1,361 research outputs found
Adaptive importance sampling for probabilistic validation of advanced driver assistance systems
We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The importance sampling pdf is estimated by a kernel density estimate, based on the results from the previous iteration. The concept is illustrated with a simple adaptive cruise control problem
Tropical analogues of a Dempe-Franke bilevel optimization problem
We consider the tropical analogues of a particular bilevel optimization
problem studied by Dempe and Franke and suggest some methods of solving these
new tropical bilevel optimization problems. In particular, it is found that the
algorithm developed by Dempe and Franke can be formulated and its validity can
be proved in a more general setting, which includes the tropical bilevel
optimization problems in question. We also show how the feasible set can be
decomposed into a finite number of tropical polyhedra, to which the tropical
linear programming solvers can be applied.Comment: 11 pages, 1 figur
Testing advanced driver assistance systems for fault management with the VEHIL test facility
This paper presents a methodological approach for validation of advanced driver assistance systems (ADASs), especially concerning fault management. Tools in this methodology are the unique VEhicle-Hardware-In-the-Loop (VEHIL) test facility and the associated simulation tool PRESCAN. With VEHIL the development process and more specifically the validation phase of intelligent vehicles can be carried out safer, cheaper, more manageable, and more reliable. In VEHIL a complete vehicle is tested in the simulation loop, such that the safety and reliability of an ADAS can be tested to great accuracy and reliability
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