A method for determining space allocation and signal timing of an isolated signalized intersection consists of at least one remote server and a processing module that is communicably coupled with the at least one remote server. A plurality of traffic-related data, wherein the plurality of traffic-related data reflects activity at the isolated signalized intersection, is received through the processing module. A space determination process is performed on the plurality of traffic-related data through the processing module. Next, a timing determination process is performed on the plurality of traffic-related data through the processing module in order to minimize the average intersection delay at the isolated signalized intersection. Based upon the results from the space determination process and the timing determination process a cycle length is determined for the isolated signalized intersection.

A method for determining space allocation and signal timing of an isolated signalized intersection consists of at least one remote server and a processing module that is communicably coupled with the at least one remote server. A plurality of traffic-related data, wherein the plurality of traffic-related data reflects activity at the isolated signalized intersection, is received through the processing module. A space determination process is performed on the plurality of traffic-related data through the processing module. Next, a timing determination process is performed on the plurality of traffic-related data through the processing module in order to minimize the average intersection delay at the isolated signalized intersection. Based upon the results from the space determination process and the timing determination process a cycle length is determined for the isolated signalized intersection.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

An example operation may include one or more of identifying transports operating on a roadway, determining a degree of transport traffic based on the identified transports, when the degree of transport traffic has exceeded a traffic level, assigning one or more of the identified transports as a roadway manager, controlling movement of the roadway manager, and generating a roadway indicator on the roadway manager to direct the identified transports.

There is provided an information processing system capable of performing driving assistance according to different automated driving levels.

An information processing system according to an embodiment of the present disclosure includes one or more mobile devices capable of setting an automated driving level, and an external network device capable of communicating with the mobile devices. The external network device includes a communication device that communicates with the mobile device, an arithmetic model determination device that determines an arithmetic model corresponding to the automated driving level and provides the arithmetic model to the mobile device via the communication device, and a registration determination device that determines whether or not registration of the automated driving level is possible on the basis of information regarding possession of the arithmetic model, and gives a notification of registration permission to the mobile device via the communication device. The mobile device includes an arithmetic model request unit that requests the arithmetic model from the arithmetic model determination device, and causes the information to be transmitted to the registration determination device when the requested arithmetic model is provided, and a movement control unit that starts movement control based on the automated driving level permitted to be registered when the notification is received from the registration determination device.

To enhance identification accuracy for the external environment of a movable object.

Acquired is image data having an image feature (such as area, date and time, and weather) corresponding to a movement scene of the movable object. Learning with the image data is performed to acquire an inference DNN coefficient for identification of the external environment of the movable object from the image data of the movement scene. For example, the external environment is identified on the basis of, for example, semantic segmentation or depth. The inference DNN to which the inference DNN coefficient is set enables accurate identification of the external environment of the movable object from the image data of the movement scene.

The purpose of the present disclosure is to achieve smooth rendezvous of a vehicle and a user even if there are numerous persons at a meeting point. A rendezvous assistance system includes a mobile terminal carried by a user who wants to rendezvous with a dispatched vehicle, and a rendezvous assistance device that assists rendezvous of the dispatched vehicle and the user at a meeting point. The rendezvous assistance device includes a message generator that generates a message that requests the user to do a gesture, a vehicle controller that determines timing of transmission of the message, and a vehicle communicator that transmits a message to the mobile terminal. The mobile terminal includes a mobile communicator that receives a message from the rendezvous assistance device and a notification unit that notifies the user of a request to do a gesture in accordance with the message.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

The methods, devices, and systems discussed herein periodically broadcast a signal containing an indicator to a first area that is near a potential safety scenario, such as an intersection. Upon entering the first area, a mobile wireless communication device (WCD) receives the broadcast signal. In response to receiving the broadcast signal, the WCD activates a collision-avoidance procedure. In some examples, the collision-avoidance procedure includes sensing device-to-device (D2D) resources in order to detect D2D transmissions from an approaching D2D-capable device (e.g., a vehicle). In other examples, the collision-avoidance procedure includes transmitting a periodic D2D safety message using D2D resources.