An Internet of Things (IoT) technique for vehicular traffic management, including an IoT sensor to measure traffic data of vehicular traffic, a traffic analyzer to determine a traffic event based on the traffic data, and an IoT gateway to issue a response based on the traffic event.

Methods, systems, and apparatus, including computer programs encoded on computer storage media for task control based on Bayesian Meta-Reinforcement learning. An exemplary method includes obtaining a base machine learning (ML) model trained based on historical data collected from historical tasks. The base ML model represents a prior distribution of model parameters in a neural network representing control policies. The exemplary method further includes receiving observed data from a new control task; training a task-level ML model based on the base ML model and the observed data, wherein the task-level ML model represents a posterior distribution of the model parameters; sampling, based on the posterior distribution of the model parameters, a set of the model parameters that represent a control policy; and applying the control policy in performing the new control task.

Methods, systems, and apparatus, including computer programs encoded on computer storage media for task control based on Bayesian Meta-Reinforcement learning. An exemplary method includes obtaining a base machine learning (ML) model trained based on historical data collected from historical tasks. The base ML model represents a prior distribution of model parameters in a neural network representing control policies. The exemplary method further includes receiving observed data from a new control task; training a task-level ML model based on the base ML model and the observed data, wherein the task-level ML model represents a posterior distribution of the model parameters; sampling, based on the posterior distribution of the model parameters, a set of the model parameters that represent a control policy; and applying the control policy in performing the new control task.

Dynamically configurable traffic controllers and methods of using the same are disclosed. An example apparatus includes a first sensor to monitor traffic in a first area. The example apparatus further includes a second sensor to monitor traffic in a second area. The example apparatus also includes a projector to project light toward a floor when traffic is detected in both the first and second areas, the light to be visible from the first and second areas.

Dynamically configurable traffic controllers and methods of using the same are disclosed. An example apparatus includes a first sensor to monitor traffic in a first area. The example apparatus further includes a second sensor to monitor traffic in a second area. The example apparatus also includes a projector to project light toward a floor when traffic is detected in both the first and second areas, the light to be visible from the first and second areas.

A traffic control system for controlling traffic at interconnected intersections is provided, where the system comprises a receiver that receives traffic data that indicates states of vehicles approaching an intersection of the interconnected intersections and directions of the vehicles exiting the intersection. Further, the system comprises a processor that determines intersection crossing times and velocities of vehicles approaching the intersection by minimizing at least one of a total travel time or a maximum travel time of the vehicles for crossing the intersection. The contribution of each vehicle of the vehicles approaching the intersection in the at least one of a total travel time or a maximum travel time is weighted based on directions of the vehicles and traffic at next intersection. Further, the system comprises a transmitter that transmits the intersection crossing times and velocities to the vehicles exiting the intersection for controlling the traffic at the interconnected intersections.

A traffic control system for controlling traffic at interconnected intersections is provided, where the system comprises a receiver that receives traffic data that indicates states of vehicles approaching an intersection of the interconnected intersections and directions of the vehicles exiting the intersection. Further, the system comprises a processor that determines intersection crossing times and velocities of vehicles approaching the intersection by minimizing at least one of a total travel time or a maximum travel time of the vehicles for crossing the intersection. The contribution of each vehicle of the vehicles approaching the intersection in the at least one of a total travel time or a maximum travel time is weighted based on directions of the vehicles and traffic at next intersection. Further, the system comprises a transmitter that transmits the intersection crossing times and velocities to the vehicles exiting the intersection for controlling the traffic at the interconnected intersections.

A method may be implemented to prioritize and analyze data exchanged in a connected vehicle transit network. The method may include receiving, at a roadside unit, vehicle data from a connected vehicle. The method may further include prioritizing the vehicle data received from the connected vehicle based on a level of urgency, network latency or available computing resources.

Provided are a data verification method and apparatus, an electronic device, and a storage medium. The method includes that the actual value of an evaluation indicator of the timing coordination data of intersection traffic lights on a green-wave coordinated trunk is determined, where evaluation indicator includes at least one of an intersection stop rate indicator, a road section speed indicator, a trunk speed indicator, or a trunk stop count indicator; the theoretical value of the evaluation indicator is determined based on the timing coordination data of the intersection traffic lights on the green-wave coordinated trunk, intersection location data, and the trajectory data of vehicles running on the green-wave coordinated trunk; and the reasonability of the timing coordination data of the intersection traffic lights on the green-wave coordinated trunk is verified based on the theoretical value of the evaluation indicator and the actual value of the evaluation indicator.

A synchronization signaling system, comprising a set of alert devices comprising at least one of a visual or audio output for producing an alert pattern, a master clock, a timing device capable of receiving updates from the master clock, a controller operably connected with the set of alert devices to control the set of alert devices.