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Dr. Loukas Dimitriou
University of Cyprus, Department of Civil and Environmental Engineering

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0 Transporatation Engineering
0 Transport and energy/environment
0 Transport policy and planning
0 Transportation and mobility systems
0 Transport & Logistics

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Journal article
Published: 02 July 2021 in Maritime Transport Research
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The growing competition among container port terminals enhances the pressure for optimizing their efficiency level in the performance of containers’ service. Comparing container terminals based on their performance is a complicated task due to the variety of ports’ type, scale, and service configuration. This however is an important task in the efforts of improving not only national trade transportation but also the global trade system, since valuable best practices can be identified and adopted among container terminals. Notwithstanding, available information about container port terminals’ efficiency level, based on their performance measured by the service of Twenty-foot Equivalent Units (TEUs), is yet incomplete due to the lack of information about which factors influence their efficiency the most. This additional information will support the decision-making processes of container terminals’ authorities to direct their focus on specific factors that will improve their efficiency. This paper investigates the efficiency of the top-50 global container port terminals that service the global freight supply chain in a period of 5 years (2013-2017) through a two-step procedure. First, a benchmarking analysis, namely, Data Envelopment Analysis, is implemented to estimate the efficiency level of the container port terminals. The second step involves the methodology followed in this paper which is further expanded to quantify the effects that different factors have on container terminals efficiency through the implementation of suitable Tobit regression models. The findings of this paper identify the benchmark container terminals that should be taken as examples for under-performing container port terminals and also points out the factors that must be enhanced for improving global trade system, like, number of cranes, terminal space and quay lenght.

ACS Style

Paraskevas Nikolaou; Loukas Dimitriou. Lessons to be Learned from Top-50 Global Container Port Terminals Efficiencies: A Multi-Period DEA-Tobit Approach. Maritime Transport Research 2021, 2, 100032 .

AMA Style

Paraskevas Nikolaou, Loukas Dimitriou. Lessons to be Learned from Top-50 Global Container Port Terminals Efficiencies: A Multi-Period DEA-Tobit Approach. Maritime Transport Research. 2021; 2 ():100032.

Chicago/Turabian Style

Paraskevas Nikolaou; Loukas Dimitriou. 2021. "Lessons to be Learned from Top-50 Global Container Port Terminals Efficiencies: A Multi-Period DEA-Tobit Approach." Maritime Transport Research 2, no. : 100032.

Journal article
Published: 21 April 2021 in Journal of Transport Geography
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Cities around the world are moving away from the car-centric infrastructure, urban design and planning policies prevalent since the 1950s and promoting sustainable mobility as an alternative, including cycling. As such, Bicycle Sharing Systems (BSS) have emerged as a transport innovation across the globe. Cycling modal share however remains low in most Southern European island cities. These cities exhibit certain characteristics considered as barriers to cycling, such as hot summers and high humidity, hilliness, and car-oriented culture and infrastructure. Despite this, BSS and policies promoting cycling have emerged in this region as well. These have the potential to provide alternatives for those marginalized by car-based mobility and to reduce traffic related diseases and injuries, noise and air pollution, which can contribute to an improved quality of life for all citizens. Using the Mediterranean island city of Limassol (Cyprus) as a case study, the utilization of bicycle sharing is investigated by constructing regression models to assess the influence of spatial and temporal factors on the demand for BSS use at stations. From the regression models it appears that land use factors such as residential, commercial and park land use, as well as the presence of the beach and cycling paths positively influences frequency of use, as does higher network connectivity. While higher tourist arrivals have a positive effect, the presence of hotels in a 300 m buffer around the stations does not. Higher rainfall, as well as higher temperatures, are associated with a decrease in BSS use. Explicitly incorporating spatial dependence, in Spatial Auto-Regressive (SAR) models, led to the formulation of models with comparable or better explanatory power, when compared to the Ordinary Least Squares (OLS) models. The insights from the regression models can be used to inform policies promoting cycling and the design and planning of BSS (expansion) in Limassol and other cities.

ACS Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. Spatial and temporal analysis of shared bicycle use in Limassol, Cyprus. Journal of Transport Geography 2021, 93, 103049 .

AMA Style

Suzanne Maas, Paraskevas Nikolaou, Maria Attard, Loukas Dimitriou. Spatial and temporal analysis of shared bicycle use in Limassol, Cyprus. Journal of Transport Geography. 2021; 93 ():103049.

Chicago/Turabian Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. 2021. "Spatial and temporal analysis of shared bicycle use in Limassol, Cyprus." Journal of Transport Geography 93, no. : 103049.

