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.

A method of controlling an autonomous vehicle and an electronic device are provided, which relate to a field of artificial intelligence technology, and in particular to a field of autonomous driving technology. The method includes: acquiring a vehicle state configuration information from a cloud; enabling a task receiving function of the vehicle, in response to the vehicle state configuration information indicating that the vehicle is in an automatic operation state; acquiring a task information from the cloud in response to the task receiving function being enabled; and controlling the vehicle according to the task information.

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.

Disclosed are a method, device, and system to control stopping of a mobility device. In particular, the method includes: receiving a stop change request of a route mobility device from a user device; determining whether the stop change request satisfies a change condition; determining a change stop of the route mobility device based on the stop change request when the change condition is satisfied; and transmitting a change stop message to the route mobility device and at least one of the user device or a mobility device used by a user.

A display device included in a vehicle includes: a communication unit, a display; and a control unit. The communication unit can receive vehicle travel information. The processor can calculate a speed range based on the received vehicle driving information and control the display to display a graphic object representative of the calculated speed range on the display.

A method is for assisting with the driving of vehicles traveling on a road by an assistance system including a sensor installed along sections of the road and an electronic processor. The method includes reception by the processor of a request indicating a road portion and requesting information on the state of the portion, determination by the processor, as a function of the requested information and the road portion, of the configuration among several determined configurations, of the sensor, sending by the processor to the sensor of a command indicating the configuration, sending the processor data delivered by the sensor in the configuration, and sending by the processor of the information determined as a function of the data.

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.

A warning system and method are provided. The warning system includes a plurality of sensing apparatuses and a server. The sensing apparatuses are used for sensing a driving trajectory of each of a plurality of two-wheeled vehicles. The server compares the driving trajectories with an accident hotspot list to determine whether at least one first driving trajectory matches an accident hotspot location, wherein the accident hotspot list is generated by a plurality of driving behavior events corresponding to each of the two-wheeled vehicles. The server generates a warning message to remind a first driver of a first two-wheeled vehicle corresponding to the at least one first driving trajectory when determining that the at least one first driving trajectory matches the accident hotspot location.

Aspects of the subject disclosure may include, for example, determining, by a system comprising a processor, a driver profile according to a driver identity for a driver of a vehicle, selecting a driver-specific enforcement scenario for the vehicle according to the driver profile and traffic enforcement information that is associated with a vehicle location, and presenting an in-vehicle alert to convey the driver-specific enforcement scenario to the driver. Other embodiments are disclosed.

The present invention includes methods, circuits, devices, systems and associated computer executable code for providing driver decision making support. According to some embodiments, there may be provided a driver decision support system, which may generate action recommendations to a commercial driver, such as a taxi driver, a cab driver, a limo driver or any other kind of driver who picks up and transports passengers or cargo on an ad hoc (or otherwise flexible/uncertain) basis.