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A Mixed-Logical-Dynamical model for Automated Driving on highways
We propose a hybrid decision-making framework for safe and efficient aut...
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A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving
Lessons learned from the increasing diversity of road trial deployments ...
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Learning Optimized Risk Scores on Large-Scale Datasets
Risk scores are simple classification models that let users quickly asse...
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Multi-Vehicle Trajectory Optimisation On Road Networks
This paper addresses the problem of planning time-optimal trajectories f...
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Incorporating Road Networks into Territory Design
Given a set of basic areas, the territory design problem asks to create ...
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5G Network Planning under Service and EMF Constraints: Formulation and Solutions
We target the planning of a 5G cellular network under 5G service and Ele...
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On Topology Optimization and Canonical Duality Method
The general problem in topology optimization is correctly formulated as ...
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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.
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