Abstract

The main impetus for this report (and for the reports prepared for the other six growth poles) is a request received from the Ministry of Regional Development and Public Administration. The request came within the context of on-going preparations for the 2014-2020 Programming period, with Energy Efficiency being one the major themes of the Europe 2020 strategy, and a critical priority for all EU Member Countries. Within Romania, local authorities that will want to access energy efficiency funds under the 2014-2020 Regional Operational Program will need to first prepare energy efficiency strategies. The TRACE tool is specifically targeted at local authorities, and is a good instrument for drafting such strategies. After the 1989 Revolution, Romania began its transition from a centralized system to a market-based economy. Today the country is a member of the European Union (EU) and NATO. After more than a decade of economic restructuring and political change, the country has taken significant steps toward catching up with the economic performance of more developed EU countries. Although radical reforms brought about significant changes in recent years, the standard of living of Romanians is still behind the EU average. The transition period after the end of the communist regime has led to significant changes in the social and economic life of the residents of Craiova. Some of these developments have positively affected people's life, whereas a few came along with inconveniences and difficulties. During the first years of transition the city attracted people from parts of Dolj County and from elsewhere in Romania. This process led to severe de-population in the rural areas of Dolj County. At the same time, due to economic constraints, some of the urban population of Craiova moved to the wider metropolitan area. Like every other city in the country, municipal buildings in Craiova require proper measures toward improving energy efficiency - particularly in health care and education facilities managed by the city government. A benchmarking of the municipal building stock, along with audit and retrofit measures, should be performed in order to identify the highest energy savings potential and proper intervention measures. As for the water sector, although the system covers the entire city and most of the households in Craiova have water meters, there are high losses in the network. In addition, in order to improve the overall efficiency of the water system, oversized pumps needs to be replaced with smaller, energy-efficient ones. Finally, although selective collection has been implemented in Craiova, there is more that can be done about improving recycling rates. Document type: Book

Abstract

ISTS 2014 - 4th International Symposium of Transport Simulation, Ajaccio, FRANCE, 01-/06/2014 - 04/06/2014; Buses on the same route tend to bunch when the system is uncontrolled. This lack of regularity leads to an increase in the average passenger waiting time, increases delays and makes travel times uncertain. A wide variety of solutions have been proposed to maintain accurate bus system performance. Unfortunately, if a strategy is applied permanently, it could detract from the entire transport system efficiency. That is why a transit operator needs an accurate forecast of the route in order to intervene before the bus route is too disrupted to be restored to regularity. This paper aims to predict critical situations in real-time forecasting of a bus route state. To accomplish this, we propose to take advantage of both theoretical and empirical information (model and data) using data assimilation (a particle filter). On one hand, a stochastic dynamic bus model forecasts future bus route states. On the other hand, archived data calibrates the model parameters while real-time data provides information about the actual route state. The methodology is applied to a real case study thanks to the quality data provided by TriMet (the Portland, Oregon transit district). Predictions are finally evaluated by an a posteriori comparison with real data. The results highlight that the method leads to a valid forecast of a bus route state with a 8 minutes time window. This duration is sufficient to predict critical situations, especially bus bunching. Further research would have to consider deterministic travel times from a traffic model instead of the distributions in order to maintain correlation between travel times on links. In that case, the assimilation process would focus on the surrounding traffic flow, also potentially available in the Portland data.