The present invention is a system and method for stopped vehicle driver alert. The system gives alert to the driver at traffic light when a vehicle is stopped at red light, when the light changes from red to green, and/or when the front vehicle clears out moving away above a threshold distance. In preferred embodiments, system comprises optical sensors to detect traffic lights and changes of traffic light status, object detection and object distance measurement sensors, GPS location sensors, a microprocessor with memory, engine control module, and alert systems capable of playing or displaying alerts of audible, visual, and haptic formats. The system is also capable of generating engine start signal. The method detects if the ego vehicle is stopped due to a traffic light and/or traffic jam or a scenario where the front vehicle is almost stopped or within a threshold distance from the ego vehicle. When the condition changes. If the traffic light is red the method determines how long the red light will exist before changing to green with the help of precalculated table where red light duration of a particular GPS location on a particular road is given. The method also calculates a complete red light duration of it can detect the start of the red light and update the red light duration. The method generates remaining light duration signal and send the signal to audible or visual alert systems. Right before or after the remaining time turns to zero, the method generates audible, visual, and/or haptic signals and sends the signals to the audible, visual, and haptic alert systems and/or sends engine start signal to engine control module. The method also determines if red light changed to green and sends audible, visual, and/or haptic signals and/or engine start signal to engine control module.

An adaptive trust calibration based autonomous vehicle may include vehicle systems, a system behavior controller, and a driving automation controller. The system behavior controller may generate a driving automation signal indicative of a desired autonomous driving adaptation. The driving automation controller may control the vehicle systems based on parameters including a desired velocity, current velocity of the autonomous vehicle, desired minimum gap distance between the autonomous vehicle and a detected object, current gap distance gap between the autonomous vehicle and a detected object, relative velocity of the detected object with respect to the autonomous vehicle, desired time headway, desired maximum acceleration, desired braking deceleration, and an exponent. The driving automation controller may receive the driving automation signal and implement the desired autonomous driving adaptation via the vehicle systems by adjusting the parameters based on a type of object associated with the detected object.

Methods, vehicles, and systems described herein generate alerts based on a generated macro state level indicative of a traffic hazard risk in view of a set of parameters which may lead driver to make various sub-conscious decisions. The set of parameters can include at least one of a vehicle parameter, driver state parameter, or external parameter.

Various embodiments include a driver assistance system for determining the position of a stopping point of a vehicle at an infrastructure device comprising: a control unit; a communication device for receiving data from a server or from the infrastructure device; and a sensor arrangement for capturing vehicle data or environmental data. The control unit determines the location of the stopping point at the infrastructure device based at least in part on the data and the vehicle data or environmental data.

A support device is a support device by which a support operation to support a host vehicle to stop is performable. The support device includes: a determination unit configured to, when a light color of a traffic light is a light color that requires the host vehicle to stop, determine whether or not alerting on the traffic light is performed as the support operation, based on a speed of the host vehicle and a distance from a current position of the host vehicle to a stop reference position; and a recognition unit configured to recognize a surrounding state around the host vehicle. The stop reference position in a case where a crossing pedestrian is recognized by the recognition unit is closer to the host vehicle than the stop reference position in a case where no pedestrian is recognized by the recognition unit.

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

A control method for a self-driving vehicle provided with an engine as a driving source, comprising: determining whether or not coast stop is executed in accordance with required driving force of the vehicle, the coast stop being for automatically stopping the engine during the vehicle traveling at speed not more than predetermined vehicle speed; setting the required driving force so that an intervehicular distance between the host vehicle and a preceding vehicle becomes closer to a predetermined distance under presence of the preceding vehicle in front of the host vehicle; predicting a behavior of the preceding vehicle from a situation in front of the preceding vehicle under presence of the preceding vehicle; and prohibiting release of the coast stop for the engine during an automatic stop when future deceleration of the preceding vehicle is predicted in response to an expansion of the intervehicular distance.

A method detects a lane for a transverse guidance of a vehicle. The transverse guidance of the vehicle is based on a roadway model. The method has the steps of ascertaining one or more features which are suitable for influencing the detection of the lane; detecting a lane on the basis of a sensor system of the vehicle; and ascertaining the roadway model on the basis of the detected lane and the ascertained one or more features. The method optionally has the steps of additionally receiving navigation data and transversely guiding the vehicle on the basis of the ascertained roadway model.

Systems, methods, tangible non-transitory computer-readable media, and devices associated with the motion prediction and operation of a device including a vehicle are provided. For example, a vehicle computing system can access state data including information associated with locations and characteristics of objects over a plurality of time intervals. Trajectories of the objects at subsequent time intervals following the plurality of time intervals can be determined based on the state data and a machine-learned tracking and kinematics model. The trajectories of the objects can include predicted locations of the objects at subsequent time intervals that follow the plurality of time intervals. Further, the predicted locations of the objects can be based on physical constraints of the objects. Furthermore, indications, which can include visual indications, can be generated based on the predicted locations of the objects at the subsequent time intervals.

According to various embodiments, a method for operating a vehicle may include determining a vehicular area having traffic conditions or characteristics different from traffic conditions of a current or previous location of the vehicle; obtaining traffic and driving information for the determined vehicular region; changing or updating one or more of driving model parameters of a safety driving model during operation of the vehicle based on the obtained traffic and driving information; and controlling the vehicle to operate in accordance with the safety driving model using the one or more changed or updated driving model parameters. A vehicle may seamlessly update operational rules and/or handover of traffic and driving information for transitioning from one region to another.