A navigation system includes: a control circuit configured to: generate a video clip by parsing an interval of a sensor data stream for a region of travel; analyze the video clip submitted to a deep learning model, already trained, including identifying a traffic flow estimate; access a position coordinate for calculating a distance to intersection; generate a traffic flow state by fusing a corrected speed, the traffic flow estimate, and the distance to intersection; merge a vehicle maneuvering instruction into the traffic flow state for maneuvering through the region of travel; and a communication circuit, coupled to the control circuit, configured to: communicate the traffic flow state for displaying on a device.

To provide a demand arbitration apparatus, a vehicle, and a demand arbitration system which can suppress that the travel routes of each vehicle are different with each other, when a plurality of vehicles of a vehicle group travel to a common destination. A demand arbitration apparatus manages a vehicle group which grouped a plurality of vehicles; sets a common destination of the vehicle group; and generates a travel route from the current position of each belonging vehicle to the common destination so that the travel route of each belonging vehicle overlaps with each other, and transmits to each belonging vehicle.

One or more processors identify an occupant of a passenger vehicle, and then receive biometric sensor readings from a biometric sensor that is monitoring the occupant in real time, where the biometric sensor readings indicate a real-time emotional state of the occupant. The processor(s) generate a personal profile for the occupant of the passenger vehicle based on the biometric sensor readings. The processor(s) receive a desired destination and travel schedule for the occupant of the passenger vehicle, as well as environmental sensor readings indicating a real-time environmental state of the passenger vehicle. The processor(s) then create a travel route for the passenger vehicle based on the biometric sensor readings, the personal profile of the vehicle occupant, the desired destination and travel schedule, and the real-time environmental state of the passenger vehicle. One or more processors then transmit, to the passenger vehicle, directions for the travel route.

System and methods for detecting and obtaining lane level insight in unplanned incidents. Probe-based vehicles and lane-level insight using a lane-level map-matcher are used to acquire information. This information is aggregated and used to differentiate lane activity in terms of traffic and safe navigation. With the identification of probes per-lane and probe speeds per-lane, sudden reductions in probe speeds may be obtained at a lane-based level. This is used to verify or detect lane-level incident or hazard warnings and consequently alert a driver to safer navigation paths ahead of time, like maneuver to a different lane or to take an alternative route.

System and methods for using probes to detect and elicit dangerous driving conditions. Historical probe data is aggregated and analyzed to identify reoccurring dangerous driving conditions down to the lane level. The lane level locations with high recurring dangerous driving condition metrics are identified and analyzed by a mapping system. The mapping system uses machine learning and other techniques to investigate, validate, and verify the dangerous driving conditions to ascertain the cause and then categorize the dangerous driving condition.

In some implementations, a mobile device transmits traffic information to a server for analysis. The traffic information includes movement information including detected stops and durations of detected stops. The traffic information is analyzed to detect traffic patterns that indicate locations of stop signs and/or stop lights. The traffic information is analyzed to determine durations of stops at stop signs and/or stop lights. The durations of stops is associated with a time of day and/or day of the week. In some implementations, navigational routes is determined based stop sign and/or stop light information, including the delays attributable to detected stop signs and/or stop lights.

A computer-implemented method of updating an auto insurance policy is provided. The method may include (1) determining that a customer's mobile device has a Telematics Application (“App”) installed on it, the Telematics App configured to (i) receive telematics data associated with another vehicle via a wireless communication broadcast; (ii) determine a travel event from analysis of the telematics data received, and (iii) generate a corrective action based upon the telematics data received or travel event determined that alleviates the risk of vehicle collision. The method may also include (2) monitoring, with the customer's permission, an amount or percentage of usage of the Telematics App on the customer's mobile device while the customer is driving in an insured vehicle; and (3) adjusting an insurance policy premium or discount based upon usage of the Telematics App to facilitate rewarding risk-averse drivers and encourage usage of risk mitigation or prevention technology.

The present application provides a method, device and system for automatically fueling a vehicle. The method includes: judging, by a fueling control device of the vehicle, whether the vehicle needs to be filled with fuel; obtaining driving route information and vehicle status information of the vehicle in the case of determining that the vehicle needs to be filled with fuel; determining fuel amount to be filled according to the driving route information and the vehicle status information of the vehicle; sending a fueling request to a fueling management system; receiving a feedback message from the fueling management system, wherein the feedback message includes position information of a fueling device; and prompting the vehicle to obtain fuel offered by the fueling device indicated by the position information of the fueling device according to the fuel amount to be filled.

The present technology relates to an information processing apparatus and an information processing method enabling a vehicle to readily pass an oncoming vehicle in a narrow road or the like. The information processing apparatus includes a map generating section generating map data associated with a circumference of a vehicle, and updating the map data in conformity with a movement of the vehicle, and a waiting space detecting section detecting a waiting space enabling the vehicle to wait on the basis of the map data, and generating waiting space information as information associated with the detected waiting space and used in setting of an escaping route on which the vehicle is escaped in order to pass an oncoming vehicle. The present technology, for example, can be applied to a vehicle controlling system which performs control of automatic driving.

Example techniques are described for determining a dynamic traffic-management plan based on factors such as predicted increases in traffic and known-structurally-deficient transportation infrastructure. Traffic patterns may be re-routed, particularly during high-congestion events, to reduce or avoid excessive weight loads travelling across weakened sections of roads, bridges, or the like.