In deceleration set processing, first-class and second-class deceleration are specified. The first-class deceleration is deceleration of the vehicle corresponding to a first-class state. The first-class state is a state of a slowdown target of the vehicle. The second-class deceleration is deceleration of a following moving body corresponding to a second-class state. The second-class state is a state of the vehicle as viewed from the following moving body. If a minimum value of the first-class deceleration (a first-class minimum value) is equal to or greater than a minimum value of the second-class deceleration (a second-class minimum value), target deceleration is set to the first-class minimum value. Otherwise, based on a second-class minimum value phase, the target deceleration is set to deceleration equal to or greater than the second-class minimum value. The second-class minimum value phase is a phase to which the second-class minimum value belongs in a second deceleration feature.

A pedestrian protection apparatus may include: an active sensor configured to sense a forward obstacle of a vehicle; a passive sensor configured to sense a collision of the vehicle; a storage unit configured to store a collision threshold value which is set according to the passive sensor and a protection subject; a protection module driving unit configured to drive a protection module for protecting the protection subject in case of a collision with the vehicle; and a control unit configured to identify the protection subject based on the sensing result of the active sensor, adjust the collision threshold value according to the protection subject, compare the sensing result of the passive sensor to the collision threshold value, and operate the protection module driving unit.

In one embodiment, a method of adjusting a speed limit of an ADV includes the operations of tracking objects within a field of view of the ADV; and identifying a set of stable objects from the objects tracked by the ADV based on a set of requirements. The method further includes the operations of identifying a subset of objects from the set of stable objects, the subset of objects having longest distances to the ADV; calculating a detection distance by averaging distances from the subset of stable obstacles to the ADV; and adjusting the speed limit of the ADV based on the detection distance using a predetermined algorithm.

Provided are a device for warning of the distance between vehicles and a control method for warning of the distance between vehicles which can further give a sense of security to an occupant. The device for warning of the distance between vehicles comprises: a preceding vehicle specifying unit which specifies a preceding vehicle that travels in front of a vehicle; and a warning output control unit which, when the preceding vehicle is in a stationary state, outputs a warning of the distance between the vehicles from a warning output unit on the condition that the vehicle is executing adaptive cruise control (ACC).

The disclosure relates to a vehicle velocity control method. The method includes: determining, by an onboard sensor, drivable distances in different directions in front of a current vehicle, and obtaining, at least based on types of targets in the different directions, an area of a drivable space in front of the current vehicle; determining, based on the area of the drivable space and a current vehicle velocity, a result of a safety degree in a current driving scenario; and controlling the vehicle velocity of the current vehicle based on the result of the safety degree. The disclosure further relates to a vehicle control device, a computer storage medium, and a vehicle.

A vehicle collision avoidance and driver notification system includes an object detection unit configured to detect environmental obstacles and a collision detection unit for assessing risk of collision. Depending on risk assessment, a collision avoidance unit gives feedback to the driver or directly interacts with the vehicle engine.

A reactive pedal algorithm is used to modify an accelerator pedal output (APO)-to-torque conversion to produce more deceleration for the same accelerator pedal position. Modifying the APO-to-torque conversion provides the driver of a vehicle the sensation that the vehicle is resisting approaching closer to a lead vehicle. The APO-to-torque conversion is modified based on a scene determination to classify vehicles as in-lane, neighbor-lane, or on-coming. Lane change assist methods and systems are used to modify the APO-to-torque conversion range based on a lead vehicle, a neighbor vehicle, or both.

A proactive pedal algorithm is used to modify an accelerator pedal map to ensure the deceleration when the accelerator pedal is released matches driver expectation. Modifying the accelerator pedal map provides the driver of a vehicle the sensation that the vehicle resists moving when travelling in dense scenes with potentially high deceleration requirements and coasts easily in scenes with low deceleration requirements. The accelerator pedal map is modified based on a scene determination to classify other remote vehicles as in-lane, neighbor-lane, or on-coming.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example system for an AV includes obtaining, by a computer located in the AV, an image from a camera located on the AV, where the image characterizes an area towards which the AV is driven on a lane on a road or a highway; determining, from the image, that a pedestrian or a cyclist is located next to the lane on the road or the highway; and in response to the determining, performing driving operations on the AV such as steering from a center of the lane to a first side of the lane that is away from the center of the lane and away from a location of the pedestrian or the cyclist, and/or slowing down the AV in response to certain conditions.

Embodiments for operational envelope detection (OED) with situational assessment are disclosed. Embodiments herein relate to an operational envelope detector that is configured to receive, as inputs, information related to sensors of the system and information related to operational design domain (ODD) requirements. The OED then compares the information related to sensors of the system to the information related to the ODD requirements, and identifies whether the system is operating within its ODD or whether a remedial action is appropriate to adjust the ODD requirements based on the current sensor information. Other embodiments are described and/or claimed.