Nissan North America, Inc.

Renault S.a.s.

Sachin Hagaribommanahalli

Christopher Ostafew

David Ilstrup

Atsuhide Kobashi

Qizhan Tam

Therese Cypher-Plissart

Thiago Aguiar

Categorizing driving behaviors of other road users includes maintaining a first history of first lateral-offset values of a road user with respect to a center line of a lane of a road; determining a first pattern based on the first history of the first lateral-offset values; determining a driving behavior of the road user based on the first pattern; and autonomously performing, by a host vehicle, a driving maneuver based on the driving behavior of the road user. The first history can be maintained for a predetermined period of time. An apparatus includes a processor that is configured to track a trajectory history of a road user; determine, based on the trajectory history, a driving behavior of the road user; and transmit a notification of the driving behavior.

Road user categorization through monitoring

Detecting prediction errors includes detecting a road user; determining respective predicted data for the road user; storing, in a data structure, the respective predicted data; storing, in the data structure, actual data of the road user; obtaining an average prediction displacement error using at least one of the actual data and at least two corresponding respective predicted data; and determining a prediction accuracy based on the average prediction displacement error. Detecting map errors includes detecting a road user; storing, in a data structure, actual data of the road user; storing, in the data structure, map data corresponding to the actual data; obtaining an average map displacement error based on a comparison of at least some of the actual data and corresponding at least some map data; and determining a map accuracy based on the average map displacement error.

Autonomous vehicle control and map accuracy determination based on predicted and actual trajectories of surrounding objects and vehicles

A method of controlling an electric vehicle includes operating the vehicle in accordance with a current pedal map. A plurality of alternative pedal maps is defined. A variance for each of the plurality of alternative pedal maps is determined. Operation of the vehicle is switched from the current pedal map to one of the alternative pedal maps based on the determined variance.

Pedal control system and method for an electric vehicle

An apparatus for traveling through a transportation network performs a method including generating a display that includes a geographical area about a starting location for route assistance through the transportation network and a virtual vehicle at the starting location, and forming a virtual path for the route assistance using the virtual vehicle. The virtual path includes a first portion obtained from advancing the virtual vehicle from the starting location while an autonomous vehicle (AV) is at the starting location and a second portion obtained from, after the virtual vehicle departs from the starting location, extrapolating from the virtual vehicle through the geographical area to a stopping location or an ending location of the route assistance. Points along the virtual path are continually transmitted to a trajectory planner of the AV while the virtual vehicle advances through the geographical area, and the trajectory planner generates a route for the AV conforming to the virtual path.

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Sunnyvale, CA, United States of America

Sachin Hagaribommanahalli