Waymo LLC

Daniella Gutlansky

Mishika Vora

Jonathan Lee Pedersen

Yu Zheng

Maria Moon

Salil Pandit

Clement Wright

Ganesh Balachandran

Amir Takhmar

Bruce Mai

Kevin Joseph Malta

Eric Friedman

Lauren Schwendimann

Sandra Lennie

Gaurav Agarwal

Jakob Robert Zwiener

Xu Dong

Eamonn Michael Doherty

Andrew Chan

Tiffany Washburn

Mingshen Chen

Trang Uyen Thien Tran

The technology involves pick-up and drop-off techniques for autonomous vehicles. Pullover selection options are evaluated by considering road user inconvenience and dynamic changes to such inconvenience. In response, a change in vehicle operation is made as needed. This process may consider whether a given situation is 'likely-inconvenient' or “unlikely-inconvenient” based on both statie and dynamic signals from the environment for a likely pick-up or drop-off location. The vehicle may request remote support to determine whether to pull over or to move from a stopped location, for instance based on changes to dynamic signals associated with other road users. In double parking situations, the vehicle may determine whether to remain double parked or move to limit inconvenience to a minimum number of other vehicles, such as by blocking as few other vehicles as possible or by making it as easy as possible for a parked vehicle to pull out.

Pick-up and drop-off signals for managing double parking obstruction

Aspects of the disclosure provide for selecting a pullover location for an autonomous vehicle. For instance, a set of potential pullover locations may be identified by, determining a plurality of rightmost points that the autonomous vehicle can reach, determining whether any of the rightmost points would result in the autonomous vehicle encroaching on a bicycle lane, and when any of the rightmost points encroaches on the bicycle lane, determining whether to adjust the location of that rightmost point. One of the set of potential pullover locations may be selected by assessing a cost of each potential pullover location of the set of potential pullover locations. The autonomous vehicle may be controlled to stop based on the selected one.

Pullovers involving bicycle lanes for autonomous vehicles

Aspects of the disclosure relate to evaluating quality of a predetermined pullover location for an autonomous vehicle. For instance, a plurality of inputs for the predetermined pullover location may be received. The plurality of inputs may each include a value representative of a characteristic of the predetermined pullover location. The plurality of inputs may be combined to determine a pullover quality value for the predetermined pullover location. The pullover quality value may be provided to a vehicle in order to enable the vehicle to select a pullover location for the vehicle.

Quality scoring for pullovers for autonomous vehicles

Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.

Evaluating pullovers for autonomous vehicles

The technology employs a holistic approach to passenger pickups and other wayfinding situations. This includes identifying where passengers are relative to the vehicle and/or the pickup location. Information synthesis from different sensors, agent behavior prediction models, and real-time situational awareness are employed to identify the likelihood that the passenger to be picked up is at a given location at a particular point in time, with sufficient confidence. The system can provide adaptive navigation by helping passengers understand their distance and direction to the vehicle, for instance using various cues via an app on the person's device. Rider support tools may be provided, which enable a remote agent to interact with a customer via that person's device, such as using the camera on the device to provide wayfinding support to enable the person to find their vehicle. Ride support may also use sensor information from the vehicle when providing wayfinding support.

Identifying a customer of an autonomous vehicle

Growing community of inventors

San Francisco, CA, United States of America

Daniella Gutlansky