Formulating a methodology for modelling revealed preference discrete choice data-the selectively replicated logit estimation

There are a number of studies on modelling with Revealed Preference (RP) data. It is a traditional technique and it is based on actual market data. The method has been extensively used in transportation as a tool for predicting travel demand. Although the method constitutes a relevant analysis on the process of modelling, it suffers from limitations, mainly associated with the lack of control over the experiment, that sometimes overwhelm the model results. This work proposes and tests a methodology for estimating a more efficient binary RP sample set. The objective is to develop and test a methodology that identifies and eliminates potentially irrational choices made. Responses are evaluated according to the set of trade-offs in values of time. Having identified these individuals they are eliminated from the original sample and a new sample is created, the selectively replicated (SR) sample. Original and SR samples are then re-estimated in a tree nested logit structure.     

Indicators of urban accessibility: Theory and application

The concept of accessibility and its related indicators have been in use for a long time, with still diverging interpretations of their significance and formulation. In this paper, a review is made of various existing theoretical bases, with special emphasis on recent behavioural approaches. It is suggested that this theoretical framework now allows a better appraisal of accessibility indicators and precise recommendations are proposed for their practical formulation and use. Various examples are given, especially for disaggregate analysis where a calculation for a given person is proposed instead of the conventional calculation .by a given mode. Finally, the relations between accessibility and trip rate are examined; from a study made in French cities, it is suggested that accessibility is a powerful determinant of trip rate.     

Commercially managed road funds: managing roads like a business,not like a bureaucracy

Nearly all countries are seriously short of revenues for investment and maintenance of roads. Improving utilization of the existing road budget has helped to narrow, but not eliminate, this financing gap. Requests for additional resources from the government's budget have fallen on deaf ears, because the road sector has grown too large to be fully-financed through general tax revenues. Government tax systems were not designed to finance major economic sectors like roads. Faced with an acute shortage of funds, many road agencies have introduced tolls on high-volume roads and have invited the private sector to build and operate such roads under concession agreements. Although this has narrowed the financing gap, tolling is only economic on a small part of the road network. Tolls have thus had a relatively small impact on the financing gap. Against this background, and mindful of the fact that roads are now 'big business' on the scale of the Fortune Global 500, a growing number of countries have started to 'bring roads into the market place, put them on a fee-for-service basis and manage them like a business.' The fee-for-service concept, though superficially like the user-pay principle and the associated road funds which became popular during the 1950s, differs from user-pay in a number of important respects. The key differences are that: (i) only road user charges go into the road fund (i.e., there are no earmarked taxes); (ii) the fund is managed by a representative board with half or more members representing road users and the business community; (iii) members are nominated by the constituencies they represent and there is an independent chairperson; (iv) financing arrangements are designed to ensure that money is not diverted from other sectors; (v) funds are managed pro-actively by a small secretariat; (vi) there are published financial regulations governing the way funds are managed; (vii) charges are adjusted regularly to meet agreed expenditure targets; and (viii) there are regular technical and financial audits. Other important characteristics are that most commercially managed road funds are managed through a separate road fund administration, funds are channeled to all roads (sometimes even to unclassified roads) and they are introduced as part of a wider agenda to commercialize road management. Some of these road funds have been set up as road public utilities under a board with powers to set their own tariffs.     

Wave data assimilation with the Kalman filter

A new data assimilation method for ocean waves is presented, based on an efficient low-rank approximation to the Kalman filter. Both the extended Kalman filter and a truncated second-order filter are implemented. In order to explicitly estimate past wind corrections based on current wave measurements, the filter is extended to a fixed-lag Kalman smoother for the wind fields. The filter is tested in a number of synthetic experiments with simple geometries. Propagation experiments with errors in the boundary condition showed that the KF was able to accurately propagate forecast errors, resulting in spatially varying error correlations, which would be impossible to model with time-independent assimilation methods like OI. An explicit comparison with an OI assimilation scheme showed that the KF also is superior in estimating the sea state at some distance from the observations. In experiments with errors in the driving wind, the modeled error estimates were also in agreement with the actual forecast errors. The bias in the state estimate, which is introduced through the nonlinear dependence of the waves on the driving wind field, was largely removed by the second-order filter, even without actually assimilating data. Assimilation of wave observations resulted in an improved wave analysis and in correction of past wind fields. The accuracy of this wind correction depends strongly on the actual place and time of wave generation, which is correctly modeled by the error estimate supplied by the Kalman filter. In summary, the KF approach is shown to be a reliable assimilation scheme in these simple experiments, and has the advantage over other assimilation methods that it supplies explicit dynamical error estimates.     

