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In recent research the CONDUITS performance evaluation framework for traffic management and Intelligent Transport Systems (ITS) was developed, consisting of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion. Follow-up work has concentrated on integrating the developed CONDUITS KPIs with microscopic traffic simulation. The outcome has been a predictive evaluation tool for traffic management and ITS, called CONDUITS_DST, in which two of the four KPI categories have been integrated previously: pollution and traffic efficiency. The objective of the present study is to further extend the predictive evaluation framework to include the theme of traffic safety. Contributing to the development of the CONDUITS_DST traffic safety module, the paper identifies and proposes relevant models and metrics linking traffic characteristics with road safety impacts. In doing so, it enables the extraction of the necessary input data for each of the three CONDUITS KPIs for traffic safety (accidents, direct impacts, and indirect impacts) directly from microscopic traffic simulation models. The proposed models and metrics are tested in conjunction with the relevant CONDUITS KPIs for safety using data from simulation models before and after the implementation of a bus priority signalling system in Brussels. Testing takes place both at the network level, but also at the level of individual links, and the results show that the framework is able to capture the expected safety impacts adequately well, paving the way towards its implementation is the traffic safety module of CONDUITS_DST.

Abstract:In recent research a performance evaluation framework for traffic management and Intelligent Transport Systems was developed, consisting of a set of Key Performance Indicators (KPIs) for the themes of traffic efficiency, safety, pollution reduction and social inclusion, all of which are key components of a smart city. One of the innovative elements of these KPIs is their ability to consider the transport policy layer, in the sense that the evaluation of the suitability and effectiveness of different strategies and ITS options is calculated in relation to the decision maker's high-level transport policy rather than objectively. This is achieved through weighting factors, whereby more important policy objectives are weighted more heavily in the calculation. But while the theoretical framework is ready to accommodate the policy layer, no methodology to determine the values of the weighting factors has been developed so far. The present study, therefore, concentrates on the development and testing of such a methodology, focusing on the environmental impact aspect of urban mobility management and ITS in the context of smart cities. The development is based on existing policy objectives and legislation in different cities and countries, while testing is carried out using the purposedeveloped CONDUITS_DST software with data from microsimulation models before and after the implementation of a bus priority signalling system in Brussels, Belgium. The results show that the method captures the expected effects, but also that it is able to reflect policy objectives and deliver evaluation results in relation to their alignment with those.

One characteristic that is highly desired in transportation-related applications, and particularly journey planners, is transferability -i.e., the capacity to be used with minimal modification in different locations. To achieve transferability, the initial design must take into account all factors that may diverge between locations, including existing modes of transport, the availability of required data, the technological habits of users, etc. In consequence, a highly transferable system is difficult and expensive to develop and maintain. A very flexible initial design, one ensuring low-cost adaptability of the system for different cities, regions, or countries, might not be cost-effective. On the other hand, a rigid design, tailored for a specific location, might act as a barrier to implementing the system elsewhere. This dilemma has motivated researchers to seek a structured process for selecting the most promising design, one that will realize the benefits of transferability while minimizing development costs. One of the fundamental building blocks of structured design in SE is requirements-design exploration. This paper evaluates the use of Multi-Attribute Tradespace Exploration (MATE), a leading design exploration process, for the effective design of journey planners. We examine the process of changeability assessment (e.g., transferability) in light of the goals of journey planning from the point of view of different stakeholders: travelers, private developers, and transport authorities. The analysis demonstrates how tradespace exploration can also be used to identify specific designs that bridge the gap between the public and private sectors and provide value over time to all parties. Moreover, when specific concerns of public authorities are not met, tradespace exploration can reveal measures the public sector can take (financial or others) for making their preferred design attractive to the private sector as well.

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