A method for determining a road condition is carried out aboard a vehicle driving on the road and comprises the following steps: capturing the noise created by the friction between at least one tire and the road; analyzing the noise signal in the high frequency range to determine whether the road condition is dry or not; and, in case the road condition is not dry, analyzing the noise signal in the low frequency range to determine whether to road condition is wet or damp.

Autonomous vehicle operational management may include traversing, by an autonomous vehicle, a vehicle transportation network. Traversing the vehicle transportation network may include operating a scenario-specific operational control evaluation module instance, wherein the scenario-specific operational control evaluation module instance is an instance of a scenario-specific operational control evaluation module, wherein the scenario-specific operational control evaluation module implements a partially observable Markov decision process. Traversing the vehicle transportation network may include receiving a candidate vehicle control action from the scenario-specific operational control evaluation module instance, and traversing a portion of the vehicle transportation network based on the candidate vehicle control action.

The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.

Various aspects of a system and method for driving assistance along a path are disclosed herein. In accordance with an embodiment, a unique identifier is received from a communication device at an electronic control unit (ECU) of a first vehicle. The unique identifier is received when the first vehicle has reached a first location along a first portion of the path. A communication channel is established between the first vehicle and the communication device based on the received unique identifier. Data associated with a second portion of the path is received by the ECU from the communication device based on the established communication channel. Alert information associated with the second portion of the path is generated by the ECU based on the received data.

An accident risk diagnosis apparatus stores travel data that is data indicating a travel state of each of a plurality of vehicles for each date and time and information on past accidents of the plurality of vehicles, extracts the travel data for a predetermined period before an accident day and the travel data on the accident day from among the travel data, generates training data for each trip that is a period from activation to termination of a vehicle based on an extracted travel data, generates an accident risk diagnosis model that is a machine learning model for diagnosing an accident risk using the training data, inputs a feature in a trip of a vehicle to be diagnosed to the accident risk diagnosis model to diagnose the accident risk, and transmits a diagnosis result to an in-vehicle device mounted on the vehicle.

An HCU is to be used in a vehicle including an autonomous driving operation, and includes a function of a presentation control device that controls presentation of information to a driver of the vehicle. The presentation control device determines interruption of a second task other than driving permitted to the driver in an autonomous traveling period where the vehicle travels by the autonomous driving operation. Based on the interruption determination of the second task, the HCU changes a provision method of content provided in association with the second task in the autonomous traveling period.

A connected-vehicle interface module is provided that includes a connected-vehicle controller, a wireless data connected-vehicle radio for receiving an activation signal indicating a road condition, and a connected-vehicle interface controller. The connected-vehicle interface controller including a microcontroller and a plurality of universal asynchronous receiver transmitters for receiving, transmitting, and processing data received by at least one of the connected-vehicle controller and the connected-vehicle radio, and communicated to the microcontroller via one or more wired connections; a memory device for storing program data, and an ethernet transceiver and communication port, coupled to the microcontroller, for connection and communication with a connected vehicle road side unit, wherein the activation signal is communicated to the connected vehicle road side unit via the communication port, and at least one operator interface in communication with at least one of the connected-vehicle radio, the connected-vehicle interface controller, and the connected-vehicle controller.

System, methods, and other embodiments described herein relate to predicting trajectories of multiple vehicles using graphs and multiple decoding models. In one embodiment, a method includes computing, using an encoding model, a graph having a geographic map and vehicle features associated with a plurality of vehicles in an area according to characteristics, prior trajectories, and spatiotemporal interactions. The method also includes processing, using the encoding model, updates for the geographic map and the vehicle features separately in association with encoded features of neighboring vehicles. The method also includes decoding, using a probability model and a regression model, the geographic map and the vehicle features to output estimated trajectories for the plurality of vehicles.

A system for determining an existence of a change in a region can include a processor, a communications device, and a memory. The memory can store a change determination module and a communications module. The change determination module can cause the processor to: (1) determine, in response to having obtained an indication of a possible change in the region, a location of a connected car in a vicinity of the region and facts about a sensor disposed on the connected car and (2) determine a strategy to obtain data about the possible change. The strategy can be based on at least one of the location of the connected car or the facts about the sensor. The communications module can cause the processor to transmit, via the communications device and to the connected car, an instruction to control, according to the strategy, the sensor to obtain the data.

A system for use with a vehicle includes at least one device installed or present onboard the vehicle and configured to sense or determine at least one condition or characteristic of the vehicle or its driver. The at least one device communicates the condition or characteristic with a remote site or web service using a wireless communication device. The remote site or web service correlates or compares the condition or characteristic of the vehicle or its driver with road conditions, capacities, facilities, and/or established safety data associated with the upcoming roadway, and determines whether the vehicle should stop or enter a facility due to an incompatibility or conflict between the condition or characteristic and the road conditions, capacities, facilities, and/or established safety data. The remote site or web service then communicates the determination of whether the vehicle should stop or enter the facility to the device on the vehicle.