Abstract
This paper functionally designs an efficient electric vehicle telematics framework for smart transportation, aiming at providing an EV-related advertisement via digital multimedia broadcasting. Taking advantage of information technology and wireless communication, the telematics system can support electric vehicle tracking, vehicle sharing, charging station selection, and location data analysis. The electric vehicle charge service develops a reservation protocol between drivers and stations, station-side scheduling, and path adaptation according to a new charge plan. In addition, as a promising business model, electric vehicle sharing needs station placement and relocation schemes, to which a previous pick-up point analysis result can give a helpful guide. The telematics framework enriches the related applications with diverse basic service building blocks and thus accelerates the penetration of electric vehicles into our daily life.
This research was supported by the MKE (The Ministry of Knowledge Economy), through the project of Region technical renovation, Republic of Korea.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gellings, C.W.: The Smart Grid: Enabling Energy Efficiency and Demand Response. CRC Press, Boca Raton (2009)
Mohsenian-Rad, A., Wong, V., Jatkevich, J., Schober, R., Leon-Garcia, A.: Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid 1, 320–331 (2010)
Korean Smart Grid Institute, http://www.smartgrid.or.kr/eng.htm
Frost & Sullivan: Strategic Market and Technology Assessment of Telematics Applications for Electric Vehicles. In: 10th Annual Conference of Detroit Telematics (2010)
Lee, J.-H., Park, G.-L., Kim, H., Yang, Y.-K., Kim, P.-K., Kim, S.-W.: A telematics service system based on the linux cluster. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2007. LNCS, vol. 4490, pp. 660–667. Springer, Heidelberg (2007)
Goldberg, A., Kaplan, H., Werneck, R.: Reach for A*: Efficient point-to-point shortest path algorithms. MSR-TR-2005-132. Microsoft (2005)
Xu, J., Lim, J.: A New Evolutionary Neural Network for Forecasting Net Flow of a Car Sharing System. In: IEEE Congress on Evolutionary Computation, pp. 1670–1676 (2007)
Ion, L., Cucu, T., Boussier, J., Teng, F., Breuil, D.: Site Selection for Electric Cars of a Car-Sharing Service. World Electric Vehicle Journal 3 (2009)
Derin, O., Ferrante, A.: Scheduling Energy Consumption with Local Renewable Micro-Generation and Dynamic Electricity Prices. In: First Workshop on Green and Smart Embedded System Technology: Infrastructures, Methods, and Tools (2010)
Lee, J., Park, G., Kang, M., Kwak, H., Lee, S.: Design of a Power Scheduler Based on the Heuristic for Preemptive Appliances. In: Nguyen, N.T., Kim, C.-G., Janiak, A. (eds.) ACIIDS 2011, Part II. LNCS (LNAI), vol. 6592, pp. 396–405. Springer, Heidelberg (2011)
Schweppe, H., Zimmermann, A., Grill, D.: Flexible In-vehicle Stream Processing with Distributed Automotive Control Units for Engineering and Diagnosis. In: IEEE 3rd International Symposium on Industrial Embedded Systems, pp. 74–81 (2008)
Chui, C., Chen, G.: Kalman Filtering with Real-Time Applications. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, J., Kim, HJ., Park, GL., Kwak, HY., Kim, Yc., Song, J. (2011). Electric Vehicle Telematics Framework for Smart Transportation. In: Kim, Th., Adeli, H., Robles, R.J., Balitanas, M. (eds) Advanced Communication and Networking. ACN 2011. Communications in Computer and Information Science, vol 199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23312-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-23312-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23311-1
Online ISBN: 978-3-642-23312-8
eBook Packages: Computer ScienceComputer Science (R0)