Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Innovation Accelerator to Make Portuguese Parishes Smarter Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Renewable Mobility in Smart Cities:TheMOVESMART Approach

verfasst von : Damianos Gavalas, Kalliopi Giannakopoulou, Vlasios Kasapakis, Dionisis Kehagias, Charalampos Konstantopoulos, Spyros Kontogiannis, Damianos Kypriadis, Grammati Pantziou, Andreas Paraskevopoulos, Christos Zaroliagis

Erschienen in: Smart Technologies for Smart Cities

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The provision of efficient, sustainable, and personalized mobility services that combine a broad range of transport modes (e.g., public transportation, electric vehicles (EVs), vehicle sharing) constitutes a fundamental challenge in urban environments. This chapter reports on the key results and contributions of the EU-funded research project MOVESMART which addresses the aforementioned challenge. MOVESMART proposes a holistic approach as regards renewable mobility services in smart cities. The MOVESMART approach involves personal mobility services, leverages crowdsourcing techniques for collecting real-time traffic information, and encompasses effective traffic prediction mechanisms. MOVESMART guarantees real-time responses to renewable (on-demand) mobility queries for efficient multimodal route planning that are time-dependent as well as sensitive to aperiodic incidents and traffic prediction forecasts. The core architectural element of MOVESMART is a hierarchical urban traffic infrastructure maintained in a cloud infrastructure. A key outcome of MOVESMART is the design and implementation of novel renewable mobility services which incorporate eco-friendly modes of transport, most notably (shared) electric vehicles. The project delivers a set of innovative cloud-based mobility services; those are delivered through an integrated mobile application which offers a holistic view of renewable mobility incorporating a personalized time-dependent multimodal route-planning service along with EV-sharing and energy efficiency assessment.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel A Vehicular Internet of Things (IoT) System for High-Granularity Air Quality Monitoring in Smart Cities
Nächstes Kapitel Intelligent System for Predicting Motorcycle Accident by Reaching into a Smart City Using a Kriging Model to Achieve Its Prevention and the Reduction of Deaths in the Medium Term
Fußnoten
1
 
3
A driving cycle is a series of data points representing the speed of a vehicle versus time. Driving cycles are produced by different countries and organizations to assess the performance of vehicles in various ways, for example, fuel consumption and polluting emissions.
 
