At least one computer-readable medium on which are stored instructions that, when executed by one or more processing devices, enable the one or more processing devices to perform a method. The method includes the steps of receiving from a user via an electronic device a request for a good or a service, receiving via the electronic device the geographic location of the user, and determining an optimal provider of the good or service based on the type of good or service and the geographic location of the user.

A simulation device that on the basis of: a traffic network (10) as a graph of route sections (3) and nodes (4), with starting places (1) and destinations (2).
so as to determine the traffic volume on the route sections (3) performs the following steps: for each starting place (1) and for each of a multiplicity of traffic participants of the starting place (1): determining allocated to each of the destinations (2) respectively a traffic participant fraction, corresponding to an allocation of the traffic participants to the destinations; determining allocated to each of the destinations (2) respectively an optimal route (6) from the starting place (1) to the destination (2); determining for each of the destinations (2) and for each route section (3) of the optimal route (6) a dwell portion (5) of the traffic participant in the route section (3) as a function of the traffic participant fraction that is allocated to this destination (2); for each of the route sections (3) of the traffic network (10): determining the traffic volume on the route section (3) by means of summating the dwell portions (5) of all traffic participants in this route section (3).

A server collects data that represents a status of a non-connected vehicle that does not exchange cooperative awareness messages (CAMs) with the server. The server synthesizes values of fields in a CAM for the non-connected vehicle based on the data. The server also incorporates information in the CAM to indicate that the CAM represents the non-connected vehicle. The server transmits the CAM to one or more connected vehicles. A connected vehicle receives a CAM that includes information indicating whether the CAM represents a non-connected vehicle. The connected vehicle determines a degree of uncertainty associated with values of fields in the CAM based on the information. The connected vehicle selectively takes an action based on the degree of uncertainty.

Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

The traffic flow estimation apparatus acquires images and position information and speed information, the images being captured at different timings by a first moving object that is in motion in a target area and including a second moving object around the first moving object, the position information and speed information being of the first moving object at the timings; estimates a lane in which the second moving object is in motion; and estimates a traffic flow for each lane in the target area based on the speed information of the first moving object, the information indicative of a change over time of positions of the second moving object, and the lanes in which the first moving object and the second moving object are in motion.

Provided are a system and a method for providing service to recommend customized exercise used for autonomous vehicle. The system and method are configured 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 a situation of the user and the situation of the autonomous control and 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 distributed hearing system includes a plurality of near audio probe modules distributed at a plurality of specified locations in a specified area for recording audio information at the specified locations in the specified area, respectively; and a central data collecting/analysis/control module in communication with the plurality of near audio probe modules for collecting and analyzing the audio information from the plurality of near audio probe modules. The audio information is generated by a vehicle and includes a characteristic feature specific to the vehicle. A traffic control method is used with the distributed hearing system.

An information management apparatus, comprising an acquisition unit configured to acquire vehicle location information indicating a location of a certain vehicle and vehicle state information indicating a state of the vehicle, a selection unit configured to select another vehicle corresponding to the vehicle state information from among other vehicles in surroundings of the vehicle that are identified based on the vehicle location information, and a notification unit configured to notify the another vehicle that has been selected in accordance with the vehicle state information.

A computer-implemented method for generating an automated response to a catastrophic event, that includes (1) analyzing a sample set of data generated in association with a catastrophic event to determine a threshold pattern; (2) receiving, with customer permission or affirmative consent, home sensor data from a smart home controller via wireless communication or data transmission, the home sensor data including data regarding at least one of (i) structural status; (ii) wind speed; (iii) availability of electricity; (iv) presence of water; (v) temperature; (vi) pressure; and/or (vii) presence of pollutants in the air and/or water; (3) determining, based upon or from computer analysis of the home sensor data, whether the home sensor data indicates a match to the threshold pattern; and (4) automatically generating a response if the home sensor data indicates a match to the threshold pattern. As a result, catastrophic events and responses thereto may be improved through usage of a remote network of home sensors.

The invention relates to a method for improving hands-off recognition in a vehicle with steering torque-based recognition in that swarm data are provided from vehicles that recognize hands-off situations with hand distance sensors in the steering wheel. Both recognition results over a certain route section are compared and, in the case of deviations, the correctness of the results of the hand distance sensors is assumed. On this basis, route sections are determined in which steering torque-based recognition is unreliable. Based on this recognition, systems with steering torque evaluation can then be re-parameterized in order to be more reliable relative to the route.