TY - GEN
T1 - Behavior and Management of Stochastic Multiple-Origin-Destination Traffic Flows Sharing a Common Link
AU - Jin, Li
AU - Wen, Yining
N1 - Funding Information:
This work was supported in part by NYU Tandon School of Engineering and C2SMART University Transportation Center. The authors appreciate discussion with Profs. Saurabh Amin and Dengfeng Sun and the comments from the anonymous reviewers.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - In transportation systems (e.g. highways, railways, airports), traffic flows with distinct origin-destination pairs usually share common facilities and interact extensively. Such interaction is typically stochastic due to natural fluctuations in the traffic flows. In this paper, we study the interaction between multiple traffic flows and propose intuitive but provably efficient control algorithms based on modern sensing and actuating capabilities. We decompose the problem into two sub-problems: the impact of a merging junction and the impact of a diverging junction. We use a fluid model to show that (i) appropriate choice of priority at the merging junction is decisive for stability of the upstream queues and (ii) discharging priority at the diverging junction does not affect stability. We also illustrate the insights of our analysis via an example of management of multi-class traffic flows with platooning.
AB - In transportation systems (e.g. highways, railways, airports), traffic flows with distinct origin-destination pairs usually share common facilities and interact extensively. Such interaction is typically stochastic due to natural fluctuations in the traffic flows. In this paper, we study the interaction between multiple traffic flows and propose intuitive but provably efficient control algorithms based on modern sensing and actuating capabilities. We decompose the problem into two sub-problems: the impact of a merging junction and the impact of a diverging junction. We use a fluid model to show that (i) appropriate choice of priority at the merging junction is decisive for stability of the upstream queues and (ii) discharging priority at the diverging junction does not affect stability. We also illustrate the insights of our analysis via an example of management of multi-class traffic flows with platooning.
KW - Piecewise-deterministic Markov processes
KW - Stochastic fluid model
KW - Traffic flow management
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U2 - 10.1109/CDC40024.2019.9028934
DO - 10.1109/CDC40024.2019.9028934
M3 - Conference contribution
AN - SCOPUS:85082506604
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 4109
EP - 4114
BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Conference on Decision and Control, CDC 2019
Y2 - 11 December 2019 through 13 December 2019
ER -