A control device outputs control information to a sidewalk configured such that an inclination of a road surface is changeable. When the control device detects a wheelchair waiting on the sidewalk for crossing a road, the control device outputs, as the control information, information of instruction to reduce the inclination of the road surface of the sidewalk.

In one aspect, a system for automatically assigning vehicle identifiers for autonomous vehicles can include a registry server computing system configured to perform operations. The operations can include receiving, at the registry server computing system and from a vehicle computing system onboard an autonomous vehicle, data describing the autonomous vehicle and generating, at the registry server computing system, a vehicle identifier for the autonomous vehicle based on the data describing the autonomous vehicle. The vehicle identifier can be different than and distinct from the data describing the autonomous vehicle. The operations can include associating, at the registry server computing system, the data describing the autonomous vehicle with the vehicle identifier for the autonomous vehicle in a vehicle registry. The vehicle registry can include respective vehicle identifiers associated with a plurality of autonomous vehicles.

In one aspect, a system for automatically assigning vehicle identifiers for autonomous vehicles can include a registry server computing system configured to perform operations. The operations can include receiving, at the registry server computing system and from a vehicle computing system onboard an autonomous vehicle, data describing the autonomous vehicle and generating, at the registry server computing system, a vehicle identifier for the autonomous vehicle based on the data describing the autonomous vehicle. The vehicle identifier can be different than and distinct from the data describing the autonomous vehicle. The operations can include associating, at the registry server computing system, the data describing the autonomous vehicle with the vehicle identifier for the autonomous vehicle in a vehicle registry. The vehicle registry can include respective vehicle identifiers associated with a plurality of autonomous vehicles.

Systems and methods by a telematics server are provided. The method includes receiving, over a network, training data including model input data and a known output label corresponding to the model input data from a first device, training a centralized machine-learning model using the training data, determining, by the centralized machine-learning model, an output label prediction certainty based on the model input data, determining an increase in the output label prediction certainty over a prior predicted output label certainty of the centralized machine-learning model, and sending, over the network, a machine-learning model update to a second device in response to determining that the increase in the output label prediction certainty is greater than an output label prediction increase threshold.

A power distribution and vehicle self-learning-based truck overload identification method, comprising: acquiring load identification data of a vehicle; calculating AOP values and STP values according to the load identification data of the vehicle; according to a plurality of sets of AOP values and STP values in a standard full-load state, constructing a power distribution curve of the vehicle in the standard full-load state; and comparing an AOP value during an actual operation process to a corresponding AOP value in the power distribution curve in the standard full-load state, and according to a comparison result, identifying whether the vehicle is overloaded. The method can show the operating states of overloaded vehicles in the road network in real time to provide convenience for oversize and overloading management. Loads of vehicles operating in the road network can be monitored in real time without additional equipment, thus improving the scope of overload identification.

A power distribution and vehicle self-learning-based truck overload identification method, comprising: acquiring load identification data of a vehicle; calculating AOP values and STP values according to the load identification data of the vehicle; according to a plurality of sets of AOP values and STP values in a standard full-load state, constructing a power distribution curve of the vehicle in the standard full-load state; and comparing an AOP value during an actual operation process to a corresponding AOP value in the power distribution curve in the standard full-load state, and according to a comparison result, identifying whether the vehicle is overloaded. The method can show the operating states of overloaded vehicles in the road network in real time to provide convenience for oversize and overloading management. Loads of vehicles operating in the road network can be monitored in real time without additional equipment, thus improving the scope of overload identification.

A digital license plate includes a display system capable of showing a license number readable by camera systems even under poor external lighting conditions. A light redistribution element is positioned near the display system and a lighting system is positioned to direct light from the light redistribution element and toward the display system. In some embodiments the lighting system includes a non-visible lighting element such as can be provided by an infrared source, and the display system includes an electrophoretic or LCD display.

A parking enforcement system includes an autonomous vehicle that is equipped with an image capture device that is configured to capture images of license plates of parked vehicles while the autonomous vehicle moves through a parking zone. The system will process the images to extract license plate numbers from the images. The system will correlate the license plate numbers with data in a parking enforcement database to determine whether the license plate numbers are associated with an unexpired parking transaction. For any license plate number that is not subject to an unexpired parking transaction, the system may initiate an enforcement action. For any license plate number that is subject to an unexpired parking transaction, the system may not initiate an enforcement action.

A parking assistance method is provided. The method includes recognizing image features of a traffic line corresponding to a parking position of a vehicle. A category of the parking position of the vehicle is determined based on the image features of the traffic line. Once the vehicle is determined to be parking illegally based on the category of the parking position of the vehicle; a warning is issued.

A portable or affixed stop sign warning system which enforce stop sign violations through automated photo enforcement with the use of radar and camera technology and incase of any incidence record the event. The system includes a plurality of surface mounted RADAR, computer, camera and video camera which provide the stable, reliable and accurate information necessary, video monitoring, and incident detection. The multi-tracking radar tracks vehicle speed and position as it approaches the stop sign. The system will use the distance, speed over time, acceleration and retardation to capture and automatically validate a stop sign violation. The violation evidence includes but not limited to high-definition picture before the stop line, high-definition picture after the line, close up of the license plate, photos show the stop sign, time, date, speed, and location of incidence.