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Several studies have focused on understanding travelers’ attitudes and characteristics toward using carpooling services. However, few of these studies have focused the driver’s behavior and carpooling services that are organized to feed public transport. This research investigates the willingness of drivers to accept a carpooling ride, as part of their trip, to/from public transport stations (i.e., rail, tram and metro). Data from the EU project Ride2Rail are used, for which a survey (n = 327) was conducted in EU27 and the UK. Fisher’s exact and chi-square tests are used to explore the relationships between drivers/non-drivers and explanatory variables. A binary logit model is developed to estimate the likelihood of carpooling as a driver to/from a public transport station. The results show that delay, convenience, residence location, security and the number of passengers influence the drivers’ decision toward using their private vehicle in carpooling services. Findings provide concrete recommendations for carpooling drivers regarding the planning of a successful carpooling service. The recommendations to “recruit” the drivers become significant, as the concept of carpooling cannot be realized without them.
Lambros Mitropoulos; Annie Kortsari; Georgia Ayfantopoulou. Factors Affecting Drivers to Participate in a Carpooling to Public Transport Service. Sustainability 2021, 13, 9129 .
AMA StyleLambros Mitropoulos, Annie Kortsari, Georgia Ayfantopoulou. Factors Affecting Drivers to Participate in a Carpooling to Public Transport Service. Sustainability. 2021; 13 (16):9129.
Chicago/Turabian StyleLambros Mitropoulos; Annie Kortsari; Georgia Ayfantopoulou. 2021. "Factors Affecting Drivers to Participate in a Carpooling to Public Transport Service." Sustainability 13, no. 16: 9129.
The hyperloop is an innovative land transport mode for passengers and freight that travels at ultra-high speeds. Lately, different stakeholders have been engaged in the research and development of hyperloop components. The novelty of the hyperloop necessitates certain directions to be followed toward the development and testing of its technological components as well the formation of regulations and planning processes. In this paper, we conduct a comprehensive literature review of hyperloop publications to record the current state of progress of hyperloop components, including the pod, the infrastructure, and the communication system, and identify involved EU stakeholders. Blending this information results in future directions. An online search of English-based publications was performed to finally consider 107 studies on the hyperloop and identify 81 stakeholders in the EU. The analysis shows that the hyperloop-related activities are almost equally distributed between Europe (39%) and Asia (38%), and the majority of EU stakeholders are located in Spain (26%) and Germany (20%), work on the traction of the pod (37%) and the tube (28%), and study impacts including safety (35%), energy (33%), and cost (30%). Existing tube systems and testing facilities for the hyperloop lack full-scale tracks, which creates a hurdle for the testing and development of the hyperloop system. The presented analysis and findings provide a holistic assessment of the hyperloop system and its stakeholders and suggest future directions to develop a successful transport system.
Lambros Mitropoulos; Annie Kortsari; Alexandros Koliatos; Georgia Ayfantopoulou. The Hyperloop System and Stakeholders: A Review and Future Directions. Sustainability 2021, 13, 8430 .
AMA StyleLambros Mitropoulos, Annie Kortsari, Alexandros Koliatos, Georgia Ayfantopoulou. The Hyperloop System and Stakeholders: A Review and Future Directions. Sustainability. 2021; 13 (15):8430.
Chicago/Turabian StyleLambros Mitropoulos; Annie Kortsari; Alexandros Koliatos; Georgia Ayfantopoulou. 2021. "The Hyperloop System and Stakeholders: A Review and Future Directions." Sustainability 13, no. 15: 8430.
The sensor-era has brought rapid changes in transportation; the abundance of data has started changing the traditional way in which planners and engineers approach mobility. Nowadays, traffic monitoring and information provision systems heavily rely on floating car data usually of special vehicles (e.g., trucks, taxi), and the question that arises is whether such sources can provide reliable data for the whole traffic in a complex urban environment. The current paper, through Thessaloniki's (GR) case study, seeks to evaluate the reliability of taxi data compared to the overall traffic. The analysis reveals that for the examined critical urban road paths, there is a strong relation among floating taxi data with the overall traffic that is additionally influenced by other significant factors (e.g., number of lanes, day, time period). Furthermore, a modelling approach with a generalized linear model (gamma with log link) seems appropriate when dealing with skewed and heteroscedastic traffic data.
