Optimal Preview Control of a Two-dof Vehicle Model Using Stochastic Optimal Control Theory

An optimal preview control algorithm is applied to a two degree of freedom(dof) vehicle model travelling with constant velocity on a randomly profiled road. The road roughness is modelled as a homogeneous random process being the output of a linear first order filter to white noise. The input from the road irregularity is assumed to be measured at some distance in front of the vehicle and this measured infonnation is utilized by the active controller to prepare the system for the ensuing input. The preview control algorithm is obtained by minimizing a quadratic performance index and by describing the average behaviour of the system by the covariance matrix of the vehicle response state vector. Results are presented for full state feedback and significant improvements in sprung mass acceleration, suspension working space and road holding are observed.     

Preview Control Algorithms for the Active Suspension of an Off-Road Vehicle

The potential performance improvement using preview control for active vehicle suspension was first recognized in the late nineteen sixties. All work done since that time has been based on optimal control theory using simple vehicle models.

In this article, the performance of quarter vehicle preview controllers when applied to a real off-road vehicle is simulated using both two degree of freedom quarter and ten degree of freedom full vehicle models. The results, which are compared with non-preview active and conventional passive suspensions, confirm that preview control reduces vertical acceleration of the body centre of gravity, which results in improved ride quality. Further, reductions in pitch and roll motion result from smaller vertical displacements of the vehicle quarters. Coupling between quarters, through the vehicle body, appears to have a smoothing effect on the control.

As an alternative to optimal control theory based controllers, a simple ad hoc preview controller based on isolating the vehicle body from dynamic loads transmitted through the suspension is proposed. Simulation results show that such a controller outperforms the optimal control theory based controllers over small discrete disturbances but responds poorly to disturbances encountered from other than steady state.     

A multiple discrete-continuous model for independent- and joint-discretionary-activity participation decisions

This paper presents a multiple discrete-continuous econometric structure to model the daily time-investment decisions of couples in solo- and joint-discretionary activities incorporating intra-personal and inter-personal inter-dependencies. The empirical model was estimated using data from the 2000 Bay Area Travel Survey. The results indicate evidence of the positive impact of vehicle availability on independent activity participation and the negative impacts of the presence of children and mandatory time investments on the joint discretionary-activity engagement of the spouses. In addition, we also find the mandatory- and maintenance-activity-participation characteristics of the spouse to influence the discretionary activity choices of individuals. Finally, the analysis also indicates a strong impact of common unobserved factors on the decisions of couples. From a policy analysis perspective, these results imply that demand-management actions directly impacting one adult could also result in changes to the activity patterns of his/her spouse and to changes in joint activity participation characteristics. Dr. Sivaramakrishnan Srinivasan is an Assistant Professor in the Department of Civil and Coastal Engineering at the University of Florida. His research interests include travel-behavior analysis, activity-based travel-demand modeling, and the application of advanced econometric methods for transportation problems. Dr. Chandra R. Bhat has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE).     

Short-term Hourly Traffic Forecasts using Hong Kong Annual Traffic Census

The need for acquiring the current-year traffic data is a problem for transport planners since such data may not be available for on-going transport studies. A method is proposed in this paper to predict hourly traffic flows up to and into the near future, using historical data collected from the Hong Kong Annual Traffic Census (ATC). Two parametric and two non-parametric models have been employed and evaluated in this study. The results show that the non-parametric models (Non-Parametric Regression (NPR) and Gaussian Maximum Likelihood (GML)) were more promising for predicting hourly traffic flows at the selected ATC station. Further analysis encompassing 87 ATC stations revealed that the NPR is likely to react to unexpected changes more effectively than the GML method, while the GML model performs better under steady traffic flows. Taking into consideration the dynamic nature of the common traffic patterns in Hong Kong and the advantages/disadvantages of the various models, the NPR model is recommended for predicting the hourly traffic flows in that region.     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

Neuro-Fuzzy Control of a Tracked Vehicle Featuring Semi-Active Electro-Rheological Suspension Units

This paper presents vibration control of a tracked vehicle installed with electro-rheological suspension units (ERSU). As a first step, an in-arm type ERSU is designed, and its spring and damping characteristics are evaluated with respect to the intensity of electric fields. Subsequently, a 16 degree-of-freedom model for a tracked vehicle equipped with the proposed ERSU is established followed by the formulation of a neuro-fuzzy controller. This controller takes account for both ride quality and steering stability by adopting a weighting parameter between two performance requirements. The parameter is appropriately determined by employing a fuzzy algorithm associated with two fuzzy variables: the vertical speed of the body and the rotational angular speed of the wheel. Control performances to isolate unwanted vibration from bump and random road excitations are evaluated through computer simulations. In addition, maximum speed of the vehicle with 6 Watt power absorption is investigated with respect to the road roughness.     

Simulation Tools, Modelling and Identification, for an Automotive Shock Absorber in the Context of Vehicle Dynamics

For purpose of simulation of vehicle dynamics, a physical model of an automotive shock absorber has been developed and implemented in several software packages for multibody simulations. In the present paper, the damper model structure is shortly elaborated together with some measurement and estimation techniques to retrieve the model parameters, possibly from dynamometer measurements only. These techniques are illustrated on a shock absorber normally used on the front suspension of a BMW series 7.     

Two-Dimensional Motion of Vehicles Damaged due to Collision

This paper deals with two-dimensional motion analysis of vehicles damaged due to collision. Various parts of vehicles are damaged due to collision in general. The effects of the damage in vehicle body and wheels on the vehicle motions are investigated. The center of gravity of the vehicle and the polar moment of inertia are changed by the deformation of vehicle body. Furthermore, the geometrical relations of wheels like wheelbase, treads and steering angles may be changed by damage of the wheels. Thus the vehicle loses symmetry with respect to the vehicle axis. The four-wheel vehicle model is extended to take into account the vehicle damage due to collision. The motions of damaged vehicles are compared with those of undamaged vehicles. It is found that vehicle damages have a significant influence on vehicle motion after impact.     

A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

REGULATION OF PRODUCTION OF PARATHYROID HORMONE－RELATED PEPTIDE （PTHrP） AND EXPRESSION OF ITS mRNA IN A HUMANLIVER－DERIVED CE

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