Literatur
1.
Salamanis, A., Drosou, A., Michalopoulos, D., Kehagias, D., & Tzovaras, D. (2016). A probabilistic framework for the reliability assessment of crowd sourcing urban traffic reports. Transportation Research Procedia, 14(2016), 4552–4561.CrossRef
2.
Salamanis, A., Kehagias, D. D., Filelis-Papadopoulos, C. K., Tzovaras, D., & Gravvanis, G. A. (2015). Managing spatial graph dependencies in large volumes of traffic data for travel-time prediction. IEEE Transactions on Intelligent Transportation Systems, 17(6), 1678–1687.CrossRef
3.
Salamanis, A., Meladianos, P., Kehagias, D., & Tzovaras, D. (2015). Evaluating the effect of time series segmentation on STARIMA-based traffic prediction model. Proceedings of the 2015 IEEE 18th international conference on intelligent transportation systems, pp. 2225–2230.
4.
Kontogiannis, S., Papastavrou, G., Paraskevopoulos, A., Wagner, D., & Zaroliagis, C. (2017). Improved oracles for time-dependent road networks. Proceedings of the 17th workshop on algorithmic approaches for transportation modeling, optimization, and systems (ATMOS 2017): 4:1–4:17.
5.
Brooker, A., Gonder, J., Wang, L., Wood, E., Lopp, S., & Ramroth, L. (2015). FASTSim: A model to estimate vehicle efficiency, cost and performance (No. 2015-01-0973). SAE Technical Paper.
6.
MOVESMART Deliverable D4.2.2: Renewable energy-efficient multimodal route planning algorithmic approaches. MOVESMART Project, July 2016.
7.
MOVESMART Deliverable D4.3.2: Renewable personal mobility trip planner. MOVESMART Project, July 2016.
8.
Angelopoulos, A., Gavalas, D., Konstantopoulos, C., Kypriadis, D., & Pantziou, G. (2016). An optimization model for the strategic design of a bicycle sharing system: A case study in the city of Athens. Proceedings of the 20th Pan-Hellenic conference on informatics (PCI 2016).
9.
Angelopoulos, A., Gavalas, D., Konstantopoulos, C., Kypriadis, D., & Pantziou, G. (2016). Incentivization schemes for vehicle allocation in one-way vehicle sharing systems. Proceedings of the 2016 IEEE international smart cities conference (ISC2 2016).
10.
Angelopoulos, A., Gavalas, D., Konstantopoulos, C., Kypriadis, D., & Pantziou, G. (2018). Incentivized vehicle relocation in vehicle sharing systems. Transportation Research Part C: Emerging Technologies, 97, 175–193.CrossRef
11.
Giannakopoulou, K., Kontogiannis, S., Papastavrou, G., & Zaroliagis, C. (2016). A cloud-based time-dependent routing service. Proceedings of the international workshop of algorithmic aspects of cloud computing (ALGOCLOUD 2016), pp. 41–64.
12.
Baum, M., Dibbelt, J., Pajor, T., & Wagner, D. (2016). Dynamic time-dependent route planning in road networks with user preferences. Proceedings of the international symposium on experimental algorithms (SEA 2016), pp. 33–49.
13.
Andreev, S., Dibbelt, J., Nöllenburg, M., Pajor, T., & Wagner, D. (2015). Towards realistic pedestrian route planning. Proceedings of the 15th workshop on algorithmic approaches for transportation modelling, optimization, and systems (ATMOS 2015), pp. 1–15.
14.
Baum, M., Dibbelt, J., Hübschle-Schneider, L., Pajor, T., & Wagner, D. (2014). Speed-consumption tradeoff for electric vehicle route planning. Proceedings of the 14th workshop on algorithmic approaches for transportation modeling, optimization, and systems (ATMOS 2014), pp. 138–151.
15.
Baum, M., Dibbelt, J., Gemsa, A., Wagner, D., & Zündorf, T. (2015). Shortest feasible paths with charging stops for battery electric vehicles. Proceedings of the 23rd SIGSPATIAL international conference on advances in geographic information systems, pp. 44:1–44:10.
16.
Cionini, A., D'Angelo, G., D'Emidio, M., Frigioni, D., Giannakopoulou, K., Paraskevopoulos, A., & Zaroliagis, C. (2017). Engineering graph-based models for dynamic timetable information systems. Journal of Discrete Algorithms, 46, 40–58.MathSciNetCrossRef
17.
Kontogiannis, S., Michalopoulos, G., Papastavrou, G., Paraskevopoulos, A., Wagner, D., & Zaroliagis, C. (2015). Analysis and experimental evaluation of time-dependent distance oracles. Proceedings of the 17th workshop on algorithm engineering and experiments (ALENEX 2015), pp. 147–158.
18.
Kontogiannis, S., Michalopoulos, G., Papastavrou, G., Paraskevopoulos, A., Wagner, D., & Zaroliagis, C. (2016). Engineering oracles for time-dependent road networks. Proceedings of the 18th Workshop on Algorithm Engineering and Experiments (ALENEX 2016), pp. 1–14.
19.
Gavalas, D., Konstantopoulos, C., & Pantziou, G. (2016). Design and management of vehicle-sharing systems: A survey of algorithmic approaches. In Smart cities and homes (pp. 261–289). Morgan Kaufmann, US.
20.
Kypriadis, D., Pantziou, G., Konstantopoulos, C., & Gavalas, D. (2018). Minimum walking static repositioning in free-floating electric car-sharing systems. In 2018 21st international conference on intelligent transportation systems (ITSC) (pp. 1540–1545). IEEE.
21.
Gavalas, D., Giannakopoulou, K., Kasapakis, V., Kehagias, D., Konstantopoulos, C., Kontogiannis, S., Kypriadis, D., Pantziou, G., Paraskevopoulos, A. & Zaroliagis, C. (2018). Renewable mobility in smart cities: Cloud-based services. Proceedings of the 2018 IEEE symposium on computers and communications (ISCC 2018), pp. 1280–1285.
22.
Gavalas, D., Kasapakis, V., & Dzardanova, E. (2019). Mobile persuasive applications. In Encyclopedia of computer graphics and games. Springer Science, in press.
Metadaten
Titel
Renewable Mobility in Smart Cities:TheMOVESMART Approach
verfasst von
Damianos Gavalas
Kalliopi Giannakopoulou
Vlasios Kasapakis
Dionisis Kehagias
Charalampos Konstantopoulos
Spyros Kontogiannis
Damianos Kypriadis
Grammati Pantziou
Andreas Paraskevopoulos
Christos Zaroliagis
Copyright-Jahr
2020
Buch
Smart Technologies for Smart Cities

Print ISBN: 978-3-030-39985-6

Electronic ISBN: 978-3-030-39986-3

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-39986-3_7

Neuer Inhalt

    Bildnachweise