A method and system for determining risk indicators for intersections. A method includes receiving, by a computing node from intersection proximate sensors at each intersection, intersection data. For each intersection, the method includes determining, by the computing node for each connected vehicle proximate to an intersection, a driver risk score based on driver distraction data from the intersection data for the intersection, determining, by the computing node, a near miss score based on the intersection data for the intersection, and assigning, by the computing node for the intersection, an intersection risk indicator level based on an exponential moving average of intersection risk indicator scores determined from driver risk scores and near miss scores. The method includes providing, by the computing node, intersection risk indicator levels to each connected vehicle to facilitate control decisions by each connected vehicle when approaching intersections.

A method for automated control of a vehicle includes automatically navigating a vehicle within a current lane of travel with a driving assistance system, and predetermining a steering maneuver during the automatic navigation with the driving assistance system. The method also includes, prior to performing the predetermined steering maneuver, biasing the vehicle within the current lane of travel with an offset from a center of the current lane of travel using the driving assistance system, the offset in a direction of the predetermined steering maneuver, and performing the predetermined steering maneuver with the driving assistance system.

A method detects presence of a multi-tone siren type in an acoustic signal. The multi-tone siren type is associated with one or more siren patterns, where each siren pattern includes a number of time patterns at corresponding frequencies. The method includes processing a number of frequency components of a frequency domain representation of the acoustic signal over time to determine a corresponding plurality of values. That processing includes determining, for each frequency component, a value characterizing a presence of a time pattern associated with at least one siren pattern. The method also includes processing the values according to the siren patterns to determine a detection result indicating whether the multi-tone siren type is present in the acoustic signal.

A longitudinally guiding driver assistance system in a motor vehicle has a first detection system for detecting currently applying events or relevant events lying ahead, which require a change of the permissible maximum speed, a second detection system for detecting the course of the route, and a function unit which, when detecting a relevant event while taking into account the location of the relevant event, determines a location-dependent point in time, whose reaching causes the function unit to initiate an automatic adaptation of the currently permissible maximum speed or an output of a prompt information for permitting an automatic adaptation of the currently permissible maximum speed to anew permissible maximum speed. The function unit is designed to take into account available information concerning the course of the route when determining the location-dependent point in time.

An intersection start judgment device judges whether to start an own vehicle at an intersection at which vehicles in all directions need to temporarily stop. The device includes an autonomous sensor, a driving environment recognizer, a locator, and a controller. The autonomous sensor is disposed on the own vehicle and configured to detect a driving environment in front of the own vehicle. The driving environment recognizer is configured to recognize, with the autonomous sensor, the driving environment of the own vehicle. The locator is configured to calculate a location of the own vehicle with map information and a global navigation satellite system; and a controller configured to give, in a case where the own vehicle stopped temporarily at the intersection, start permission to the own vehicle when the number, counted by the driving environment recognizer, of other vehicles that are already stopping at the intersection becomes zero by subtraction counting.

Systems, methods, computer-readable media, techniques, and methodologies are disclosed for performing end-to-end, learning-based keypoint detection and association. A scene graph of a signalized intersection is constructed from an input image of the intersection. The scene graph includes detected keypoints and linkages identified between the keypoints. The scene graph can be used along with a vehicle's localization information to identify which keypoint that represents a traffic signal is associated with the vehicle's current travel lane. An appropriate vehicle action may then be determined based on a transition state of the traffic signal keypoint and trajectory information for the vehicle. A control signal indicative of this vehicle action may then be output to cause an autonomous vehicle, for example, to implement the appropriate vehicle action.

A control method for an autonomous driving vehicle is provided. The method includes: obtaining perception information of road conditions around a vehicle; determining a first control decision based on the perception information and autonomous driving decision logic; controlling the vehicle to perform autonomous driving according to the first control decision; determining, in response to detecting an assisted driving instruction, a second control decision that is different from the first control decision based on the perception information, the autonomous driving decision logic, and the assisted driving instruction; and controlling the vehicle to perform autonomous driving according to the second control decision.

A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to access sensor data of a first sensor of a vehicle while an adaptive cruise control feature of the vehicle is active, detect, based on the sensor data of the first sensor, a stationary object located along a path of travel of the vehicle, wherein the stationary object is located outside of a range of a second sensor of the vehicle, determine a presence of an intersection within a threshold distance of the stationary object that is along the path of travel of the vehicle, and responsive to a determination that the stationary object is a stopped vehicle of the intersection, adjust, by the adaptive cruise control feature, the speed of the vehicle.

Enclosed are embodiments of motion control operations in various traffic scenarios in consideration of the kinematic factor for trajectory planning. In some embodiments, a method includes: determining a danger rating for at least one object identified in an environment, wherein the danger rating represents a perceived risk associated with a respective object; evaluating a set of hierarchical factors with respect to a traffic scenario, wherein a metric is derived for trajectories of the traffic scenario that quantifies passenger ride comfort based on the danger rating and the set of hierarchical factors; determining a motion control operation in the traffic scenario to increase the passenger ride comfort based on the metric; and augmenting a route planner of an autonomous vehicle with motion control operations in different traffic scenarios to increase the passenger ride comfort.

A vehicle includes a sensor circuit configured to detect an obstacle in a first region which is located on the predetermined traveling route and in a second region which is adjacent to the first region on the predetermined traveling route, the second region being farther than the first region. The vehicle enters the first region in a case where: there is no obstacle in the first region; and there is no obstacle in the second region, and does not enter the first region and stops before the first region in a case where: there is no obstacle in the first region; and there is an obstacle in the second region.