The present disclosure is directed to deviating from a planned path for an autonomous vehicle. In particular, a computing system comprising one or more computing devices physically located onboard an autonomous vehicle can identify one or more boundaries at least in part defining a lane in which the autonomous vehicle is traveling along a path of a planned route. Responsive to identifying one or more obstructions ahead of the autonomous vehicle along the path, the computing system can: determine one or more deviations from the path that would result in the autonomous vehicle avoiding the obstruction(s) and at least partially crossing at least one of the one or more boundaries; and generate, based at least in part on the deviation(s), a motion plan instructing the autonomous vehicle to deviate from the path such that it avoids the obstruction(s) and continues traveling along the planned route.

A method for optimal notification of a relevant object in a potentially unsafe situation includes training a machine learning model using a plurality of object parameters and a plurality of vehicle state parameters to generate a trained machine learning model. Output data is predicted using the trained machine learning model. The output data represents an optimal mode of notification and a set of notification parameters for a specific state of interaction between the vehicle and the relevant object.

Methods and systems are provided for adapting a driving condition of a vehicle. The system includes a non-transitory computer readable medium having stored thereon a pre-programmed driving maneuver of the vehicle. The system also includes a processor configured to obtain audio data of acoustic sources in the environment of the vehicle. The processor is further configured to determine a receiving direction of the acoustic source based on the audio data. The processor is further configured to determine whether the acoustic source are located within the maneuver of the vehicle based on the pre-programmed or updated driving maneuvers and the determined receiving direction of the acoustic source. Furthermore, the processor is configured to determine a range between the vehicle and the acoustic source in order to determine that the acoustic source is located within the driving path of the vehicle.

A lifeform transmission system is used to locate a lifeform wanting to be identified as a lifeform for collision avoidance. The lifeform transmission system comprises a lifeform vitals detector, a GPS transmitter and various other electrical circuits. The lifeform transmitter is worn on a limb or neck of the lifeform. If the lifeform does not wear a transmitter no signal is emitted. The collision avoidance system is housed inside the vehicle and receives communication from invention. If any lifeform is positioned in the path or approaching the path that the ground vehicle is traveling, the vehicle's collision avoidance system is advised to avoid the collision to enhance the accuracy of the collision avoidance system. This invention complements the existing collision avoidance system and enhances the accuracy of vehicle systems by providing an input from the lifeform, making detection easier.

Systems and methods for determining strategy modes for autonomous vehicles are described. An autonomous vehicle may detect aspects of other vehicles and aspects of the environment using one or more sensors. The autonomous vehicle may then determine strategy modes of the other vehicles, and select a strategy mode for its own operation based on the determined strategy modes and an operational goal for the autonomous vehicle. The strategy modes may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The autonomous vehicle may further determine elements in the environment and topological constraints associated with the environment, and select the strategy mode for its own operation based thereon.

Systems and methods for connected vehicle and mobile device communications are provided herein. An example method includes determining a distracted condition for at least one of a driver or a pedestrian by evaluating actions occurring within in a vehicle of the driver or on a mobile device of the pedestrian; determining a distraction level for either the driver or the pedestrian based on the actions occurring within in the vehicle or on the mobile device; and providing an alert message to the mobile device or a human machine interface of the vehicle based on the distraction level, the alert message warning of a distracted condition of the pedestrian or the driver.

A safe passing system for a vehicle includes: a road ambient environment sensing system (101), configured to obtain sensing information of a road ambient environment in real time, process the sensing information to obtain vehicle driving assistance information, and send the vehicle driving assistance information to a vehicle-mounted terminal (102); and the vehicle-mounted terminal (102), configured to receive the vehicle driving assistance information, and plan a driving route according to the vehicle driving assistance information and vehicle-acquired information.

A driver assistance system includes a detector configured to detect pedestrians or obstacles in a front detection area and a rear detection area of a vehicle; an accelerator pedal sensor configured to detect a position of an accelerator pedal of the vehicle; and a controller configured to selectively activate the front detection area and the rear detection area according to a gear state of the vehicle, when there is the pedestrians or the obstacles in the activated detection area, to recognize an acceleration pedal change amount from an acceleration pedal position detected through the accelerator pedal sensor, to determine whether emergency braking of the vehicle is necessary based on the recognized acceleration pedal change amount, and when the emergency braking is necessary, to perform the emergency braking for the vehicle.

In a cruise assist control apparatus, a controller controls a cruise assist unit in a pedestrian assist mode upon it being determined that a target object is detected around a vehicle and recognized as a pedestrian. The controller determines whether a similar object that is similar to a pedestrian is located close to the target object upon it being determined that the target object is detected around the vehicle and recognized as a pedestrian. The controller maintains the pedestrian assist mode for a predetermined maintenance period even upon it being determined that the recognized pedestrian is not detected by a determiner. The controller alters at least one parameter of the pedestrian assist mode based on whether a similar object is located close to the target object.

An apparatus includes a memory, and circuitry which, in operation, performs operations including, storing, in the memory, an object occurrence map defining an occurrence area where there is a possibility that an object appears, detecting the object included in a captured image of a scene seen in a running direction of a vehicle, switching a vehicle drive mode, based on a result of the detection of the object and the object occurrence map, from an automatic drive mode in which the vehicle is automatically driven to a manual drive mode in which the vehicle is driven manually by a driver, and controlling driving of the vehicle in the switched manual drive mode.