Gm Global Technolgoy Operations, Inc.

Dhruv Patel

Joseph F Szczerba

Abbas Mohammed

Fahim Javid

Paul Edward Krajewski

Sai Vishnu Aluru

Ralph D Schlottke

Shiv G Patel

Rupesh S Kakade

Daniel S Glaser

Matthew S Zebiak

Karl Bo Albert Mikkelsen

Steven Aiuto

Kevin William Rypstra

Cynthia A Nicholson

David Alexander Hinz

Mutaz Keldani

A smart parking recommendation system for energy conservation in a vehicle includes a smart parking recommendation application (SPRA) that determines that enabling conditions have been met and obtains from sensors and actuators of the vehicle, information about the vehicle and the vehicle's environment. The SPRA monitors information from the sensors and actuators and obtained from remote computing resources, a vehicle operator's current vehicle usage and determines a typical parking duration for a current parking location, and categorizes the current parking location. The SPRA utilizes an artificial intelligence (AI) or machine learning (ML) model to suggest a parking spot within the parking location that satisfies user and energy consumption passenger compartment thermal quality preferences. The SPRA selectively parks or guides the vehicle to be parked within a parking spot that satisfies the constraints and preferences, and minimizes energy consumption for maintaining passenger compartment and battery thermal qualities.

Smart parking recommendation system for energy conservation

A system for detecting external leaks in a cabin of a vehicle includes sensors and onboard vehicle controls disposed on the vehicle. Control modules of the system have processors, memory, and input/output (I/O) ports. The I/O ports communicate with the sensors and onboard vehicle controls. The control modules execute program code portions stored memory. The program code portions include first and second algorithm portions. The first algorithm portion receives data from the sensors and controls and determines that the data from the sensors and controls meets initialization threshold values. When the data from the sensors and controls meets the threshold values, the second algorithm portion generates a cabin leak detection output including: a first output, a second output, or a third output. The first output indicates a large leak, the second output indicates no leak, and the third output indicates that a small leak has been detected.

Detection of external leaks utilizing cabin humidity model

A system and method of predicting a target vehicle entry into a side blind zone of an ADAS equipped vehicle and displaying a real-time alert to inform an operator or occupant of the ADAS equipped vehicle of the predicted target vehicle entry into the side blind zone. The system includes exterior sensors, interior sensors, an augmented reality rearview mirror, and a module. The module is configured to detect an object behind the ADAS equipped vehicle, predict a path of the object, determine a probability that the predicted path of the object will enter a side blind zone of the vehicle, and determine an entry of the object into the side blind zone of the vehicle when the probability exceeds a predetermined threshold.

System and method of predicting and displaying a side blind zone entry alert

A method for surveilling with a vehicle includes receiving an area-of-interest data from a vehicle user. The area-of-interest data delineates a virtual fence around the vehicle. The virtual fence is boundary of an area of interest around the vehicle. The vehicle is parked adjacent to an infrastructure. The method further includes receiving sensor data from a sensor of the vehicle that is monitoring the area of interest. Further, the method includes detecting a predetermined activity by a predetermined object of interest within the area of interest based on the sensor data received from the sensor of the vehicle. Also, the method includes notifying the vehicle user of the predetermined activity sensed using the sensor of the vehicle.

Vehicle surveillance system

Methods and systems are provided for controlling thermal conditioning of a battery system associated with brakes of a vehicle towing a trailer. In one embodiment, a method includes: determining, by a processor, that a temperature of the battery system is outside of a defined temperature range; determining, by the processor, a delta value between a brake request and a battery charge limit; generating, by the processor, a control signal to at least one of a heater and a compressor of the vehicle based on the delta value; generating, by the processor, a control signal to the battery system to initiate regeneration braking; and generating, by the processor, a braking reduction request to reduce braking by the trailer.

Methods and systems for enhanced thermal braking for electric vehicle applications

A method for classifying a weight of a vehicle includes determining a system enablement state of the vehicle load detection and classification system, monitoring a vehicle weight, determining a change in the vehicle weight, comparing the change in the vehicle weight to a first predefined weight change threshold, and categorizing the change in the vehicle weight in response to determining that the change in the vehicle weight exceeds the first predefined weight change threshold. The method also includes determining if a weight has been left in the vehicle after key-off and determining if a weight has been placed in a cargo compartment of the vehicle which exceeds the weight rating of the cargo compartment. The method also includes optimizing a route to a destination based at least on the change in the vehicle weight and displaying the optimized route to the destination using a human machine interface of the vehicle.

Dynamic vehicle weight classification for route optimization

A vehicle off-guard monitoring system includes an automobile vehicle having multiple sensor inputs capturing sensor data representing hazards including garage fires, excessive water or flooding, rain, snow, and at least one person loitering proximate to the automobile vehicle. A database has multiple saved images of the hazards. A computer compares the multiple saved images to the sensor data captured by the multiple inputs to identify if at least one match exists between any one of the multiple saved images of the hazards and the sensor data and when the at least one match exists generating a predefined warning signal. A smart-phone application in communication with the computer and a remote system signals the predefined warning signal to a user of the automobile vehicle to mitigate against damage occurring to the automobile vehicle.

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Oshawa, Canada

Dhruv Patel