Journal article
Published: 16 March 2021 in Sustainability
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Bicycle sharing systems (BSSs) have been implemented in cities worldwide in an attempt to promote cycling. Despite exhibiting characteristics considered to be barriers to cycling, such as hot summers, hilliness and car-oriented infrastructure, Southern European island cities and tourist destinations Limassol (Cyprus), Las Palmas de Gran Canaria (Canary Islands, Spain) and the Valletta conurbation (Malta) are all experiencing the implementation of BSSs and policies to promote cycling. In this study, a year of trip data and secondary datasets are used to analyze dock-based BSS usage in the three case-study cities. How land use, socio-economic, network and temporal factors influence BSS use at station locations, both as an origin and as a destination, was examined using bivariate correlation analysis and through the development of linear mixed models for each case study. Bivariate correlations showed significant positive associations with the number of cafes and restaurants, vicinity to the beach or promenade and the percentage of foreign population at the BSS station locations in all cities. A positive relation with cycling infrastructure was evident in Limassol and Las Palmas de Gran Canaria, but not in Malta, as no cycling infrastructure is present in the island’s conurbation, where the BSS is primarily operational. Elevation had a negative association with BSS use in all three cities. In Limassol and Malta, where seasonality in weather patterns is strongest, a negative effect of rainfall and a positive effect of higher temperature were observed. Although there was a positive association between BSS use and the number of visiting tourists in Limassol and Malta, this is predominantly explained through the multi-collinearity with weather factors rather than by intensive use of the BSS by tourists. The linear mixed models showed more fine-grained results and explained differences in BSS use at stations, including differences for station use as an origin and as a destination. The insights from the correlation analysis and linear mixed models can be used to inform policies promoting cycling and BSS use and support sustainable mobility policies in the case-study cities and cities with similar characteristics.

ACS Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands. Sustainability 2021, 13, 3274 .

AMA Style

Suzanne Maas, Paraskevas Nikolaou, Maria Attard, Loukas Dimitriou. Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands. Sustainability. 2021; 13 (6):3274.

Chicago/Turabian Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. 2021. "Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands." Sustainability 13, no. 6: 3274.

Journal article
Published: 05 February 2021 in Accident Analysis & Prevention
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Traffic conflicts are heavily correlated with traffic collisions and may provide insightful information on the failure mechanism and factors that contribute more towards a collision. Although proactive traffic management systems have been supported heavily in the research community, and autonomous vehicles (AVs) are soon to become a reality, analyses are concentrated on very specific environments using aggregated data. This study aims at investigating –for the first time- rear-end conflict frequency in an urban network level using vehicle-to-vehicle interactions and at correlating frequency with the corresponding network traffic state. The Time-To-Collision (TTC) and Deceleration Rate to Avoid Crash (DRAC) metrics are utilized to estimate conflict frequency on the current network situation, as well as on scenarios including AV characteristics. Three critical conflict points are defined, according to TTC and DRAC thresholds. After extracting conflicts, data are fitted into Zero-inflated and also traditional Negative Binomial models, as well as quasi-Poisson models, while controlling for endogeneity, in order to investigate contributory factors of conflict frequency. Results demonstrate that conflict counts are significantly higher in congested traffic and that high variations in speed increase conflicts. Nevertheless, a comparison with simulated AV traffic and the use of more surrogate safety indicators could provide more insight into the relationship between traffic state and traffic conflicts in the near future.

ACS Style

Christos Katrakazas; Athanasios Theofilatos; Ashraful Islam; Eleonora Papadimitriou; Loukas Dimitriou; Constantinos Antoniou. Prediction of rear-end conflict frequency using multiple-location traffic parameters. Accident Analysis & Prevention 2021, 152, 106007 .

AMA Style

Christos Katrakazas, Athanasios Theofilatos, Ashraful Islam, Eleonora Papadimitriou, Loukas Dimitriou, Constantinos Antoniou. Prediction of rear-end conflict frequency using multiple-location traffic parameters. Accident Analysis & Prevention. 2021; 152 ():106007.

Chicago/Turabian Style

Christos Katrakazas; Athanasios Theofilatos; Ashraful Islam; Eleonora Papadimitriou; Loukas Dimitriou; Constantinos Antoniou. 2021. "Prediction of rear-end conflict frequency using multiple-location traffic parameters." Accident Analysis & Prevention 152, no. : 106007.

