TR2020-095
Autonomous Vehicle Decision-Making and Monitoring based on Signal Temporal Logic and Mixed-Integer Programming
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- "Autonomous Vehicle Decision-Making and Monitoring based on Signal Temporal Logic and Mixed-Integer Programming", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147917, July 2020.BibTeX TR2020-095 PDF
- @inproceedings{Sahin2020jul,
- author = {Sahin, Yunus Emre and Quirynen, Rien and Di Cairano, Stefano},
- title = {Autonomous Vehicle Decision-Making and Monitoring based on Signal Temporal Logic and Mixed-Integer Programming},
- booktitle = {American Control Conference (ACC)},
- year = 2020,
- month = jul,
- doi = {10.23919/ACC45564.2020.9147917},
- url = {https://www.merl.com/publications/TR2020-095}
- }
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- "Autonomous Vehicle Decision-Making and Monitoring based on Signal Temporal Logic and Mixed-Integer Programming", American Control Conference (ACC), DOI: 10.23919/ACC45564.2020.9147917, July 2020.
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MERL Contacts:
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Research Areas:
Abstract:
We propose a decision-making system for automated driving with formal guarantees, synthesized from Signal Temporal Logic (STL) specifications. STL formulae specifying overall and intermediate driving goals and the traffic rules are encoded as mixed-integer inequalities and combined with a simplified vehicle motion model, resulting in a mixed-integer optimization problem. The specification satisfaction for the actual vehicle motion is guaranteed by imposing constraints on the quantitative semantics of STL. For reducing the computational burden, we propose an STL encoding that results in a block-sparse structure. The same STL formulae are used for monitoring faults due to imperfect prediction on the vehicle and environment. We demonstrate our method on an urban scenario with intersections, obstacles, and no-pass zones.
Related News & Events
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NEWS MERL researchers presented 10 papers at American Control Conference (ACC) Date: July 1, 2020 - July 3, 2020
Where: Denver, Colorado (virtual)
MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Stefano Di Cairano; Saleh Nabi; Rien Quirynen; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference, MERL presented 10 papers on subjects including autonomous-vehicle decision making and motion planning, nonlinear estimation for thermal-fluid models and GNSS positioning, learning-based reference governors and reference governors for railway vehicles, and fail-safe rendezvous control.