Informe del World Library and Information Congress: 73rd IFLA General Conference and Council (Durban, Sud-àfrica, 19-23 d'agost de 2007)

This year, IFLA's World Library and Information Congress (WLIC) was held in Durban, South Africa, under the title ¿Libraries for the future: progress, development and partnerships¿. The association thus continued its policy of holding the event in different continents: Buenos Aires (South America) 2004, Oslo (Europe) 2005, Seoul (Asia) 2006, Durban (Africa) 2007, Quebec (North America) 2008, Milan (Europe) 2009 and Brisbane (Oceania) 2010.

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Simulating fuel consumption and vehicle emissions in an Australian context

Road transport is a major source of air pollution and greenhouse gas emissions around the world. There is an increasing interest in accurate information on local vehicle emission levels for policy development and sustainable traffic management. Previous studies have shown that emission predictions for the Australian situation need to reflect both the Australian fleet and driving behaviour to avoid unreliable outcomes. This paper discusses a new Australian vehicle emission software (PΔP) and a case-study where traffic simulation software (Aimsun) is combined with PΔP to demonstrate how consistent results can be achieved for the Australian situation. The case-study is an Australian city modelled using the microscopic simulator to generate the required trajectory data of each individual vehicle for the emission model. The simulation results are used in a number of ways: to assess the impacts of urban driving behaviour on fuel consumption, to create maps showing where and when elevated emission levels occur and to compare results with another program (COPERT Australia). The paper will also discuss where further research is required.