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公开(公告)号：US11532188B2
公开(公告)日：2022-12-20
申请号：US16548166
申请日：2019-08-22
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Arun Adiththan , Praveen Palanisamy , SeyedAlireza Kasaiezadeh Mahabadi , Ramesh S
Abstract: A vehicle and a system and method for operating a vehicle. The system includes a state estimator and a processor. A detected value of a parameter of the vehicle is determined using sensor data obtained by in-vehicle detectors. The processor determines a check value of the parameter based on crowdsourced data, validates the detected value of the parameter based on the check value of the parameter, and operates the vehicle based on the validation.
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公开(公告)号：US20200050207A1
公开(公告)日：2020-02-13
申请号：US16059403
申请日：2018-08-09
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Marcus J. Huber , Praveen Palanisamy
Abstract: Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a plurality of encoded context2vec AV words in a sequence of timing to embed data of context and behavior; a set of inputs which comprise: at least one of a current, a prior, and a subsequent encoded context2vec AV word; a neural network solution applied by the at least one computer to determine a target context2vec AV word of each set of the inputs based on the current context2vec AV word; an output vector computed by the neural network that represents the embedded distributional one-hot scheme of the input encoded context2vec AV word; and a set of behavior control operations for controlling a behavior of the AV.
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公开(公告)号：US10474149B2
公开(公告)日：2019-11-12
申请号：US15680599
申请日：2017-08-18
Applicant: GM Global Technology Operations LLC
Inventor： Praveen Palanisamy , Upali P. Mudalige
Abstract: An autonomous vehicle, a system and method of operating the autonomous vehicle. An environmental sensor obtains one or more parameters of external agents of the vehicle. A processor of the vehicle obtains a route having a destination at the autonomous vehicle, builds a Markov state model of the route that includes a plurality of states for the autonomous vehicle and one or more parameters of the external agents, generates a plurality of driving policies for navigating the route, selects a policy for navigating the route from the plurality of driving policies using a Markov Decision Process, and executes the selected policy at the autonomous vehicle to navigate the vehicle along the route towards the destination.
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公开(公告)号：US20200293041A1
公开(公告)日：2020-09-17
申请号：US16354522
申请日：2019-03-15
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Praveen Palanisamy
Abstract: A system and method for determining a vehicle action to be carried out by an autonomous vehicle based on a composite behavior policy. The method includes the steps of: obtaining a behavior query that indicates which of a plurality of constituent behavior policies are to be used to execute the composite behavior policy, wherein each of the constituent behavior policies maps a vehicle state to one or more vehicle actions; determining an observed vehicle state based on onboard vehicle sensor data, wherein the onboard vehicle sensor data is obtained from one or more onboard vehicle sensors of the vehicle; selecting a vehicle action based on the composite behavior policy; and carrying out the selected vehicle action at the vehicle.
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公开(公告)号：US20200033868A1
公开(公告)日：2020-01-30
申请号：US16048144
申请日：2018-07-27
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Praveen Palanisamy , Upali P. Mudalige
Abstract: Systems and methods are provided autonomous driving policy generation. The system can include a set of autonomous driver agents, and a driving policy generation module that includes a set of driving policy learner modules for generating and improving policies based on the collective experiences collected by the driver agents. The driver agents can collect driving experiences to create a knowledge base. The driving policy learner modules can process the collective driving experiences to extract driving policies. The driver agents can be trained via the driving policy learner modules in a parallel and distributed manner to find novel and efficient driving policies and behaviors faster and more efficiently. Parallel and distributed learning can enable accelerated training of multiple autonomous intelligent driver agents.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20190286151A1
公开(公告)日：2019-09-19
申请号：US15920810
申请日：2018-03-14
Applicant: GM Global Technology Operations LLC
Inventor： Praveen Palanisamy , Sayyed Rouhollah Jafari Tafti , Soheil Samii , Marcus J. Huber
Abstract: Presented are scenario-planning and route-generating distributed computing systems, methods for operating/constructing such systems, and vehicles with scenario-plan selection and real-time trajectory planning capabilities. A method for controlling operation of a motor vehicle includes determining vehicle state data, such as a current position and velocity of the vehicle, and path plan data, such as an origin and desired destination of the vehicle. A remote computing node off-board from the motor vehicle generates a list of trajectory plan candidates based on the vehicle state data, the path plan data, and current road scenario data. The remote computing node then calculates a respective travel cost for each candidate in the trajectory plan candidates list, and sorts the list from lowest to highest travel cost. The candidate with the lowest travel cost is transmitted to a resident vehicle controller. The vehicle controller executes an automated driving operation based on the received trajectory plan candidate.
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公开(公告)号：US20190066502A1
公开(公告)日：2019-02-28
申请号：US15685360
申请日：2017-08-24
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Xinyu Du , Praveen Palanisamy , Bo Yu , Prathap Venugopal , Tian Ni , Vivek Vijaya Kumar , Paul E. Krajewski
Abstract: A system and method for assisting vehicle parking is disclosed. The method includes transmitting, by an electronic controller of a vehicle, a parking space request. The parking space request is transmitted to a reservation system. The reservation system determines whether a parking space is available to fulfill the parking space request. The determining is based on availability information that is received from a parking infrastructure. The method also includes receiving an indication. The indication indicates whether a parking spot has been reserved to fulfill the parking space request.
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公开(公告)号：US20210074162A1
公开(公告)日：2021-03-11
申请号：US16564550
申请日：2019-09-09
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Sayyed Rouhollah Jafari Tafti , Pinaki Gupta , Syed B. Mehdi , Praveen Palanisamy
IPC: G08G1/16 , B60W30/12 , B60W30/09 , B60W40/04 , B60W30/02 , B62D15/02 , B60W30/095 , B60W30/18 , B60W10/20 , G05D1/02
Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a processor, that a lane change is desired; determining, by the processor, a lane change action based on a reinforcement learning method and a rule-based method, wherein each of the methods evaluates lane data, vehicle data, map data, and actor data; and controlling, by the processor, the vehicle to perform the lane change based on the lane action.
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公开(公告)号：US10678252B2
公开(公告)日：2020-06-09
申请号：US16059403
申请日：2018-08-09
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Marcus J. Huber , Praveen Palanisamy
Abstract: Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the AV; a plurality of encoded context2vec AV words in a sequence of timing to embed data of context and behavior; a set of inputs which comprise: at least one of a current, a prior, and a subsequent encoded context2vec AV word; a neural network solution applied by the at least one computer to determine a target context2vec AV word of each set of the inputs based on the current context2vec AV word; an output vector computed by the neural network that represents the embedded distributional one-hot scheme of the input encoded context2vec AV word; and a set of behavior control operations for controlling a behavior of the AV.
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公开(公告)号：US10678241B2
公开(公告)日：2020-06-09
申请号：US15696670
申请日：2017-09-06
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Praveen Palanisamy , Upali P. Mudalige
Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a computer-implemented method includes: training an autonomous driving agent is provided, the method including the steps of: extracting, by a processor, information from demonstrations of driving behavior using a neural network; transmitting the extracted information to a generator module; transmitting a real environmental state associated with the demonstrations of driving behavior to a discriminator module; generating, by a processor, environmental state interpretations from the extracted information using the generator module; training, by a processor, the discriminator module to better determine whether the generated environmental state interpretations correspond to the real environmental state, whilst training, by a processor, the generator module to generate an improved environmental state interpretation that the discriminator determines to correspond to the real environmental state; and recovering, by a processor, a reward map using generated environmental state interpretations from the trained generator module.
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