Glykeria Myrovali; Theodoros Karakasidis; Maria Morfoulaki; Georgia Ayfantopoulou. Representativeness of Taxi GPS-Enabled Travel Time Data Using Gamma Generalized Linear Model. International Journal of Decision Support System Technology 2021, 13, 36 -53.
AMA StyleGlykeria Myrovali, Theodoros Karakasidis, Maria Morfoulaki, Georgia Ayfantopoulou. Representativeness of Taxi GPS-Enabled Travel Time Data Using Gamma Generalized Linear Model. International Journal of Decision Support System Technology. 2021; 13 (3):36-53.
Chicago/Turabian StyleGlykeria Myrovali; Theodoros Karakasidis; Maria Morfoulaki; Georgia Ayfantopoulou. 2021. "Representativeness of Taxi GPS-Enabled Travel Time Data Using Gamma Generalized Linear Model." International Journal of Decision Support System Technology 13, no. 3: 36-53.
Although the value-of-time and willingness-to-pay are critical measures in a broad range of public transport policy and planning applications, they cannot be measured directly. The purpose of the present research is the estimation of these measures in Thessaloniki, where a pilot mobility scheme inspired by the concept of sharing economy is implemented. The pilot focuses on reducing the commuting trips to the city centre, aggregating as much as possible the origins-destinations and the timetables, by using a taxi sharing service. A questionnaire including a stated-preference experiment has been developed and delivered to a random sample of 90 people. Discrete choice models are developed within a methodological framework and VOT has been estimated through the estimated coefficients. For the estimation of WTP, the Price Sensitivity Model is used based on two samples consisted of the pilot service's users at the beginning and at the end of the pilot period. The model results in a range of acceptable prices from 2.00 to 3.50€ for the both samples supporting the long-term sustainability of the taxi-sharing service.
Josep Maria Salanova Grau; Maria Konstantinidou; Neofytos Boufidis; Georgia Aifandopoulou. Estimation of value-of-time and a comparison of an ex ante and an ex post willingness to pay for shared transport services in Thessaloniki. Research in Transportation Economics 2021, 101092 .
AMA StyleJosep Maria Salanova Grau, Maria Konstantinidou, Neofytos Boufidis, Georgia Aifandopoulou. Estimation of value-of-time and a comparison of an ex ante and an ex post willingness to pay for shared transport services in Thessaloniki. Research in Transportation Economics. 2021; ():101092.
Chicago/Turabian StyleJosep Maria Salanova Grau; Maria Konstantinidou; Neofytos Boufidis; Georgia Aifandopoulou. 2021. "Estimation of value-of-time and a comparison of an ex ante and an ex post willingness to pay for shared transport services in Thessaloniki." Research in Transportation Economics , no. : 101092.
Urban mobility is subject to deep changes, imposed by technological advancements and new concepts of operation in transport and serious challenges on urban space are expected to be introduced. Transport modelling should follow the urban mobility trends to connect the new arrays of demands and the new services they will provide, guiding future mobility. The integration of urban mobility trends into mobility planning, through the 8 principles and the 4 phases of Sustainable Urban Mobility Plans (SUMPs) to support policy goals, is essential, as well. Modelling the complexity and uncertainty enforced by the urban mobility trends necessitate a move from common modelling techniques? How to accomplish a transition in mobility planning shifting from conventional and static planning approaches? Are current transport modelling approaches able to integrate urban mobility trends, to fulfil SUMP’s implementation? Traditional planning and modelling methods cannot face the challenges of urban mobility trends integration. Long-term planning, collaborative and participatory planning processes, co-creation of scenarios for the future and measure packages using specialized tools on the one hand, multi-sectoral and dynamic modelling approaches, the Big Data potentials on the other hand, are cases of on-going research for transport planning and modelling new requirements respectively, identified through an extensive literature review. The integration of transport modelling requirements, in the urban policy cycle is anticipated to guarantee the reliability of the modelled scenarios, ensure the accuracy of modeling outcomes and offer guidance on how to accomplish the integration of data-driven methods in participatory and collaborative planning approaches.
Georgia Ayfantopoulou; Maria Natalia Konstantinidou; Maria Chatziathanasiou; Josep Maria Salanova Grau. Integrating Modelling in Urban Policy Cycle and Decision Making. Advances in Intelligent Systems and Computing 2020, 1149 -1158.
AMA StyleGeorgia Ayfantopoulou, Maria Natalia Konstantinidou, Maria Chatziathanasiou, Josep Maria Salanova Grau. Integrating Modelling in Urban Policy Cycle and Decision Making. Advances in Intelligent Systems and Computing. 2020; ():1149-1158.
