Towards an integrated urban development considering novel intelligent transportation systems

Richter, Andreas; Löwner, Marc-Oliver; Ebendt, Rüdiger; Scholz, Michael

doi:10.1016/j.techfore.2020.119970

Cited by 45 publications

(19 citation statements)

References 26 publications

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“…In fact, one issue, which is particularly pertinent to the use of DT for simulating urban freight distribution in a planning context, relates to data types and stakeholder preferences. Richter et al [23] critically discuss and illustrate data-related challenges and a possible solution to the problem with respect to the issues urban areas are currently facing due to the challenges urbanisation, passenger transport, logistics, maintenance of complex traffic and supply infrastructure are posing when considering the limited space and resources available. In fact, different stakeholders including, among others, governmental actors, road operators, fleet managers, car manufacturers and private companies in general are interested in using detailed, precise and up-to-date data.…”

Section: Structure and Usementioning

confidence: 99%

Digital Twins: A Critical Discussion on Their Potential for Supporting Policy-Making and Planning in Urban Logistics

et al. 2020

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Poor logistics efficiency, due to low load factors caused by high demand fragmentation, will have relevant negative consequences for cities in terms of pollution, congestion and overall city liveability. Policy-makers should equip themselves with appropriate tools to perform reliable, comprehensive and timely analyses of urban logistics scenarios, also considering upcoming (i) technological changes, (ii) business model evolutions and (iii) spatial-temporal changes these innovations will produce. This paper discusses the Digital Twin (DT) concept, illustrating the role it might play and clarifying how to properly conceive it with respect to urban freight transport policy-making and planning. The main message is that without a sound theory and knowledge with respect to the relationships linking contextual reality and choice/behaviour, it is not possible to make sense of what happens in the real world. Therefore, the joint use of behavioural and simulation models should characterise a DT within a Living Lab approach so to stimulate effective, well-informed and participated planning processes, but also to forecast both behaviour and reactions to structural changes and policy measures implementations.

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Section: Structure and Usementioning

confidence: 99%

Digital Twins: A Critical Discussion on Their Potential for Supporting Policy-Making and Planning in Urban Logistics

et al. 2020

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“…In the course of this process, OpenDRIVE datasets are transformed to CityGML datasets and used for generating a pedestrian simulation scenario. Richter et al [47] analyze the requirements to the development and test of automated driving systems using virtual city and traffic models and propose a concept for an integrated urban development framework. Strassenburg-Kleciak [36] stated that information on street edges can be used in order to increase driving safety.…”

Section: Automotive Applicationsmentioning

confidence: 99%

Detailed Streetspace Modelling for Multiple Applications: Discussions on the Proposed CityGML 3.0 Transportation Model

Beil

Ruhdorfer²,

Coduro³

et al. 2020

IJGI

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In the context of smart cities and digital twins, three-dimensional semantic city models are increasingly used for the analyses of large urban areas. While the representation of buildings, terrain, and vegetation has become standard for most city models, detailed spatio-semantic representations of streetspace have played a minor role so far. This is now changing (1) because of data availability, and (2) because recent and emerging applications require having detailed data about the streetspace. The upcoming version 3.0 of the international standard CityGML provides a substantially updated data model regarding the transportation infrastructure, including the representation of the streetspace. However, there already exist a number of other standards and data formats dealing with the representation and exchange of streetspace data. Thus, based on an extensive literature review of potential applications as well as discussions and collaborations with relevant stakeholders, seven key modelling aspects of detailed streetspace models are identified. This allows a structured discussion of representational capabilities of the proposed CityGML3.0 Transportation Model with respect to these aspects and in comparison to the other standards. Subsequently, it is shown that CityGML3.0 meets most of these aspects and that streetspace models can be derived from various data sources and for different cities. Models generated compliant to the CityGML standard are immediately usable for a number of applications. This is demonstrated for some applications, such as land use management, solar potential analyses, and traffic and pedestrian simulations.

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“…The ability to accurately predict the future is essential for decision processes in many scientific areas and real applications, let it be the planning, organizing, strategy formulation, policy-making, and so on [1,2]. Thus, particularly in the last few decades, time series (TS) forecasting has become a stimulating research matter with mounting attention to various areas [3][4][5][6] The capability to provide accurate forecasts is also significant in the field of broader planning of any essential road transport projects and investments. In this context, the planning of potential strategies must also take into consideration the accurate forecasting of future trends in freight transport.…”

Section: Introductionmentioning

confidence: 99%

Road Freight Transport Forecasting: A Fuzzy Monte-Carlo Simulation-Based Model Selection Approach

et al. 2022

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As important as the classical approaches such as Akaikeꞌs AIC information and Bayesian BIC criterion in model-selection mechanism are, they have limitations. As an alternative, a novel modeling design encompasses a two-stage approach that integrates Fuzzy logic and Monte Carlo simulations (MCSs). In the first stage, an entire family of ARIMA model candidates with the corresponding information-based, residual-based, and statistical criteria is identified. In the second stage, the Mamdani fuzzy model (MFM) is used to uncover interrelationships hidden among previously obtained modelsꞌ criteria. To access the best forecasting model, the MCSs are also used for different settings of weights loaded on the fuzzy rules. The obtained model is developed to predict the road freight transport in Slovenia in the context of choosing the most appropriate electronic toll system. Results show that the mechanism works well when searching for the best model that provides a well-fit to the real data.

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Towards an integrated urban development considering novel intelligent transportation systems

Cited by 45 publications

References 26 publications

Digital Twins: A Critical Discussion on Their Potential for Supporting Policy-Making and Planning in Urban Logistics

Digital Twins: A Critical Discussion on Their Potential for Supporting Policy-Making and Planning in Urban Logistics

Detailed Streetspace Modelling for Multiple Applications: Discussions on the Proposed CityGML 3.0 Transportation Model

Road Freight Transport Forecasting: A Fuzzy Monte-Carlo Simulation-Based Model Selection Approach

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