Systems and methods for navigating a host vehicle. The system may perform operations including receiving, from an image capture device, at least one image representative of an environment of the host vehicle; analyzing the at least one image to identify an object in the environment of the host vehicle; determining a location of the host vehicle; receiving map information associated with the determined location of the host vehicle, wherein the map information includes elevation information associated with the environment of the host vehicle; determining a distance from the host vehicle to the object based on at least the elevation information; and determining a navigational action for the host vehicle based on the determined distance.

System for automatically recognising anomalous situations along roads travelled by motor-vehicles for intelligent motor-vehicle driving speed control along roads.

The motor-vehicles are configured to transmit data allowing anomalous situations to be recognised along roads travelled by the motor-vehicles.

The system comprises data processing resources configured to:

receive and process data transmitted by the motor-vehicles to recognise anomalous situations along the roads travelled by the motor-vehicles based on a recognition algorithm,

when anomalous situations are recognised along roads travelled by the motor-vehicles, generate associated alert events and compute reference driving speeds along the roads recognised to be affected by anomalous situations, and

transmit data representative of the alert events and of the reference driving speeds along the roads recognised to be affected by anomalous situations.

The motor-vehicles are further configured to:

receive data representative of alert events and reference driving speeds, and

use the received data to implement one or both of the following actions: inform the drivers of motor-vehicles, through automotive user interfaces of motor-vehicles of the anomalous situations recognised along roads travelled by motor-vehicles, and cause current driving speeds of the motor-vehicles to be adjusted to the reference driving speeds along roads recognised to be affected by anomalous situations.

Various aspects of the present disclosure generally relate to sensor systems. In some aspects, a method may include determining a classification of a first vehicle of a plurality of vehicles traveling in a platoon. The method may include causing, based at least in part on the classification, the first vehicle to share sensor data with a second vehicle in the platoon according to a sensor data sharing profile, wherein the sensor data is associated with a sensor system of the first vehicle. Numerous other aspects are provided.

Provided are a method and apparatus for processing a parking space state, and a non-transitory computer-readable storage medium. The method includes: acquiring parking space state association data determined by parking space monitoring devices in a target parking lot, where the parking space monitoring devices comprise an in-parking space monitoring device and an out-parking space monitoring device; determining a parking space state of a target parking space in the target parking lot according to the parking space state association data; and updating, according to the parking space state of the target parking space, parking space state data in a multi-source parking space management platform to which the target parking space belongs.

At least one nearby vehicle may be extracted from a vehicle vicinity image collected by a sensor equipped in the target vehicle. Lane recognition information representing which one position a position of the extracted nearby vehicle corresponds to with respect to the target vehicle, and/or vehicle position information representing a relative distance from the target vehicle to the nearby vehicle may be identified. An attention degree of the nearby vehicle may be calculated based on a speed of the nearby vehicle calculated from the relative distance and a vehicle speed of the target vehicle, the vehicle position information of the nearby vehicle, the relative distance of the nearby vehicle, the speed of the target vehicle, or any combination thereof. An alarm for the nearby vehicle may be displayed on a screen according to the calculated attention.

An approach is provided for accessing traffic impact caused by individual driving behaviors. For example, the approach involves receiving, by one or more processors, sensor data collected from one or more sensors of a vehicle traveling on a road network. The approach also involves processing, by the processors, the sensor data to determine one or more driving behaviors associated with the vehicle. The approach further involves computing, by the processors, a traffic impact index based on the one or more driving behaviors and at least one contextual parameter associated with the vehicle, the road network, a driver of the vehicle, or a combination thereof. The traffic impact index represents an estimated impact of the vehicle on a traffic flow within at least a portion of the road network. The approach further involves providing, by the processors, the traffic impact index as an output.

Techniques for providing real-time vehicle surveillance is disclosed. An in-vehicle surveillance device continuously captures images from the surroundings of a vehicle and the interior of the vehicle and transmits them to a surveillance management system. The images are processed in real-time using machine learning modules to determine primary, secondary, and adverse events. Upon determining the events, alerts are generated and sent to a display unit provided on the in-vehicle surveillance device to improve the safety of the passengers. The techniques further allow vehicle-to-vehicle communication and vehicle to third party device communication upon determining an event.

A vehicle computer for use in a vehicle. The vehicle computer includes at least one processor; an interface to a radio communications network; and a memory including software instructions configured to control the at least one processor to implement a method including steps of: receiving, from a traffic information hub in the radio communications network, intersection condition information regarding a next intersection along a route of the vehicle; and calculating route and navigation information based at least in part on the received intersection condition information. Also disclosed is a traffic information hub including: at least one processor; an interface to a data network; and a memory including software instructions configured to control the at least one processor to implement a method including steps of: receiving intersection condition information for each one of a plurality of traffic intersections; and receiving a query from a vehicle.

A wireless communication apparatus mounted on a mobile body includes a transmitter and a receiver. The transmitter is configured to transmit position information indicating a position to which the mobile body is scheduled to move, to a server apparatus. The receiver is configured to receive communication quality information indicating a communication quality corresponding to the position, from the server apparatus. The transmitter is configured to transmit the date at a communication position specified based on the communication quality information.

An apparatus, method and computer program product are provided for predicting wrong-way-driving events. A WWD event defines an event in which a vehicle travels in a direction opposing a traffic direction designated for a portion of a road. In one example, the apparatus estimates a likelihood of portion of the road inducing a wrong-way-driving (WWD) event by using a machine learning model as a function of map data, sensor data, or a combination thereof. If the likelihood satisfies a threshold, the apparatus updates a map layer to indicate the WWD event at the portion of the road.