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
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2021

18.02.2021

Route Guidance System for the Road Network-A Review

verfasst von: Raushan Kumar Singh, Mukesh Kumar

Erschienen in: Wireless Personal Communications | Ausgabe 2/2021

Einloggen

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

search-config
loading …

Abstract

A comprehensive and satisfying route- guidance system is considered valuable for citizens and tourists worldwide. An effective route-guidance system is essential because of the sophisticated city formation and transportation system in India. For better utilization of route-guidance systems. It needs to be easy to use and informational but to be more sensible to give optimal route options in terms of low cost and low time in various situations (Such as climate conditions, traffic jam, road structure). This paper aims to comprehend the research trend in the route guidance system and easily observe the various technique of route guidance. Different impressive findings have come out of this study, supporting current and future researchers to evaluate and set their research roadmap. This paper also explains the existing approaches for route guidance systems in simple language, which will be fruitful for researchers. Furthermore, this paper also envisions the future of RGs, which may open up new research directions in this domain.
Vorheriger Artikel Large-Scale Analysis for Corridors of Different Dimensions and Morphology at 10 GHz Frequency
Nächster Artikel A Random Sensitive Area Based Privacy Preservation Algorithm for Location-Based Service

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

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+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 "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
Literatur
1.
Noreen, I., Khan, A., & Habib, Z. (2016). Optimal path planning using RRT* based approaches: a survey and future directions. International Journal of Advanced Computer Science and Application, 7(11), 97–107.CrossRef
2.
LaValle, S. M. (2006). Planning algorithms. Cambridge: Cambridge University Press.CrossRef
3.
He, Z., Chen, K., & Chen, X. (2017). A collaborative method for route discovery using taxi drivers’ experience and preferences. IEEE Transactions on Intelligent Transportation Systems, 19(8), 2505–2514.CrossRef
4.
Bao, S., Nitta, T., Yanagisawa, M., & Togawa, N. (2017). A safe and comprehensive route finding algorithm for pedestrians based on lighting and landmark conditions. IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, 100(11), 2439–2450.CrossRef
5.
Desai, P., Loke, S. W., Desai, A., & Singh, J. (2013). CARAVAN: Congestion avoidance and route allocation using virtual agent negotiation. IEEE Transactions on Intelligent Transportation Systems, 14(3), 1197–1207.CrossRef
6.
Jo, K., & Sunwoo, M. (2018). Development of localisation and mapping software for autonomous cars. IET Intelligent Transport Systems, 13(2), 406–416.CrossRef
7.
Boriboonsomsin, K., Barth, M. J., Zhu, W., & Vu, A. (2012). Eco-routing navigation system based on multisource historical and real-time traffic information. IEEE Transactions on Intelligent Transportation Systems, 13(4), 1694–1704.CrossRef
8.
Rahimi-Farahani, H., Rassafi, A. A., & Mirbaha, B. (2019). Forced-node route guidance system: Incorporating both user equilibrium and system optimal benefits. IET Intelligent Transport Systems, 13(12), 1851–1859.CrossRef
9.
Edelkamp, S., Jabbar, S., & Willhalm, T. (2005). Geometric travel planning. IEEE Transactions on Intelligent Transportation Systems, 6(1), 5–16.CrossRef
10.
Guo, C., Kidono, K., Terashima, R., & Kojima, Y. (2017). Humanlike behavior generation in urban environment based on learning-based potentials with a low-cost lane graph. IEEE Transactions on Intelligent Vehicles, 3(1), 46–60.CrossRef
11.
Jo, K., Lee, M., Lim, W., & Sunwoo, M. (2019). Hybrid local route generation combining perception and a precise map for autonomous cars. IEEE Access, 7, 120128–120140.CrossRef
12.
Liu, S., Yue, Y., & Krishnan, R. (2015). Non-myopic adaptive route planning in uncertain congestion environments. IEEE Transactions on Knowledge and Data Engineering, 27(9), 2438–2451.CrossRef
13.
Qu, B., Yang, W., Cui, G., & Wang, X. (2019). Profitable taxi travel route recommendation based on big taxi trajectory data. IEEE Transactions on Intelligent Transportation Systems, 21(2), 653–668.CrossRef
14.
Ding, J. W., Wang, C. F., Meng, F. H., & Wu, T. Y. (2010). Real-time vehicle route guidance using vehicle-to-vehicle communication. IET communications, 4(7), 870–883.MathSciNetCrossRef
15.
Federgruen, A., & Simchi-Levi, D. (1995). Analysis of vehicle routing and inventory-routing problems. Handbooks in operations research and management science, 8, 297–373.MathSciNetCrossRef
16.
Zhou, Y., Luo, Q., Xie, J., & Zheng, H. (2016). A hybrid bat algorithm with path relinking for the capacitated vehicle routing problem. In: Metaheuristics and Optimization in Civil Engineering , Springer, Cham (pp. 255–276).
