Provided are a system and a method for providing service to recommend customized exercise used for autonomous vehicle according to a situation of a user and a situation of autonomous control by determining that a user does an exercise safely and freely during autonomous control of the vehicle through a monitoring system in the vehicle. According to the present disclosure, it is possible to determine whether the user does the exercise safely and freely during autonomous control of the vehicle through the monitoring system in the autonomous vehicle and recommend the customized exercise used for the autonomous vehicle according to the situation of the user and the situation of the autonomous control. Further, according to the present disclosure, it is possible to determine whether the user does the exercise safely and freely during the autonomous control of the vehicle through the monitoring system in the autonomous vehicle and recommend the autonomous vehicle in which the user can do the recommended exercise according to the situation of the user and the situation of the autonomous control.

A system and a method for cooperative maneuvering and cooperative risk warning of vehicles. The system includes monocular surveillance cameras, local computing devices, and a master server. Each local computing device receives video frames from the camera, detects and tracks vehicles from the video frames, and converts the video frames to bird-view. Each detected vehicle is represented by a detection vector having first dimensions representing two dimensional (2D) parameters of the vehicle and second dimensions representing three dimensional (3D) parameters of the vehicle. Tracking of the vehicles is performed by minimizing loss calculated based on the first dimensions and the second dimensions of the detection vectors. The master server receives bird-views from different computing devices and combines the bird-views into a global bird-view, and performs cooperative maneuvering and cooperative risk warning of the vehicles using the global bird-view.

The following are executed: received power acquisition processing; propagation loss calculation processing of calculating propagation losses between the transmitter and the receiver, based on received power; median processing of calculating a median of a plurality of the propagation losses calculated in the propagation loss calculation processing in a predetermined time period, and outputting the median as propagation losses to be used for subsequent processing; loss peak acquisition processing of acquiring a maximum value of the propagation losses output in the median processing; distance calculation processing of calculating a distance between the transmitter or the receiver and blocking entities, at least based on the maximum value, heights of antennas, and a wavelength of the radio communication; and congestion degree calculation processing of estimating a congestion degree by calculating the number of the blocking entities in chronological order, based on the distance, integrating the number for a predetermined time period, and thereby calculating the number of the blocking entities per unit area.

Traffic data reconciliation and brokering are provided. A traffic data brokering system ingests traffic-related data provided from a plurality of data sources, analyzes the data, and reconciles the data for identifying accurate, up-to-date, and comprehensive traffic data. The system identifies current traffic conditions based on identified relationships between pieces of received data, calculates confidence scores, and determines which pieces of data are accurate based on the calculated confidence scores. The traffic data brokering system provides the reconciled traffic data to various users of traffic data, such as individuals or third-party services. One aspect includes a route generation engine that determines and provides recommended route(s) to clients. Another aspect includes a forecast engine that predicts traffic conditions based on past traffic data. The forecasted data can be used to determine recommended routes. The system provides APIs for enabling sources and clients to provide and receive traffic data.

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 and apparatus for assisting driving include: identifying one or more set of video frames from captured video regarding surrounding condition of a vehicle, wherein the one or more set of video frames comprise a moving object; extracting one or more features indicating motion characteristics of the moving object from the one or more set of video frames; and predicting motion intention of the moving object in the one or more set of video frames based on the one or more features.

Embodiments described herein may provide a method for using map data to alter criteria for the identification of road work in locations where false positives are more likely. Methods may include: receiving probe data from a plurality of probe apparatuses traveling within a road network; determining, from the probe data captured at a first location, an indication of road work; determining a type of map area of the first location; applying a suppression method to the probe data captured at the first location in response to the type of map area of the first location corresponding to an area having a relatively high false positive rate of indications of road work; and determining, based on the suppression method to the probe data captured at the first location, the presence or absence of road work occurring at the first location.

Systems and methods are provided to implementing a set of instructions related to a vehicle configuration template at a vehicle. Vehicle configuration templates may define instructions for automated vehicle driving parameters within a particular road region. The set of instructions within the first road region may correspond with a vehicle transition sequence based on the vehicle configuration template, where the vehicle transition sequence adjusts at least one of a vehicle position and dynamics to achieve a desired traffic flow.

A method and corresponding device for the decentralized cooperative coordination of at least two vehicles includes: determining an abstract driving maneuver to realize at least one nominal driving maneuver by a first vehicle, determining driving maneuver information regarding the first vehicle's at least one abstract driving maneuver, transmitting the first vehicle's driving maneuver information to at least one further vehicle, calculating or reconstructing the first vehicle's nominal trajectory and/or nominal driving maneuver based on the received driving maneuver information by the further vehicle, comparing the first vehicle's reconstructed nominal trajectory and/or the reconstructed nominal driving maneuver with the further vehicle's nominal trajectory and/or nominal driving maneuver and, if a conflict exists between the nominal trajectory and/or the nominal driving maneuver of the first vehicle and the nominal trajectory and/or the nominal driving maneuver of the further vehicle, transmitting a cooperation request and/or information indicating the conflict to the first vehicle.

A method may include obtaining input information relating to an environment in which an autonomous vehicle (AV) operates in which the input information describes at least one of: a state of the AV, an operation of the AV within the environment, a property of the environment, or an object included in the environment. The method may include identifying a region of interest that represents a section of the environment based on the input information and identifying a portion of the environment based on the identified region of interest. The portion of the environment may include an object that affects operation of the AV. The method may include determining a first decision that relates to the object and sending an instruction to a control system of the AV describing a given operation of the AV responsive to the object according to the first decision.