received, and outputs a reliability value on the bases of the number of roadside units detecting the same obstacle, the number of sensors in one roadside unit detecting the same obstacle, and a difference value of detecting the same obstacle between different roadside units or that of detecting the same obstacle between different sensors; and a correction term is outputted on the basis of information on a road-surface condition.

In an obstacle detection apparatus, the captured image of a vicinity of a vehicle from an imaging apparatus is acquired. A three-dimensional estimation image showing a three-dimensional position of a feature point in the captured image is generated, and a three-dimensional position of an object is estimated. An attribute image in which an object in the captured image is classified into one or more classes that include at least a road-surface class is generated. The three-dimensional estimation image and the attribute image are fused, the feature points and the classes are associated, and road-surface points associated with the road-surface class are extracted. Based on the road-surface points, a road-surface height in the vicinity of the vehicle is estimated. Based on the estimated road-surface height, the three-dimensional position of the object is corrected. Based on the three-dimensional position of the object, an obstacle in the vicinity of the vehicle is detected.

Processors determine one or more aggregate confidence scores for a road segment; and based at least in part on the confidence score, determine a map-enabled driving scenario for a road segment. Determining the confidence score for the road segment comprises obtaining feature weights corresponding to road segment characteristics associated with the road segment; obtaining feature data associated with features along the road segment; based on the feature weights, and the feature data, defining continuous parameter range intervals along the road segment; assigning a respective interval confidence score to each continuous parameter range interval along the road segment based on a respective most relevant feature present in that interval; and determining the one or more aggregate confidence scores for the road segment based at least in part on each of the respective interval confidence scores.

A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Among other things, one or more techniques and/or systems are provided for providing users with access to a route for travelling. A user, of a client device, may send a request for access to the route to a route planning service. The route may correspond to a starting location and an ending location. The route planning service may query a route database to identify an entry indicating that a restricted access road segment (e.g., a high occupancy vehicle lane, a shoulder lane, a bus lane, etc.) and/or a road segment (e.g., comprising a traffic light alteration capability) exists between the starting location and the ending location. Responsive to successfully authorizing the user for travelling the restricted access road segment and/or the road segment, the route, comprising the restricted access road segment and/or the road segment, may be provided to the client device.

A method for anticipating a lane change by another vehicle ahead of a vehicle equipped with a sensing system having a camera and a radar sensor includes processing captured image data to determine lane markers of a traffic lane along which the equipped vehicle is traveling, and to determine presence of another vehicle in an adjacent traffic lane. Responsive to processing of captured radar data, an oblique angle of a direction of travel of the other vehicle relative to the traffic lane is determined. Responsive to determination that the oblique angle of the direction of travel of the other vehicle is indicative of a cut-in intent of the other vehicle, and based on the determined range to the determined other vehicle, the system anticipates the cut-in of the other vehicle and applies a braking system of the equipped vehicle to mitigate collision with the determined other vehicle.

An apparatus for displaying a driving state of a vehicle, a system including the same and a method thereof is provided. The apparatus includes a processor that determines a change in a state of a lane change assistance function and controls a step-by-step notification based on the change in the state of the lane change assistance function, and a display controlled by the processor to display the step-by-step notification based on the change in the state of the lane change assistance function.