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Situation Principles. Objects in lanes we plan to cross are more interesting. Closer objects are more interesting. Moving objects are more interesting. Objects moving towards us are more interesting. State ‘Parsing’.
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Situation Principles • Objects in lanes we plan to cross are more interesting. • Closer objects are more interesting. • Moving objects are more interesting. • Objects moving towards us are more interesting.
State ‘Parsing’ • Each tracked object i will have a probability of being in each lane l, pil. • They will also have a distribution over speed and distance to next waypoint, Pil_distance(x) and Pil_speed(v). • These will be half guessed based on the output of the Dynamic State Estimator and the RNDF.
Planner Interaction • The ‘planner’ will need to provide input to the interpreter. • One way is some kind of query/reply. • The Interpreter will find the relevant parts of the state and estimate the probability of a conflict with the intention. • It will then provide a useful response to the Planner.
Query/Reply: Road-follow • Query: What is the road-follow situation at segment 5.2, position 15 m., timestamp t? • Reply: safe, lane center/right/left edges in dead reckoning frame, minimum speed and distance of moving car ahead, grid map of relevant region showing drivable road surface. • For unknown situations, it might be possible to just put a phantom object at the unknown location until it is known thus causing the planner to slow down and prepare to stop.
Query/Reply Lane Change • Query: what is lane change situation at lane 3.4, position 23.4 m, timestamp t? • Reply: Safe, new lane center/edges in dead-reckoning frame, speed and position of car ahead and behind in new lane, grid map of drivable road expected to be safe. • Lack of knowledge might cause an unsafe reply. This might then change to safe as time goes on.
Query/Reply: Left Turn • Query: What about a left turn from exit waypoint x to entry waypoint y at time t? • Reply: Safe, the exit and the entry in the dead-reckoning frame, along with a grid map of the intersection in that frame showing the cells that are expected to be safe during the turn. • Unsafe might be due to lack of information. The reply will give the position of the last safe part of our lane, (for nosing out to look).
Implementation • We could parameterize each common situation, pre-calculate the decision surfaces and put in a table. (Fast but not so general). • We need to detect when the world is not as expected, cars behaving erratically. This should trigger some kind of safe behavior? • Need to break out of deadlocks. • Deciding that we do not know enough is hard.