Efficient Roadway Modeling and Behavior Control for Real-time ...
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)
IntersectionsWhere 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 c
a K p (v d v ) c Following: Proportional Derivative Controller a f f K p
( s ) f Kv ( v ) 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
c0 c1 tenter texit c2 time Intersection Exceptions
Unending stream of opposition Solution: Guaranteed progress a v 2 /(2 s ) Whats 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 LC LC
o K p (o o ) K v ( o) t Speed Coupling 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 progress Following prevents overtaking Solution: Reduce following distance Stiffen controller
Problem: unveiled threat Appearance 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 David Schwebel Penney Nichols-Whitehead Jennifer Lee Sarah Rains
Sara Koschmeder Ben Fraga Kim Schroeder Stephanie Dawes Lloyd Frei Keith Miller Geb Thomas Pete Willemsen HongLing Wang Steffan Munteanu Joan Severson
Tom Drewes Forrest Meggers Paul Debbins Bohong Zhang Zhi-hong Wang Xiao-Qian Jiang
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