Toyota Jidosha Kabushiki Kaisha

Other

Toyota Motor Engineering & Manufacturing North America, Inc.

Denso Corporation

Toyota Motor Engineering & Manufacturing N.a. Inc.

Emrah Akin Sisbot

Kentaro Oguchi

Seyhan Ucar

Yusuke Nakano

Yongkang Liu

Eric Martinson

Akansel Cosgun

Tomohiro Matsuda

Xiaofei Cao

Takamasa Higuchi

Veera Ganesh Yalla

Haritha Muralidharan

Takuya Hasegawa

Yashar Zeiynali Farid

Veeraganesh Yalla

Hirokazu Nomoto

Yutaka Takaoka

Halit Bener Suay

Xuewei Qi

Rahul Parundekar

David Kim

John Mark Agosta

Joseph Djugash

Young-Ho Kim

Hangquan Zhao

Systems and methods are provided for the reduction or elimination of redundant, uninteresting, and/or inefficient communications to remote devices (e.g. cloud servers) from vehicles collecting observation data. In-vehicle examples of the systems and methods are provided, wherein the associated methods for reducing or eliminating such redundant, uninteresting, and/or inefficient communications are performed on a vehicle. Cloud-based examples of the systems and methods are provided, wherein the associated methods for reducing or eliminating such redundant, uninteresting, and/or inefficient communications are performed on a remote device (e.g. a cloud server).

Selective information gathering system for multiple vehicles

Embodiments of systems and methods for adapted vehicle geometry include a vehicle and one or more processors. The vehicle includes a camera operable to generate an image of an environment surrounding the vehicle. The environment includes a parking space and an object removably attached to the vehicle. The one or more processors operable to identify the object as attached to the vehicle, generate, using a pre-trained depth algorithm, a depth map based on the image, generate a boundary of the parking space and a boundary of the vehicle combined with the object based on the depth map, determine whether a distance between the boundary of the parking space and the boundary of the vehicle combined with the object is less than a threshold value, and output an alert in response to determining that the distance is less than the threshold value.

Systems and methods of visual sonar for adapted vehicle geometry

Systems, methods, and vehicles for classifying driving behavior of a target vehicle are provided. The systems include a controller programmed to identify a target vehicle associated with a pseudo-id, obtain a first tag representing first driving behavior of the target vehicle during a first period of time along with the pseudo-id based on first motion data of the target vehicle, obtain a second tag representing second driving behavior of the target vehicle during a second period of time along with the pseudo-id based on second motion data of the target vehicle, the second period of time being after the first period of time, and classify driving behavior of the target vehicle based on interpretation of the first tag and the second tag.

Systems, methods, and vehicles for classifying driving behavior of a target vehicle

A method may include receiving driving data from a plurality of vehicles within a sampling region. The driving data may include speeds, positions, and lane change activity of the plurality of vehicles. The method may further include determining speeds of the plurality of vehicles based on the driving data. The method may further include performing cluster analysis on the speeds of the plurality of vehicles. The method may further include determining whether the speeds of the plurality of vehicles comprise more than one cluster based on the cluster analysis. Upon determination that the speeds of the plurality of vehicles comprise more than one cluster, the method may include determining that lane-level traffic is present within the sampling region.

Detecting lane-level traffic using connected vehicle data without lane identification information

Systems and methods described herein relate to configuring a hierarchical traffic management system. One embodiment receives, at a cloud server, a request from an application, the request including requirements and implicating configuration of a hierarchical traffic management system; determines, based on information received from one or more connected vehicles in an area of interest pertaining to the request, a minimum density of connected vehicles in the area of interest to meet the requirements; calculates an optimum number of connected vehicles to assign to a section manager in the hierarchical traffic management system; calculates the size of a section of the roadway to be managed by the section manager in the area of interest based, at least in part, on the minimum density of connected vehicles and the optimum number of connected vehicles; and activates the hierarchical traffic management system in accordance with the calculated size of the section.

Systems and methods for configuring a hierarchical traffic management system

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

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

Systems and methods are provided for generating a real-time lane-level traffic map based on outbound sensor information. In particular, some embodiments generate lane-level traffic maps using radar sensor information. The populated real-time lane-level traffic maps are shared to other vehicles and may be used by autonomous vehicle systems to maneuver the vehicle.

System and method to generate a lane-level traffic map using vehicle sensor data

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

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

Systems and methods are provided for estimating the energy range of an electric vehicle, including updating an energy consumption estimation model based on the location of a vehicle or based on the current time. One embodiment comprises obtaining a route of a vehicle and deploying an energy consumption estimation model to provide an energy consumption estimate along the route from a first location to a destination. In response to determining that the vehicle enters a subsequent location, the energy consumption estimation model is updated with a location model received from an edge/cloud server, to estimate an energy range along the route through the subsequent location.

Customized electrical vehicle range estimation system based on location and driver

Systems include a controller programmed to instruct a sensor to detect an object in an environment of a vehicle in response to an activation of a fall-on-car prevention function, determine a first value of a parameter pertaining to the object at a first time with the sensor, determine a second value of the parameter pertaining to the object at a second time with the sensor, and automatically cause an action to occur based on a comparison of the first value of the parameter and the second value of the parameter.

Growing community of inventors

Mountain View, CA, United States of America

Emrah Akin Sisbot