Disclosed are systems and methods relating to providing intersection metrics based on road network data and telematic data.

Techniques for collecting, synchronizing, and displaying various types of data relating to a road segment enable, via one or more local or remote processors, servers, transceivers, and/or sensors, (i) enhanced and contextualized analysis of vehicle events by way of synchronizing different data types, relating to a monitored road segment, collected via various different types of data sources; (ii) enhanced and contextualized analysis of filed insurance claims pertaining to a vehicle incident at a road segment; (iii) advantageous machine learning techniques for predicting a level of risk assumed for a given vehicle event or a given road segment; (iv) techniques for accounting for region-specific driver profiles when controlling autonomous vehicles; and/or (v) improved techniques for providing a GUI to display collected data in a meaningful and contextualized manner.

A vehicle control system includes: an on-board control module, configured to control driving of the vehicle according to a control instruction sent by a vehicle dispatching command platform; a vehicle state module, configured to collect state information of the vehicle; an environment sensing module, configured to collect first road environment information of the vehicle; a UAV scanning module, configured to collect second road environment information of the vehicle; a data center module, configured to generate fusion information according to the state information, the first road environment information, and the second road environment information; a map module, configured to generate a driving route map of the vehicle according to the fusion information; and a vehicle dispatching command platform, configured to generate the control instruction according to the fusion information and the driving route map.

A vehicle control system includes: an on-board control module, configured to control driving of the vehicle according to a control instruction sent by a vehicle dispatching command platform; a vehicle state module, configured to collect state information of the vehicle; an environment sensing module, configured to collect first road environment information of the vehicle; a UAV scanning module, configured to collect second road environment information of the vehicle; a data center module, configured to generate fusion information according to the state information, the first road environment information, and the second road environment information; a map module, configured to generate a driving route map of the vehicle according to the fusion information; and a vehicle dispatching command platform, configured to generate the control instruction according to the fusion information and the driving route map.

A method and apparatus for aiding a police officer in writing a report by creating a depiction of an incident scene is provided herein. During operation a drone will photograph an incident scene from above. Relevant objects will be identified and a depiction of the incident scene will be created by overlaying the relevant photographed real world objects onto a map retrieved from storage. The depiction of the incident scene will be made available to police officers to increase the officers' efficiency in report writing. More particularly, officers will no longer need to re-create the depiction of the incident scene by hand. Instead, the officer will be able to use the depiction of the incident scene.

A method and apparatus for aiding a police officer in writing a report by creating a depiction of an incident scene is provided herein. During operation a drone will photograph an incident scene from above. Relevant objects will be identified and a depiction of the incident scene will be created by overlaying the relevant photographed real world objects onto a map retrieved from storage. The depiction of the incident scene will be made available to police officers to increase the officers' efficiency in report writing. More particularly, officers will no longer need to re-create the depiction of the incident scene by hand. Instead, the officer will be able to use the depiction of the incident scene.

The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.

The present application discloses a method and an apparatus of obstacle three-dimensional position acquisition for a roadside computing device, and relates to the fields of intelligent transportation, cooperative vehicle infrastructure, and autonomous driving. The method may include: acquiring pixel coordinates of an obstacle in a to-be-processed image; determining coordinates of a bottom surface center point of the obstacle according to the pixel coordinates; acquiring a homography relationship between a ground surface corresponding to the to-be-processed image and a ground surface corresponding to a template image; transforming the coordinates of the bottom surface center point of the obstacle into coordinates on the template image according to the homography relationship; and determining three-dimensional coordinates of the bottom surface center point of the obstacle according to the coordinates obtained by transformation and a ground equation corresponding to the template image. By use of the solution of the present application, implementation costs can be saved, and the accuracy is better.

The present application discloses a method and an apparatus of obstacle three-dimensional position acquisition for a roadside computing device, and relates to the fields of intelligent transportation, cooperative vehicle infrastructure, and autonomous driving. The method may include: acquiring pixel coordinates of an obstacle in a to-be-processed image; determining coordinates of a bottom surface center point of the obstacle according to the pixel coordinates; acquiring a homography relationship between a ground surface corresponding to the to-be-processed image and a ground surface corresponding to a template image; transforming the coordinates of the bottom surface center point of the obstacle into coordinates on the template image according to the homography relationship; and determining three-dimensional coordinates of the bottom surface center point of the obstacle according to the coordinates obtained by transformation and a ground equation corresponding to the template image. By use of the solution of the present application, implementation costs can be saved, and the accuracy is better.

The present invention is a method and system to verify carpool occupancy compliance for access to High Occupancy Vehicle (HOV) lanes, High Occupancy or Toll (HOT) lanes, or other vehicle-occupancy contingent rewards. The present invention uses software and hardware devices with radio-frequency transmitter modules to capture one or more photo images of vehicle occupants and to perform boxed headcounts of humans in any given photo frame. The present invention uses biometric signature detection to confirm the boxed headcounts and a realness algorithm to further confirm the genuineness of any human image. Occupancy compliance can be communicated directly to an appropriate regulatory body.