A vehicle presence detection system for determining whether a parking space is vacant or occupied and utilizing this information to guide vehicles to available parking spaces. generally includes a LIDAR device, a cloud-based processing unit, a database, and a guidance light. The LIDAR device generally includes a light emitter, a light sensor, a CPU, a memory unit, and a communications device. The LIDAR device determines the distance between itself and a parking spot or a vehicle parked in that parking spot using an algorithm that accounts for variances in the ambient conditions. This status information can be communicated to a cloud-based processing unit, which can store this information in a database and/or use this information to send parking status indications to an autonomous vehicle dynamic sign, mobile device, or guidance light.

Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

This disclosure describes systems and methods for virtual parking lot space allocation. An example method may include receiving, by a processor and from a first vehicle, sensor data relating to a first location. The example method may also include generating, by the processor and based on the sensor data, a first virtual parking space of a virtual parking location within the first location.

A parking management system that facilitates motorist guidance, payment, violation detection, and enforcement using highly accurate space occupancy detection, unique vehicle identification, guidance displays, payment acceptance, violation detection, enforcement data generation, electronic booting, and towing management is described. The system enables reduced time to find parking, congestion mitigation, accurate violation detection, and easier enforcement, and increased payment and enforcement revenues to cities.

According to a method for self-localization, a vehicle is detected by a vehicle-external sensor system of a parking infrastructure when it is located in a detection region of the vehicle-external sensor system. By way of a vehicle-external communication interface of the parking infrastructure, position information regarding the detection region is relayed in dependence on the detection of the vehicle to at least one vehicle computer unit and an initial pose of the vehicle is determined by the at least one vehicle computer unit in dependence on the position information.

The disclosure describes systems and methods for determining and adjusting a parking position of a vehicle. In particular, the vehicle may determine a first parking space where the vehicle can move to a second parking space and exit the second parking space in a forward direction.

Wireless occupancy sensors and methods for using the same are provided. In some embodiments, a occupancy sensor comprises: a housing that includes a window positioned at a top portion of the housing; a battery at a lower portion of the housing; a first magnetometer that detects changes in a magnetic field when a vehicle moves over the first magnetometer; an optical sensor that detects one or more objects in a field of view of the optical sensor through the window; a transmitter for transmitting sensor data to a gateway device, and a processor that controls the first magnetometer, the optical sensor, and the transmitter.

This application provides an information processing method performed by a computing device. The method includes the following steps: acquiring free parking space information of a target path in a time period T1, the target path including N stop areas, the time period T1 being divided into K unit times; determining a free parking space change trend of the N stop areas in the time period T1 according to the free parking space information, and mining the free parking space change trend of the N stop areas in the time period T1 to obtain parking space prediction information; and performing traffic planning for a vehicle along the target path according to the parking space prediction information. The solution can well adapt to traffic scene requirements and improve the accuracy of traffic planning.

To provide a vehicle control system which can reduce dependence on determination of an automatic driving vehicle and can make the automatic driving vehicle perform evacuation driving under control of the vehicle control system, at the time of occurrence of an evacuation cause. A vehicle control system acquires traveling nodes for automatic driving which makes the object vehicle perform automatic driving from the travel node storage unit, and transmits it to the object vehicle; and irrespective of a presence or absence of occurrence of an evacuation cause for evacuating the object vehicle, acquires the evacuation nodes corresponding to the travel nodes for automatic driving from the evacuation node storage unit, and transmits to the object vehicle.

This disclosure describes systems and methods for determining vehicle parking scores. An example method may include calculating, subsequent to a first vehicle parking within a first parking space of a parking lot and based on first sensor data obtained by the first vehicle, a first vehicle parking score. The example method may also include calculating, subsequent to a second vehicle parking within the first parking space of the parking lot and based on second sensor data obtained by the second vehicle, a second vehicle parking score. The example method may also include calculating a first average vehicle parking score for the first parking space based on the first vehicle parking score and the second vehicle parking score. The example method may also include presenting an indication of the first average vehicle parking score for the first parking space to a third vehicle within the parking lot.