Bendix Commercial Vehicle Systems LLC

Valeo Schalter Und Sensoren Gmbh

Rm Acquisition, LLC

Other

Iteris, Inc.

Valeo Schalter Sensoren Gmbh

Andreas U Kuehnle

Hans M Molin

Cathy L Boon

Zheng Li

Marton Gabor Gyori

Shaun M Howard

Andre Tokman

Travis G Ramler

Karl H Jones

Jeffrey A Coleman

Huba Nemeth

Adam Szoellosi

Brendan E Buzer

Mark Muncy

Thomas J Hayes

Dilip Swaminathan

Robert Charnock

Ken D Au

Thomas S Legeza

Reza Khamsi

Eric E Bloam

Jeffrey S Lawson

Arturo M Guzman

Chandra Sekhar Gatla

Brendan Buzer

Robert G Charnock

Marton Gyori

A system and method for insight-triggered opportunistic imaging in a vehicle are provided. In one embodiment, a plurality of images are captured opportunistically using an image capture device in a vehicle. A compressive sensing sampling technique is used to store a subset of image pixels of at least some of the plurality of images. A retention filter is applied to the plurality of images to select a subset of the plurality of images to retain based on a signal from a sensor in the vehicle. The retained image information can be sent to an entity external to the vehicle for processing.

System and method for insight-triggered opportunistic imaging in a vehicle

A vehicle-based safety intervention system receives sensor data collected or generated by an onboard computing system of a vehicle. The sensor data is divided into a plurality of blocks, each of the blocks having a duration. A driver behavioral model is applied to one or more of the plurality of blocks to generate one or more driver behavioral parameters. A trend of the one or more driver behavioral parameters is extracted from the plurality of blocks. Based on the extracted trend, it is determined that a driver's performance when operating the vehicle is unsatisfactory or will be unsatisfactory in the future. A vehicle-based intervention is generated based on the determination that the driver's performance is unsatisfactory or will be unsatisfactory in the future.

Vehicle-based intervention based on modeling driver performance

Each of a plurality of on-vehicle event detection systems generate vehicle event datasets characterizing detected vehicle events, while each of one or more off-vehicle driver log-in/log-out devices generate at least one of: a driver log-in event dataset characterizing a detected driver log-in event, and a driver log-out event dataset characterizing a detected driver log-out event, wherein each driver log-in and driver log-out event is for a respective driver. A database stores the event datasets for retrieval by a linking module. The linking module analyzes two or more of the event datasets, and associates one or more vehicle events with one or more of the respective drivers based on the retrieved event datasets. A vehicle control module generates and transmits a control signal for controlling a vehicle system based on the association.

Post-work-shift driver to vehicle event association for controlling vehicle functions based on monitored driver performance

A system for identifying a change in the operator of a vehicle includes a controller configured to determine, during operation of the vehicle by a current operator of the vehicle over a period of time, a plurality of values for at least two variables associated with the current operator. The controller correlates the values for the two variables to form a plurality of data points which together form a point cloud associated with the current operator. The controller performs a comparison of the point cloud to a point cloud stored in a memory and associated with a prior operator of the vehicle and determines, responsive to the comparison, whether the current operator of the vehicle is the prior operator of the vehicle.

System and method for identifying a change in the operator of a vehicle

A system for opportunistic imaging includes an imaging device that generates data comprising a plurality of sequential image frames. The system also includes a control module that causes the imaging device to generate standard-resolution image frames at a standard-frame rate and a standard-resolution, such that there is a processing time lull between the generation of sequential standard-resolution image frames. The control module also causes the imaging device to generate one or more burst-resolution image frames at a burst-frame rate and a burst-resolution within the processing time lull.

System and method for opportunistic imaging

A system and method for monitoring a driver's operation of a vehicle and automatically providing a lesson to a driver based on the driver's operation are provided. Input data generated by an onboard vehicle computing system specifying actions taken by the driver while operating the vehicle are received. Based on the input data, a determination is made whether a driving event has occurred that requires the lesson to be output to the driver. The driving event is analyzed based on threshold data stored in the memory, and based on the results of the analysis of the driving event one or more lessons are automatically output to the driver. Additionally, the driver's completion of the lesson can be monitored, and subsequent instances of the driver's operation of the vehicle may include controlling movement of the vehicle based on the results of the analysis of the driving event.

Automatic teaching device

A fleet management server includes a memory and a processor. The processor is configured to: receive past event data associated with at least one vehicle and at least one driver, the past event data representing at least one respective past vehicle event that occurred when one of the drivers was driving one of the vehicles; receive respective predetermined classifications of the past vehicle events that were previously manually assigned based on respective contemporaneous videos of the past vehicle events; receive novel event data representing at least one respective novel vehicle event; automatically assign respective ones of the predetermined classifications to the novel vehicle events based on the previous manually assigned classifications to the past vehicle events; and output, to a user of the fleet management server, the respective automatically assigned predetermined classifications of the novel vehicle events.

