A method, a system, and a computer program product may be provided for providing traffic data to a client device. The system may receive from the client device, a request for traffic data corresponding to road segments of at least one map area, said request identifying the at least one map area and determine road segment identifiers corresponding to each of the road segments of the at least one map area and determine traffic data for at least a portion of the road segment identifiers, said traffic data obtained from a traffic data source. The system may further determine a plurality of traffic ranges based on the obtained traffic data and generate a bloom filter set, each bloom filter of the bloom filter set corresponding to a traffic range of the plurality of traffic ranges, wherein each bloom filter encodes road segment identifiers corresponding to the respective traffic range.

Technologies and techniques for anonymizing vehicle data. A data set is created on the basis of captured vehicle data and includes information regarding the location and/or time of the data capture. The information may be anonymized on the basis of traffic flow data by locally concealing the information regarding the location of the data capture and/or by temporally concealing the information regarding the time of the data capture. The traffic flow data may be based on group information received by the vehicle providing the vehicle data via vehicle-to-vehicle communication from other vehicles. A related motor vehicle and a network server directed to the anonymization is also provided herein.

Technologies and techniques for quality determination for a traffic system. First traffic parameter data is acquired from the traffic system, indicative of a parameter of the traffic system. Second traffic parameter data is acquired, indicative of another parameter of the traffic system, wherein the second traffic parameter data originate from a plurality of traffic participants. The parameter from the first traffic parameter data and second traffic parameter are obtained, wherein the parameter obtained from the first traffic parameter data is compared to the parameter obtained from the second traffic parameter data in order to determine the quality of the first traffic parameter data.

The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.

A system comprises a computer including a processor, and a memory. The memory stores instructions such that the processor is programmed to determine two or more clusters of vehicle operating parameter values from each of a plurality of vehicles at a location within a time. Determining the two or more clusters includes clustering data from the plurality of vehicles based on proximity to two or more respective means. The processor is further programmed to determine a reportable condition when a mean for a cluster representing a greatest number of vehicles varies from a baseline by more than a threshold.

Aspects of the present disclosure include a navigation system and computer-implemented methods for detecting traffic disruption events based on an analysis of input component data obtained from navigation-enabled devices of vehicles near a particular location. Traffic disruption events are events such as accidents, construction road closures, police and speed traps, or road hazards that cause a decrease in the flow of traffic along a particular route and thus, added time delays for occupants of vehicles traveling along those routes. The navigation system scores the input component data associated with each vehicle and aggregates the scored input component data to obtain a frustration score associated with the vehicle. The navigation system may detect traffic disruption events based on a number of vehicles near a particular area having associated frustration scores above a certain threshold.

One or more devices may obtain traffic data, such as video from intersection cameras, point cloud data from Light Detection and Ranging (or “LiDAR”) sensors, and so on. Metrics may be calculated from the traffic data. For each frame, the metrics may be analyzed to detect whether a near miss/collision occurs between each object in the frame (such as motorized or non-motorized vehicles, pedestrians, and so on) and each of the other objects in the frame. These metrics may be analyzed to evaluate whether or not a group of conditions are met. If the group of conditions are met, a near miss/collision may be detected. This may be recorded in the metrics for the objects involved. In some implementations, one or more indicators may be added to the traffic data and/or to one or more visualizations generated using the metrics, the traffic data, the structured data, and so on.

A vehicle collects video data of an environment surrounding the vehicle including traffic entities, e.g., pedestrians, bicyclists, or other vehicles. The captured video data is sampled and presented to users to provide input on a traffic entity's state of mind. The user responses on the captured video data is used to generate a training dataset. A machine learning based model configured to predict a traffic entity's state of mind is trained with the training dataset. The system determines input video frames and associated dimension attributes for which the model performs poorly. The dimension attributes characterize stimuli and/or an environment shown in the input video frames. The system generates a second training dataset based on video frames that have the dimension attributes for which the model performed poorly. The model is retrained using the second training dataset and provided to an autonomous vehicle to assist with navigation in traffic.

A system and method for controlling vehicles and for providing assistance to operated vehicles is discussed and described herein.

A navigation processing method is provided. In the method, a map is displayed in a user interface. A navigation route for a vehicle is displayed on the map in response to a navigation operation, for example, of a user. If at least one condition is satisfied, a video portal of a target road segment is displayed in the navigation route. The target road segment is in a target state indicating at least one of a jammed state, an accident state, or a damaged state of the target road segment. If a triggering operation is performed on the video portal, a video of the target road segment can be played. The video can be a live streaming video or a recorded video. The video can include captured scene information of the target road segment. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.