Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective
Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections. In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.
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- New Jersey Institute of Technology
- Newark, New Jersey
- United States
- Building: ECE Building
- Room Number: ECEC 202
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Please contact Dr. Mengchu Zhou for any questions at zhou@njit.edu.
Phone: 908-458-6129. - Co-sponsored by CS23 - Control Systems Section
- Starts 08 February 2018 01:21 AM UTC
- Ends 16 February 2018 01:00 PM UTC
- No Admission Charge
Speakers
Dr. Hong Wang
Biography:
Dr. Hong Wang received the BSc, MEng and PhD degrees from Huainan University of Mining Engineering (AHUST) and Huazhong University of Science and Technology (HUST) in P R China 1982, 1984 and 1987, respectively. He then worked as a postdoc at Salford, Brunel and Southampton Universities between 1988 and 1992 in the United Kingdom.
He joined University of Manchester Institute of Science and Technology
(UMIST) in 1992 as a lecturer, and was then promoted to a Senior Lecturer in August 1997, to a Reader in August 1999, and to a full chair professor in April, 2002. He had been the deputy Head of Paper Science Department and the director of the UMIST Control Systems Centre, and was a university senate member during his time in Manchester. Hong Wang joined PNNL in February 2016 as a chief scientist and laboratory fellow working in the area of advanced modelling, control and optimization of complex dynamic systems. Dr.
Wang is the lead author of five books and has published over 300 papers in international journals and conferences, and has been invited to give keynote/plenary talks at some international conferences and workshops. He originated the research on stochastic distribution control where the main purpose of control input design is to make the shape of the output probability density functions to follow a targeted function. This area alone has found a wide spectrum of potential applications in modeling, data-mining, signal processing, optimization and distributed control systems design.
Hong Wang is the FIET, FInstMC, he is the member of 3 technical Cttees of the IFAC, and editorial member of 12 international journals including IEEE Transaction on Control Systems Technology, IEEE Transactions on Automation Science and Engineering and Optimal Control Methods and Applications, etc.