Journal article
Published: 03 February 2021 in Transportation Research Procedia
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According to the annual accident report (2018) of the European Commission it is clear that during the decade 2007-2016 fatalities by mode of transport have dropped significantly inside the European Union (EU). However, there is always a place for further improvements. It is also clear that the changes in the socio-economic and demographic context of the EU countries have reported impacts on the fatalities by different modes of transport and overall, to their road safety levels. Therefore, in order to support the road safety strategies of the EU countries that have an under-performing system (in terms of road safety levels), it is essential to incorporate exposure and socio-economic factors and provide a comparative analysis of the performances of EU countries. This paper aims the support of road safety policymakers by investigating the road safety performance of 18 EU countries over the time period 2007-2016 (incorporating their exposure level and socio-economic context) and measuring the effect that these factors have on the countries’ road safety performance. For the evaluation of the countries’ road safety performance, a benchmarking analysis was implemented, namely Data Envelopment Analysis (DEA). The resulted technical efficiency scores of the countries in relation to their exposure and socio-economic context were used in a censored regression framework, i.e., Tobit regression analysis, for measuring the extent of relation with road safety performance. Overall, this paper aims to provide a ‘picture’ of the road safety levels inside the EU region during the decade 2007-2016.

ACS Style

Paraskevas Nikolaou; Katerina Folla; Loukas Dimitriou; George Yannis. European Countries’ Road Safety Evaluation by Τaking Ιnto Αccount Multiple Classes of Fatalities. Transportation Research Procedia 2021, 52, 284 -291.

AMA Style

Paraskevas Nikolaou, Katerina Folla, Loukas Dimitriou, George Yannis. European Countries’ Road Safety Evaluation by Τaking Ιnto Αccount Multiple Classes of Fatalities. Transportation Research Procedia. 2021; 52 ():284-291.

Chicago/Turabian Style

Paraskevas Nikolaou; Katerina Folla; Loukas Dimitriou; George Yannis. 2021. "European Countries’ Road Safety Evaluation by Τaking Ιnto Αccount Multiple Classes of Fatalities." Transportation Research Procedia 52, no. : 284-291.

Journal article
Published: 03 February 2021 in Transportation Research Procedia
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Infrastructure databases have been widely used to obtain statistical deterioration models that assist decision makers in optimally allocating available budgets to maintain infrastructures in a functioning and at the same time safe state. Although infrastructure databases contain a plethora of information for the contained structure’s characteristics and structural condition, additional trusted data sources, should be used effectively to model environmental or other factors, which could affect deterioration rates. In most studies, the selection of deterioration factors is based on a small preselected set of factors or based on expert judgment. In this work, Artificial Neural Networks (ANN) and pattern recognition are used to capture structural deterioration information for bridges of the US National Bridge Inventory (NBI). A data-driven framework including Genetic Algorithms and ANNs, successfully utilized in other research fields, is proposed here in for simultaneously optimizing the architecture of an ANN and performing an unbiased variable selection process. The framework is applied to a large-scale bridge database and an initial selection of 52 variables. The results of the application are assessed for their accuracy and efficiency and show promising prospect for using GA-ANN pattern recognition for capturing bridge deterioration information.

ACS Style

Filippos Alogdianakis; Loukas Dimitriou; Dimos C. Charmpis. Pattern Recognition in Road Bridges’ Deterioration Mechanism: An Artificial Approach for Analysing the US National Bridge Inventory. Transportation Research Procedia 2021, 52, 187 -194.

AMA Style

Filippos Alogdianakis, Loukas Dimitriou, Dimos C. Charmpis. Pattern Recognition in Road Bridges’ Deterioration Mechanism: An Artificial Approach for Analysing the US National Bridge Inventory. Transportation Research Procedia. 2021; 52 ():187-194.

Chicago/Turabian Style

Filippos Alogdianakis; Loukas Dimitriou; Dimos C. Charmpis. 2021. "Pattern Recognition in Road Bridges’ Deterioration Mechanism: An Artificial Approach for Analysing the US National Bridge Inventory." Transportation Research Procedia 52, no. : 187-194.

Journal article
Published: 03 February 2021 in Transportation Research Procedia
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The enormous economic impact of air transportation networks on a local, national, and international level has created an interest for further investments and increased the complexity of the global air transport network. The increased number of worldwide airport passengers and of the aircraft movements and also of the international airport cargo shipments is evident. Therefore, the functionality of this complex air transport network is very important and requires to be investigated and evaluated for identifying the airports that appear to be critical to this network. However, besides the economic benefits that air transport network is offering in local, national and international level through their services (shipments of goods and transport of passengers) play an ever-increasing role in safeguarding global health security. This paper investigated the global air transport network for identifying the airports that may constitute a public health event of international concern from infectious diseases (e.g. COVID-19). In detail, critical airports, in terms of centrality measures (e.g. Closeness, Degree, Betweenness, and Page Rank Centrality) were identified and addressed by pointing them to global authorities for suggesting and implementing routine prevention and control measures for possible future disease outbreaks.

ACS Style

Paraskevas Nikolaou; Loukas Dimitriou. Investigating and Identifying Critical Airports for Controlling Infectious Diseases Outbreaks. Transportation Research Procedia 2021, 52, 437 -444.

AMA Style

Paraskevas Nikolaou, Loukas Dimitriou. Investigating and Identifying Critical Airports for Controlling Infectious Diseases Outbreaks. Transportation Research Procedia. 2021; 52 ():437-444.