Chicago/Turabian StyleGeorgia Ayfantopoulou; Maria Natalia Konstantinidou; Maria Chatziathanasiou; Josep Maria Salanova Grau. 2020. "Integrating Modelling in Urban Policy Cycle and Decision Making." Advances in Intelligent Systems and Computing , no. : 1149-1158.
Urban traffic is undoubtedly a dynamic phenomenon presenting variations over both time and space, that in the majority of cases are the result of a mixture of, either well known (i.e. weather, seasonality) or not easily predictable (i.e. events, accidents) external factors. Identification of similarities in the performance of different urban road paths under different traffic states (different travel demand conditions) is the main subject of the current paper. Floating taxi travel time data (timeseries per road path) collected in the framework of Thessaloniki Smart Mobility Living Lab (initiated and operated by CERTH/HIT) consist the basic input for the hierarchical clustering that is applied. Clustering applies upon different combinations of road paths’ features (data points of travel time timeseries, descriptive statistics and mutual information of timeseries). The comparison of the clustering results based on average weekdays travel times per road path (from a six months period) with the respective results of a typical and an atypical day adds on the interpretability of underlying relations among paths under different states. The analysis reveals that resulting clusters can be a building block for the spatiotemporal understanding of urban traffic. Furthermore, it is shown that adding as clustering feature the criterion of mutual information of timeseries, therefore taking into account also non-linear dependences of the different road paths, the clustering interpretability is differentiated.
Glykeria Myrovali; Theodoros Karakasidis; Maria Morfoulaki; Georgia Ayfantopoulou. Clustering of Urban Road Paths; Identifying the Optimal Set of Linear and Nonlinear Clustering Features. Advances in Intelligent Systems and Computing 2020, 1107 -1116.
AMA StyleGlykeria Myrovali, Theodoros Karakasidis, Maria Morfoulaki, Georgia Ayfantopoulou. Clustering of Urban Road Paths; Identifying the Optimal Set of Linear and Nonlinear Clustering Features. Advances in Intelligent Systems and Computing. 2020; ():1107-1116.
Chicago/Turabian StyleGlykeria Myrovali; Theodoros Karakasidis; Maria Morfoulaki; Georgia Ayfantopoulou. 2020. "Clustering of Urban Road Paths; Identifying the Optimal Set of Linear and Nonlinear Clustering Features." Advances in Intelligent Systems and Computing , no. : 1107-1116.
Connected and autonomous mobility are of great interest in transport research. Furthermore, Rail-Road Level Crossings represent high-risk locations of the network and the accidents that take place at them are considered as one of the most significant accident categories that occur at rail infrastructure. Hence, the evaluation of cooperative systems with the aim of increasing safety at Rail-Road Level Crossings is a crucial issue especially towards the evaluation of the system’ objectives as well as decision making for investments regarding in-vehicle warning systems. However, there are many barriers regarding the ex-post evaluation of these systems such as difficulty in collecting and analyzing quantitative data as well as GPS low accuracy. The present research examines the ex-post evaluation of an in-vehicle warning system for Rail-Road Level Crossings developed within the Horizon 2020 project “SAFER-LC” and tested in the city of Thessaloniki, Greece. The evaluation made with a questionnaire-based survey which was carried out in August-October 2019. Statistical analysis revealed numerous interesting findings between drivers’ socioeconomic attributes and the way they assess the in-vehicle warning system, indicating the high level of acceptance towards the tested driver assistance system, by a demanding professional drivers’ group.
Anastasios Skoufas; Neofytos Boufidis; Josep Maria Salanova Grau; Georgia Ayfantopoulou; Socrates Basbas. Εx-Post Evaluation of an In-Vehicle Warning System for Rail-Road Level Crossings: The Case of Taxi Drivers. Advances in Intelligent Systems and Computing 2020, 243 -252.
AMA StyleAnastasios Skoufas, Neofytos Boufidis, Josep Maria Salanova Grau, Georgia Ayfantopoulou, Socrates Basbas. Εx-Post Evaluation of an In-Vehicle Warning System for Rail-Road Level Crossings: The Case of Taxi Drivers. Advances in Intelligent Systems and Computing. 2020; ():243-252.
