Innovative strategies for urban car-sharing systems and a simulator to assess their performance

In this paper, three innovative car-sharing systems for urban areas are proposed, based on fleets of individual intelligent vehicles with three service characteristics: instant access, open-ended reservations and one-way trips. These features provide high flexibility but create an uneven distribution of vehicles among stations. Therefore, relocation of vehicles must be performed. Three different system procedures are proposed: in the first system, relocations are performed by users; in the other two, vehicles relocate automatically, thanks to their automation. In the first two systems, vehicles are accessible only at stations, whereas in the third they are also accessible along roads. In order to provide transport managers with a tool to test systems in different realities, an object-oriented simulator is developed. The simulation provides outputs of system performance, in terms of user waiting times and system efficiency. The proposed systems are simulated for the city of Genoa, in Italy, and a comparative analysis is presented.     

A critical evaluation of strategic alliances in liner shipping

During the last few years, the liner industry has endured a period of radical change, largely due to the formation of the so-called global strategic alliances amongst leading container carriers. However, not even after a full year of operations, a series of cross-alliance mergers and acquisitions has forced three out of the four newly formed alliances to restructure and/or modify their partner base. While this recent development does not put an end to such kind of agreements, as the merged companies are still committed in a second generation of strategic alliances, it highlights the fact that, despite the intentions of their respective partners, such alliances are actually characterized by a high level of instability. This paper, after considering the key profiles of strategic alliances in liner shipping, argues that their current structure may prove inherently inadequate to deliver an acceptable level of stability. The main factors driving such instability can be found in the increased organizational complexity of the alliance as well as in the establishment of a certain degree of intra-alliance competition, whose effects are likely to undermine the level of mutual trust between partner companies. Causes and effects of such factors are investigated and some measures aimed at controlling alliance instability are also suggested.     

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.     

Should I stay or should I go? Investigating route switching behavior from revealed preferences data

A large variety of factors influence the route choice decisions of road users, and modelers consider these factors within the perceived utility that road users are assumed to maximize. However, this perceived utility may be different even for the same origin–destination pair and this leads road users to choose different routes for different trips. In this study, we focus on this particular phenomenon of route switching behavior by estimating discrete choice models with the aim of understanding the key factors at its foundation. The estimated route choice models account for route characteristics, socio-economic information, activity based data, inertial mechanism and learning effects, and they are applied to revealed preference data consisting of 677 actual day by day route choices (referred to 77 road users) collected by GPS in Cagliari (Italy). Route switching models were estimated with both fixed and random coefficient models. The model estimation results show that the variables referred to habit and learning have an important relevance on explaining the route switching phenomenon. Specifically, the higher is the travel habit, the less is the propensity of the road users to switch their route. Moreover, the learning effect shows that the accumulation of past experiences has more influence on the choice than the most recent ones.

     

An H2 Formulation for the Design of a Passive Vibration-Isolation System for Cars

Optimal design of an active suspension system for road vehicles can be solved using LQR techniques. Such a problem is equivalent, in the frequency domain, to determine the state feedback gain matrix that minimizes the H₂ norm of a suitable transfer matrix.

A passive suspension system can be seen as the physical realization of a suitable state feedback law whose gains are function of the system parameters. This law, and thus the characteristic elements of the passive suspension, can be determined as an approximation of the H₂ optimal solution. This methodology allows one to choose the best controller from a constrained subset (i.e., all possible passive suspensions of a particular form) of all possible controllers.     

A new shared vehicle system for urban areas

The paper concerns the conceptual design of a transport system for pedestrian areas. The proposed transport system is based on a fleet of eco-sustainable Personal Intelligent City Accessible Vehicles (PICAVs). The vehicles are shared through the day by different users and the following specific services will be provided: instant access, open ended reservation and one way trips. Referring to the proposed transport system, a new methodology to optimise the fleet dimension and its distribution among the stations is proposed in this paper. The problem faced is an optimisation problem where the cost function to be minimised takes into account both the transport system cost and the user costs that depend on the waiting times. A random search algorithm has been adopted. Given a fleet dimension and its distribution among the stations, the waiting times of the users are assessed by a microscopic simulation. The simulation model tracks the second-by-second activity of each PICAV user, as well as the second-by-second activity of each vehicle. The overall methodology has been implemented in an object-oriented simulator. The proposed transport system has been planned and simulated for the historical city centre of Genoa, Italy.     

Semiactive Suspension Design with an Optimal Gain Switching Target

The paper presents a two-phase design technique for semiactive suspensions. In the first phase, we use a procedure proposed by Yoshida et al. to compute a target active control law that can be implemented by Optimal Gain Switching. This control law is such that the force generated by the suspension system is bounded within a set U . In the second phase, we approximate this target by controlling the damper coefficient of the semiactive suspension. We also compute the region of the state space in which the force generated by the semiactive suspension is still within the set U . The results of several simulations show that the use of a semiactive suspension leads to minimal loss with respect to optimal performance of an active suspension.     

Implementing the street-turn strategy by an optimization model

The street-turn option represents a major strategy for the profitability of shipping companies supplying container-based transportation. This option consists in the distribution of trucks delivering loaded containers to import customers, the subsequent allocation of empty containers to export customers and the final dispatch of loaded containers to departure ports. However, the determination of truck routes is a time-consuming activity for shipping companies, because available information can suddenly change while they are making their decisions. In this paper we aim to propose a decision support tool to quickly determine truck routes and implement the street-turn strategy. This tool is based on an optimization model determining the allocation of empty containers between customers and defining truck routes in a post-optimization phase. We compare routes resulting from the proposed model to the decisions of a real shipping company. Early results indicate that this approach represents a promising support for shipping companies in dealing with street-turns. It can significantly reduce distances travelled by trucks and times requested to determine routes.     

A nonlinear model of bicycle shimmy

This paper presents a nonlinear model accurately describing, both qualitatively and quantitatively, the onset and dynamics of bicycle shimmy. Methods of nonlinear dynamics, such as numerical continuation and bifurcation analysis, show that the model exhibits two stable periodic motions found experimentally in on-road tests: the weave and wobble (or shimmy) mode. The modelling results are compared with experimental data collected by riding a racing bicycle downhill at high speeds with hands on the handlebar. The model predicts with surprising accuracy the amplitudes and frequencies of the oscillations, the longitudinal velocity at which they occur, as well as the substantial independence of wobble frequency and amplitude from the forward speed. The lateral acceleration of the upper tube of the frame near the steering axis reaches 5–10?g, both in the model and in the data. The analysis shows that wobble onset and amplitude is particularly sensitive to changes in the torsional stiffness of the frame and strongly depends on tyre lateral force and aligning torque at the wheel–road contact point. It also allows to quantify the additional viscous rotary damping that should be added to the steering assembly to prevent wobble.     

PID Controller Modelling and Optimization in Cr Systems with Standard and Reduced Accumulators

The proportional-integrative-derivative (PID) controller and the pressure control valve of a Common Rail system are modelled by taking into account electronic, electrical, hydraulic and mechanical aspects. A fully predictive model of the injection apparatus is realized and validated by means of comparison with experimental data. The effects of the PID parameters on the injection system dynamics are illustrated and discussed on the basis of model results, which refer to steadystate and transient working conditions. The influence of the accumulator size on the rail pressure time history is investigated when the rail volume is dramatically reduced (up to 2.5 cm³). In particular, the effect of the large rail pressure drop that occurs at the end of the main injection for Minirail layout solutions is examined when after injections are implemented. An objective is to try to determine possible suitable values of the PID controller parameters and of the pressure-sensor sampling-frequency for rails of reduced size.