Methods and systems for providing standardized mobile device distraction prevention and safety protocols are disclosed. In particular, an embodiment of a method for activating a distraction prevention or safety protocol behavior in a mobile device when the mobile device satisfies a specific condition is disclosed. The method includes discovering one or more protocol activators configured to transmit discovery information associated with a specific condition. The method further includes activating distraction prevention safety protocol behavior in the mobile device based at least in part on the discovery information. In an implementation, the specific condition may be a specified environment itself and or include an event when the mobile device enters a specified environment or a specified sequence of numbers is dialed from the mobile device.

A method is described for performing a real time analysis of traffic flow control device related data using a plurality of vehicles connected in at least one vehicle cell network. The method compares position data from vehicles defining a traffic flow with received data for a traffic flow control device and geometry and topology data concerning a transport engineering construction related to the traffic flow control device to evaluate if a discrepancy can be detected between the geometry and topology data concerning the transport engineering construction and the traffic flow defined by the vehicles positions. The method may be used for updating and/or finding errors in the geometry and topology data concerning the transport engineering construction.

The invention discloses a method, system and related device of implementing vehicle automatic loading and unloading, so as to achieve the automatic loading and unloading of the unmanned vehicle. The method includes: controlling, by a vehicle controller, a vehicle to drive automatically and stop at a loading and unloading position; obtaining, by a loading and unloading control apparatus corresponding to the loading and unloading position, vehicle identification information of the vehicle; verifying the vehicle identification information and controlling a loading and unloading machine to load and unload when the verification succeeds; sending a loading and unloading completion indication to the vehicle controller after the loading and unloading is completed; and controlling, by the vehicle controller, the vehicle to leave the loading and unloading position when receiving the loading and unloading completion indication.

The invention discloses a method, system and related device of implementing vehicle automatic loading and unloading, so as to achieve the automatic loading and unloading of the unmanned vehicle. The method includes: controlling, by a vehicle controller, a vehicle to drive automatically and stop at a loading and unloading position; obtaining, by a loading and unloading control apparatus corresponding to the loading and unloading position, vehicle identification information of the vehicle; verifying the vehicle identification information and controlling a loading and unloading machine to load and unload when the verification succeeds; sending a loading and unloading completion indication to the vehicle controller after the loading and unloading is completed; and controlling, by the vehicle controller, the vehicle to leave the loading and unloading position when receiving the loading and unloading completion indication.

A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

At least a method for determining risk behavior of a driver is described. While a vehicle is being driven, data is obtained related to the position and movement of a wireless communications device. The data may indicate the type of behavior exhibited by the driver while the vehicle is being driven.

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.

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 present invention relates to a portable traffic management system comprising a portable traffic signal assembly; a portable signal assembly; and a control unit in wireless communication with the portable traffic signal assembly and the portable signal assembly. The present invention alleviates one or more of the problems associated with the presently available traffic management systems.

A system includes an autonomous vehicle (AV) comprising a sensor, a control subsystem, and an operation server. The control subsystem receives sensor data comprising location coordinates of the AV from the sensor. The operation server detects an unexpected event from the sensor data, comprising at least one of an accident, an inspection, and a report request. The operation server receives a message from a user comprising a request to access particular information regarding the AV and location data. The operation server associates the AV with the user if the location coordinates of the AV match location data of the user. The operation server establishes a communication path between the user and a remote operator for further communications.