An approach is provided for generating/breaking vehicle paths on a limited graph area. The approach, for example, determining an expected frequency of location data collected from a sensor of a vehicle traveling on a roadway, wherein the location data include a plurality of probe points that are time-sequenced. The approach also involves detecting an exit or an entry of the vehicle on the roadway based on comparing the expected frequency to an observed frequency of the location data on at least one portion of the roadway. The approach further involves initiating an identification, a creation, a breaking, or a combination thereof of a path constructed from the location data based on the detecting of the exit or the entry of the vehicle. The approach further involves providing the path as an output.

A system and method for determining a predicted trajectory of a human-driven host vehicle as the human-driven host vehicle approaches a traffic signal. The method includes: obtaining a host vehicle-traffic light distance d.sub.x and a longitudinal host vehicle speed v.sub.x that are each taken when the human-driven host vehicle approaches the traffic signal; obtaining a traffic light signal phase P.sub.t and an traffic light signal timing T.sub.t; obtaining a time of day TOD; providing the host vehicle-traffic light distance d.sub.x, the longitudinal host vehicle speed v.sub.x, the traffic light signal phase P.sub.t, the traffic light signal timing T.sub.t, and the time of day TOD as input into an artificial intelligence (AI) vehicle trajectory prediction application, wherein the AI vehicle trajectory prediction application implements an AI vehicle trajectory prediction model; and determining the predicted trajectory of the human-driven host vehicle using the AI vehicle trajectory prediction application.

Techniques for determining a location and type of traffic-related features and using such features in route planning are discussed herein. The techniques may include determining that sensor data represents a feature such as a traffic light, road segment, building type, and the like. The techniques further include determining a cost of a feature, whereby the cost is associated with the effect of a feature on a vehicle traversing an environment. A feature database can be updated based on features in the environment. A cost of the feature can be used to update costs of routes associated with the location of the feature.

This application relates to the automated driving field, and discloses a method for identifying abnormal driving behavior, a system, and a vehicle including the system. The method for identifying abnormal driving behavior includes: obtaining vehicle driving behavior data, and determining, based on the vehicle driving behavior data, whether a vehicle is in a state of suspicious abnormal driving behavior; obtaining current vehicle driving scenario data if the vehicle is in the state of suspicious abnormal driving behavior; and determining, based on the vehicle driving behavior data and the current vehicle driving scenario data, whether the suspicious abnormal driving behavior is abnormal driving behavior. In the technical solutions of this application, current driving scenario information is introduced to an identification process of abnormal driving behavior of the vehicle, so that accuracy of identifying the abnormal driving behavior is improved.

A vehicle control device including a microcontroller, a wifi/bluethoot device, a voltage stabilizer circuit and a voltage protector circuit, a battery and a battery charge control circuit, an analogue-digital bus can adapter circuit of transceiver type, an optical-digital signal adapter, a radiofrequency (rf) module, an external antenna adapter circuit and a non-volatile data storage device (rom) that allows the generation of an internal and an external wireless network at the same time and connection with other devices, to make control, warning, management and storage of driver's data and his driving style, his load and related units in real-time, and the interrelation with other vehicles that also have the device, for communication.

A boarding/deboarding point providing system includes a probe vehicle group, a data server, and an on-board unit or a mobile terminal. When vehicle data transmitted from the probe vehicle group are input, the data server extracts a boarding/deboarding point suitable for boarding a vehicle or deboarding a vehicle from the vehicle data, and stores the point while updating the boarding/deboarding point information database. When a request for boarding/deboarding point information is received from the on-board unit or the mobile terminal, the boarding/deboarding point information stored in the boarding/deboarding point information database is searched for a boarding/deboarding point that meets the request conditions, and the search result that includes the boarding/deboarding point is transmitted to the on-board unit or the mobile terminal.

An example operation may include one or more of detecting a potential event via sensors on a transport, sending data related to the potential event to other transports within a predefined distance, storing the data at the transports and a server, and performing a transport operation response on the transports.

An apparatus for predicting traffic information includes a storage storing a traffic information prediction model, and a controller configured to calculate a congestion transfer rate W.sub.AB of a target section based on a volume of traffic and vehicle density and input the congestion transfer rate, a speed of the target section, a speed of a section in front of the target section, and a speed of a section behind the target section to the traffic information prediction model to estimate traffic information of the target section.

A vehicle behavior of a monitored vehicle is learned. A vehicle illumination of the monitored vehicle is detected and monitored. If a light-pattern occurs in the detected vehicle illumination, wherein the light-pattern corresponds to a frequency, intensity and/or color dependent glowing of the vehicle illumination, and further wherein the light-pattern starts with a flashing up of the detected vehicle illumination and ends after a certain time without glowing of the respective part of the detected vehicle illumination, then the method further monitors the light-pattern; monitors a vehicle movement of the monitored vehicle during the occurrence of the light-pattern; and compares the monitored light-pattern with a known light-pattern from a light-pattern data entry stored in an light-pattern database. If the comparison results in the monitored light-pattern being unknown, the method stores the light-pattern and the vehicle movement together as a new light-pattern data entry in the light-pattern database.

A sign comprising a substrate having a planar sign face and an opposing planar back face having peripheral side edges; a recessed portion formed within said substrate having an opening and a bottom, and side walls; a RFID tag assembly having a metal shielding sheet, said RFID tag assembly having a mounting substrate, a double-sided adhesive sheet with one side adhered to a metal shielding sheet and an opposing side adhered to said bottom of said recessed portion; a retroreflective sheeting having a double-sided pressure-sensitive adhesive sheeting for application over said RFID tag assembly to hermetically seal said RFID tag assembly within said recessed portion; a translucent vinyl backed material with primary indicia applied to said retroreflective sheeting; and a label with secondary indicia applied to said back face via label adhesive.