Chicago/Turabian Style

Paraskevas Nikolaou; Loukas Dimitriou. 2021. "Investigating and Identifying Critical Airports for Controlling Infectious Diseases Outbreaks." Transportation Research Procedia 52, no. : 437-444.

Journal article
Published: 03 February 2021 in Transportation Research Procedia
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The conversion from single-entity level characteristics of traffic flow to comparable system-level characteristics shaped a new era for traffic monitoring and control. Since then landmark studies explored network-level traffic flow relationships across entire urban networks or regions and cities, mainly based on simulation data but also with empirical data. Although, the ability to observe and monitor the traffic state of the system on a network-wide level depends on the availability of existing traffic surveillance systems, adequately deployed such as to cover a complete network. To overcome this deficit, we propose a method to estimate a network’s Macroscopic Fundamental Diagrams (MFD) using traffic flow mechanics at the microscopic level and exploiting class-type traffic information that can be obtained from online traffic maps. This valuable information depicted on maps is extracted based on image processing techniques, able to simultaneously perform discretization of the urban space-and the road network therein- in seamless pixels and further capture the color-coded traffic information in a suitable data structure valuable for meta-analysis. Then, the fundamental traffic flow mechanics are used for connecting the captured pixels properties with macroscopic traffic phenomena, especially with the well-defined (MFDs). The validity of the method is tested by comparing the estimated MFDs to ground-truth MFD obtained using empirical data from loop detectors. The results are providing valuable evidence on the operational characteristics of large urban areas, while at a meta-analysis stage it was able to capture spatio-temporal phenomena of urban mobility, like concentration, hysteresis and homogeneity. Since online traffic maps provide almost global coverage the proposed method is practically feasible and offers a novel approach for monitoring large-scale traffic systems.

ACS Style

Vana Gkania; Loukas Dimitriou. Linking the microscopic traffic flow mechanics with the macroscopic phenomena by exploiting class-type traffic information retrieved from online traffic maps. Transportation Research Procedia 2021, 52, 645 -652.

AMA Style

Vana Gkania, Loukas Dimitriou. Linking the microscopic traffic flow mechanics with the macroscopic phenomena by exploiting class-type traffic information retrieved from online traffic maps. Transportation Research Procedia. 2021; 52 ():645-652.

Chicago/Turabian Style

Vana Gkania; Loukas Dimitriou. 2021. "Linking the microscopic traffic flow mechanics with the macroscopic phenomena by exploiting class-type traffic information retrieved from online traffic maps." Transportation Research Procedia 52, no. : 645-652.

Journal article
Published: 26 December 2020 in Transportation Research Interdisciplinary Perspectives
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Containers’ handling in dedicated port terminals correspond to a highly competitive market where pricing strategies play a decisive role in their economic and operational performance. For that reason, the formation of an appropriate pricing strategy should follow a thorough methodological treatment supporting policy-making and state-of-the-practice. In the current paper, such a methodological framework is developed and applied to a realistic system, incorporating the concept of pricing differentiation among competing container port facilities. Such an approach may identify pricing strategies that significantly differ from the marginal cost pricing practice, typically adopted by the majority of port authorities. As so, the proposed framework uses elements from non-cooperative game theory and equilibrium network design, enabling its application in realistic large-scale cases. Two distinctive instances are analysed in an additive manner, (a) one simplified case demonstrating the properties of the methodological framework and (b) a generalized case reflecting the market of European container terminals. Moreover, optimal pricing strategies are estimated by two distinctive game formats: a strategic/matrix form of discrete strategies and a continuous game form, each confirmatory of the other. The results provide evidence of the pricing opportunities associated with ports’ geographical location especially in relation with the demand profiles manifested in such spatially separated markets.

ACS Style

Loukas Dimitriou. Optimal competitive pricing in European port container terminals: A game-theoretical framework. Transportation Research Interdisciplinary Perspectives 2020, 9, 100287 .

AMA Style

Loukas Dimitriou. Optimal competitive pricing in European port container terminals: A game-theoretical framework. Transportation Research Interdisciplinary Perspectives. 2020; 9 ():100287.

Chicago/Turabian Style

Loukas Dimitriou. 2020. "Optimal competitive pricing in European port container terminals: A game-theoretical framework." Transportation Research Interdisciplinary Perspectives 9, no. : 100287.

