A three-dimensional information processing method includes: obtaining, via a communication channel, map data that includes first three-dimensional position information; generating second three-dimensional position information from information detected by a sensor; judging whether one of the first three-dimensional position information and the second three-dimensional position information is abnormal by performing, on one of the first three-dimensional position information and the second three-dimensional position information, a process of judging whether an abnormality is present; determining a coping operation to cope with the abnormality when one of the first three-dimensional position information and the second three-dimensional position information is judged to be abnormal; and executing a control that is required to perform the coping operation.

Utilizing existing information of community transportation offerings, the present invention builds customized travel routes to enable independent mobility for individuals with cognitive disabilities. Visual, aural, and sensory prompts are provided based on the location of, and through, a mobile device. Concurrently with providing direction and reassurance to the traveler, the system monitors the location and progress of the traveler along the route. Upon recognition that the mobile device (traveler) is no longer on the initiated route, a caregiver, or the like, is notified to render assistance.

A method for generating guidance information is disclosed, which uses one or more machine learning algorithms to continually adapt and update a version of a model used to generate guidance instructions based on feedback data received from one or more users, such that the instructions generated by the model better fit the expectations or behaviour of the user or users. The method can be performed on a mobile navigation device, such that the model is adjusted to suit the needs of a single user. Alternatively, the method can be performed on a server based on feedback data from a plurality of users, and the updated model, once generated, transmitted to a plurality of mobile navigation devices to replace the existing model.

A method, system and computer program tie physical events to virtual events by analyzing motion information from a detecting device or analyzing contextual information, initiating a virtual event with a display device in response to detecting an impending change in center of mass motion of a user from analyzing the motion information or contextual information, and associating a virtual event with subsequent motion information from the detecting device.

Provided are methods and apparatuses for navigation guidance and establishing a three-dimensional real scene model, a device and a medium, which relate to the field of artificial intelligence and, in particular, intelligent transportation technologies. A specific implementation includes: determining a navigation route of a navigation device and candidate three-dimensional real scene data corresponding to the navigation route; where the candidate three-dimensional real scene data includes candidate location information, candidate three-dimensional model data and a candidate observation viewing angle; matching real-time positioning information of the navigation device with the candidate location information in the candidate three-dimensional real scene data to obtain target three-dimensional real scene data; and simulating target three-dimensional model data in the target three-dimensional real scene data at a target observation viewing angle in the target three-dimensional real scene data and at a location corresponding to the real-time positioning information to obtain a real-time navigation guidance image.

In device-assisted navigation, audio navigation cues are often presented at particular locations along a route (e.g., “in 200 meters, turn left” and “turn left here”). However, if the user stops, navigation cues also stop since the user's position is not changing. Additionally, the navigation instruction at the next navigation point may be conflated with the actual position of the next navigation point; e.g., an instruction to “turn left” may be confusing if the road takes a sharp right turn immediately before the next navigation point. Instead, the device may periodically compare the current position of the user and the next navigation point, and periodically present guidance audio cues that indicate the distance and heading offset to the next navigation point. Guidance audio cues may be integrated with and/or supplemented by audio navigation instructions to indicate both the location of the next navigation point and instructions to be followed there.

In device-assisted navigation, audio navigation cues are often presented at particular locations along a route (e.g., “in 200 meters, turn left” and “turn left here”). However, if the user stops, navigation cues also stop since the user's position is not changing. Additionally, the navigation instruction at the next navigation point may be conflated with the actual position of the next navigation point; e.g., an instruction to “turn left” may be confusing if the road takes a sharp right turn immediately before the next navigation point. Instead, the device may periodically compare the current position of the user and the next navigation point, and periodically present guidance audio cues that indicate the distance and heading offset to the next navigation point. Guidance audio cues may be integrated with and/or supplemented by audio navigation instructions to indicate both the location of the next navigation point and instructions to be followed there.

A method, apparatus, and system for integrating a non-autonomous vehicle into a transit environment populated with autonomous vehicles. An autonomous vehicle network integration apparatus is disclosed which collects data over a wireless network regarding a vehicle's route and surroundings, including nearby fully and partially autonomous vehicles. The apparatus is configured to analyze data and dynamically determine a range of influence, within which it communicates with vehicles to suggest driver actions and inform self-driving vehicle behavior.

A notification system includes a route decision unit that decides a route to a destination of a vehicle, a notification unit that notifies an occupant of guidance information for guiding the occupant regarding a lane change from a traveling lane of the vehicle to a recommended lane associated with the route to the destination decided by the route decision unit, and an HMI control unit that controls a notification start time of the guidance information for each lane on the basis of the number of lanes between the traveling lane and the recommended lane. In a case where the vehicle performs a lane change after a notification of the guidance information, the HMI control unit continues a notification of the guidance information even when a notification start time which is set for a lane after a lane change has not been reached.

A system and method provides a route and turn-by-turn directions based on estimates of current and future traffic along the route. A client device may request turn-by-turn directions between an initial and a final location. A server may identify a plurality of routes between the locations. Each route of the plurality of routes may be divided into route segments. For each route segment of a particular route, the server may estimate a travel time. The travel time may be based on estimated vehicle volume data generated from information received from other users vehicle Based on the estimated travel time for each route segment of a particular route, the server may estimate a total travel time for the particular route. The server may repeat this estimate for each of the plurality of routes between the locations and select the route with the lowest estimated travel time. Based on the selected route, the server may generate turn-by-turn directions and transmit the directions to the client device for display.