2 research outputs found
From Specifications to Behavior: Maneuver Verification in a Semantic State Space
To realize a market entry of autonomous vehicles in the foreseeable future,
the behavior planning system will need to abide by the same rules that humans
follow. Product liability cannot be enforced without a proper solution to the
approval trap. In this paper, we define a semantic abstraction of the
continuous space and formalize traffic rules in linear temporal logic (LTL).
Sequences in the semantic state space represent maneuvers a high-level planner
could choose to execute. We check these maneuvers against the formalized
traffic rules using runtime verification. By using the standard model checker
NuSMV, we demonstrate the effectiveness of our approach and provide runtime
properties for the maneuver verification. We show that high-level behavior can
be verified in a semantic state space to fulfill a set of formalized rules,
which could serve as a step towards safety of the intended functionality.Comment: Published at IEEE Intelligent Vehicles Symposium (IV), 201
Optimal Behavior Planning for Autonomous Driving: A Generic Mixed-Integer Formulation
Mixed-Integer Quadratic Programming (MIQP) has been identified as a suitable
approach for finding an optimal solution to the behavior planning problem with
low runtimes. Logical constraints and continuous equations are optimized
alongside. However, it has only been formulated for a straight road, omitting
common situations such as taking turns at intersections. This has prevented the
model from being used in reality so far. Based on a triple integrator model
formulation, we compute the orientation of the vehicle and model it in a
disjunctive manner. That allows us to formulate linear constraints to account
for the non-holonomy and collision avoidance. These constraints are
approximations, for which we introduce the theory. We show the applicability in
two benchmark scenarios and prove the feasibility by solving the same models
using nonlinear optimization. This new model will allow researchers to leverage
the benefits of MIQP, such as logical constraints, or global optimality.Comment: Published at IEEE Intelligent Vehicles Symposium (IV), 202