Conference paper
Published: 04 November 2020 in Advances in Intelligent Systems and Computing
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Smart Cities promise to their residents, quick journeys in a clean and sustainable environment. Despite, the benefits accrued by the introduction of traffic management solutions (e.g. improved travel times, maximisation of throughput, etc.), these solutions usually fall short on ensuring the environmental sustainability around the implementation areas. This is because the environmental dimension (e.g. vehicle emissions) is usually absent from the optimisation methodologies adopted for traffic management strategies. Nonetheless, since environmental performance corresponds as a primary goal of contemporary mobility planning, solutions that can guarantee air quality are significant. This study presents an advanced Artificial Intelligence-based (AI) signal control framework, able to incorporate environmental considerations into the core of signal optimisation processes. More specifically, a highly flexible Reinforcement Learning (RL) algorithm has been developed in order to identify efficient but -more importantly- environmentally friendly signal control strategies. The methodology is deployed on a large-scale micro-simulation environment able to realistically represent urban traffic conditions. Alternative signal control strategies are designed, applied, and evaluated against their achieved traffic efficiency and environmental footprint. Based on the results obtained from the application of the methodology on a core part of the road urban network of Nicosia, Cyprus the best strategy achieved a 4.8% increase of the network throughput, 17.7% decrease of the average queue length and a remarkable 34.2% decrease of delay while considerably reduced the CO emissions by 8.1%. The encouraging results showcase ability of RL-based traffic signal controlling to ensure improved air-quality conditions for the residents of dense urban areas.

ACS Style

Haris Ballis; Loukas Dimitriou. Evaluating the Performance of Reinforcement Learning Signalling Strategies for Sustainable Urban Road Networks. Advances in Intelligent Systems and Computing 2020, 97 -105.

AMA Style

Haris Ballis, Loukas Dimitriou. Evaluating the Performance of Reinforcement Learning Signalling Strategies for Sustainable Urban Road Networks. Advances in Intelligent Systems and Computing. 2020; ():97-105.

Chicago/Turabian Style

Haris Ballis; Loukas Dimitriou. 2020. "Evaluating the Performance of Reinforcement Learning Signalling Strategies for Sustainable Urban Road Networks." Advances in Intelligent Systems and Computing , no. : 97-105.

Conference paper
Published: 04 November 2020 in Advances in Intelligent Systems and Computing
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Electromobility is considered the foreseeable future of road transportation and a significant shift to vehicles' consumer behaviour. Electric Vehicles (EV) adoption has environmental benefits linked to lower emissions and noise levels, that improve the quality of life, especially in urban areas. Nevertheless, to reap these benefits, both the energy and the transport sector have to be reformed. However, the combination of both sectors provides a complex system within which electromobility adoption has to be planned. The work herein proposes a framework to plan the shift to electromobility on the urban level. The proposed framework uses system theory and the Cost-Benefit-Analysis (CBA) tool to plan the shift to electromobility. An application of the framework is provided for the case of Cyprus’s capital, Nicosia, within a 20-year scope. The results of the do-nothing scenario presented herein, indicate that increased socio-environmental benefits can be anticipated by embracing electromobility, providing room for optimal policies.

ACS Style

Filippos Alogdianakis; Loukas Dimitriou. Planning the Urban Shift to Electromobility Using a Cost-Benefit-Analysis Optimization Framework: The Case of Nicosia Cyprus. Advances in Intelligent Systems and Computing 2020, 230 -240.

AMA Style

Filippos Alogdianakis, Loukas Dimitriou. Planning the Urban Shift to Electromobility Using a Cost-Benefit-Analysis Optimization Framework: The Case of Nicosia Cyprus. Advances in Intelligent Systems and Computing. 2020; ():230-240.

Chicago/Turabian Style

Filippos Alogdianakis; Loukas Dimitriou. 2020. "Planning the Urban Shift to Electromobility Using a Cost-Benefit-Analysis Optimization Framework: The Case of Nicosia Cyprus." Advances in Intelligent Systems and Computing , no. : 230-240.

Conference paper
Published: 04 November 2020 in Advances in Intelligent Systems and Computing
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According to European urban sustainable planning guidelines, road safety corresponds to one of the most important elements of cities’ performance. Several methods have been developed over the years for supporting policy-making, towards the improvement of road safety levels mainly at the national level. In this study, a methodological framework is developed, extending the macro-level (national) analysis and focusing at a higher spatial resolution, that of urban regions. The methodological approach is based on benchmarking analysis, able to suitably rank alternative cases/regions with distinctive characteristics within a multivariate comparative framework and on the investigation of the components that affect their ranking. In particular, an extensive and representative dataset from 101 European regions is collected and analyzed, incorporating their socio-economic, demographic and road infrastructure characteristics. Then, Data Envelopment Analysis (suitably adapted to road fatalities framework) has been developed, evaluating the urban regions’ road safety performance over a period of 9 years. The resulted region ranking is further examined by using Tobit regression models for identifying the components that appear to affect their performance in different extents providing a valuable guiding ‘tool’ for experience/knowledge-transfer and policy-making. The datasets and the results are presented and discussed in detail, such as they will be useful not only for demonstration purposes but also they will be suitable as a benchmark for researchers and practitioners.

