A method of generating an output movement layout for a traffic intersection is disclosed which includes receiving intersection geographical data, establishing a center point for the intersection, receiving vehicle global positioning system (GPS) data, establishing a radius of interest for the intersection based on the received vehicle GPS data, establishing entry and exit headings for each vehicle based on the GPS data, generating an angular cluster chart based on the entry and exit headings of each vehicle, and generating an output movement layout for the intersection based on the generated angular cluster chart. Further, a method for green time reallocation at traffic signals is disclosed that is based on the congestion experienced by vehicles identified as following specific movements.

System and techniques for an environmental control loop are described herein. A device for an environmental control loop can include a memory including instructions and processing circuitry that when in operation, can be configured by the instructions to receive environmental sensor data from a first component in a set of heterogeneous components installed in an environment with a controller. The environmental sensor data can indicate a service level value sensed by the first component. The controller can also measure a violation of a service level objective based on comparing the environmental sensor data to a threshold. The controller can also transmit an adjustment to an operating parameter of a second component of the set of heterogeneous components. The adjustment can be operative to attenuate the violation of the service level objective when implemented by the second component.

A computer is provided for a system for detecting, characterizing, and mitigating road network congestion. The system includes a plurality of motor vehicles. Each motor vehicle includes a telematics control unit (TCU) for generating one or more location signals for a location of the associated motor vehicle and one or more event signals for an event related to the associated motor vehicle. The computer includes one or more processors for receiving the location signal and/or the event signal from the TCU of the associated motor vehicles. The computer further includes a non-transitory computer readable storage medium (CRM) including instructions, such that the processor is programmed to identify a location of the road network congestion at a current time step. The processor is further programmed to track the road network congestion and predict the road network congestion at a next time step.

Upon identifying a plurality of target regions for a monitored region, priority levels for the respective target regions are determined based on a user input. Vehicle sensors that are available to monitor the respective target regions are determined based on the priority levels for the respective target regions and parameters for the respective vehicle sensors. Based on the available vehicle sensors and the priority levels for the respective target regions, a pose is determined for a vehicle that optimizes monitoring of the target regions. The vehicle is operated to the pose.

According to one example there is provided a method comprising selecting a first location from a set of locations and analysing, by a processor, data collected from a first vehicle located within a first distance of the first location. A first value representative of a first performance parameter of the first vehicle is generated. A second value representative of a second performance parameter of the first vehicle is generated. At least one of the first and second values is compared with a first threshold and, when one of the first and second values is greater than the first threshold, a safety alert is issued greater than (in some examples, less than).

In an approach to safely facilitate driver responses to road traffic event alerts, computer-implemented methods, computer program products, and computer systems for reducing vehicle occupant distractions are described. The computer-implemented method includes processors configured for receiving vehicle alert data corresponding to a road traffic event, generating a user alert prompt corresponding to the vehicle alert data, transmitting the user alert prompt to a user vehicle satisfying a first condition, and receiving a user response from an occupant of the user vehicle. Responsive to receiving an affirmative user response, activating one or more vehicle activity systems to reduce vehicle cabin activity by occupants within the user vehicle.

A method of directing traffic flow includes receiving, by a processor, navigation information from a vehicle in a multi-edge communication network, and receiving, by the processor, a status of an edge node traffic control device of the multi-edge communication network. The edge node traffic control device is configured to regulate traffic flow on a path segment. The method includes determining, by the processor, a navigation command based on the navigation information and the status, and outputting, by the processor, the navigation command to the vehicle through the multi-edge communication network.

This application provides an information processing method performed by a computing device. The method includes the following steps: acquiring free parking space information of a target path in a time period T1, the target path including N stop areas, the time period T1 being divided into K unit times; determining a free parking space change trend of the N stop areas in the time period T1 according to the free parking space information, and mining the free parking space change trend of the N stop areas in the time period T1 to obtain parking space prediction information; and performing traffic planning for a vehicle along the target path according to the parking space prediction information. The solution can well adapt to traffic scene requirements and improve the accuracy of traffic planning.

A method comprises determining a vectorized representation of positions of road agents and road geometry based on sensor data from a vehicle, inputting the vectorized representation of the positions of the road agents and the road geometry into a trained transformer network, predicting one or more road agent trajectories at one or more future time steps based on an output of the transformer network, predicting an acceleration of the vehicle at the one or more future time steps based on the predicted one or more road agent trajectories at the one or more future time steps, and causing the vehicle to perform the predicted acceleration at the one or more future time steps.

One or more potential drone and/or flying car (DFC) corridors are identified based on the topology of a road network. Trajectories traveled by vehicles are determined from a plurality of instances of probe data received from a plurality of vehicle apparatuses onboard the vehicles. A volume of traffic for a path through the road network and corresponding to a potential DFC corridor is determined based on the trajectories. A delay metric for the path through the road network and corresponding to the potential DFC corridor is determined based on the trajectories. A traffic metric is then determined for the path based on a combination of the volume of traffic, the delay metric and a measure of the topology of the road network. The one or more potential DFC corridors are ranked by their corresponding traffic metrics.