The Rolling Motions of Road Vehicles

This paper examines the rolling motions of vehicles with pneumatic tires. From a simplified analysis two sources of instability are identified-one related to center of gravity position and the other to tire and suspension characteristics. When a specimen vehicle is considered, it is shown that current semi-trailer design can display instability from either source.     

Preview-Based Control of Suspension Systems for Commercial Vehicles

An active suspension with preview is developed for the rear axle of a commercial vehicle. The obtained improvements are promising and justify further investigation of the more feasible semi-active suspensions with preview. The inherent non-linearity of semi-active suspensions with switching shock absorbers and the need for controllers that can handle a broad class of control objectives has led to the development of several numerical control methods for both multi-level and continuously variable shock absorbers. The most promising control method and shock absorber type are selected and mounted in a test vehicle. Some first experimental results are discussed.     

Optimization for Vehicle Suspension II: Frequency Domain

The objective of this study is optimizing the components design of a vehicle suspension system under excitation due to road roughness. The vehicle is modelled as a dynamic system made of masses interconnected by, linear, springs and dampers. The optimizing code provides values corresponding to the caracteristics of masses, dampers and springs which, within a range, minimize the objective function for a defined excitation. This objective function auantifies the vehicle comfort level.

The optimization method used is the sequential linear programming by iteratively applying the Simplex algorithm. The model response is obtained in frequency domain and the vehicle excitation can be either random or deterministic.

The exact nature of the optimization problem, objective function and restrictions, depend on the type of excitation considered.

In succeeding paragraphs, the problem formulation together with a comparison with other authors is presented.     

Active Control of Non-stationary Response of Vehicles with Nonlinear Suspensions

Active control of non-stationary response of a single degree of freedom vehicle model with nonlinear passive suspension elements is considered in this paper. The method of equivalent linearization is used to derive the equivalent linear model and the optimal control laws are obtained by using stochastic optimal control theory based on full state information. Velocity squared quadratic damping and hysteresis type of stiffness nonlinearities are considered. The effect of the nonlinearities on the active system performance is studied. The performance of active suspensions with nonlinear passive elements is found to be superior to the corresponding passive suspension systems.     

Automated detection of lane-blocking freeway incidents using artificial neural networks

A major source of urban freeway delay in the U.S. is non-recurring congestion caused by incidents. The automated detection of incidents is an important function of a freeway traffic management center. A number of incident detection algorithms, using inductive loop data as input, have been developed over the past several decades, and a few of them are being deployed at urban freeway systems in major cities. These algorithms have shown varying degrees of success in their detection performance. In this paper, we present a new incident detection technique based on artificial neural networks (ANNs). Three types of neural network models, namely the multi-layer feedforward (MLF), the self-organizing feature map (SOFM) and adaptive resonance theory 2 (ART2), were developed to classify traffic surveillance data obtained from loop detectors, with the objective of using the classified output to detect lane-blocking freeway incidents. The models were developed with simulation data from a study site and tested with both simulation and field data at the same site. The MLF was found to have the highest potential, among the three ANNs, to achieve a better incident detection performance. The MLF was also tested with limited field data collected from three other freeway locations to explore its transferability. Our results and analyzes with data from the study site as well as the three test sites have shown that the MLF consistently detected most of the lane-blocking incidents and typically gave a false alarm rate lower than the California, McMaster and Minnesota algorithms currently in use.