Real time passenger information systems and quality of bus services

One of the main problems in urban areas is the steady growth in car ownership and traffic levels. Therefore, the challenge of sustainability is focused on a shift of the demand for mobility from cars to collective means of transport. For this end, buses are a key element of the public transport systems. In this respect Real Time Passenger Information (RTPI) systems help citizens change their travel behaviour towards more sustainable transport modes. This paper provides an assessment methodology which evaluates how RTPI systems improve the quality of bus services in two European cities, Madrid and Bremerhaven. In the case of Madrid, bus punctuality has increased by 3%. Regarding the travellers perception, Madrid raised its quality of service by 6% while Bremerhaven increased by 13%. On the other hand, the users ́ perception of Public Transport (PT) image increased by 14%.

Modeling, simulation and application of bacterial transduction in genetic algorithms

At present, all methods in Evolutionary Computation are bioinspired by the fundamental principles of neo-Darwinism, as well as by a vertical gene transfer. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganisms (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring the possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). Our results showed how PETRI approaches higher fitness values as transduction probability comes close to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ?bacterial colonies?.

Two risky and costly end-user related taboos when developing information systems: qualifications and accountability

This work highlights two critical taboos in organizations: 1)taking for granted the quality of certain capabilities and attitudes of the end-user representatives (EUR) in information systems development projects (ISDP), and 2) the EUR´s inherent accountability for losses in IS investments. These issues are neither addressed by theory nor research when assessing success/ failure. A triangulation approach was applied to combine quantitative and qualitative methods, having convergent results and showing that in problematic cases, paradoxically, the origin of IS rejection by end users (EU) points towards the EUR themselves. It has been evaluated to what extent some EUR factors impacted a macro ISDP involving an enterprise resource planning (ERP) package, ranking the ‘knowledge of the EUR’ as the main latent variable. The results validate some issues found throughout decades of praxis, confirming that when not properly managed the EUR role by itself has a direct relationship with IS rejection and significant losses in IS investments.

Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

Aerodynamic Optimization of a High-speed Train using Genetic Algorithms

Genetic algorithms (GA) have been used for the minimization of the aerodynamic drag of a train subject to front wind. The significant importance of the external aerodynamic drag on the total resistance a train experiments as the cruise speed is increased highlights the interest of this study. A complete description of the methodology required for this optimization method is introduced here, where the parameterization of the geometry to be optimized and the metamodel used to speed up the optimization process are detailed. A reduction of about a 25% of the initial aerodynamic drag is obtained in this study, what confirms GA as a proper method for this optimization problem. The evolution of the nose shape is consistent with the literature. The advantage of using metamodels is stressed thanks to the information of the whole design space extracted from it. The influence of each design variable on the objective function is analyzed by means of an ANOVA test.

Automated incident management plan using geographic information systems technology for traffic management centers. Final report.

Texas Department of Transportation, Austin

Integration of in-vehicle electronics for IVHS and the electronics for other vehicle systems. Summary report.

National Highway Traffic Safety Administration, Washington, D.C.

Integration of in-vehicle electronics for IVHS and the electronics for other vehicle systems.

National Highway Traffic Safety Administration, Washington, D.C.

Human factors requirements for real-time motorist information displays. Volume 6: questionnaire survey of motorist route selection criteria. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

Evaluation of warning and information systems. Part II, commercial radio advisories. Final report.

Federal Highway Administration, Washington, D.C.

Human factors requirements for real-time motorist information displays. Volume 2: state-of-the-art: messages and displays in freeway corridors. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

Human factors requirements for real-time motorist information displays. Vol. 1 - design guide. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

The role of management incentives in successful information systems development and implementation

Because organizations are making large investments in Information systems (IS), efficient IS project management has been found critical to success. This study examines how the use of incentives can improve the project success. Agency theory is used to: identify motivational factors of project success, help the IS owners to understand to what extent management incentives can improve IS development and implementation (ISD/I). The outcomes will help practitioners and researchers to build on theoretical model of project management elements which lead to project success. Given the principal-agent nature of most significant scale of IS development, insights that will allow for greater alignment of the agent’s goals with those of the principal through incentive contracts, will serve to make ISD/I both more efficient and more effective, leading to more successful IS projects.

Optimal design of a regenerative dynamic dynamometer using genetic algorithms

This paper presents an approach for optimal design of a fully regenerative dynamic dynamometer using genetic algorithms. The proposed dynamometer system includes an energy storage mechanism to adaptively absorb the energy variations following the dynamometer transients. This allows the minimum power electronics requirement at the mains power supply grid to compensate for the losses. The overall dynamometer system is a dynamic complex system and design of the system is a multi-objective problem, which requires advanced optimisation techniques such as genetic algorithms. The case study of designing and simulation of the dynamometer system indicates that the genetic algorithm based approach is able to locate a best available solution in view of system performance and computational costs.