Automatic event classification

Vehicle fleet management includes processing event-based data corresponding to detected events to generate event data sets that include: at least video corresponding to the event and data identifying an event-type for the event. One or more pedagogical event pairs are identified, each of which includes a first event data set reflecting a 'good' response to an event-type and a second event data set reflecting a “bad” response to the event-type. At least one cluster of drivers having similar occurrence rates for the event-type is identified. One or more training lessons are generated for the cluster based on the event type, which training lessons include at least the video of the first event data set and the video of the second event data set. The training lessons are administered to a driver of the cluster via a computing device. The autonomous control of one or more vehicle systems is instituted based on the administered training lessons.

Systems and methods for automated vehicle fleet management according to dynamic pedagogical behavior reinforcement

A system for controlling a vehicle based on a driving style determined driver identity includes sensors that capture driving-style-based data characterizing a driving style of an unknown driver. The system also includes a control unit that determines a driving style vector of the unknown driver from the captured driving-style-based data. The control unit compares the driving style vector of the unknown driver to driving style vectors of a plurality of known drivers to generate a similarity score for each of the plurality of known drivers. The control unit ranks the plurality of known drivers according to their respective similarity scores, and identifies the unknown driver as at least one of the ranked known drivers based on the respective similarity scores. The control unit controls vehicle systems based on the identification of the unknown driver.

System and method for driving style driver identity determination and control of vehicle functions

A control device for a recorder in an associated vehicle includes a processor and an input port operatively coupled with the processor. The input port receives a parking brake status signal comprising parking brake data representative of a parking brake status. A non-transient memory device is operatively coupled with the processor. The non-transient memory device stores parking brake status data representative of whether the parking brake is engaged. Control logic stored in the non-transient memory device is executable by the processor to: determine a parking brake status as engaged based on the parking brake data. An output port is operatively coupled with the processor. The output port transmits a recording control signal enabling the recording based on the determined parking brake status.

System and method for controlling a driver facing camera

The system assigns a plurality of drivers to one or more identified routes. An onboard computing system of a vehicle collects or generates a plurality of vehicle events, which are received at a server via a network. The onboard computing system includes a plurality of sensors and subsystems that are connected to monitor various vehicle components, such as braking, steering, and radar, as well as one or more cameras. A difficulty of each of the identified routes is characterized based on the plurality of vehicle events. A performance of each driver is characterized based on a subset of the plurality of vehicle events collected or received from the vehicle of each driver.

Identifying driver and route characteristics based on vehicle data

A fleet management server is configured to receive, via a wireless transceiver, driver and vehicle information from a plurality of vehicles relating to a plurality of drivers. The server computes, based on the received driver and vehicle information, occurrence rates for predetermined vehicle events and predetermined vehicle error codes that are associated with possible vehicle tampering, and then compares, based on the received driver and vehicle information, an occurrence rate for the predetermined vehicle events and predetermined vehicle error codes of a first driver to occurrence rates for the predetermined vehicle events and predetermined vehicle error codes of one or more of the other plurality of drivers. The server is further configured to determine, based on a result of said comparing, a tampering indicator for the first driver, and to output, to a user of the fleet management server, a confidence level that the first driver has tampered with at least one information component of at least one vehicle of the plurality of vehicles based at least in part on the tampering indicator.

System and method for detecting driver tampering of vehicle information systems

Systems and methods monitor driver behavior for vehicular fleet management in a fleet of vehicles using driver-facing imaging device. The systems and methods herein relate generally to vehicular fleet management for enhancing safety of the fleet and improving the performance of the fleet drivers, and further relate to monitoring the operation of fleet vehicles using one or more driver-facing imaging devices disposed in the fleet vehicles for recording activities of the fleet drivers and their passengers, storing information relating to the monitored activities, selectively generating warnings related to the monitored activities, and reporting the monitored activities to a central fleet management system for use in enhancing the safety of the vehicles of the fleet and for helping to improve the performance of the fleet drivers.

System and methods of monitoring driver behavior for vehicular fleet management in a fleet of vehicles using driver-facing imaging device

A system for recording vehicle occupants and their immediate environment includes a driver-facing camera for capturing video data, an input that receives data from one or more sensors configured to detect vehicle related data and a processor. The processor is configured to embed, based on the sensor data, at least one indicator in a portion of the video data. The indicator designates that the portion of the video data is to be obscured during playback of the video data.

System and method for adjusting recording modes for driver facing cameras

A calibration apparatus and method are provided for a surround-view camera system having a plurality of cameras mounted to an object (e.g., a vehicle). A plurality of markers are arbitrarily placed around the object and configured to measure a plurality of distances between one another. From at least one image from one or more cameras, a controller is configured to visually identify at least two markers which define a coordinate system. Based on the measured plurality of distances between markers and the visually identified markers, the controller generates calibration information as an output, saved in the form of a look-up table, which will be retrieved and used when a display device generates a bird's-eye view for a viewer.

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Villa Park, CA, United States of America

Andreas U Kuehnle