Abstract: An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Abstract: A system for 5G MICO mode operation of a vehicle during an ignition off mode includes a telematics unit and a telematics communication mode controller. The controller monitors energy consumption by the telematics unit and estimates a total energy consumption of the telematics unit through a time period. The controller further compares the total energy consumption to a first threshold energy consumption and a second threshold energy consumption and, when the total energy consumption is less than the first threshold energy consumption, operates the telematics unit in a first mode including unrestricted communication. The telematics communication mode controller, when the total energy consumption is between the first threshold energy consumption and the second threshold energy consumption, operates the telematics unit in a second MICO mode and, when the total energy consumption is greater than the second threshold energy consumption, deactivates communications by the telematics unit.

Abstract: The invention relates to a method (200) for training a dynamic-architecture convolutional neural network for semantic image segmentation, comprising a phase (102) of auto-annotation of images, to constitute a database (B1), called the first database, of auto-annotated images, comprising the following steps: applying (104) at least one transformation to at least one source image, and adding (106), to each transformed image thus obtained, a tag, called the first tag, corresponding to said transformation; said method (200) comprising at least one iteration of a phase (110) of training said neural network with the first image database (B1), and a second image database (B2) annotated with a tag, called a second tag, relating to the content of said image. It also relates to a computer program and a device implementing such a method, and a deep-learning dynamic-architecture convolutional neural network obtained by such a method.

Abstract: A system for ambient temperature and battery voltage compensation for operation of a telematics module through an ignition-off low-power mode is provided. The system includes the telematics module configured for providing data communication and for operating in the ignition-off low-power mode through a telematics remaining reduced power operating period. The system further includes a battery system providing electrical power to the telematics module, a battery voltage sensor measuring a battery voltage of the battery system, and an ambient temperature sensor measuring an ambient temperature. The system further includes a computerized ignition-off low-power controller, including programming to periodically monitor the battery voltage, periodically monitor the ambient temperature, and determine a relative energy consumption ratio based upon comparing the measured values to nominal values.

Abstract: Presented are intelligent vehicle communications systems for cellular link monitoring and failure detection, methods for making/using such systems, and vehicles equipped with such systems. A method for operating a wireless-enabled vehicle component of a motor vehicle includes a cellular communications device of the vehicle component detecting an uplink (or downlink) network data packet transmitted by (or to) the vehicle. An electronic vehicle controller then establishes an observation period as a function of the time at which the network data packet was transmitted. The opposite downlink (or uplink) of the wireless-enabled vehicle component is monitored to determine if a downlink (or uplink) network data packet is received within the observation period, thereby indicating detection of a cellular link failure.

Abstract: An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Abstract: An engine and cabin thermal management system for use with a vehicle having an engine, a cabin heating system configured to thermally heat a cabin of the vehicle, a coolant system operably coupled to the engine and to the cabin heating system to thermally manage a temperature of the engine and a temperature of the cabin. The coolant system having one or more coolant thermal storage units fluidly coupled with a radiator and heater core of the coolant system forming a coolant loop. The system further having a control system configured to monitor and maintain at least a predetermined coolant temperature at the cabin heating system even during a coolant temperature decrease at the engine stops.

Abstract: An engine and cabin thermal management system for use with a vehicle having an engine, a cabin heating system configured to thermally heat a cabin of the vehicle, a coolant system operably coupled to the engine and to the cabin heating system to thermally manage a temperature of the engine and a temperature of the cabin. The coolant system having one or more coolant thermal storage units fluidly coupled with a radiator and heater core of the coolant system forming a coolant loop. The system further having a control system configured to monitor and maintain at least a predetermined coolant temperature at the cabin heating system even during a coolant temperature decrease at the engine stops.

Abstract: Systems and methods for automatically generating at least one of facial expressions, body gestures, vocal expressions, or verbal expressions for a virtual agent based on emotion, mood and/or personality of a user and/or the virtual agent are provided. Systems and method for determining a user's emotion, mood and/or personality are also provided.

Abstract: There is provided a method for automatically determining an output utterance for a virtual agent based on output of two or more conversational interfaces. A candidate output utterance from each of the two or more conversational interfaces can be received, and one candidate output utterance from all received candidate outputs can be selected based on a predetermined priority factor. The selected utterance can be output by the virtual agent.

Abstract: Systems and methods for automatically generating at least one of facial expressions, body gestures, vocal expressions, or verbal expressions for a virtual agent based on emotion, mood and/or personality of a user and/or the virtual agent are provided. Systems and method for determining a user's emotion, mood and/or personality are also provided.

Abstract: A method for a virtual agent to process natural language utterances from a user is provided. The method can include receiving natural language utterance from the user, determining a type of the utterance, and based on the utterance type, determining an action for the virtual agent to take. The virtual agent can execute the action.

Abstract: Systems and methods for automatically generating at least one of facial expressions, body gestures, vocal expressions, or verbal expressions for a virtual agent based on emotion, mood and/or personality of a user and/or the virtual agent are provided. Systems and method for determining a user's emotion, mood and/or personality are also provided.