Prioritizing public transport is one of the most effective measure to increase the attractiveness and competitiveness of public transport in relation to individual vehicles. The main goal of this study was to examine the possibilities for reducing the travel time of tram vehicles by giving priority at signalized intersections in terms of sharing the traffic lane with personal vehicles and under conditions of strong conflict flows with private transport. For this purpose, we used the simulation tool VISSIM and its module EPICS. A methodology for determining weighting factors for prioritizing public transport flows was developed based on conflicting passenger flows in public transport vehicles and passenger cars. Three scenarios were tested in the study area: (1) “do nothing”; (2) unconditional priority; and (3) conditional priority. The results showed that unconditional priority led to unsustainable traffic conditions for personal vehicles and public transport. In contrast, conditional priority reduced the travel time of public transport on certain corridors by between 7.64% and 18.76% in the morning peak period, and 5.60% to 22.50% in the afternoon peak period.

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This research aims to assess available spatial open data related to access to hospitals in the three largest Croatian cities (Zagreb, Split, Rijeka), with a future aim to create digital services as an ecosystem that will be used in everyday situations, as part of the concept of “digital society”. Data analysis is performed for the following datasets: hospitals, hospital specialization, public transport (tram, bus), bike routes, car routes, parking and parking for people with disabilities. The future aim is to create a new mobile, multilingual and voice-based application that would enable quick access to information on hospital access, relying on the principles of the open data ecosystem, which would improve over time. There are four specific aims: (1) to identify and analyze portals and open datasets of the selected categories for the three largest Croatian cities; (2) to analyze existing open data assessment frameworks and detect gaps; (3) to create a conceptual open data assessment framework as an open data ecosystem that integrates new end-user perspectives; and (4) to analyze existing open datasets for the three largest cities in Croatia, based on supply and demand by researcher/developer categories, using the newly developed framework. The results show that existing open datasets related to hospital access in the three largest Croatian cities are scattered across different portals. Analyzed frameworks existing on the supply side of open data are more focused on the status of the components, lacking evaluation scales and not including end-user-driven aspects, which would be crucial for the open data ecosystem. As a result, the new “Hospital Access Framework” is created as a conceptual ecosystem, including five categories: supply, demand by researcher/developer, demand by end-user, legal aspect and impact. Analysis of existing open data for the three Croatian cities is performed for two categories (supply and demand by researcher/developer), for which KPIs, indicators and evaluation scales are developed. The other three categories are not analyzed, since the application cannot be developed from existing data, which are insufficient for the creation of a smart application. Results show that existing open data related to hospital access are incomplete or do not exist at all (hospital specialization, parking for people with disabilities, data on multilingualism and voice enabling). Average scores of the supply category are higher than those for demand by researcher/developer, although they are below the average grade, showing a lack of available data that could be used for further development. The new conceptual “Hospital Access Framework” open data ecosystem would benefit from end-user interaction, therefore, improving over time with end-users through interaction.

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