An interactive system for use in connection with recreational vehicle usage includes a server system, including an off-road trail database containing trail data, trail condition information, and points-of-interest information, as well as a trip mapping system accessible by any of a plurality of riders, allowing a rider to create a route based on the data in the off-road trip database. The server system further includes a trail maintenance interface accessible by users affiliated with an authorized group to edit the trail data, trail condition information, and points-of-interest information associated with the authorized group. The server system includes a location data management system configured to receive location data, allowing a rider to publish location information to one or more other riders, and a user feedback interface configured to receive trip data from riders for publication, including information describing an actual route and user data associated with that route.

A flood display device includes: a processor with hardware, the processor being provided to: acquire flood point information in which a detection result of a flood point of a road and a classification of a flood situation at the flood point determined based on traveling state data of a vehicle traveling at the detected flood point are associated with each other based on the traveling state data related to the traveling of the vehicle, generate flood detection information in which a display mode of the detection result is changed based on the classification of the flood situation as flood detection information obtained by superimposing the detection result on a position on a map corresponding to the flood point based on the flood point information, and output the flood detection information to a display.

Movement guidance information for performing traveling guidance for a vehicle is requested to a guidance information delivering server device based on an area update table and an area identification table for managing an update state of map information in a communication terminal, and traveling guidance for the vehicle is performed based on the movement guidance information delivered from the guidance information delivering server device in response to the request.

Aspects of this disclosure relate to controlling one or more vehicle systems based on a determined weather condition. In some embodiments, a radar system can be mounted on a vehicle and can collect weather data by receiving electromagnetic signals. A weather condition can be determined based on the collected weather data, and a vehicle system can be controlled based on the determined weather condition, such as vehicle lighting, windscreen wipers, or cruise control. In some embodiments, weather conditions can include fog, sleet, or smog. The weather condition can be determined by analyzing scattered reflections from incident microwaves and/or radio waves to determine a level of attenuation of the scattered electromagnetic energy indicative of a presence or absence of particles. A map can be displayed displaying the weather condition and controlling vehicle navigation systems. The collected weather data can be compared with data from a LiDAR or camera system for reliability.

A high-definition map system receives sensor data from vehicles travelling along routes and combines the data to generate a high definition map for use in driving vehicles, for example, for guiding autonomous vehicles. A pose graph is built from the collected data, each pose representing location and orientation of a vehicle. The pose graph is optimized to minimize constraints between poses. Points associated with surface are assigned a confidence measure determined using a measure of hardness/softness of the surface. A machine-learning-based result filter detects bad alignment results and prevents them from being entered in the subsequent global pose optimization. The alignment framework is parallelizable for execution using a parallel/distributed architecture. Alignment hot spots are detected for further verification and improvement. The system supports incremental updates, thereby allowing refinements of sub-graphs for incrementally improving the high-definition map for keeping it up to date

The present disclosure relates to a method for determining a vehicle pose, predicting a pose (x.sub.k, y.sub.k, θ.sub.k) of vehicle on a map based on sensor data acquired by a vehicle localization system, transforming a set of map road references of a segment of a digital map from a global coordinate system to an image-frame coordinate system of a vehicle-mounted camera based on map data and predicted pose of the vehicle. The transformed set of map road references form a set of polylines in image-frame coordinate system. Identifying a set of corresponding image road reference features in an image acquired by vehicle mounted camera, where each identified road references feature defines a set of measurement coordinates (x.sub.i, y.sub.i) in image-frame. Projecting each of identified set of image road reference features onto formed set of polylines in order to obtain a set of projection points.

A vehicle includes: a communication device configured to obtain traffic information from a server; an input device configured to receive departure information and destination information from a user; a display device; a storage configured to store driving record information; and a controller configured to obtain movement route information by searching for at least one movement route based on the departure information and the destination information, calculate a congestion level of the movement route based on the movement route information and the traffic information, if the congestion level is less than a predetermined reference value, determine a first urgency level in response to a destination based on at least one of the driving record information or the destination information, determine a final movement route based on the first urgency level, and display the final movement route on the display device.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying choke points in an environment. One of the methods includes obtaining road data representing a plurality of roads in an environment; identifying one or more blockage points in the environment; generating a graph representing the environment, wherein: the graph comprises a plurality of nodes and edges, each node of the graph represents a respective location in the environment, each edge between a first node and a second node represents a road that connects the location in the environment represented by the first node and the location in the environment represented by the second node, and blockage points are not represented by nodes in the graph; processing the graph to determine a minimum cut of the graph; and determining, using the minimum cut of the graph, one or more choke points in the environment.

A method, apparatus and computer program product are provided for predicting a split lane traffic pattern for a road segment. In this regard, first traffic data for an upstream road segment of the road segment is aggregated based on a distribution of speeds associated with location probe points representative of travel of vehicles along the road segment. Furthermore, second traffic data for a first downstream road segment of the road segment is aggregated based on the distribution of speeds associated with the location probe points for the vehicles. Third traffic data for a second downstream road segment of the road segment is also aggregated based on the distribution of speeds associated with the location probe points for the vehicles. Additionally, a machine learning model that predicts a traffic pattern is trained based on the first traffic data, the second traffic data and the third traffic data.

System, method and computer program products are provided for detecting an environmental zone, generating a time schedule of an environmental zone in a region and providing route navigation instructions. The method may include obtaining at least one observation associated with the environmental zone in a region. The method may further include determining a confidence value associated with the at least one observation in the region and detecting the environmental zone in the region based on the confidence value associated with the at least one observation. The detection of the environmental zone comprises determining either one of a presence or an absence of the environmental zone in the region. Further, the detection of the environmental zone may be used to generate a time schedule indicating presence or absence of the environmental zone in the region for different time intervals.