ACS Style

Katerina Folla; Paraskevas Nikolaou; Loukas Dimitriou; George Yannis. Benchmarking Analysis of Road Safety Levels for an Extensive and Representative Dataset of European Cities. Advances in Intelligent Systems and Computing 2020, 1066 -1075.

AMA Style

Katerina Folla, Paraskevas Nikolaou, Loukas Dimitriou, George Yannis. Benchmarking Analysis of Road Safety Levels for an Extensive and Representative Dataset of European Cities. Advances in Intelligent Systems and Computing. 2020; ():1066-1075.

Chicago/Turabian Style

Katerina Folla; Paraskevas Nikolaou; Loukas Dimitriou; George Yannis. 2020. "Benchmarking Analysis of Road Safety Levels for an Extensive and Representative Dataset of European Cities." Advances in Intelligent Systems and Computing , no. : 1066-1075.

Journal article
Published: 29 October 2020 in Research in Transportation Economics
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Bicycle sharing systems (BSS) have been implemented in cities worldwide in an attempt to promote cycling. Analysing BSS usage in ‘starter’ cycling cities in Southern Europe (Limassol, Las Palmas de Gran Canaria and Malta) can aid in understanding how BSS use and cycling can be promoted in such a context. A year of trip data is used to understand to what extent the BSS is characterized by tourist use or by local residents, trips are classified based on trip type, trip duration and diurnal and seasonal usage patterns. An analysis of the origin-destination matrices highlights spatial patterns and temporal dynamics, and analysis of the spatial coverage is used to calculate what percentage of the city's population is served by the BSS. The comparative analysis shows that despite sharing commonalities, the cities exhibit differences in BSS use: while in Limassol BSS use is mainly for leisure, in Las Palmas de Gran Canaria and Malta there is more cycling for transport. Investing in connections between the BSS, public transport, points-of-interests and cycling infrastructure can encourage more cycling. In all cities there is scope to integrate the BSS with public transport and promote the service amongst tourists and visitors.

ACS Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. Examining spatio-temporal trip patterns of bicycle sharing systems in Southern European island cities. Research in Transportation Economics 2020, 86, 100992 .

AMA Style

Suzanne Maas, Paraskevas Nikolaou, Maria Attard, Loukas Dimitriou. Examining spatio-temporal trip patterns of bicycle sharing systems in Southern European island cities. Research in Transportation Economics. 2020; 86 ():100992.

Chicago/Turabian Style

Suzanne Maas; Paraskevas Nikolaou; Maria Attard; Loukas Dimitriou. 2020. "Examining spatio-temporal trip patterns of bicycle sharing systems in Southern European island cities." Research in Transportation Economics 86, no. : 100992.

Journal article
Published: 02 July 2020 in Transportation Research Part B: Methodological
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Over the last decades, technological advances have allowed the capturing of travel behaviour at large-scale. Despite the unprecedented volume and the variety of personal mobility data, aggregate Origin-Destination (OD) matrices are still the most widespread means to organise and represent travel demand. Nonetheless, standard ODs cannot adequately capture significant elements affecting travel behaviour such as trip-interdependency and trip-chaining, therefore they are not particularly suitable for travel behaviour analysis at person-level. The currently presented modelling framework enables the in-depth study of personal mobility by firstly combining the trips present in OD matrices into home-based trip-chains (i.e. tours) and subsequently into sequences of activities (activity schedules). The above-mentioned process is completed based on advanced graph-theoretical and combinatorial optimisation concepts. The applicability of the methodology is meticulously verified through a large-scale test case where a set of multi-period, purpose dependant ODs is converted into realistic activity schedules able to incorporate more than 99% of the inputted travel demand. The accurate and highly detailed results showcase the significant potential of the proposed methodology to support the comprehensive analysis of travel behaviour at person level.

ACS Style

Haris Ballis; Loukas Dimitriou. Revealing personal activities schedules from synthesizing multi-period origin-destination matrices. Transportation Research Part B: Methodological 2020, 139, 224 -258.

AMA Style

Haris Ballis, Loukas Dimitriou. Revealing personal activities schedules from synthesizing multi-period origin-destination matrices. Transportation Research Part B: Methodological. 2020; 139 ():224-258.

Chicago/Turabian Style

Haris Ballis; Loukas Dimitriou. 2020. "Revealing personal activities schedules from synthesizing multi-period origin-destination matrices." Transportation Research Part B: Methodological 139, no. : 224-258.

