Toyota Motor North America, Inc.

Devang H Parekh

Louis Brugman

Christopher J Risberg

Felipe G Salles

Robert D Slater

Nutonya Lynn Parker

Wilson-Boon Siang Khoo

Shintaro Iwaasa

Joshua C Batie

Aghyad Saleh

Christopher Ogden

An example operation may include one or more of detecting, by a parking processing node, a parking of a transport at an event location, accessing, by the parking processing node, a device of a transport occupant to determine a transport pickup location and a pickup time based on a conclusion of an event, detecting, by the parking processing node, from the device of the transport occupant at least one modification of the pickup location and the pickup time made based on an updated conclusion of the event, and sending a command to move the transport to a location proximate to the event based on the modified pickup location and the modified pickup time.

Transport relocation

An example operation may include one or more of receiving a software update at a transport of a subset of transports, validating the software update based on one or more of: a period of time when the software update is in use, and a number of utilizations of the software update by the subset of the transports, propagating the software update based on the validating, to a further subset of transports, wherein the further subset of the transports is larger than the subset of the transports.

Management of transport software updates

An example operation includes one or more of determining, by a server, that a transport is inoperable on a route, instructing, by the server, an alternate transport to navigate to the transport, configuring, by the server, the alternate transport based on a configuration of the transport and routing, by the server, the configured alternate transport to an intended destination of the transport.

Automatic alternate transportation

An example operation may include one or more of receiving a software update at a transport, performing a first validation of the software update in a first environment, wherein the first environment includes a least amount of potential interactions, and performing a further validation of the software update when the first validation is successful, in a further environment, wherein the further environment includes an amount of potential interactions greater than the first environment.

An example operation may include one or more of detecting a potential event via sensors on a transport, sending data related to the potential event to other transports within a predefined distance, storing the data at the transports and a server, and performing a transport operation response on the transports.

Vehicle-to-vehicle sensor data sharing

An example operation may include one or more of sending, by a master transport, a first portion of a software update to a transport of a first subset of transports, sending, by a master transport, a second portion of the software update to a transport of a further subset of transports, when a first transport of the subset of the transports and a second transport of the further subset of the transports are in proximity, causing the first transport to send the first portion of the software update to the second transport, and causing the second transport to send the second portion of the software update to the first transport.

An example operation includes one or more of detecting, by a server, a target transport operating in an unsafe manner, locating, the by the server, at least one autonomous transport in front of the target transport, and maneuvering the at least one autonomous transport to affect the target transport.

Control of transport en route

An example operation includes one or more of receiving, via a transport, a transport audio, classifying, via the transport, a subset of the transport audio as an atypical transport audio, determining, via the transport, a possible source location of the atypical transport audio, transmitting, via the transport, the atypical transport audio and the possible source location to a server, determining, via the server, a set of potential causes of the atypical transport audio and receiving, via the transport, the set of potential causes of the atypical transport audio.

Automatic warning of atypical audio indicating a transport event

An example operation includes one or more of determining, via a server, a dangerous area on a route of a transport, wherein the dangerous area is based on a new condition of an area, sending a notification to the transport, via the server, of the dangerous area and the new condition and performing, via the transport, at least one atypical action to traverse the dangerous area until a resolution of the new condition occurs, wherein the atypical action comprises one or more movements that do not typically occur on or around the dangerous area.

Automatic warning of navigating towards a dangerous area or event

An example operation includes one or more of determining automatically, by a processor based on data received from at least one sensor on a transport, a driving behavior associated with an operator of the transport over at least one first period of time as the operator's normal driving behavior, determining automatically by the processor a difference between the operator's normal driving behavior and a second driving behavior currently occurring over a second period of time as the operator's current driving behavior, and in the case the difference between the operator's normal driving behavior and the operator's current driving behavior indicates the operator's current driving behavior is unsafe, automatically guiding at least one of the operator and the transport to operate the transport in a safe driving behavior.

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Dallas, TX, United States of America

Devang H Parekh