Chicago/Turabian StyleAnastasios Skoufas; Neofytos Boufidis; Josep Maria Salanova Grau; Georgia Ayfantopoulou; Socrates Basbas. 2020. "Εx-Post Evaluation of an In-Vehicle Warning System for Rail-Road Level Crossings: The Case of Taxi Drivers." Advances in Intelligent Systems and Computing , no. : 243-252.
Travelling to and from school forms mobility habits and travel behavior aspects of students from a very young age, also adopted in later life. Parents are the key players of the whole mode choice process as in most cases they are the ones to decide how and by which transport mode their children will complete their everyday school trips. Understanding parents’ perceptions on different travel modes and studying the motives behind the mode choice decision in school trips, is a rather essential issue as it may provide useful information to policy-makers, transport and spatial planners on how to overcome possible barriers and difficulties in order to satisfactory cover all students’ future mobility needs. The paper provides an extensive literature review regarding a wide range of factors found to influence students’ travel, following a statistical exploratory factor analysis of a questionnaire survey took place in Thessaloniki, Greece. The initial analysis of the sample identifies key themes while it also develops a comprehensive picture of caregivers’ experiences about travel mode choice to school in a typical Greek urban environment. Some interesting findings verify that socio-economic and household demographic factors, built-environment variables, and parents’ attitudes regarding their daily trips and mobility habits, are important factors affecting the school mode choice procedure.
Kornilia Maria Kotoula; George Botzoris; Georgia Ayfantopoulou; Vassilios Profillidis. Urban School Travel – Understanding the Critical Factors Affecting Parent’s Choices. Advances in Intelligent Systems and Computing 2020, 912 -922.
AMA StyleKornilia Maria Kotoula, George Botzoris, Georgia Ayfantopoulou, Vassilios Profillidis. Urban School Travel – Understanding the Critical Factors Affecting Parent’s Choices. Advances in Intelligent Systems and Computing. 2020; ():912-922.
Chicago/Turabian StyleKornilia Maria Kotoula; George Botzoris; Georgia Ayfantopoulou; Vassilios Profillidis. 2020. "Urban School Travel – Understanding the Critical Factors Affecting Parent’s Choices." Advances in Intelligent Systems and Computing , no. : 912-922.
The COVID-19 pandemic had a significant effect in urban mobility, while essential changes are being observed in travelers’ behavior. Travelers in many cases shifted to other transport modes, especially walking and cycling, for minimizing the risk of infection. This study attempts to investigate the impact that COVID-19 had on travelers’ perceptions towards bike-sharing systems and whether the pandemic could result in a greater or lesser share of trips that are being conducted through shared bikes. For that reason, a questionnaire survey was carried out in the city of Thessaloniki, Greece, and the responses of 223 people were analyzed statistically. The results of the analysis show that COVID-19 will not affect significantly the number of people using bike-sharing for their trips. However, for a proportion of people, bike-sharing is now more attractive. Moreover, the results indicate that bike-sharing is now more likely to become a more preferable mobility option for people who were previously commuting with private cars as passengers (not as drivers) and people who were already registered users in a bike-sharing system. The results also provide evidence about the importance of safety towards COVID-19 for engaging more users in bike-sharing, in order to provide them with a safe mobility option and contribute to the city’s resilience and sustainability.
Andreas Nikiforiadis; Georgia Ayfantopoulou; Afroditi Stamelou. Assessing the Impact of COVID-19 on Bike-Sharing Usage: The Case of Thessaloniki, Greece. Sustainability 2020, 12, 8215 .
AMA StyleAndreas Nikiforiadis, Georgia Ayfantopoulou, Afroditi Stamelou. Assessing the Impact of COVID-19 on Bike-Sharing Usage: The Case of Thessaloniki, Greece. Sustainability. 2020; 12 (19):8215.
Chicago/Turabian StyleAndreas Nikiforiadis; Georgia Ayfantopoulou; Afroditi Stamelou. 2020. "Assessing the Impact of COVID-19 on Bike-Sharing Usage: The Case of Thessaloniki, Greece." Sustainability 12, no. 19: 8215.
The purpose of this paper is to propose a holistic optimization-based framework for addressing the re-balancing problem of vehicle-sharing schemes. In order to address this issue, the problem is decomposed into three (3) sub-problems that include: (1) the dynamic prediction of vehicle demand in stations or zones (in the case of free-floating systems); (2) the optimization of the assignment of vehicles from stations/zones using the predicted demand of the first step; and (3) the optimization of the route that the re-balancing vehicle should follow, under transverse distance minimization objectives, and given the optimized assignment of the second step. As the route optimization of the rebalancing vehicle is computationally intensive, a heuristic algorithm is developed that transforms the route optimization problem into the one (1)-Commodity Pickup and Delivery Capacitated Traveling Salesman Problem. The applicability of the proposed methodology is illustrated through its application on the real case of the bike-sharing system in the city of Thessaloniki in Greece.