Journal article
Published: 10 April 2020 in Journal of Air Transport Management
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As the global population increases and transportation connectivity improves in quality and prices, the demand for mobility increases, especially in long-haul services. According to the 2017 report of the European Commission in Mobility and Transport, the performance of all modes for passenger transport (roadways and airways) are reaching record highs. Although the benefits of the increased demand for mobility are substantial and welcome, an effort should be paid such as to ameliorate possible threatening side-effects that may also arise. As World Health Organization (WHO) denotes and as has been evident from the global COVID-19 epidemic outbreak, infectious diseases can be spread directly or indirectly from one person to another under common exposure circumstances such as air transportation (especially long-haul airline connections) that may act as the medium for transmitting and spreading infectious diseases. In this paper, analytical and realistic models have been integrated, for providing evidence on the spread dynamics of infectious diseases that may face Europe through the airlines system. In particular, a detailed epidemiological model has been integrated with the airlines’ and land transport network, able to simulate the epidemic spread of infectious diseases originated from distant locations. Additionally, a wide set of experiments and simulations have been conducted, providing results from detailed stress-tests covering both mild as well as aggressive cases of epidemic spreading scenarios. The results provide convincing evidence on the effectiveness that the European airports' system offer in controlling the emergence of epidemics, but also on the time and extent that controlling measures should be taken in order to break the chain of infections in realistic cases.

ACS Style

Paraskevas Nikolaou; Loukas Dimitriou. Identification of critical airports for controlling global infectious disease outbreaks: Stress-tests focusing in Europe. Journal of Air Transport Management 2020, 85, 101819 -101819.

AMA Style

Paraskevas Nikolaou, Loukas Dimitriou. Identification of critical airports for controlling global infectious disease outbreaks: Stress-tests focusing in Europe. Journal of Air Transport Management. 2020; 85 ():101819-101819.

Chicago/Turabian Style

Paraskevas Nikolaou; Loukas Dimitriou. 2020. "Identification of critical airports for controlling global infectious disease outbreaks: Stress-tests focusing in Europe." Journal of Air Transport Management 85, no. : 101819-101819.

Journal article
Published: 01 September 2019 in Accident Analysis & Prevention
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Given the importance of rigorous quantitative reasoning in supporting national, regional or global road safety policies, data quality, reliability, and stability are of the upmost importance. This study focuses on macroscopic properties of road safety statistics and the temporal stability of these statistics at a global level. A thorough investigation of two years of measurements was conducted to identify any unexpected gaps that could highlight the existence of inconsistent measurements. The database used in this research includes 121 member countries of the United Nation (UN-121) with a population of at least one million (smaller country data shows higher instability) and includes road safety and socioeconomic variables collected from a number of international databases (e.g. WHO and World Bank) for the years 2010 and 2013. For the fulfillment of the earlier stated goal, a number of data visualization and exploratory analyses (Hierarchical Clustering and Principal Component Analysis) were conducted. Furthermore, in order to provide a richer analysis of the data, we developed and compared the specification of a number of Structural Equation Models for the years 2010 and 2013. Different scenarios have been developed, with different endogenous variables (indicators of mortality rate and fatality risk) and structural forms. The findings of the current research indicate inconsistency phenomena in global statistics of different instances/years. Finally, the results of this research provide evidence on the importance of careful and systematic data collection for developing advanced statistical and econometric techniques and furthermore for developing road safety policies.

ACS Style

Loukas Dimitriou; Paraskevas Nikolaou; Constantinos Antoniou. Exploring the temporal stability of global road safety statistics. Accident Analysis & Prevention 2019, 130, 38 -53.

AMA Style

Loukas Dimitriou, Paraskevas Nikolaou, Constantinos Antoniou. Exploring the temporal stability of global road safety statistics. Accident Analysis & Prevention. 2019; 130 ():38-53.

Chicago/Turabian Style

Loukas Dimitriou; Paraskevas Nikolaou; Constantinos Antoniou. 2019. "Exploring the temporal stability of global road safety statistics." Accident Analysis & Prevention 130, no. : 38-53.

Book chapter
Published: 01 January 2019 in Mobility Patterns, Big Data and Transport Analytics
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ACS Style

Constantinos Antoniou; Loukas Dimitriou; Francisco Câmara Pereira. Big Data and Transport Analytics: An Introduction. Mobility Patterns, Big Data and Transport Analytics 2019, 1 -5.

AMA Style

Constantinos Antoniou, Loukas Dimitriou, Francisco Câmara Pereira. Big Data and Transport Analytics: An Introduction. Mobility Patterns, Big Data and Transport Analytics. 2019; ():1-5.

Chicago/Turabian Style

Constantinos Antoniou; Loukas Dimitriou; Francisco Câmara Pereira. 2019. "Big Data and Transport Analytics: An Introduction." Mobility Patterns, Big Data and Transport Analytics , no. : 1-5.

