Toyota Motor Engineering & Manufacturing North America, Inc.

Toyota Jidosha Kabushiki Kaisha

Other

Mcmaster University

Seyhan Ucar

Takamasa Higuchi

Onur Altintas

Kentaro Oguchi

Emrah Akin Sisbot

Chang-Heng Wang

Baik Hoh

Sergei S Avedisov

Yongkang Liu

Shalini Keshavamurthy

Tomohiro Matsuda

Rui Guo

Xuewei Qi

Toru Nakanishi

Haritha Muralidharan

Enes Krijestorac

Ahmed Hamdi Sakr

Hao Yang

Akihiko Yamamuro

Manali Sharma

Ryan Mercer

Emrah A Sisbot

Dylan J Lebedin

Systems and methods are provided for the classification of anomalies present in road regions. Anomalies may be extrinsic or intrinsic. Intrinsic anomalies may pose a greater safety risk to drivers than extrinsic anomalies. Intrinsic anomalies may be identified by detection of an evasive maneuver of a vehicle in a road region, measurement of the properties of other vehicles and the surrounding environment in the road region, determination of a vehicle behavior pattern in a road region, and comparison of the determined vehicle behavior pattern in the road region to other vehicle behavior patterns stored in a database.

Systems and methods for leveraging evasive maneuvers to classify anomalies

A parking assist system for a vehicle includes a processor and a memory communicably coupled to the processor. The memory stores instructions that when executed by the processor cause the processor to detect a parking space for a vehicle. The instructions further cause the processor to identify one or more parking parameters related to parking the vehicle in the parking space. The parking parameters include a point-of-interest associated with the parking space. The instructions further cause the processor to determine a suitability of the parking space based on the one or more parking parameters. Determining the suitability of the parking space includes predicting a point-of-interest-related action to be performed by an occupant after parking the vehicle in the parking space.

Parking assist system

System, methods, and other embodiments described herein relate to improving latency when establishing peer-to-peer connections between devices. In one embodiment, a method includes, responsive to determining that a connection is to be established with at least one remote vehicle by a subject vehicle, acquiring parameters, from a remote server, that define characteristics of the connection. The method includes performing device discovery and service discovery simultaneously by embedding information about available services within a communication for device discovery. The method includes establishing the connection between the subject vehicle and the at least one remote vehicle according to the parameters.

Systems and methods for efficiently establishing peer-to-peer connections

Systems and methods are provided for programmatically verifying an origin of abnormal driving. Some examples of abnormal driving may include aggressive driving (e.g., tailgating, cut-in lane, etc.), distracted driving (e.g., swerving, delayed reaction, etc.), and reckless driving (e.g., green light running, lane change without signaling, etc.). For example, the systems and methods may receive an identification of a second vehicle performing abnormal driving from an ego vehicle; initiate a verification process of the identification of the abnormal driving; access driving data associated with an origin of the abnormal driving, wherein the driving data includes the ego vehicle and the second vehicle; using the driving data, determine a confirm or deny decision regarding the identification of the second vehicle from the ego vehicle; and provide the confirm or deny decision.

Verification of the origin of abnormal driving

A method for detecting objects that are likely to fall from vehicle cargo includes obtaining first data of a cargo of a first vehicle captured at a first time and second data of the cargo captured by a second vehicle in an environment of the first vehicle at a second time after the first time, determining a first distance between two key points of the first data or a first shape constructed by key points of the first data and a second distance between two key points of the second data or a second shape constructed by key points of the second data, and detecting a movement of the cargo based on a comparison of the first distance and the second distance or a comparison of the first shape and the second shape.

Methods and systems for a detection of objects that are likely to fall from vehicle cargo

Systems and methods are provided for programmatically determining traffic management operations in response to conflicts on a roadway. For example, the systems and methods may determine a first traffic management instruction for a first vehicle for a first conflict on a roadway; access characteristics of the first vehicle associated with the first management instruction in response to the first conflict; determine a second conflict occurring after and connected to the first conflict; using the characteristics of the first vehicle, determine a second traffic management instruction for the first vehicle for the second conflict; and provide the second traffic management instruction to the first vehicle.

Traffic management after an initial conflict event

An example operation includes one or more of directing a group of connected vehicles to occupy one or more lanes approaching an intersection and notifying one of the connected vehicles to exit the group using another of the one or more lanes prior to the intersection.

Extending EV range through connected vehicles

Systems, methods, and other embodiments described herein relate to estimating the origins of abnormal driving through observed driving patterns. In one embodiment, a method includes detecting, using parallel computations, abnormal classifications associated with a subject vehicle and nearby vehicles according to driving patterns derived from observation data, the abnormal classifications being associated with exceeding a position range in the observation data. The method also includes estimating an origin of abnormal driving with happens-before analysis according to the abnormal classifications, and the abnormal driving is associated with deviations in a traffic flow associated with the subject vehicle and the nearby vehicles. The method also includes controlling the subject vehicle using a driving command according to the origin.