Georgia Aifadopoulou; Georgios Tsaples; Josep Maria Salanova Grau; Ioannis Mallidis; Nikolaos Sariannidis. Management of resource allocation on vehicle-sharing schemes: the case of Thessaloniki’s bike-sharing system. Operational Research 2020, 1 -16.
AMA StyleGeorgia Aifadopoulou, Georgios Tsaples, Josep Maria Salanova Grau, Ioannis Mallidis, Nikolaos Sariannidis. Management of resource allocation on vehicle-sharing schemes: the case of Thessaloniki’s bike-sharing system. Operational Research. 2020; ():1-16.
Chicago/Turabian StyleGeorgia Aifadopoulou; Georgios Tsaples; Josep Maria Salanova Grau; Ioannis Mallidis; Nikolaos Sariannidis. 2020. "Management of resource allocation on vehicle-sharing schemes: the case of Thessaloniki’s bike-sharing system." Operational Research , no. : 1-16.
The present research has investigated the impact of a Cooperative – Intelligent Transport Systems service for increasing Rail – Road Level Crossing safety, in terms of driving dynamic of the taxi drivers who used the service at the city of Thessaloniki, Greece. The Cooperative – Intelligent Transport Systems service informed drivers when approaching a Rail – Road Level Crossing, through 6 different paths, at the western area of the city of Thessaloniki. The results were yielded after comparing two datasets concerning the use of the Cooperative – Intelligent Transport Systems service by 168 taxi drivers for 28 days and without the use of the Cooperative – Intelligent Transport Systems service by 15 taxi drivers for 25 days. Even if conclusions are contrasting for the different types of the Rail – Road Level Crossing transits, the findings highlight a relation between speed reduction with types of transits whose first road segment is rectilinear, during Cooperative – Intelligent Transport Systems service use, while minor differentiations are noticed for Rail – Road Level Crossing transits with sharp turns and stop signs.
Anastasios Skoufas; Socrates Basbas; Josep Maria Salanova Grau; Georgia Aifadopoulou. Analysis of In-Vehicle Warning System for Rail-Road Level Crossings: Case Study in the City of Thessaloniki, Greece. Periodica Polytechnica Transportation Engineering 2020, 49, 42 -59.
AMA StyleAnastasios Skoufas, Socrates Basbas, Josep Maria Salanova Grau, Georgia Aifadopoulou. Analysis of In-Vehicle Warning System for Rail-Road Level Crossings: Case Study in the City of Thessaloniki, Greece. Periodica Polytechnica Transportation Engineering. 2020; 49 (1):42-59.
Chicago/Turabian StyleAnastasios Skoufas; Socrates Basbas; Josep Maria Salanova Grau; Georgia Aifadopoulou. 2020. "Analysis of In-Vehicle Warning System for Rail-Road Level Crossings: Case Study in the City of Thessaloniki, Greece." Periodica Polytechnica Transportation Engineering 49, no. 1: 42-59.
Rising interest in the field of Intelligent Transportation Systems combined with the increased availability of collected data allows the study of different methods for prevention of traffic congestion in cities. A common need in all of these methods is the use of traffic predictions for supporting planning and operation of the traffic lights and traffic management schemes. This paper focuses on comparing the forecasting effectiveness of three machine learning models, namely Random Forests, Support Vector Regression, and Multilayer Perceptron—in addition to Multiple Linear Regression—using probe data collected from the road network of Thessaloniki, Greece. The comparison was conducted with multiple tests clustered in three types of scenarios. The first scenario tests the algorithms on specific randomly selected dates on different randomly selected roads. The second scenario tests the algorithms on randomly selected roads over eight consecutive 15 min intervals; the third scenario tests the algorithms on random roads for the duration of a whole day. The experimental results show that while the Support Vector Regression model performs best at stable conditions with minor variations, the Multilayer Perceptron model adapts better to circumstances with greater variations, in addition to having the most near-zero errors.
