US 11,657,318 B2
Assessing ride quality for autonomous vehicles
Ioan-Alexandru Sucan, Mountain View, CA (US); Fang Da, Sunnyvale, CA (US); Poonam Suryanarayan, San Francisco, CA (US); Nathaniel Fairfield, Mountain View, CA (US); Yutaka Leon Suematsu, Mountain View, CA (US); Omer Baror, Mountain View, CA (US); Jian Leong, Mountain View, CA (US); and Michael Epstein, Danville, CA (US)
Assigned to Waymo LLC, Mountain View, CA (US)
Filed by Waymo LLC, Mountain View, CA (US)
Filed on Dec. 10, 2018, as Appl. No. 16/214,991.
Claims priority of provisional application 62/747,815, filed on Oct. 19, 2018.
Prior Publication US 2020/0125989 A1, Apr. 23, 2020
Int. Cl. G06N 20/00 (2019.01); B60W 50/00 (2006.01); G05D 1/02 (2020.01)
CPC G06N 20/00 (2019.01) [B60W 50/0098 (2013.01); G05D 1/0276 (2013.01); G05D 2201/0213 (2013.01)] 19 Claims
OG exemplary drawing
1. A method of training a model for identification of events likely to cause discomfort to passengers of autonomous vehicles, the method comprising:
receiving, by one or more server computing devices, first ride data identifying a first output from a planner system and a second output from a perception system, the first ride data being associated with a ride quality value indicating a level of discomfort identified by a passenger of an autonomous vehicle during a first ride, wherein the first ride data further includes information about locations and types of road users other than the autonomous vehicle; and
training, by the one or more server computing devices, the model using the first ride data and any associated ride quality values such that the model is configured to, in response to receiving second ride data for a second ride as input, output a list of events that occur in the second ride that are likely to cause discomfort to one or more passengers during the second ride.