公开(公告)号：US11131992B2

公开(公告)日：2021-09-28

申请号：US16206506

申请日：2018-11-30

Applicant: DENSO International America, Inc. ,  Sriram Subramanian ,  Sushrut Bhalla ,  Jaspreet Sambee ,  Mark Crowley ,  Sebastian Fischmeister ,  Donghyun Shin ,  William Melek ,  Baris Fidan ,  Ami Woo ,  Bismay Sahoo

Inventor： Zhiyuan Du ,  Joseph Lull ,  Rajesh Malhan ,  Sriram Subramanian ,  Sushrut Bhalla ,  Jaspreet Sambee ,  Mark Crowley ,  Sebastian Fischmeister ,  Donghyun Shin ,  William Melek ,  Baris Fidan ,  Ami Woo ,  Bismaya Sahoo

IPC: G05D1/00 ,  G05D1/02 ,  G06N3/04 ,  G06N3/08

Abstract: A RLP system for a host vehicle includes a memory and levels. The memory stores a RLP algorithm, which is a multi-agent collaborative DQN with PER algorithm. A first level includes a data processing module that provides sensor data, object location data, and state information of the host vehicle and other vehicles. A second level includes a coordinate location module that, based on the sensor data, the object location data, the state information, and a refined policy provided by the third level, generates an updated policy and a set of future coordinate locations implemented via the first level. A third level includes evaluation and target neural networks and a processor that executes instructions of the RLP algorithm for collaborative action planning between the host and other vehicles based on outputs of the evaluation and target networks and to generate the refined policy based on reward values associated with events.

公开(公告)号：US10300894B2

公开(公告)日：2019-05-28

申请号：US15456880

申请日：2017-03-13

Applicant: DENSO International America, Inc. ,  DENSO CORPORATION

Inventor： Zaydoun Rawashdeh ,  Rajesh Malhan ,  Trong Duy Nguyen ,  Anoop Pottammal

IPC: B60T7/12 ,  B60T8/172 ,  G06K9/00 ,  B60T7/18 ,  B60T7/22 ,  G06K9/46 ,  G06K9/62

Abstract: The present disclosure provides an auto-braking system which includes a braking device, a receiver, and a controller. The controller includes a determining portion, a verifying portion and an executing portion. The determining portion determines whether a vehicle will violate a red signal of the traffic light based on the traffic light state information. The verifying portion verifies the traffic light state information is valid by comparing the traffic light state information with the image of the traffic light captured by the sensor. The executing portion executes a first braking control to slow the vehicle at a first deceleration rate when the determining portion determines that the vehicle will violate a red signal. The executing portion executes a second braking control to slow the vehicle at a second deceleration rate to stop at a specified position when the verifying portion verifies that the traffic light state information is valid.

公开(公告)号：US20240274000A1

公开(公告)日：2024-08-15

申请号：US18506352

申请日：2023-11-10

Applicant: Denso International America, Inc.

Inventor： Rajesh Malhan ,  Mahdi Bandegi ,  Patrick Bodun ,  Oscar Crowley

IPC: G08G1/01 ,  G06N3/0464

CPC classification number: G08G1/0133 ,  G06N3/0464 ,  G08G1/0116 ,  G08G1/0129 ,  G08G1/0145

Abstract: Systems, methods, and other embodiments described relate to estimating a traffic pattern using learning models that process data from road sensors that are sparse. In one embodiment, a method includes forming multi-channel data from partial data and timing data about traffic on a road, the partial data acquired from road sensors. The method also includes generating an adjacency matrix from the partial data and geometry about the road. The method also includes training a graph model using temporal patterns for graph nodes from the multi-channel data and the adjacency matrix to complete the partial data and output a traffic pattern estimate.

公开(公告)号：US11210937B2

公开(公告)日：2021-12-28

申请号：US16525800

申请日：2019-07-30

Applicant: DENSO International America, Inc.

Inventor： Rajesh Malhan ,  Joseph Lull

IPC: G08G1/01 ,  G08G1/07

Abstract: The present disclosure is directed toward a method that includes acquiring current dynamic characteristics of a moving object about an un-signalized intersection, determining a dynamic traffic flow of the un-signalized intersection based on the current dynamic characteristics to determine a position of the moving object about the un-signalized intersection, and predicting future dynamic characteristics of the moving object based on the dynamic traffic flow and a predictive control. The future dynamic characteristics includes a predicted position of the moving object at a predefined time in the future. The method further calculates an entry parameter for a vehicle about an entrance of the un-signalized intersection based on the dynamic traffic flow and the predicted future dynamic characteristics and notifies the vehicle of the entry parameter.

公开(公告)号：US20200233060A1

公开(公告)日：2020-07-23

申请号：US16519583

申请日：2019-07-23

Applicant: Denso International America, Inc.

Inventor： Joseph C. Lull ,  Rajesh Malhan

IPC: G01S7/40 ,  G01S13/93

Abstract: A sensor data anomaly detection system for a vehicle includes one or more processors and a memory in communication with the one or more processors that stores an anomaly detection module and an anomaly correction module. The anomaly detection module causes the one or more processors to analyze one or more signals from at least one sensor of the vehicle for at least one potential anomaly and compare correlating information from one or more external sources to the at least one potential anomaly to confirm when the potential anomaly is an actual anomaly The anomaly correction module causes the one or more processors to correct the actual anomaly in the one or more signals to generate a corrected signal when the actual anomaly is present.