Systems and methods for generating driving recommendations are disclosed herein. One embodiment divides automatically a roadway into a plurality of lane-level cells; generates a graph network that represents the plurality of lane-level cells; gathers information pertaining to one or more detected road agents; projects onto the graph network the gathered information pertaining to the one or more detected road agents to update a current status of the plurality of lane-level cells; processes the graph network based on the updated current status of the plurality of lane-level cells to predict a future status of the plurality of lane-level cells, the predicted future status including at least occupancy, by a detected road agent, of the respective lane-level cells in the plurality of lane-level cells; and generates a driving recommendation based, at least in part, on the predicted future status of the plurality of lane-level cells.

Systems, devices and methods provide, implement, and use vision-based methods of sequence inference for a device affixed to a vehicle.

A method determines support points for estimating a progression of roadside development of a road. The method determines a position of a first support point in the surroundings of a vehicle; determines a plurality of regions in a travel direction and/or counter to the travel direction of the vehicle on the basis of the position of the first support point; and determines support points of roadside development for each of the determined regions in the travel direction, counter to the travel direction and left and right of the vehicle.

A movement analytics platform can generate instructions for collecting video data from a site that includes a roadway. The instructions can be provided to a device having augmented reality capabilities, wherein the instructions include content displayed by the device to indicate an area at the site that an operator of the device is to position within a field of view of a camera. A data feed received from the device can include video data corresponding to the area and contextual data to annotate the video data based on observations by the device operator. The data feed can be processed to derive movement analytics associated with the area at the site (e.g., classifications, locations, speeds, travel directions, and/or the like for one or more objects depicted in the video data). The device can be provided with additional augmented reality content based on the movement analytics.

The invention relates to a luminaire network, comprising a plurality of luminaires comprising a lighting apparatus, wherein a plurality of the luminaires comprise a communication unit configured to enable communication of data between said plurality of luminaires and/or with a central unit; a processing unit; a control unit configured to control the lighting apparatus as well as the communication and processing units and at least one first sensor configured to output first sensed data. The processing unit of the luminaire is configured to process the first sensed data to produce first processed data, and the luminaire network is further configured such that the first processed data of at least two luminaires is further processed to produce second processed data. The invention further relates to a method of processing sensor data in a luminaire network.

As described herein, systems and methods for estimating traffic volume provide the ability to identify an area of interest in which to determine an estimated traffic volume, obtain point data associated with the area of interest, determine a concentration of the area of interest based on the point data, obtain one or more known volume-to-concentration ratios, and determine the estimated traffic volume for the area of interest based the concentration of the area of interest and the one or more known volume-to-concentration ratios. The point data includes at least spatiotemporal data and geographic information data. In some cases, the estimated traffic volume is provided to an end user. In some cases, at least one traffic element recommendation for the area of interest based on the estimated traffic volume can be determined and provided to an end user.

Embodiments of the present invention provide a traffic control method and an apparatus. The method includes: obtaining, by a server, a traffic flow of a road; adjusting, by the server, a lane quantity or a lane width of the road at a lane layer on a map according to the traffic flow of the road; and sending, by the server, a lane layer obtained after the adjustment, so that a vehicle running on the road runs according to a lane obtained after the adjustment. In the embodiments of the present invention, the traffic flow of the road is obtained, and the lane quantity or the lane width of the road is adjusted at the lane layer on the map according to the traffic flow of the road, so that the vehicle running on the road can run according to the lane obtained after the adjustment.

A system and method are for determining a vehicle speed. In an embodiment, the system includes a first collecting module, adapted to collect traffic information; and a deep learning module, including a control model and a neural network. The control model is generated after the neural network autonomously deeply learns based on inputted traffic information. The control model is adapted to receive current traffic information including a speed and a location of a vehicle, traffic light status at a junction ahead, and traffic condition information in a road segment ahead currently collected by the first collecting module; to compute a recommended vehicle speed for the vehicle based on the current traffic information; and to output the recommended vehicle speed. Such a system may reduce the stopping times at the intersection.

The invention relates to a luminaire network, comprising a plurality of luminaires comprising a lighting apparatus, wherein a plurality of the luminaires comprise a communication unit configured to enable communication of data between said plurality of luminaires and/or with a central unit; a processing unit; a control unit configured to control the lighting apparatus as well as the communication and processing units and at least one first sensor configured to output first sensed data. The processing unit of the luminaire is configured to process the first sensed data to produce first processed data, and the luminaire network is further configured such that the first processed data of at least two luminaires is further processed to produce second processed data. The invention further relates to a method of processing sensor data in a luminaire network.

A method for assisting in the parking of a vehicle in a vacant parking area, wherein the position of at least one vacant parking area is calculated on the basis of a vehicle-to-vehicle and/or a vehicle-to-infrastructure communication from the current position of the vehicle and is conveyed to a navigation apparatus of the vehicle, wherein a parking process is started by virtue of a radio key of the vehicle being placed onto a smartphone display, so that a lens in the vehicle key captures a flashing code and the radio key returns the flashing codes to the vehicle by radio.