Optimisation of policies for transport integration in metropolitan areas: report on work packages 30 and 40

The overall objectives of Project OPTIMA are:- (i) to identify optimal urban transport strategies for a range of urban areas within the EU; (ii) to compare the strategies which are specified as optimal in different cities, and to assess the reasons for these differences; (iii) to assess the acceptability and feasibility of implementation of these strategies both in the case study cities and more widely in the EU, and (iv) to use the results to provide more general guidance on urban transport policy within the EU. There is a wide range of objectives of transport policy in urban areas, but most can be grouped under the broad headings of economic efficiency, including economic development, on the one hand, and sustainability, including environment, safety, equity and quality of life, on the other. It is now generally accepted that the overall strategy for achieving these objectives must include an element of reduction of private car use and transfer of travel to other modes. The policy instruments for achieving these objectives can include infrastructure provision, management measures to enhance other modes and to restrict car use, and pricing measures to make public transport more attractive and to increase the marginal cost of car use. It is now widely accepted that the most appropriate strategy will involve several of these measures, combined in an integrated way which emphasises the synergy between them. The most appropriate strategy for a city will depend on its size, the current built form, topography, transport infrastructure and patterns of use; levels of car ownership, congestion and projected growth in travel; transport policy instruments already in use; and the acceptability of other measures in political and legislative terms. These will differ from city to city. Policy advice cannot therefore be generalised, but must be developed for a range of different types of city. This is the approach adopted in this study, in which nine different cities in five countries (Edinburgh, Merseyside, Vienna, Eisenstadt, Trams@, Oslo, Helsinki, Torino and Salerno) have been studied in detail, using a common study methodology. This report summarises the output of two work packages in OPTIMA: WP30: Test Combinations of Policy Instruments WP40: Identify Optim

Improving the capabilities and use of strategic decision making tools.

Recent research has shown that a substantial proportion of local authorities do not use models for strategy formulation or scheme design and appraisal. Models were perceived to be unable to reflect the range of policy instruments which local authorities now use; and were seen as too complex for local authority staff and stakeholders to use themselves. To overcome these issues the MARS model has been enhanced to provide a transparent and easy to use tool with a flight simulator front-end. This paper describes the model along with improvements to the representation of public transport by inclusion of quality and crowding factors and the incorporation of urban heavy rail

Designing optimal urban transport strategies : the role of individual policy instruments and the impact of financial constraints

This paper presents a methodology for the design of optimal transport strategies and the case study results of the methodology for the City of Edinburgh, using the two multi-modal transport/land-use models MARS and TPM. First, a range of policy instruments are optimised in turn and their relative impacts explored. Second, optimisations with and without financial constraints are performed and compared. Although both models produce similar optimal policies, the relative contribution of the instruments differs between models as does the impact on outcome indicators. It is also shown that by careful design it is possible to identify a strategy which costs no more than the do-minimum but which can generate substantial additional benefits. The optimisation methodology is found to be robust, and is able to be used with different transport models, and with and without financial constraints

A Systemic Analysis of Impacts of Individual and Shared Automated Mobility in Austria

Rationale: Increasing digitalization and automation is expected to significantly change the transport system, mobility and settlement structures. A decade ago automated, self-driving vehicles were nothing more than an unrealistic (boyhood) dream. But today the concept of highly and fully automated vehicles is rapidly becoming a reality, with a series of real-world trial applications underway. Government plans and industry predictions expect automation to be introduced from the early 2020s onwards. Nevertheless, there is still a high level of uncertainty in which form and to what extent automated vehicles will enter the market. Furthermore, there are ongoing discussions concerning net effects of positive and negative aspects of automation. Background: The authors have been involved in several research projects analyzing potential impacts of automated driving. The EU funded project CityMobil (Towards Advanced Road Transport for the Urban Environment) was one of first to address automated driving on a large scale. As part of this project the System Dynamics based model MARS (Metropolitan Activity Relocation Simulator) was adapted to assess scenarios of automated driving in four European cities. Simulations demonstrated that automated vehicles integrated into public transport have a potential to reduce car kilometers travelled and improve carbon footprint. On the contrary, privately owned automated vehicles lead to an increase in car kilometers travelled and carbon footprint, unless propulsion technology is changed. While the focus of CityMobil was on the urban scale, the nationally funded Austrian project Shared Autonomy (Potential Effects of the Take-up of Automated Vehicles in Rural Areas – own translation) focused on rural areas. The findings of Shared Autonomy show potential contributions of automated cars to improve the environmental situation and social inclusion in rural areas. Finally, the nationally funded Austrian project SAFiP (System Scenarios Automated Driving in Personal Mobility) takes a look at the national territory of Austria. Method: The relationship between vehicle automation, travel demand and environmental effects consists of a multitude of complex cause-effect-chains. The toolbox of System Dynamics offers appropriate methods to tackle such complexities. Causal Loop Diagrams are used to analyze and discuss relevant cause-effect-chains and are used to adapt an existing Stock-Flow-Model of the Austrian land use and transport demand system. The modified Stock-Flow-Model is used for a quantitative impact assessment. Sensitivity analysis in form of Monte-Carlo-Simulations is employed to tackle the high level of uncertainty concerning key factors. Findings, results: The key factors, influencing mode choice and travel demand, are generalized costs of travel time, weighted costs of use and availability. The automation of driving, expressed as the share of highly and fully automated vehicles in the fleet, is influencing all three key factors via different cause-effect-chains and feedback loops. In SAFiP we identified four key impact sources: automated and remote parking, road capacity and travel speed, value of in-vehicle time and widening the range of users. Sensitivity tests for each of the impact sources have been carried out. Widening the range of users has the highest impact on a national level, potentially increasing car kilometers by about 17 percent in 2050. Remote parking increases car kilometers by about 5 percent in total, ranging from about 1 percent in peripheral districts to about 17 percent in Vienna

