Title :
Freeway traffic systems: prediction and control
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers State Univ., Piscataway, NJ, USA
fDate :
28 Apr-1 May 1996
Abstract :
Since traffic congestion is becoming a serious and worsening problem, extensive research and development are now undertaken to reduce congestion and enhance safety. A new area, namely intelligent vehicle-high systems (IVHS), has drawn great attention from industries and academic institutions. This paper builds a deterministic linear time-variant model for freeway traffic system. Then we study the stability property of the system. In order to reduce the computation time, we decouple the given freeway system with many segments into a sequence of separate subsystems. Thereafter, we formulate a discrete-time moving horizon optimization problem and finally get the optimal solution for ramp-metering, which is in an explicit form of the predictive states
Keywords :
automated highways; computational complexity; control systems; discrete time systems; linear systems; optimal control; predictive control; road traffic; stability; traffic control; IVHS; computation time reduction; deterministic linear time-variant model; discrete-time moving horizon optimization; feedback control laws; freeway system; freeway traffic system; intelligent vehicle-high systems; optimal solution; predictive states; ramp-metering; research and development; safety; subsystems; system control; system prediction; system stability; traffic congestion reduction; Control systems; Intelligent systems; Intelligent vehicles; Predictive models; Research and development; Road accidents; Road transportation; Safety; Stability; Traffic control;
Conference_Titel :
Vehicular Technology Conference, 1996. Mobile Technology for the Human Race., IEEE 46th
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3157-5
DOI :
10.1109/VETEC.1996.504071