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Behavior Control of Virtual Vehicle

Behavior Control of Virtual Vehicle. Hongling Wang April 21, 2003. Introduction. Purpose of behavior control Run a virtual vehicle on a road network Following traffic rules A vehicle should be able to get anywhere in the road network Behavior control is complex

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Behavior Control of Virtual Vehicle

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  1. Behavior Control of Virtual Vehicle Hongling Wang April 21, 2003

  2. Introduction • Purpose of behavior control • Run a virtual vehicle on a road network • Following traffic rules • A vehicle should be able to get anywhere in the road network • Behavior control is complex • Divided into basic component behaviors • Integrate all the basic components

  3. Components of Vehicle Behavior • Cruising behavior • Vehicle drives at desired speed • Following behavior • Vehicle keeps a safe distance behind its leader • Intersection behavior • Vehicle traverses intersections safely • Obeys traffic signals • Respects right of way • Lane changing behavior • Vehicle leaves the current lane and enters an adjacent target lane

  4. Behavior and Kinematics • Behavior sets control parameters • Acceleration • Driving curvature • Kinematics moves a vehicle to a new position according to parameter values

  5. Path • Path, a ribbon composed of road lanes and intersection corridors • Path used to guide vehicle moving • Path forms a consistent frame of reference • Pursuit point on path centerline • Path is an interface between a vehicle and outside world

  6. Path (Cont.) • Path simplifies behavior control • Driving curvature determined by path • Acceleration determined by behaviors • Path provides a basis for spatial relationship

  7. Cruising behavior • Determines desired speed • Compare current speed with desired speed • Current speed is higher, negative acceleration • Current speed is lower, positive acceleration • Proportional controller • Reactive behavior • Decision depends only on the state at this moment

  8. Following behavior • Query the leader on the path of a vehicle • Compute relative distance and relative speed • Proportional-derivative controller • Contribute the acceleration if negative, discard it if positive • Reactive behavior

  9. PD controller response to a slow leader • acceleration • Before critical point, positive • After critical point, negative and increasing • After negative maximum, negative and decreasing to approach 0 • phases of vehicle actions • No response • Slow down to leader’s speed • Keep a safe distance from its leader

  10. Integration of cruising and following behaviors • If following acceleration >0, choose cruising acceleration • If following acceleration <=0, choose smaller value among the two • Integrated behavior: a vehicle always tries to drive at a desired speed, while keeps from running into or too close to its leader

  11. Intersection behavior • What a vehicle does before entering an intersection • Stop • Keep going • Stop and go alternatively • Actions chosen according to ambient traffic and traffic control signals • Sequential behavior • Decision depends on both the state in last moment and the state in this moment

  12. Intersection behavior (Cont.) • An intersection is a resource • A vehicle should not enter it if it can’t leave it soon • Three sub behaviors because of different right-of-way rules • Going straight • Turning left • Turning right

  13. Intersection behavior (Cont.) • Main problems • Stop a vehicle on desired position • Using state machines to control action flow • Gap acceptance • Immediate gap (e.g., turning right on RED) • Predicted gap (e.g., turning left on GREEN)

  14. Stopping behavior • Requirements • Inform a vehicle it is the time to decelerate • Stop a vehicle in desired position if computed acceleration applied • Keep a vehicle stopped after it stopped • Acceleration computation method • PD controller • Invariant acceleration controller

  15. PD controller for stopping • Acceleration formula • Phases of vehicle actions • No response • Slow down and stop at desired position • Stay stopped at desired position

  16. PD controller for stopping • disadvantages • No fully stopping, speed infinitely approaches 0 • Acceleration value may be too big, if critical point is missed

  17. Invariant acceleration controller for stopping • Controller • Advantages • Be able to give a full stop at desired position • Gives a reasonable acceleration in some cases where PD controller gives a too big acceleration • Disadvantage • Sensitive to small errors of both speed and distance • Conclusion: a better choice than PD controller

  18. State machines for Intersection behavior • Basic states of state machines for intersection behavior • START, no response to state of control signal • CONTINUE, keep going while stopping still possible • SLOWDOWN, decelerate for stopping • STOPPED, speed is 0 • END, stopping becomes impossible or is no longer necessary • One state machine built for each sub behavior

  19. Gap acceptance computation • Gap is a time period within which my required space is free • A resource • Relationship between time and space • Immediate gap • Estimate when others will get to my required space • Check if it is within the gap • Predicted gap • Estimate when I will get to and leave my required space • Estimate when others will get to my required space • Check if they overlay

  20. Intersection behavior by simple right of way rules • Simple right of way rules • Problems: • Deadlock • Starvation • Solutions • Deadlock breaking rule • Starvation avoidance rule

  21. Integration of cruising, following and intersection behaviors • Before intersection behavior is activated, choose the former acceleration • After it is activated • In SLOWDOWN or STOPPED phase, choose the smaller value among the former acceleration and intersection acceleration • In other phases, choose the former acceleration • Integrated behavior: A vehicle tries to drive at a desired speed, keeps a safe distance with its leader and responds to traffic control signals on intersections

  22. Lane change behavior • Modeled as a sequence of four steps • Consider a lane change • Choice of a target lane • Gap acceptance • Move over to the target lane • Classified as MLC and DLC • MLC, mandatory lane change • DLC, discretionary lane change • Sequential behavior • State machine with 4 states corresponding to the 4 steps

  23. Discretionary Lane Change • Consider DLC when the speed is below a desired speed • Change to a neighboring lane for opportunity to increase speed • A gap is acceptable when both lead and lag gaps on target lane are acceptable

  24. Trajectories of a vehicle and its pursuit point during lane changing • Move pursuit point from center of current lane to center of target lane • Use PD controller to control lateral moving of pursuit point • Vehicle overshoots the target offset

  25. Gap acceptance for lane change • Both lead gap and lag gap are acceptable • My current leader and follower are not changing to my target lane • No vehicle on another adjacent lane of my target lane is changing to my target lane

  26. Integrate lane change behavior with following behavior • The concept of following leader changed • The ahead vehicle in my current lane • The ahead vehicle in my target lane if I am in lane change • The ahead vehicle whose target lane is my current lane and who is in lane change • Problem: too conservative • Solution: visibility computation

  27. Visibility computation • The ahead vehicle in my current lane may be out of my way when I am in lane change • Lane change will complete sooner with visibility computation, especial when ahead vehicle is very slow

  28. Take MLC into consideration • MLC is necessary • The concept and structure of path don’t support MLC efficiently • Route, a higher level conceptual structure, is necessary for MLC • Route of a vehicle is composed of roads • Relation between route and path • Route is a long term plan • Path is a short term plane • Path is built to follow route

  29. Take MLC into consideration • A multiple-lane MLC is treated as multiple single-lane changes • When still far from road end, consider only DLC, not MLC • DLC consistent with target of MLC is given priority • DLC against target of MLC is given some penalty for resource requirement

  30. General Behavior Integration • Acceleration combined contribution from • Cruising behavior • Following behavior • Intersection behavior • Driving curvature combined contribution from • Path following • Lane changing behavior

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