Systems and methods for estimating the origins of abnormal driving

A method according to some embodiments includes sensing, by a sensor set of the ego vehicle, a remote vehicle to generate sensor data describing driving behavior of the remote vehicle. The method further includes classifying a type of the remote vehicle based on the sensor data. The method further includes retrieving a behavior profile for the type of the remote vehicle that identifies criteria for the type of the remote vehicle and classifications of abnormal behavior and normal behavior based on the criteria. The method further includes comparing the behavior of the remote vehicle to the behavior profile for the type of the remote vehicle. The method further includes determining that the behavior of the remote vehicle is normal based on the comparing.

Detection of abnormal driving based on behavior profiles

The disclosure includes embodiments for a phantom system. A method according to some embodiments is executed by an onboard vehicle computer. The method includes generating a model of a driving behavior of a target vehicle based on sensor data describing the driving behavior and a roadway environment. The method also includes determining a graphic of a phantom vehicle based on the model. The method also includes causing an electronic display of an ego vehicle to depict the graphic as an element of a graphical user interface that depicts the graphic and an image of a remote vehicle that is following the ego vehicle. For example, the method includes generating graphical data describing the graphical user interface including the graphic and the image and providing the graphical data to the electronic display to cause the electronic display to depict the graphical user interface including the graphic and the image.

Generating and depicting a graphic of a phantom vehicle

Systems and methods are provided for detecting when a vehicle engages in anomalous driving behavior and managing nearby vehicles to mitigate risk to the nearby vehicles due to the anomalous driving behavior. According to some embodiments, the methods and systems comprise receiving an indication that an anomalous driving behavior of a first vehicle is detected, and identifying a plurality of vehicles within a geographic area of the first vehicle based on receiving the indication. The methods and systems further include generating an arrangement for the plurality of vehicles based on the detected anomalous driving behavior, determining a target speed for each of the plurality of vehicles based on the determined arrangement and a current speed of each of the plurality of vehicles, and communicating control messages to each of the plurality of vehicles. The control messages comprising the target speed to distribute the plurality of vehicles into the determined arrangement.

Systems and methods to manage drivers under abnormal driving

The disclosure includes embodiments for identifying an origin of abnormal driving behavior for improved vehicle operation. A method includes identifying an abnormal driving behavior of a driver of a vehicle at a time T. The method includes identifying a set of events that occurred within a predetermined time Δt before time T. The method includes executing, by a processor, a cause-and-effect analysis on the set of events to determine one or more events from the set of events that caused the abnormal driving behavior. The method includes executing a strategy to reduce the abnormal driving behavior so that vehicle operation is improved.

Identifying an origin of abnormal driving behavior for improved vehicle operation

A system for determining an identification of an occupant within a vehicle can include a processor, a communications interface, and a memory. The memory can store an information reception module, an identification prediction module, and an actuation module. The information reception module can cause the processor to receive, via the communications interface, from at least one sensor, and at a time when a source of a propulsion force for the vehicle is in an off state, at least one signal having information about at least one detectable characteristic associated with the occupant within the vehicle. The identification prediction module can cause the processor to produce, based on the information, a prediction of the identification of the occupant. The actuation module can cause the processor to cause, in response to a production of the prediction, a setting of a component of the vehicle to have a specific value.

Determining an identification of an occupant within a vehicle

System, methods, and other embodiments described herein relate to identifying connected vehicles through invoking maneuvers by vehicles that assist with distinguishing between safety messages having unassociated identifiers originating from the connected vehicles. In one embodiment, a method includes identifying surrounding vehicles including indeterminate vehicles from a driving environment using temporary identifiers received from the surrounding vehicles. The method also includes generating trajectories for the indeterminate vehicles. The method also includes distinguishing the indeterminate vehicles from communications using the temporary identifiers by observing execution of the trajectories by the indeterminate vehicles. The method also includes executing a planning task by a subject vehicle using safety information from the communications.

Systems and methods for identifying vehicles to communicate safety messages

The disclosure includes embodiments re-identification and revocation for misbehaving vehicle detection. A misbehaving vehicle is an example of an anomaly. A method includes receiving from a vehicular micro cloud, by a connected vehicle that is a member of the vehicular micro cloud, vehicular micro cloud data describing an anomaly and a first state of the anomaly in a geographic area. The method includes causing a sensor to record sensor data describing the geographic area. The method includes determining, based on the sensor data and the vehicular micro cloud data, whether the anomaly is still present and in the first state. The method includes generating evidence data describing a second state of the anomaly. The method includes transmitting the evidence data to the vehicular micro cloud. The method includes modifying an operation of the connected vehicle based on the evidence data.

Growing community of inventors

Mountain View, CA, United States of America

Seyhan Ucar