Book chapter
Published: 30 November 2018 in Mobility Patterns, Big Data and Transport Analytics
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ACS Style

Vana Gkania; Loukas Dimitriou. A Back-Engineering Approach to Explore Human Mobility Patterns Across Megacities Using Online Traffic Maps. Mobility Patterns, Big Data and Transport Analytics 2018, 345 -363.

AMA Style

Vana Gkania, Loukas Dimitriou. A Back-Engineering Approach to Explore Human Mobility Patterns Across Megacities Using Online Traffic Maps. Mobility Patterns, Big Data and Transport Analytics. 2018; ():345-363.

Chicago/Turabian Style

Vana Gkania; Loukas Dimitriou. 2018. "A Back-Engineering Approach to Explore Human Mobility Patterns Across Megacities Using Online Traffic Maps." Mobility Patterns, Big Data and Transport Analytics , no. : 345-363.

How to use
Published: 30 November 2018 in Mobility Patterns, Big Data and Transport Analytics
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Constantinos Antoniou; Loukas Dimitriou; Francisco Pereira. Conclusions. Mobility Patterns, Big Data and Transport Analytics 2018, 415 -417.

AMA Style

Constantinos Antoniou, Loukas Dimitriou, Francisco Pereira. Conclusions. Mobility Patterns, Big Data and Transport Analytics. 2018; ():415-417.

Chicago/Turabian Style

Constantinos Antoniou; Loukas Dimitriou; Francisco Pereira. 2018. "Conclusions." Mobility Patterns, Big Data and Transport Analytics , no. : 415-417.

Contributors
Published: 30 November 2018 in Mobility Patterns, Big Data and Transport Analytics
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ACS Style

Mohamed Abdel-Aty; Constantinos Antoniou; Stanislav S. Borysov; Symeon E. Christodoulou; François Combes; Adam Davis; Loukas Dimitriou; Song Gao; Vassilis Gikas; Vana Gkania; Konstadinos G. Goulias; George Hadjidemetriou; Kristian Henrickson; Yingjie Hu; Krzysztof Janowicz; Bin Jiang; Samaneh Beheshti Kashi; Allison Kealy; Aseem Kinra; Haris N. Koutsopoulos; Charalambos Kyriakou; Jae Hyun Lee; Zhenliang Ma; Elizabeth McBride; Grant McKenzie; Peyman Noursalehi; Vasileia Papathanasopoulou; Inon Peled; Francisco Câmara Pereira; Zheng Ren; Guenther Retscher; Filipe Rodrigues; Werner Rothengatter; Katerina Stylianou; Michalis Xyntarakis; Rui Zhu; Yiwen Zhu. Contributors. Mobility Patterns, Big Data and Transport Analytics 2018, 1 .

AMA Style

Mohamed Abdel-Aty, Constantinos Antoniou, Stanislav S. Borysov, Symeon E. Christodoulou, François Combes, Adam Davis, Loukas Dimitriou, Song Gao, Vassilis Gikas, Vana Gkania, Konstadinos G. Goulias, George Hadjidemetriou, Kristian Henrickson, Yingjie Hu, Krzysztof Janowicz, Bin Jiang, Samaneh Beheshti Kashi, Allison Kealy, Aseem Kinra, Haris N. Koutsopoulos, Charalambos Kyriakou, Jae Hyun Lee, Zhenliang Ma, Elizabeth McBride, Grant McKenzie, Peyman Noursalehi, Vasileia Papathanasopoulou, Inon Peled, Francisco Câmara Pereira, Zheng Ren, Guenther Retscher, Filipe Rodrigues, Werner Rothengatter, Katerina Stylianou, Michalis Xyntarakis, Rui Zhu, Yiwen Zhu. Contributors. Mobility Patterns, Big Data and Transport Analytics. 2018; ():1.

Chicago/Turabian Style

Mohamed Abdel-Aty; Constantinos Antoniou; Stanislav S. Borysov; Symeon E. Christodoulou; François Combes; Adam Davis; Loukas Dimitriou; Song Gao; Vassilis Gikas; Vana Gkania; Konstadinos G. Goulias; George Hadjidemetriou; Kristian Henrickson; Yingjie Hu; Krzysztof Janowicz; Bin Jiang; Samaneh Beheshti Kashi; Allison Kealy; Aseem Kinra; Haris N. Koutsopoulos; Charalambos Kyriakou; Jae Hyun Lee; Zhenliang Ma; Elizabeth McBride; Grant McKenzie; Peyman Noursalehi; Vasileia Papathanasopoulou; Inon Peled; Francisco Câmara Pereira; Zheng Ren; Guenther Retscher; Filipe Rodrigues; Werner Rothengatter; Katerina Stylianou; Michalis Xyntarakis; Rui Zhu; Yiwen Zhu. 2018. "Contributors." Mobility Patterns, Big Data and Transport Analytics , no. : 1.