17.
Pattanaik, V., Singh, M., Gupta, P. K., & Singh, S. K. (2016, November). Smart real-time traffic congestion estimation and clustering technique for urban vehicular roads. In IEEE region 10 conference (TENCON) (pp. 3420–3423). IEEE.
18.
Yan, L., Hu, W., & Hu, S. (2019). SALA: a self-adaptive learning algorithm—towards efficient dynamic route guidance in urban traffic networks. Neural Processing Letters, 50(1), 77–101.CrossRef
19.
Tian, Y., Hu, W., Du, B., Hu, S., Nie, C., & Zhang, C. (2019). IQGA: A route selection method based on quantum genetic algorithm-toward urban traffic management under big data environment. World Wide Web, 22(5), 2129–2151.CrossRef
20.
Yuan, J., Zheng, Y., Zhang, C., Xie, W., Xie, X., Sun, G., & Huang, Y. (2010, November). T-drive: driving directions based on taxi trajectories. In Proceedings of the 18th SIGSPATIAL International conference on advances in geographic information systems (pp. 99–108).
21.
Yuan, J., Zheng, Y., Xie, X., & Sun, G. (2011). T-drive: Enhancing driving directions with taxi drivers’ intelligence. IEEE Transactions on Knowledge and Data Engineering, 25(1), 220–232.CrossRef
22.
Chen, Z., Shen, H. T., & Zhou, X. (2011, April). Discovering popular routes from trajectories. In 2011 IEEE 27th International Conference on Data Engineering (pp. 900–911). IEEE.
23.
Wei, L. Y., Chang, K. P., & Peng, W. C. (2015). Discovering pattern-aware routes from trajectories. Distributed and Parallel Databases, 33(2), 201–226.CrossRef
24.
Zhang, J., Meng, W., Liu, Q., Jiang, H., Feng, Y., & Wang, G. (2016). Efficient vehicles path planning algorithm based on taxi GPS big data. Optik, 127(5), 2579–2585.CrossRef
25.
Liu, S., Hou, Z., Tian, T., Deng, Z., & Li, Z. (2019). A novel dual successive projection-based model-free adaptive control method and application to an autonomous car. IEEE transactions on neural networks and learning systems, 30(11), 3444–3457.MathSciNetCrossRef
26.
Teixeira, L., Oswald, M. R., Pollefeys, M., & Chli, M. (2020). Aerial single-view depth completion with image-guided uncertainty estimation. IEEE Robotics and Automation Letters, 5(2), 1055–1062.CrossRef
27.
Zhu, Y., Wang, Y., Forman, G., & Wei, H. (2015). Mining large-scale GPS streams for connectivity refinement of road maps. The Computer Journal, 58(9), 2109–2119.CrossRef
28.
Vreeswijk, J. D., Landman, R. L., van Berkum, E. C., Hegyi, A., Hoogendoorn, S. P., & van Arem, B. (2015). Improving the road network performance with dynamic route guidance by considering the indifference band of road users. IET Intelligent Transport Systems, 9(10), 897–906.CrossRef
29.
Li, Q., Shangguan, W., Cai, B., & Chai, L. (2019, July). Traffic flow guidance and optimization of connected vehicles based on swarm intelligence. In 2019 Chinese Control Conference (CCC) (pp. 2099–2104). IEEE.
30.
Kim, K., Kwon, M., Park, J., & Eun, Y. (2016). Dynamic vehicular route guidance using traffic prediction information. Mobile Information Systems, 2016, 3727865.
31.
Latip, N. B. A., Omar, R., & Debnath, S. K. (2017). Optimal Path Planning using Equilateral Spaces Oriented Visibility Graph Method. International Journal of Electrical & Computer Engineering, 7(6), 2088–8708.
32.
Yang, H., Cherry, C. R., Zaretzki, R., Ryerson, M. S., Liu, X., & Fu, Z. (2016). A GIS-based method to identify cost-effective routes for rural deviated fixed route transit. Journal of Advanced Transportation, 50(8), 1770–1784.CrossRef
33.
El-Sayed, H., Thandavarayan, G., & Hawas, Y. (2017). A Cost Effective Route Guidance Method for Urban Areas Using Histograms. Wireless Communications and Mobile Computing, 2017, 4507352.
34.
Liang, Z., & Wakahara, Y. (2014, October). A route guidance system with personalized rerouting for reducing traveling time of vehicles in urban areas. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC) (pp. 1541–1548). IEEE.
Metadaten
Titel
Route Guidance System for the Road Network-A Review
verfasst von
Raushan Kumar Singh
Mukesh Kumar
Publikationsdatum
18.02.2021
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-021-08255-z

Weitere Artikel der Ausgabe 2/2021

Wireless Personal Communications 2/2021 Zur Ausgabe

OriginalPaper

Energy Efficient Intra Cluster Gateway Optimal Placement in Wireless Sensor Network

OriginalPaper

Formal Specification and Verification of MQTT Protocol in PlusCal-2

OriginalPaper

Energy Efficient and Reliability Aware Workflow Task Scheduling in Cloud Environment

OriginalPaper

Computational Design, Analysis and Characterization of Beetle Shaped High Isolation Multiple-Input-Multiple-Output Reconfigurable Monopole-Antenna with Dual Band Filters for Wireless Applications

OriginalPaper

Greedy Forwarding Routing Schemes using an Improved K-Means Approach for Wireless Sensor Networks

OriginalPaper

Developing a Web Platform for the Management of the Predictive Maintenance in Smart Factories

Neuer Inhalt

    Bildnachweise