This paper presents a new approach to congestion management at traffic-light intersections. The approach is based on controlling the relative lengths of red/green cycles in order to have the congestion level track a given reference. It uses an integral control with adaptive gains, designed to provide fast tracking and wide stability margins. The gains are inverse-proportional to the derivative of the plant-function with respect to the control parameter, and are computed by infinitesimal perturbation analysis. Convergence of this technique is shown to be robust with respect to modeling uncertainties, computing errors, and other random effects. The framework is presented in the setting of stochastic hybrid systems, and applied to a particular...
Practical large-scale nonlinear control systems require an intensive and time-consuming effort for t...
This thesis aims to address three research topics in intelligent transportation systems which inclu...
This paper proposes a stochastic hybrid dynamic model of the queue-length at a signalized intersecti...
Abstract: We address the traffic light control problem for multiple intersections in tandem by viewi...
We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengt...
Abstract: We consider the traffic light control problem for a single intersection modeled as a stoch...
Control and optimization of Stochastic Hybrid Systems (SHS) constitute increasingly active fields o...
This dissertation is concerned with specific uncertainties in traffic flow control, which is the mos...
Abstract: In this paper, we consider the problem of dynamically regulating the timing of traffic lig...
The problem of optimizing traffic light phases dates back to the fifties. Since there, many solution...
In this dissertation we make use of the theories of stochastic processes and operations research to ...
AbstractThe problem of optimizing traffic light phases dates back to the fifties. Since there, many ...
While the problem of optimizing traffic light phases dates back to the fifties, in the daily practic...
We develop simulation optimization algorithms for determining the traffic light signal timings for a...
In this paper, we adobe the Stochastic Fluid Modeling framework to model the critical density of a r...
Practical large-scale nonlinear control systems require an intensive and time-consuming effort for t...
This thesis aims to address three research topics in intelligent transportation systems which inclu...
This paper proposes a stochastic hybrid dynamic model of the queue-length at a signalized intersecti...
Abstract: We address the traffic light control problem for multiple intersections in tandem by viewi...
We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengt...
Abstract: We consider the traffic light control problem for a single intersection modeled as a stoch...
Control and optimization of Stochastic Hybrid Systems (SHS) constitute increasingly active fields o...
This dissertation is concerned with specific uncertainties in traffic flow control, which is the mos...
Abstract: In this paper, we consider the problem of dynamically regulating the timing of traffic lig...
The problem of optimizing traffic light phases dates back to the fifties. Since there, many solution...
In this dissertation we make use of the theories of stochastic processes and operations research to ...
AbstractThe problem of optimizing traffic light phases dates back to the fifties. Since there, many ...
While the problem of optimizing traffic light phases dates back to the fifties, in the daily practic...
We develop simulation optimization algorithms for determining the traffic light signal timings for a...
In this paper, we adobe the Stochastic Fluid Modeling framework to model the critical density of a r...
Practical large-scale nonlinear control systems require an intensive and time-consuming effort for t...
This thesis aims to address three research topics in intelligent transportation systems which inclu...
This paper proposes a stochastic hybrid dynamic model of the queue-length at a signalized intersecti...