Charalampos Bratsas; Kleanthis Koupidis; Josep-Maria Salanova; Konstantinos Giannakopoulos; Aristeidis Kaloudis; Georgia Aifadopoulou. A Comparison of Machine Learning Methods for the Prediction of Traffic Speed in Urban Places. Sustainability 2019, 12, 142 .
AMA StyleCharalampos Bratsas, Kleanthis Koupidis, Josep-Maria Salanova, Konstantinos Giannakopoulos, Aristeidis Kaloudis, Georgia Aifadopoulou. A Comparison of Machine Learning Methods for the Prediction of Traffic Speed in Urban Places. Sustainability. 2019; 12 (1):142.
Chicago/Turabian StyleCharalampos Bratsas; Kleanthis Koupidis; Josep-Maria Salanova; Konstantinos Giannakopoulos; Aristeidis Kaloudis; Georgia Aifadopoulou. 2019. "A Comparison of Machine Learning Methods for the Prediction of Traffic Speed in Urban Places." Sustainability 12, no. 1: 142.
Many cities have already installed bike-sharing systems for several years now, but especially in recent years with the rise of micro-mobility, many efforts are being made worldwide to improve the operation of these systems. Technology has an essential role to play in the success of micro-mobility schemes, including bike-sharing systems. In this paper, it is examined if a state-of-the-art mobile application (app) can contribute to increasing the usage levels of such a system. It is also seeking to identify groups of travelers, who are more likely to be affected by the sophisticated app. With this aim, a questionnaire survey was designed and addressed to the users of the bike-sharing system of the city of Thessaloniki, Greece, as well as to other residents of the city. Through a descriptive analysis, the most useful services that an app can provide are identified. Most importantly, two different types of predictive models (i.e., classification tree and binary logit model) were applied in order to identify groups of users who are more likely to shift to or to use the bike-sharing system due to the sophisticated app. The results of the two predictive models confirm that people of younger ages and those who are not currently users of the system are those most likely to be attracted to the system due to such an app. Other factors, such as car usage frequency, education, and income also appeared to have slight impact on travelers’ intention to use the system more often due to the app.
Andreas Nikiforiadis; Katerina Chrysostomou; Georgia Aifadopoulou. Exploring Travelers’ Characteristics Affecting their Intention to Shift to Bike-Sharing Systems due to a Sophisticated Mobile App. Algorithms 2019, 12, 264 .
AMA StyleAndreas Nikiforiadis, Katerina Chrysostomou, Georgia Aifadopoulou. Exploring Travelers’ Characteristics Affecting their Intention to Shift to Bike-Sharing Systems due to a Sophisticated Mobile App. Algorithms. 2019; 12 (12):264.
Chicago/Turabian StyleAndreas Nikiforiadis; Katerina Chrysostomou; Georgia Aifadopoulou. 2019. "Exploring Travelers’ Characteristics Affecting their Intention to Shift to Bike-Sharing Systems due to a Sophisticated Mobile App." Algorithms 12, no. 12: 264.
This paper presents a framework for data collection, filtering, and fusion, together with a set of operational tools to validate, analyze, utilize, and highlight the added value of probe data. Data is collected by both conventional (loops, radars, and cameras) and innovative (Floating Car Data, detectors of Bluetooth devices) technologies and refers to travel times and traffic flows on road networks. The city of Thessaloniki, Greece, serves as a case study for the implementation of the proposed framework. The methodology includes the estimation of traffic flow based on measured travel time along predefined routes and short-term forecasting of traffic volumes and their spatial expansion in the road network. The proposed processes and the framework itself have the potential of being implemented in urban road networks.
Josep Maria Salanova Grau; Evangelos Mitsakis; Panagiotis Tzenos; Iraklis Stamos; Luigi Selmi; Georgia Aifadopoulou. Multisource Data Framework for Road Traffic State Estimation. Journal of Advanced Transportation 2018, 2018, 1 -9.
AMA StyleJosep Maria Salanova Grau, Evangelos Mitsakis, Panagiotis Tzenos, Iraklis Stamos, Luigi Selmi, Georgia Aifadopoulou. Multisource Data Framework for Road Traffic State Estimation. Journal of Advanced Transportation. 2018; 2018 ():1-9.
Chicago/Turabian StyleJosep Maria Salanova Grau; Evangelos Mitsakis; Panagiotis Tzenos; Iraklis Stamos; Luigi Selmi; Georgia Aifadopoulou. 2018. "Multisource Data Framework for Road Traffic State Estimation." Journal of Advanced Transportation 2018, no. : 1-9.