A system and method for alerting a driver of a motor vehicle or a person walking along a road or hiking on a trail of potentially dangerous hazards in their path. Hazards may be deep water, ice, oil slicks or other hazards. In the case of a motor vehicle, the system uses cameras mounted on or within the vehicle to detect potential hazards and then analyzes the images combined with the known topography of the location to evaluate the ability of the vehicle to safely traverse the hazard. In the case of a person walking or hiking, the person may use the camera on a personal mobile device to capture images of the hazard and to combine the images with the known topography at the location to evaluate the danger presented by the hazard.

Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.

Systems, methods, and other embodiments described herein relate to generating a notification about a risk of a target vehicle toppling over due to wind. In one embodiment, a method includes determining a wind force of the wind at a location of the target vehicle and determining one or more characteristics of the target vehicle. The method includes determining whether there is a risk of the target vehicle toppling over based on the wind force of the wind and the one or more characteristics of the target vehicle. The method includes generating a notification about the risk.

A method and system for road condition monitoring including receiving roadway data from connected vehicles in response to a third party request. The connected vehicles include sensors for capturing the roadway data. The method and system include determining a roadway condition based on the roadway data and calculating a data price based on the roadway condition and the roadway data. Further, the method and system include controlling access to the roadway data according to the data price.

A method and system for road condition monitoring including receiving roadway data from connected vehicles in response to a third party request. The connected vehicles include sensors for capturing the roadway data. The method and system include determining a roadway condition based on the roadway data and calculating a data price based on the roadway condition and the roadway data. Further, the method and system include controlling access to the roadway data according to the data price.

A computer is provided for a system for detecting, characterizing, and mitigating road network congestion. The system includes a plurality of motor vehicles. Each motor vehicle includes a telematics control unit (TCU) for generating one or more location signals for a location of the associated motor vehicle and one or more event signals for an event related to the associated motor vehicle. The computer includes one or more processors for receiving the location signal and/or the event signal from the TCU of the associated motor vehicles. The computer further includes a non-transitory computer readable storage medium (CRM) including instructions, such that the processor is programmed to identify a location of the road network congestion at a current time step. The processor is further programmed to track the road network congestion and predict the road network congestion at a next time step.

A computer is provided for a system for detecting, characterizing, and mitigating road network congestion. The system includes a plurality of motor vehicles. Each motor vehicle includes a telematics control unit (TCU) for generating one or more location signals for a location of the associated motor vehicle and one or more event signals for an event related to the associated motor vehicle. The computer includes one or more processors for receiving the location signal and/or the event signal from the TCU of the associated motor vehicles. The computer further includes a non-transitory computer readable storage medium (CRM) including instructions, such that the processor is programmed to identify a location of the road network congestion at a current time step. The processor is further programmed to track the road network congestion and predict the road network congestion at a next time step.

Aspects of traffic warning and data capture are discussed. An indication of an approaching vehicle and an ambient light level are received by a device associated with a signboard. Based on the indication and the ambient light level, an alert is provided to a driver of the approaching vehicle. For providing the alert, a first illumination panel positioned to direct light onto a face of signboard is lighted. In various embodiments, lights in different colors are flashed for alerting a driver of the approaching vehicle of different hazardous driving conditions, wherein the lights of different colors are flashed at different instances and in one more directions. Further, the device can record and store or share traffic and pedestrian movement information for further analysis.

An information processing server includes a target vehicle data recognition unit configured to recognize target vehicle data including a traveling state of a target vehicle and position information of the target vehicle on a map, an unstable behavior position recognition unit configured to recognize an unstable behavior position which is a position on the map, at which at least one target vehicle has performed an unstable behavior, based on a plurality of pieces of the target vehicle data, a determination unit configured to determine whether the unstable behavior position is in a continuous occurrence situation or a discontinuous situation, based on whether or not a plurality of the target vehicles perform the unstable behavior at the unstable behavior position, and a storage processing unit configured to store a determination result by the determination unit, in a storage database in association with the unstable behavior position.

Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.