Bioclimatic analysis in a region of southern Italy (Calabria)

In this study, an analysis of precipitation and temperature data has been performed over 67 series observed in a region of southern Italy (Calabria). At first, to detect possible trends in the time series, an analysis was performed with the Mann–Kendall non-parametric test applied at monthly and seasonal scale. An additional investigation, useful for checking the climate change effects on vegetation, has also been included analysing bioclimatic indicators. In particular, Emberger, Rivas-Martinez and De Martonne indices were calculated by using monthly temperature and precipitation data in the period 1916–2010. The spatial pattern of the indices has been evaluated and, in order to link the vegetation and the indices,different indices maps have been intersected with the land cover data, given by the Corine Land Cover map. Moreover, the temporal evolution of the indices and of the vegetation has been analysed. Results suggest that climate change may be responsible for the forest cover change, but, given also the good relationship between the various types of bioclimate and forest formations, human activities must be considered

Software Compensation for Highly Granular Calorimeters using Machine Learning

A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied

The eROSITA X-ray telescope on SRG

eROSITA (extended ROentgen Survey with an Imaging Telescope Array) is the primary instrument on the Spectrum-Roentgen-Gamma (SRG) mission, which was successfully launched on July 13, 2019, from the Baikonour cosmodrome. After the commissioning of the instrument and a subsequent calibration and performance verification phase, eROSITA started a survey of the entire sky on December 13, 2019. By the end of 2023, eight complete scans of the celestial sphere will have been performed, each lasting six months. At the end of this program, the eROSITA all-sky survey in the soft X-ray band (0.2-2.3 keV) will be about 25 times more sensitive than the ROSAT All-Sky Survey, while in the hard band (2.3-8 keV) it will provide the first ever true imaging survey of the sky. The eROSITA design driving science is the detection of large samples of galaxy clusters up to redshifts z > 1 in order to study the large-scale structure of the universe and test cosmological models including Dark Energy. In addition, eROSITA is expected to yield a sample of a few million AGNs, including obscured objects, revolutionizing our view of the evolution of supermassive black holes. The survey will also provide new insights into a wide range of astrophysical phenomena, including X-ray binaries, active stars, and diffuse emission within the Galaxy. Results from early observations, some of which are presented here, confirm that the performance of the instrument is able to fulfil its scientific promise. With this paper, we aim to give a concise description of the instrument, its performance as measured on ground, its operation in space, and also the first results from in-orbit measurements

Detector Technologies for CLIC

The Compact Linear Collider (CLIC) is a high-energy high-luminosity linear electron-positron collider under development. It is foreseen to be built and operated in three stages, at centre-of-mass energies of 380 GeV, 1.5 TeV and 3 TeV, respectively. It offers a rich physics program including direct searches as well as the probing of new physics through a broad set of precision measurements of Standard Model processes, particularly in the Higgs-boson and top-quark sectors. The precision required for such measurements and the specific conditions imposed by the beam dimensions and time structure put strict requirements on the detector design and technology. This includes low-mass vertexing and tracking systems with small cells, highly granular imaging calorimeters, as well as a precise hit-time resolution and power-pulsed operation for all subsystems. A conceptual design for the CLIC detector system was published in 2012. Since then, ambitious R&D programmes for silicon vertex and tracking detectors, as well as for calorimeters have been pursued within the CLICdp, CALICE and FCAL collaborations, addressing the challenging detector requirements with innovative technologies. This report introduces the experimental environment and detector requirements at CLIC and reviews the current status and future plans for detector technology R&D.Comment: 152 pages, 116 figures; published as CERN Yellow Report Monograph Vol. 1/2019; corresponding editors: Dominik Dannheim, Katja Kr\"uger, Aharon Levy, Andreas N\"urnberg, Eva Sickin