The Impact of Intelligent Transportation System Implementations on the Sustainable Growth of Passenger Transport in EU Regions

Stawiarska, Ewa; Sobczak, Paweł

doi:10.3390/su10051318

Cited by 25 publications

(13 citation statements)

References 25 publications

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“…Next, basic network parameters were calculated using Gephi in accordance with formulas described by other authors (Newman, 2010;Sobczak, 2017; Engineering Management in Production and Services Stawiarska & Sobczak, 2018;Tarapata, 2015). Due to a large volume of calculated data (202 nodes/stops) in Tab.…”

Section: Research Resultsmentioning

confidence: 99%

“…Of course, the following relationship applies to every analysed network: & Wilkinson, 2017;Li et al, 2014;Newman, 2010;Ouyang et al, 2015;Rual et al, 2005;Sporns, 2002;Stam & Reijneveld, 2007;Tarapata, 2015;Valverde & Solé, 2003;Wilkinson et al, 2012) transport networks can be analysed using a group of meters that allow obtaining information regarding the characteristics of the analysed network. The meters used to calculate the parameters of individual network nodes and the entire network are also described in publications by other authors (Stawiarska & Sobczak, 2018;Newman, 2010;Sobczak, 2017;Tarapata, 2015).…”

Section: Graph Theory In Network Analysis Including Transport Networkmentioning

confidence: 99%

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Logistics management of the rail connections using graph theory: the case of a public transportation company on the example of Koleje Dolnośląskie S.A.

Sobczak

Stawiarska

Oláh

et al. 2018

Engineering Management in Production and Services

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The main purpose of the paper was the structural analysis of the connections network used by a railway carrier Koleje Dolnośląskie S.A. operating in southern Poland. The analysis used simulation methods. The analysis and simulation were based on graph theory, which is successfully used in analysing a wide variety of networks (social, biological, computer, virtual and transportation networks). The paper presents indicators which allow judging the analysed connections network according to an appropriate level of transport services. Simulation results allowed proposing some modifications for the improvement of the analysed connections network. The paper also demonstrates that graph theory and network simulations should be used as tools by transportation companies during the stage of planning a connections network.

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Section: Research Resultsmentioning

confidence: 99%

Section: Graph Theory In Network Analysis Including Transport Networkmentioning

confidence: 99%

Logistics management of the rail connections using graph theory: the case of a public transportation company on the example of Koleje Dolnośląskie S.A.

Sobczak

Stawiarska

Oláh

et al. 2018

Engineering Management in Production and Services

Self Cite

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“…Vehicle manufacturers-supply chain integrators implement Green Supply Chain Management (GSCM), European Supply Chain Management (ESCM), and Electronic Supply Chain Management (e-SCM) concepts. Industry 4.0 solutions dedicated to green supply chains have been described [104][105][106][107][108]. The level of maturity in implementing Industry 4.0 solutions and, at the same time, the intensity of CSR activities was dealt with [109].…”

Section: Symptoms Of Implementing Industry 40 In Socially Responsible Corporationsmentioning

confidence: 99%

Diagnosis of the Maturity Level of Implementing Industry 4.0 Solutions in Selected Functional Areas of Management of Automotive Companies in Poland

et al. 2021

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The automotive sector is one of the key branches of the global economy. The automotive industry is also a very important sector of the Polish economy, as it generates over 8% of GDP and accounts for over 20% of the annual export value. Industry 4.0 and the effective use of modern technologies give a chance for its further dynamic development. The implementation of Industry 4.0 solutions in the business processes of automotive companies should not only take place in the area of production or logistics, as it is usually indicated, but also in their other functional areas, such as quality management, human resources management, and innovation management. The purpose of the article is to diagnose the level of maturity in the implementation of Industry 4.0 solutions in selected management areas of automotive companies operating in Poland. Using a maturity assessment tool, the authors assessed the level of maturity in six selected functional areas of an enterprise, such as production and logistics management, quality management, human resources management, social and environmental responsibility, and product innovation management. The authors also formulated conclusions and recommendations concerning actions that should be taken by automotive companies in order to achieve higher maturity levels in the implementation of Industry 4.0 solutions.

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“…The usage of intelligent transportation systems (ITSs) is motivated in a significant part by passenger increases and sustainable development [ 1 , 2 ]. The ITS has a direct impact on energy consumption, personal living expenses, public health and safety.…”

Section: Introductionmentioning

confidence: 99%

Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys

Shen

2020

Sensors

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Travel time prediction is critical for advanced traveler information systems (ATISs), which provides valuable information for enhancing the efficiency and effectiveness of the urban transportation systems. However, in the area of bus trips, existing studies have focused on directly using the structured data to predict travel time for a single bus trip. For state-of-the-art public transportation information systems, a bus journey generally has multiple bus trips. Additionally, due to the lack of study on data fusion, it is even inadequate for the development of underlying intelligent transportation systems. In this paper, we propose a novel framework for a hybrid data-driven travel time prediction model for bus journeys based on open data. We explore a convolutional long short-term memory (ConvLSTM) model with a self-attention mechanism that accurately predicts the running time of each segment of the trips and the waiting time at each station. The model is more robust to capture long-range dependence in time series data as well.

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The Impact of Intelligent Transportation System Implementations on the Sustainable Growth of Passenger Transport in EU Regions

Cited by 25 publications

References 25 publications

Logistics management of the rail connections using graph theory: the case of a public transportation company on the example of Koleje Dolnośląskie S.A.

Logistics management of the rail connections using graph theory: the case of a public transportation company on the example of Koleje Dolnośląskie S.A.

Diagnosis of the Maturity Level of Implementing Industry 4.0 Solutions in Selected Functional Areas of Management of Automotive Companies in Poland

Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys

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