Paul K. Houpt

Dynamic model-based techniques for the detection of incidents on freeways

In this paper we discuss an approach to the detection of incidents on freeways. Our techniques are based on the use of a macroscopic dynamic model describing the evolution of spatial-average traffic variables (velocities, flows, and densities) over sections of the freeway. With such a model as a starting point we develop two incident detection algorithms based on the multiple model and generalized likelihood ratio techniques. We also describe a new and very simple system for processing raw data from presence-type vehicle detectors to produce estimates of the aggregate variables, which are then in turn used as the input variables to the incident detection algorithms. Simulation results using a microscopic simulation of a two-lane freeway indicate that 1) our algorithm are robust to the differences between the dynamics of actuals traffic and the aggregated dynamics used to design the detection systems; and 2) our methods appear to work as well as existing algorithms in heavy traffic conditions and work better in moderate to light traffic. Areas for future work are outlined at the end of the paper.

Roundoff noise and scaling in the digital implementation of control compensators

Researchers in digital signal processing have examined at length the effects of finite wordlength in the design of digital filters. The issues that have been considered apply to any digital system. In particular, the design of digital control systems must consider these issues. In this paper we will use, adapt, and extend the ideas developed in digital signal processing to the issue of roundoff noise in digital linear-quadratic-Gaussian (LQG) compensators. We will then examine the roundoff noise effects for a particular LQG example and several different implementation structures.

Stochastic control of freeway corridor systems

This paper deals with the dynamic stochastic control of a freeway corridor system, which consists of a multilane freeway interconnected with entry and exit ramps to one or more parallel traffic arterials, and subject to ramp controls and signals at intersections. Key issues associated with the use of modern estimation and control theory are presented.

Identification of a thermodynamic model for spark ignited internal combustion engines

A classical air-cycle thermodynamic combustion model for cylinder pressure in an internal combustion engine is recast into a certain state space form in which pressure evolves according to a linear time varying difference equation. Model parameter identification from observation of cylinder pressure data via maximum likelihood is shown to have a simple form which may permit on-line implementation. Experimental demonstration of the method is provided using data from a one-cylinder CFR research engine.

Architectural Issues in the Implementation of Digital Compensators

Abstract There are many techniques for designing discrete-time compensators. However, the digital implementation of such designs has not typically been addressed. The nature of digital hardware impacts the computational structure of the compensator and also can affect the original system design parameters. This paper deals with the architectural issues of serialism, parallelism and pipelining in implementing digital feedback compensators. The concepts of serialism and parallelism are shown to involve essentially thp same considerations for digital compensators as for digital filters. However, the same cannot be said of pipelining, due to the feedback loop. A design technique is proposed for dealing with the problem of compensator pipelining, and several examples of pipelining LQG compensators are presented.

Estimation of roadway traffic density on freeways using presence detector data

A simple data processing algorithm is presented for estimating the density of vehicular traffic flow on freeways between two conventional (presence) type loop detectors. Using flow and occupancy data from adjacent detector stations, a simple scalar Kalman filter is derived under assumption of homogeneous (in space) flow conditions. Correction for inhomogeneous conditions is provided by a bias detection-compensation technique based on the generalized likelihood ratio method. Accurate performance over a wide range of speed-density flow conditions is demonstrated.