Formal Control of Traffic Systems via Network Decomposition

Date

2018-08-16

Author

Bardakci, Kemal Cagri
Aydın Göl, Ebru

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

129
views

0
downloads

We study the problem of synthesizing a signal control strategy for a traffic system from Linear Temporal Logic specifications. In particular, we focus on the scalability issue in the formal control of large traffic systems and propose to tackle it by decomposing the main problem into smaller problems. The developed decomposition algorithm partitions the main traffic system into subsystems and derives a specification for each subsystem from the main specification. In addition, we derive additional constraints on the signals lying on the boundaries of subsystems to ensure fairness. Abstraction based techniques are employed to find control strategies for subsystems. During the computation of a finite abstraction, the dynamics and specifications of adjacent systems are also considered. We show that the controllers found for each system guarantee that the main traffic system satisfies the given specification.

Subject Keywords

Heuristic algorithms, Roads, Trajectory, Computational modeling, Space vehicles, Automata

URI

https://hdl.handle.net/11511/44091

DOI

https://doi.org/10.23919/acc.2018.8430880

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Controlling a network of signalized intersections from temporal logical specifications Coogan, Samuel; Aydın Göl, Ebru; Arcak, Murat; Belta, Calin (2015-07-30) We propose a framework for generating a control policy for a traffic network of signalized intersections to accomplish control objectives expressed in linear temporal logic. Traffic management indeed calls for a rich class of objectives and offers a novel domain for these formal methods tools. We show that traffic networks possess structural properties that allow significant reduction in the time required to compute a finite state abstraction. We further extend our approach to a probabilistic framework by m...
Linear Algebraic Analysis of Fractional Fourier Domain Interpolation Öktem, Sevinç Figen (2009-01-01) n this work, we present a novel linear algebraic approach to certain signal interpolation problems involving the fractional Fourier transform. These problems arise in wave propagation, but the proposed approach to these can also be applicable to other areas. We see this interpolation problem as the problem of determining the unknown signal values from the given samples within some tolerable error We formulate the problem as a linear system of equations and use the condition number as a measure of redundant ...
Fast Algorithms for Digital Computation of Linear Canonical Transforms Koc, Aykut; Öktem, Sevinç Figen; Ozaktas, Haldun M.; Kutay, M. Alper (2016-01-01) Fast and accurate algorithms for digital computation of linear canonical transforms (LCTs) are discussed. Direct numerical integration takes O.N-2/time, where N is the number of samples. Designing fast and accurate algorithms that take O. N logN/time is of importance for practical utilization of LCTs. There are several approaches to designing fast algorithms. One approach is to decompose an arbitrary LCT into blocks, all of which have fast implementations, thus obtaining an overall fast algorithm. Another a...
Numerical methods for multiphysics flow problems Belenli Akbaş, Mine; Kaya Merdan, Songül; Rebholz, Leo G.; Department of Mathematics (2016) In this dissertation, efficient and reliable numerical algorithms for approximating solutions of multiphysics flow problems are investigated by using numerical methods. The interaction of multiple physical processes makes the systems complex, and two fundamental difficulties arise when attempting to obtain numerical solutions of these problems: the need for algorithms that reduce the problems into smaller pieces in a stable and accurate way and for large (sometimes intractable) amount of computational resou...
Blind Deinterleaving of Signals in Time Series with Self-Attention Based Soft Min-Cost Flow Learning Can, Oğul; Gürbüz, Yeti Ziya; Yildirim, Berkin; Alatan, Abdullah Aydın (2021-01-01) We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals. We link signal clustering problem to min-cost flow as an equivalent problem once the proper costs exist. We formulate a bi-level optimization problem involving min-cost flow as a sub-problem to learn such costs from the supervised training data. We then approximate the lower level optimization problem by self-attention based neural networks and provide a trainable framework that clu...

Citation Formats

K. C. Bardakci and E. Aydın Göl, “Formal Control of Traffic Systems via Network Decomposition,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/44091.