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The purpose is to create an algorithm that optimizes the trajectories that an autonomous vehicle must follow to reduce its energy consumption and reduce the emission of greenhouse gases.

An algorithm is presented that respects the dynamic constraints of the robot, including the characteristics of power delivery by the motor, the behaviour of the tires and the basic inertial parameters. Using quadratic sequential programming with distributed and non-monotonous search direction (Quadratic Programming Algorithm with Distributed and Non-Monotone Line Search), an optimization algorithm proposed and developed by Professor K. Schittkowski is implemented.

Relations between important operating variables have been obtained, such as the evolution of the autonomous vehicle’s velocity, the driving torque supplied by the engine and the forces acting on the tires. In a subsequent analysis, the aim is to analyse the relationship between trajectory made and energy consumed and calculate the reduction of greenhouse gas emissions. Also this method has been checked against another different methodology commented on in the references.

The main limitation comes from the modelling that has been done. As greater is the mechanical systems analysed, more simplifying hypotheses should be introduced to solve the corresponding equations with the current computers. However, the solutions are obtained and they can be used qualitatively to draw conclusions.

One main objective is to obtain guidelines to reduce greenhouse gas emissions by reducing energy consumption in the realization of autonomous vehicles’ trajectories. The first step to achieve that is to obtain a good model of the autonomous vehicle that takes into account not only its kinematics but also its dynamic properties, and to propose an optimization process that allows to minimize the energy consumed. In this paper, important relationships between work variables have been obtained.

The idea is to be friendly with nature and the environment. This algorithm can help by reducing an instance of greenhouse gases.

Originality comes from the fact that we not only look for the autonomous vehicle’s modelling, the simulation of its motion and the analysis of its working parameters, but also try to obtain from its working those guidelines that are useful to reduce the energy consumed and the contamination capability of these autonomous vehicles or car-like robots.

This study aims to propose a complete and powerful methodology that allows the optimization of the passive suspension system of vehicles, which simultaneously takes comfort and safety into account and provides a set of optimal solutions through a Pareto-optimal front, in a low computational time.

Unlike papers that consider simple vehicle models (quarter vehicle model or half car model) and/or simplified road profiles (harmonic excitation, for example) and/or perform a single-objective optimization and/or execute the dynamic analysis in the time domain, this paper presents an effective and fast methodology for the multi-objective optimization of the suspension system of a full-car model (including the driver seat) traveling on an irregular road profile, whose dynamic response is determined in the frequency domain, considerably reducing computational time.

The results showed that there was a reduction of 28% in the driver seat vertical acceleration weighted root mean square (RMS) value of the proposed model, which is directly related to comfort, and, simultaneously, an improvement or constancy concerning safety, with low computational cost. Hence, the proposed methodology can be indicated as a successful tool for the optimal design of the suspension systems, considering, simultaneously, comfort and safety.

Despite the extensive literature on optimizing vehicle passive suspension systems, papers combining multi-objective optimization presenting a Pareto-optimal front as a set of optimal results, a full-vehicle model (including the driver seat), an irregular road profile and the determination of the dynamic response in the frequency domain are not found.

In this paper, improvements in reducing transmitted accelerations in a full vehicle are obtained by optimizing the gain parameters of an active control in a roughness road profile.

For a classically designed linear quadratic regulator (LQR) control, the vibration attenuation performance will depend on weighting matrices Q and R. A methodology is proposed in this work to determine the optimal elements of these matrices by using a genetic algorithm method to get enhanced controller performance. The active control is implemented in an eight degrees of freedom (8-DOF) vehicle suspension model, subjected to a standard ISO road profile. The control performance is compared against a controlled system with few Q and R parameters, an active system without optimized gain matrices, and an optimized passive system.

The control with 12 optimized parameters for Q and R provided the best vibration attenuation, reducing significantly the Root Mean Square (RMS) accelerations at the driver’s seat and car body.

The research has positive implications in a wide class of active control systems, especially those based on a LQR, which was verified by the multibody dynamic systems tested in the paper.

Better active control gains can be devised to improve performance in vibration attenuation.

The main contribution proposed in this work is the improvement of the Q and R parameters simultaneously, in a full 8-DOF vehicle model, which minimizes the driver’s seat acceleration and, at the same time, guarantees vehicle safety.

