Car Parameters Identification by Handling Manoeuvres

A methodology is presented for identifying car parameters by studying the vehicle's handling. The methodology is based on the Kalman filter and makes it possible to determine the parameters on the basis of the results obtained from standard, on-road handling manoeuvres.     

The car pooling problem: Heuristic algorithms based on savings functions

The present research deals with car pooling as a means of making better use of existing infrastructure and as a means of reducing traffic congestion with all its associated induced effects. Car pooling schemes involve several drivers getting together to share a private vehicle simultaneously, in order to reach their destinations points according to a semi‐common route rather than each driver using their own vehicle. The Car Pooling Problem belongs to the non‐polynomial computational complexity family of operations problems. In the current literature there are only a few studies on this optimization problem: the research group has designed several different new automatic and heuristic data processing routines to support efficient matching in car pool schemes. These are based on savings functions and belong to two distinct macro classes of algorithms to give two different modelings of this problem. They offer average savings of more than 50% in traveled distances demonstrating the effectiveness of a trivial matching scheme for real applications.     

Substitution and complementarity patterns between traditional transport means and car sharing: a person and trip level analysis

Transportation - Car sharing is a new transport mode which combines characteristics of private and collective traditional transport means. Understanding the relationship of this mode with existing...     

Natural and anthropogenic hydrocarbons in the water column of the Ross Sea (Antarctica)

In the framework of the Italian Research Programme in Antarctica (PNRA) an oceanographic cruise was carried out between December 2000 and February 2001 in the Western Ross Sea. n-Alkanes and PAHs concentrations were analysed in sea-water samples collected at different depths at four sites (D, B, CA2, and CA). Vertical profiles of pressure, temperature, salinity and fluorescence were also performed in order to distinguish the water masses present in the sampling areas. n-Alkanes concentrations were consistent with those found in the same area during previous expeditions and showed higher values in the particulate due to the low temperatures. n-Alkanes profiles exhibited different features in the dissolved and particulate phases. The dissolved phase was characterised by a bimodal distribution with two maxima at C16 and C24 and prevalent compounds in the range C15–C32 whereas particulate was strongly dominated by long chain n-alkanes C23–C34 with C24 (Site B, CA and CA2) or C32 (Site B) as Cmax. CPI values and Pr/Ph ratios suggested a prevalent biogenic origin for aliphatic hydrocarbons. n-Alkanes vertical distributions were affected by the dynamic of the pack-ice melting and phytoplankton activity as well by the chemical–physical properties of water masses. Higher n-alkanes values were found in the High Salinity Shelf Waters (HSSW), lower n-alkanes values were found in the Antarctic Surface Waters (AASW) and Modified Circumpolar Deep Water (MCDW).The low PAHs concentration levels confirmed the still pristine character of the Antarctic environment. Neither particular trend in total PAHs concentrations along the water column and nor correlations with the most characteristic water masses of the investigated area of the Ross Sea were observed, except that total PAH higher concentrations were generally observed in correspondence of HSSW.     

Optical device for measuring the injectors opening in common rail systems

Since the needle displacement exerts a fundamental influence on the operation of Common Rail injection systems, accurate measurements of the control piston position can be crucial for a more thorough analysis of the behaviour of injectors, in particular when multiple injections are employed. Eddy current sensors have traditionally been used in lab activities to measure the control piston position inside injectors; apart from the high cost, the scientific literature clearly shows their inadequacy, which is mainly due to the presence of electromagnetic disturbance: the current pulse, which controls the opening of the injector, generates electromagnetic fields which strongly affect the acquisition of data. Many attempts have recently been made either to solve the interference occurring during such measurements or to propose alternative displacement transducers whose operation is not influenced by electromagnetic interference. In this paper, a new device for measuring the injector opening is proposed: it is an optical transducer characterized both by simple and very cheap construction and by a reliable physical principle for measuring the control piston lift. The reliability of the proposed sensor is assessed by a thorough experimental campaign and by comparing the experimental results with the numerical predictions achieved by a Common Rail injector model. Since the assembly of the optical sensor does not affect the injector operation, it can efficiently be used both for experimental tests and for on-board diagnosis and monitoring of the injector operation.     

Social marginal cost pricing and second best alternatives in partnerships for transport infrastructures

According to the economic theory, if all the first-best conditions are met, social optimality involves the prices to be set equal to social marginal costs. When it is not possible to set prices equal to social marginal costs, due to the presence of constraints within the transport sector or distortions elsewhere in the economy, the theory suggests corrections to the SMC principle (second-best alternatives). But the implementation of second best alternatives can give rise to serious problems when transferred from theory to practice. This chapter will discuss in particular the problems that might rise when investment cost are included (totally or partially) in the social marginal costs rules, and in particular when private operators are involved.     

A modelling system to simulate goods movements at an urban scale

The paper reports a modelling system to simulate goods movements at an urban scale. It allows joint analysis of choices made by end-consumers (assumed to be families) and retailers. These movements are examined at two levels: analysis of commodity flows, in terms of quantity, generated by the consumption of commodities; analysis of commodity flows, in terms of vehicles, due to restocking. The first level allows us to calculate the goods quantity flows due to consumption and restocking; the second level allows us to determine the service, vehicles used and target time, as well as the route chosen for restocking sales outlets in order to estimate vehicle flows on the urban/metropolitan transportation network. The modelling system is a multi-step model and considers a disaggregated approach for each decisional level.     

Design and analysis of control strategies for pedestrian flows

Transportation - Exploiting the full potential of pedestrian infrastructure is becoming critical in many environments which cannot be easily expanded to cope with the increasing pedestrian demand....     

Calibrating aggregate travel demand models with traffic counts: Estimators and statistical performance

Traffic counts on network links constitute an information source on travel demand which is easy to collect, cheap and repeatable. Many models proposed in recent years deal with the use of traffic counts to estimate Origin/Destination (O/D) trip matrices under different assumptions on the type of "a-priori" information available on the demand (surveys, outdated estimates, models, etc.) and the type of network and assignment mapping (see Cascetta & Nguyen 1988). Less attention has been paid to the possibility of using traffic counts to estimate the parameters of demand models. In this case most of the proposed methods are relative to particular demand model structures (e.g. gravity-type) and the statistical analysis of estimator performance is not thoroughly carried out. In this paper a general statistical framework defining Maximum Likelihood, Non Linear Generalized Least Squares (NGLS) and Bayes estimators of aggregated demand model parameters combining counts-based information with other sources (sample or a priori estimates) is proposed first, thus extending and generalizing previous work by the authors (Cascetta & Russo 1992). Subsequently a solution algorithm of the projected-gradient type is proposed for the NGLS estimator given its convenient theoretical and computational properties. The algorithm is based on a combination of analytical/numerical derivates in order to make the estimator applicable to general demand models. Statistical performances of the proposed estimators are evaluated on a small test network through a Monte Carlo method by repeatedly sampling "starting estimates" of the (known) parameters of a generation/distribution/modal split/assignment system of models. Tests were carried out assuming different levels of "quality" of starting estimates and numbers of available counts. Finally NGLS estimator was applied to the calibration of the described model system on the network of a real medium-size Italian town using real counts with very satisfactory results in terms of both parameter values and counted flows reproduction.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.