Steering Behaviors for Autonomous Vehicles in Virtual Evironments

Hongling Wang

Joseph K. Kearney

James Cremer

Department Of Computer Science

University of Iowa

Peter Willemsen

School of Computing

University of Utah

Focus• Control of Autonomous Vehicles in VE

– Ambient traffic– Principal roles in scenarios

• Importance of Road Representation– Frame of reference– Natural coordinate system

• Intersection and Lane Changing Behaviors– Complex interactions among vehicles

• Limits of independent control

Motivation• VE as Laboratories for Studying Human Behavior

– Developmental differences in road crossing– The influence of disease, drugs, and disabilities– Design of in-vehicle technology

• Cell phones, navigation aids, collision warning

Bicycle Simulator Video

Gap Acceptance in the Hank Bicycle Simulator

Related Work

• Flocking– Complex group behavior from simple rule-based behaviors

(Reynolds)

• Hierarchical Distributed Contol– Independent, goal-oriented sub-behaviors (Badler et al.; Blumberg

and Galyean; Cremer, Kearney, and Papelis)

• Driving– Simulation (Donikian; Lemessi)

– ALV (Coulter, Sukthankar; Wit, Crane, and Armstrong)

– Human Driving Behavior (Ahmed; Boer, Kuge, and Yamamura; Fang, Pham, and Kobayashi; Salvucci and Liu)

Roadway Modeling• Roads as Ribbons

– Oriented Surface

– Smooth Strips

– Twist and turn in space

• Central Axis– Arc-length parameterized curve

• Twist Angle• Linked through Intersections

Ribbon• Ribbon coordinate system

– Distance, Offset, and loft (D,O,L)

• Egocentric frame of reference• Efficient Mapping (D,O,L) (X,Y,Z)

Intersections—Where Roads Join

• Shared regions• Non-oriented• Corridors connect incoming and outgoing lanes

– Single lane ribbons– Annotated with right-of-way rules

Ribbon to Ribbon Transitions• Problem: Tangle of Ribbons

Bookkeeping Tedious and Error Prone• Possible switch in orientation• Possible shift in alignment

• Solution: Paths • Composite ribbons

Path

• One-lane Overlay– Removes transitions

between ribbons

• Immediate Plan of Action- Highly dynamic- Natural frame of reference

Distributed Control

• Multiple, Independent Controllers– Each responsible for some aspect of behavior

• e.g. Cruising, Following

– Compete for control

• Control Parameters– Acceleration– Steering Angle

Road Tracking

• Non-holonomic constraint

Rolling wheels

Move on a circle

• Pursuit point control– Steer to a point on the path– Look-ahead distance

Controlling Speed

• Cruising: Proportion Control

• Following: Proportional Derivative Controller

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Intersection Behavior Gates access to shared regions

– Decision:

Go / No Go– Action:

stop at stopline

Gap Acceptance Based on Interval Analysis

– Right-of-way rules encoded in DB– Corridors as resources

Compare crossing intervals

time

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Intersection Exceptions Problem: deadlock

Double blocked threats• Solution:

Recognition and response

Problem: starvationUnending stream of opposition

• Solution: Guaranteed progress

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What’s missing?

• Where do paths come from?– Vehicles meander

Pick corridors

Add outgoing road

• No goal seeking behavior– Need directions

“Turn right at the first intersection,

drive through two intersections,

and then turn left.”

Route

• A succession of roads and intersections– Like MapQuest Directions

• A global, strategic goal – The path must conform to the route

• May require lane changes

Stages of Lane Changing

• Motivation

Why change lanes?

• Decision Choosing a target lane

Deciding when to go

• Action How to change lanes?

Motivation to Change Lanes– Discretionary Lane Change (DLC) to improve driving conditions (e.g. speed, density)

– Mandatory Lane Change (MLC) to meet destination requirements (e.g. lane termination)

Decision to Initiate a Lane Change– Best conditions (e.g. flow)– Gap Acceptance

• Lead gap• Lag gap

Lane Changing Action

• Shift Pursuit Point– Proportional Derivative

Controller

– Speed Coupling

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vLCp

Behavior Combination

• Combine accelerations from– Cruising behavior– Following behavior– Intersection behavior

• Combine steering angle from– Tracking behavior– Lane changing behavior

Interactions Between Controllers

Problem: impeded progressFollowing prevents overtaking

• Solution: Reduce following distance

Stiffen controller

Problem: unveiled threatAppearance of leader in new lane

• Solution: Split attention – follow 2 leaders

Summary

• An accurate, efficient, robust roadway model– Ribbon network– Arc length parameterization– Efficient mapping between ribbon and Cartesian

coordinates

• A framework for modeling behaviors– Ribbon based tracking– Path based behaviors– Route as a strategic goal

Future Work

• Pedestrians

• Modeling non-oriented navigable surfaces

(e.g. intersections)

• Pursuit Point Control

• Behavioral Diversity

Acknowledgments

• NSF Support: INT-9724746, EIA-0130864, and IIS-0002535

• Contributing students, staff, faculty Jodie Plumert Geb Thomas

David Schwebel Pete WillemsenPenney Nichols-Whitehead HongLing WangJennifer Lee Steffan MunteanuSarah Rains Joan Severson Sara Koschmeder Tom DrewesBen Fraga Forrest MeggersKim Schroeder Paul DebbinsStephanie Dawes Bohong ZhangLloyd Frei Zhi-hong WangKeith Miller Xiao-Qian Jiang