Patent classifications
G08G1/048
Motor Vehicle Artificial Intelligence Expert System Dangerous Driving Warning And Control System And Method
Specifically programmed, integrated motor vehicle dangerous driving warning and control system and methods comprising at least one specialized communication computer machine including electronic artificial intelligence expert system decision making capability further comprising one or more motor vehicle electronic sensors for monitoring the motor vehicle and for monitoring activities of the driver and/or passengers including activities related to the use of cellular telephones and/or other wireless communication devices and further comprising electronic communications transceiver assemblies for communications with external sensor networks for monitoring dangerous driving situations, weather conditions, roadway conditions, pedestrian congestion and motor vehicle traffic congestion conditions to derive warning and/or control signals for warning the driver of dangerous driving situations and/or for controlling the motor vehicle driver use of a cellular telephone and/or other wireless communication devices.
Motor Vehicle Artificial Intelligence Expert System Dangerous Driving Warning And Control System And Method
Specifically programmed, integrated motor vehicle dangerous driving warning and control system and methods comprising at least one specialized communication computer machine including electronic artificial intelligence expert system decision making capability further comprising one or more motor vehicle electronic sensors for monitoring the motor vehicle and for monitoring activities of the driver and/or passengers including activities related to the use of cellular telephones and/or other wireless communication devices and further comprising electronic communications transceiver assemblies for communications with external sensor networks for monitoring dangerous driving situations, weather conditions, roadway conditions, pedestrian congestion and motor vehicle traffic congestion conditions to derive warning and/or control signals for warning the driver of dangerous driving situations and/or for controlling the motor vehicle driver use of a cellular telephone and/or other wireless communication devices.
Determining traffic congestion patterns
Embodiments generally relate to determining traffic congestion patterns. In some embodiments, a method includes identifying congestion events for each road of a plurality of roads in a road network, where each congestion event indicates a drop in average vehicle speed below a predetermined speed threshold for a particular road in the road network, and where the congestion events span a predetermined time period. The method further includes determining local clusters of the congestion events based on one or more road condition parameters, where each local cluster defines a local congestion pattern for a particular road of the plurality of roads in the road network. The method further includes grouping the local clusters into one or more global clusters based on the one or more road condition parameters, where the global clusters define global congestion patterns in the road network.
Determining traffic congestion patterns
Embodiments generally relate to determining traffic congestion patterns. In some embodiments, a method includes identifying congestion events for each road of a plurality of roads in a road network, where each congestion event indicates a drop in average vehicle speed below a predetermined speed threshold for a particular road in the road network, and where the congestion events span a predetermined time period. The method further includes determining local clusters of the congestion events based on one or more road condition parameters, where each local cluster defines a local congestion pattern for a particular road of the plurality of roads in the road network. The method further includes grouping the local clusters into one or more global clusters based on the one or more road condition parameters, where the global clusters define global congestion patterns in the road network.
Determining traffic congestion patterns
Embodiments generally relate to determining traffic congestion patterns. In some embodiments, a method includes identifying congestion events for each road of a plurality of roads in a road network, where each congestion event indicates a drop in average vehicle speed below a predetermined speed threshold for a particular road in the road network, and where the congestion events span a predetermined time period. The method further includes determining local clusters of the congestion events based on one or more road condition parameters, where each local cluster defines a local congestion pattern for a particular road of the plurality of roads in the road network. The method further includes grouping the local clusters into one or more global clusters based on the one or more road condition parameters, where the global clusters define global congestion patterns in the road network.
Determining traffic congestion patterns
Embodiments generally relate to determining traffic congestion patterns. In some embodiments, a method includes identifying congestion events for each road of a plurality of roads in a road network, where each congestion event indicates a drop in average vehicle speed below a predetermined speed threshold for a particular road in the road network, and where the congestion events span a predetermined time period. The method further includes determining local clusters of the congestion events based on one or more road condition parameters, where each local cluster defines a local congestion pattern for a particular road of the plurality of roads in the road network. The method further includes grouping the local clusters into one or more global clusters based on the one or more road condition parameters, where the global clusters define global congestion patterns in the road network.
Method, apparatus, and system for determining a navigation route based on vulnerable road user data
An approach is provided for determining a navigation route based on vulnerable road user data. The approach, for example, involves generating one or more candidate navigation routes for a vehicle. The approach also involves querying a geographic database for vulnerable road user data for a respective set of road links comprising each of the one or more candidate navigation routes. The approach further involves selecting the navigation route from among the one or more candidate navigation routes based on the vulnerable road user data.
Method, apparatus, and system for determining a navigation route based on vulnerable road user data
An approach is provided for determining a navigation route based on vulnerable road user data. The approach, for example, involves generating one or more candidate navigation routes for a vehicle. The approach also involves querying a geographic database for vulnerable road user data for a respective set of road links comprising each of the one or more candidate navigation routes. The approach further involves selecting the navigation route from among the one or more candidate navigation routes based on the vulnerable road user data.
SMOG ANALYSIS VIA DIGITAL COMPUTING PLATFORMS
Disclosed is a system, computer program product and computer-implemented method for smog analysis which provides sending a data collection signal to one or more vehicles including one or more sensors via a base station, receiving data from the one or more vehicles, including sensor data, analyzing the received data for determining a smog status, and sending traffic information to a plurality of vehicles. The traffic information may include the determined smog status and the plurality of vehicles may include the one or more vehicles.
SMOG ANALYSIS VIA DIGITAL COMPUTING PLATFORMS
Disclosed is a system, computer program product and computer-implemented method for smog analysis which provides sending a data collection signal to one or more vehicles including one or more sensors via a base station, receiving data from the one or more vehicles, including sensor data, analyzing the received data for determining a smog status, and sending traffic information to a plurality of vehicles. The traffic information may include the determined smog status and the plurality of vehicles may include the one or more vehicles.