Semi-active suspension systems with electromagnetic dampers allow energy regeneration and the required control strategies are easier to implement than the active suspensions are. This paper aims to address the application of a tubular linear permanent magnet synchronous machine for a semi-active suspension system.

Classical rules of mechanics and electromagnetics were applied to describe a dynamic model combining vibration and electrical machines theories. A multifaceted MATLAB®/Simulink model was implemented to incorporate equations and simulate global performance. Experimental tests on an actual prototype were carried out to investigate displacement transmissibility of the passive case. In addition, simulation results were shown for the dissipative semi-active case.

The application of the developed model suggests convergent results. For the passive case, numerical and experimental outcomes validate the parameters and confirm system function and proposed methodology. MATLAB®/Simulink results for the semi-active case are consistent, showing an improvement on the displacement transmissibility. These agree with the initial conceptual thoughts.

The use of linear electromagnetic devices in suspension systems is not a novel idea. However, most published papers on this subject outline active solutions, neglect semi-active ones and focus on experimental studies. However, here a dynamic mechanical-electromagnetic coupled model for a semi-active suspension system is reported. This is in conjunction with a linear electromagnetic damper.

The ascendancy of vertical marketing structures as total systems has brought about considerable interest in designing distribution systems. Various administered and co‐operative alignments have been successful in the marketplace by enabling lower total costs through central buying practices and by producing a more predictable demand pattern. As these planned systems begin to create de facto competition among individual firms, the need for methods of discovering optimal vertical arrangements will increase. One method of finding optimal arrangements of interacting phenomena is by modelling—and linear programming techniques have been found to be particularly useful. The transportation problem or distribution model was one of the first applied special cases of linear programming. Mathematical solutions to this “special case” of linear programming began appearing in the literature during World War II. Since that time, the management science literature has been replete with significant contributions in the transportation area such as those of Hitchcock, Dantzig, Chames and Cooper, and Orden.

During the past ten years, product proliferation, the trend toward larger facilities serving more markets, dramatic increases in the cost of labour and of plant and equipment and customers requiring faster, more dependable deliveries of smaller quantities have greatly increased management's awareness of the need for product flow planning and control. It is now well recognised that the movement and storage of goods is a vital link between production and marketing which is capable of having a significant impact on the overall profitability of the firm and, therefore, must be carefully planned and controlled.

Parking choice involves an individual selecting a parking place based upon various inter-related factors. This chapter examines the factors that influence parking choice decisions.

A review of the literature on parking choice has been undertaken. The influence of various factors on parking choice and recommendations for future parking policy will be outlined.

Most often it is a combination of several factors which influence individuals’ choice of parking place.

Increased knowledge of the factors which influence parking-search behaviour will inform urban parking policy applications with associated environmental and economic benefits.

This chapter investigates the impacts of households’ residential self-selection, parents’ perceptions and travel patterns on their children’s daily travel mode shares, among single parent households.

To capture the complexity of the relationships between parent and children daily travel mode choices, an integrated model structure is introduced and the model estimated with simultaneous equation modelling.

The results show that, beside the daily activity-travel engagements of the parent, both parent’s perceptions and his/her residential self-selection reasons play significant roles in influencing their children daily travel mode shares. The parent’s perceptions play more significant roles in influencing children’s travel modes shares, whilst the residential self-selection reasons have more significant influence on the parent’s travel mode choice.

The finding of this study reveals a fact that wherever the children live, their travel behaviour tend to be ‘neutral’ and open to influence by their parents throughout their childhood.

This study adds to our understanding of the interactions between parents’ attitudes and behaviours with their children’s travel patterns. This study focuses on single parent households, on which there is very little literature.

Why is it important to use computers in physical distribution management (PDM)? The reason is simple. PDM covers almost all of the activities concerned with distributing a product. Some authorities claim that logically the functions of procurement‐and manufacturing should also be considered as part of the overall process of making goods available to customers at the right place, at the right time, and in the right quantity. These activities and functions are inherently complex, involving many stock‐keeping items (SKIs) different in size, colour and other product characteristics. In addition to multiple items, there are multiple options for producing and distributing these items. Think of the many combinations of plant locations, distribution centre locations, choices of transportation modes, inventory levels, and channels of distribution that the physical distribution manager must consider. Imagine having to compare the many possible alternatives by hand calculations, and you can get some feel for the necessity of using modern computers for planning, operating, and controlling physical distribution.