A controller and a control method for a vehicle including an engine with a supercharger and an automatic transmission provided in a power transmission path between the engine and driving wheels are provided. The controller is configured to perform learning control of learning a command value associated with gear shifting of the automatic transmission. The controller is configured to limit a supercharging pressure of the supercharger when the automatic transmission is performing gear shifting to be equal to or less than a predetermined pressure until initial learning which is performed by the learning control unit in a predetermined period after the vehicle has been manufactured is completed.

In examples provided herein, a system in a vehicle comprises a processor and a memory including instructions executable by the processor to aggregate and transmit to a context-aware platform (CAP) diagnostic data for a vehicle; receive from the CAP responsive information based on analysis of the diagnostic data; and cause the responsive information to be audibly provided to a driver of the vehicle.

A controller and a control method for a vehicle including an engine with a supercharger and an automatic transmission provided in a power transmission path between the engine and driving wheels are provided. The controller is configured to perform learning control of learning a command value associated with gear shifting of the automatic transmission. The controller is configured to limit a supercharging pressure of the supercharger when the automatic transmission is performing gear shifting to be equal to or less than a predetermined pressure until initial learning which is performed by the learning control unit in a predetermined period after the vehicle has been manufactured is completed.

The Dynamic Vehicle Separation System (DVSS) according to the present application allows properly equipped vehicles in traffic to maintain safe and optimal separation distances (i.e., following distances), which are automatically and continually calculated based on numerous criteria. Vehicles are equipped with Dynamic Vehicle Separation Controllers (DVSCs) that communicate with each other to maintain proper separation distances among the vehicles.

The Dynamic Vehicle Separation System (DVSS) according to the present application allows properly equipped vehicles in traffic to maintain safe and optimal separation distances (i.e., following distances), which are automatically and continually calculated based on numerous criteria. Vehicles are equipped with Dynamic Vehicle Separation Controllers (DVSCs) that communicate with each other to maintain proper separation distances among the vehicles.

Exemplary implementations may: generate output signals conveying contextual information and vehicle information; determine, based on the output signals, the contextual information; determine, based on the output signals, the vehicle information, determine, in an ongoing manner, based on the contextual information and/or the vehicle information, values of a complexity metric, the complexity metric quantifying predicted complexity of a current contextual environment and/or predicted complexity of a likely needed response to a change in the contextual information; filter, based on the values of the complexity metric, the contextual information spatially; and control, based on the vehicle information and the spatially filtered contextual information, the vehicle such that the likely needed response is satisfied.

A vehicle traveling support control apparatus includes a traveling environment determining portion that determines a traveling environment of a vehicle, a support device determining portion that determines a serviceable traveling support device from one or more traveling support devices mounted in the vehicle in accordance with the traveling environment determined by the traveling environment determining portion, a presentation portion that presents support guidance of the serviceable traveling support device, and a control portion that controls the presentation portion to present the support guidance of the serviceable traveling support device based on use frequency of the serviceable traveling support device determined by the support device determining portion.

A server device can obtain historical location data, concerning a vehicle, captured by a global positioning system (GPS) device of the vehicle and historical engine control unit (ECU) data concerning the vehicle captured by an ECU of the vehicle. The server device can process the historical location data and the historical ECU data to train a machine learning model to determine a relationship between the historical location data and the historical ECU data. The server device can receive location data and ECU data concerning the vehicle and update the machine learning model based on the location data and the ECU data. The server device can receive real-time location data concerning the vehicle and derive an equivalent real-time ECU speed using the machine learning model. The server device can generate a message regarding the equivalent real-time ECU speed of the vehicle and send the message to a remote device for display.

A hybrid electric vehicle system comprises an internal combustion (IC) engine and an electric engine providing power to a drive shaft of the vehicle. The IC engine receives a fuel from a fuel tank. Exhaust gases from the IC engine are treated at an exhaust treatment apparatus including a reagent tank containing a reagent. A controller monitors a quality of the fuel in the fuel tank and the reagent in the reagent tank and if needed, initiates fuel degradation reduction event or a reagent degradation reduction event. These events can include running the IC engine even if a battery supplying power to the motor is not discharged. The fuel degradation reduction event includes dosing the fuel tank with an antioxidant to reduce the rate of degradation of the fuel.

A server device can obtain historical location data, concerning a vehicle, captured by a global positioning system (GPS) device of the vehicle and historical engine control unit (ECU) data concerning the vehicle captured by an ECU of the vehicle. The server device can process the historical location data and the historical ECU data to train a machine learning model to determine a relationship between the historical location data and the historical ECU data. The server device can receive location data and ECU data concerning the vehicle and update the machine learning model based on the location data and the ECU data. The server device can receive real-time location data concerning the vehicle and derive an equivalent real-time ECU speed using the machine learning model. The server device can generate a message regarding the equivalent real-time ECU speed of the vehicle and send the message to a remote device for display.