The present invention provides a method, system, terminal, and storage medium for rapid generation of reference lines. Path planning points are classified according to driving difficulty of different road segments, and the segments with low driving difficulty are assigned reference lines obtained by geometric processing; the segments with high driving difficulty are assigned reference lines obtained by algorithmic processing in combination with vehicle dynamics constraints. Then the reference lines of all segments are combined to form a complete reference line. This method requires little system resource and the algorithm consumes less time.

In certain embodiments, a vehicle may obtain a video stream via a camera system of the vehicle. The video stream may be processed to extract one or more feature vectors from the video stream. Based on the feature vectors extracted from the video stream, vehicle description information related to one or more parked vehicles in the parking area may be determined. Space information indicating locations of the parked vehicles relative to available parking spaces in the parking area may also be determined based on the feature vectors extracted from the video stream. A mapping of the parking area may then be generated based on the vehicle description information and the space information.

In a method for moving a vehicle out of a parking area, the vehicle obtains map information of the parking area and determines a current parking space of the vehicle and an exit location of the parking area. The vehicle determines a plurality of target departure routes from the current parking space to the exit location, and identifies blocking vehicles on the target departure routes that blocks it from reaching the exit. The vehicle estimates the preferability of each of the target departure routes based on a number of blocking vehicles on the target departure route and a difficulty level of removing the blocking vehicles from the target departure route. The vehicle then selects from the target departure routes a preferred departure route, and transmits requests to remove the blocking vehicles off the preferred departure route.

Smart vehicle parking apparatus and related methods are disclosed herein. An example system includes a processor to reserve a personal vehicle for a time interval. The personal vehicle is to park at a location during the time interval. The processor is also to match a vehicle use option to the personal vehicle based on the time interval and the location. The vehicle use option is associated with a person to use the personal vehicle during the time interval.

A method and apparatus for positioning a vehicle. The method may include: acquiring an identification element and non-identification elements of a current vehicle. The method can further include matching the identification element of the current vehicle with position elements in a high-precision map to determine an initial position of the current vehicle. The method can further include using at least one position element in the high-precision map to perform observational constraints on the non-identification elements of the current vehicle to acquire position elements corresponding to the non-identification elements of the current vehicle. The method can further include adjusting the initial position of the current vehicle using the position elements corresponding to the non-identification elements of the current vehicle to obtain a target position of the current vehicle.

The invention relates to a motor vehicle having a positioning system for determining the position (and for example the orientation) of the motor vehicle, wherein the motor vehicle comprises a communication interface for reading in parking space information (via a wireless communication system), wherein the parking space information comprises the position of the parking space and for example the size of the parking space, wherein the motor vehicle comprises a tracking module for determining the position of the parking space in relation to the position (as well as for example the orientation) of the motor vehicle as well as an image generator for determining the position of a virtual image component on a transparent display (of the motor vehicle) depending on the position of the parking space in relation to the position (as well as for example the orientation) of the motor vehicle.

An approach is provided for mapping a parking facility using multi-modal trajectories collected using mobile device(s). The approach, for example, involves collecting sensor data from sensor(s) of mobile device(s). The sensor data represents the multi-modal trajectories comprising (1) vehicle trajectory segments during which the device(s) traveling into/out of a parking facility, and (2) pedestrian trajectory segments during which the device(s) traveling to/from pedestrian entry/exit point(s) of the parking facility. The approach also involves processing the sensor data to determine semantic event(s) associated with parking in the parking facility based on the multi-modal trajectories. The approach further involves determining parking spot location(s) and/or orientation(s) of the parking facility based on the semantic event(s). The approach further involves generating map data indicating the parking spot location(s) and/or orientation(s). The approach further involves providing the map data as an output.

A computer-implemented method for vehicle parking analysis and identification is disclosed. The computer-implemented method includes determining one or more parking preferences and one or more parking requirements of a user. The computer-implemented method includes determining one or more parking spaces based on comparing the one or more ranked parking preferences and the one or more ranked parking requirements of the user to parking data associated with one or more available parking spaces. The computer-implemented method includes generating a parking space recommendation, wherein the parking space recommendation includes the one or more optimal parking spaces selected from the one or more available parking spaces.

Various technologies described herein pertain to autonomous vehicle consumption of real-time public transportation data to guide curb access and usage. An autonomous vehicle receives a trip request for a ride specifying a requested pullover location. The autonomous vehicle receives public transportation data specifying an expected arrival time of a public transportation vehicle at a reserved zone within proximity of the requested pullover location. The autonomous vehicle evaluates availability of the reserved zone during an expected occupancy time of the reserved zone by the autonomous vehicle based on the expected arrival time of the public transportation vehicle at the reserved zone. The autonomous vehicle selects an actual pullover location for the ride in the autonomous vehicle based on the availability of the reserved zone during the expected occupancy time. The autonomous vehicle stops at the actual pullover location for the ride in the autonomous vehicle.

Route planning for a hybrid electric vehicle (HEV) includes obtaining a route between an origin and a destination, where the route is optimized for at least one of a noise level or energy consumption of an engine of the HEV that is used to charge a battery of the HEV, and where the route comprises respective engine activation actions for at least some segments of the route; and controlling the HEV to follow the segments of the route and to activate the engine according to the respective engine activation actions.