Skip to main content

Advertisement

Log in

Emerging Applications for Cyber Transportation Systems

  • Survey
  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

Recent advances in connected vehicles and autonomous driving are going to change the face of ground transportation as we know it. This paper describes the design and evaluation of several emerging applications for such a cyber transportation system (CTS). These applications have been designed using holistic approaches, which consider the unique roles played by the human drivers, the transportation system, and the communication network. They can improve driver safety and provide on-road infotainment. They can also improve transportation operations and efficiency, thereby benefiting travelers and attracting investment from both government agencies and private businesses to deploy infrastructures and bootstrap the evolutionary process of CTS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Slavik M, Mahgoub I. Spatial distribution and channel quality adaptive protocol for multihop wireless broadcast routing in VANET. IEEE Transactions on Mobile Computing, 2013, 12(4): 722-734.

    Article  Google Scholar 

  2. Guo L, Huang S, Sadek A W. An evaluation of likely environmental benefits of a time-dependent green routing system in the greater Buffalo-Niagara region. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 2013, 17(1): 18-30.

    Article  Google Scholar 

  3. Barnum D T, Karlaftis M G, Tandon S. Improving the efficiency of metropolitan area transit by joint analysis of its multiple providers. Transportation Research Part E: Logistics and Transportation Review, 2011, 47(6): 1160-1176.

    Article  Google Scholar 

  4. U.S. Department of Transportation. Safety pilot program overview, www.its.dot.gov/safety_pilot/spmd.htm, May 2014.

  5. Markoff J. Google cars drive themselves in traffic. The New York Times, October 2010. http://www.nytimes.com/2010/10/10/science/10google.html?pagewanted=all, May 2014.

  6. Zhang Y, Wu C, Wan J, Qiao C. Development and validation of warning message utility scale (WMUS). Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2013, 57(1): 1179-1183.

    Article  Google Scholar 

  7. Farah H, Koutsopoulos H N, Saifuzzaman H et al. Evaluation of the effect of cooperative infrastructure-to-vehicle systems on driver behavior. Transportation Research Part C: Emerging Technologies, 2012, 21(1): 42-56.

    Article  Google Scholar 

  8. Marshall D, Lee J D, Austria R A. Alerts for in-vehicle information systems: Annoyance, urgency, and appropriateness. Human Factors, 2007, 49(1): 145-157.

    Article  Google Scholar 

  9. Jamson A H, Merat N. Surrogate in-vehicle information systems and driver behavior: Effects of visual and cognitive load in rural driving. Transportation Research Part F: Traffic Psychology and Behaviour, 2005, 8(2): 79-96.

    Article  Google Scholar 

  10. Donmez B, Boyle L N, Lee J D. The impact of distraction mitigation strategies on driving performance. Human Factors, 2006, 48(4): 785-804.

    Article  Google Scholar 

  11. Verwey W B. On-line driver workload estimation: Effects of road situation and age on secondary task measures. Ergonomics, 2000, 43(2): 187-209.

    Article  Google Scholar 

  12. SAE International. Its in-vehicle message priority. Standard, J2395, 2002. http://subscriptions.sae.org/content/j2395_200-202, May 2014.

  13. Sohn H, Lee J D, Bricker D L et al. A dynamic programming algorithm for scheduling in-vehicle messages. IEEE Trans. Intelligent Transportation Systems, 2008, 9(2): 226-234.

    Article  Google Scholar 

  14. Wu C, Liu Y. Queuing network modeling of driver workload and performance. IEEE Trans. Intelligent Transportation Systems, 2007, 8(3): 528-537.

    Article  Google Scholar 

  15. Li X, Yu X, Wagh A, Qiao C. Human factors-aware service scheduling in vehicular cyber-physical systems. In Proc. IEEE International Conference on Computer Communications, April 2011, pp.2174-2182.

    Google Scholar 

  16. Guo M, Ammar M H, Zegura E W. V3: A vehicle-to-vehicle live video streaming architecture. In Proc. the 3rd Int. Conf. Pervasive Comp. and Commun., March 2005, pp.171-180.

  17. Yoon S, Ha D T, Ngo H Q, Qiao C. MoPADS: A mobility profile aided file downloading service in vehicular networks. IEEE Trans. Vehicular Technology, 2009, 58(9): 5235-5246.

    Article  Google Scholar 

  18. Chu Y, Huang N. Delivering of live video streaming for vehicular communication using peer-to-peer approach. In Proc. Mobile Networking for Vehicular Environments, May 2007, pp.1-6.

  19. Cheng H T, Shan H, Zhuang W. Infotainment and road safety service support in vehicular networking: From a communication perspective. Mechanical Systems and Signal Processing, 2011, 25(6): 2020-2038.

    Article  Google Scholar 

  20. Bucciol P, Masala E, Kawaguchi N, Takeda K, De Martin J. Performance evaluation of H. 264 video streaming over inter-vehicular 802.11 ad hoc networks. In Proc. the 16th Int. Symp. Personal, Indoor and Mobile Radio Communications, Sept. 2005, pp.1936-1940.

  21. Xue J, Chen C W. A new perceptual quality metric for video transrating for mobile devices. In Proc. the 2010 ACM Multimedia Workshop on Mobile Cloud Media Computing, Oct. 2010, pp.35-40.

  22. Song W, Tjondronegoro D W, Wang S et al. Impact of zooming and enhancing region of interests for optimizing user experience on mobile sports video. In Proc. the 18th ACM Int. Conf. Multimedia, Oct. 2010, pp.321-330.

  23. Dobrian F, Sekar V, Awan A et al. Understanding the impact of video quality on user engagement. In Proc. the ACM SIGCOMM Conference, Aug. 2011, pp.362-373.

    Google Scholar 

  24. Tan W L, Lau W C, Yue O, Hui T H. Analytical models and performance evaluation of drive-thru internet systems. IEEE J. Selected Areas in Communications, 2011, 29(1): 207-222.

    Article  Google Scholar 

  25. He K, Li X, Schick B, Qiao C, Sudhaakar R, Addepalli S, Chen X. On-road video delivery with integrated heterogeneous wireless networks. Ad Hoc Networks, 2013, 11(7): 1992-2001.

    Article  Google Scholar 

  26. Morwitza V G, Steckela J H, Guptab A. When do purchase intentions predict sales? Int. J. Forecasting, 2007, 23(3): 347-364.

    Article  Google Scholar 

  27. Sun B, Morwitz V G. Stated intentions and purchase behavior: A unified model. International Journal of Research in Marketing, 2010, 27(4): 356-366.

    Article  Google Scholar 

  28. Goldfarb A, Tucker C. Online advertising. Advances in Computers, 2011, 81: 289-315.

    Article  Google Scholar 

  29. Liu N, Liu M, Cao J et al. When transportation meets communication: V2P over VANETs. In Proc. the 30th IEEE Int. Conf. Distributed Computing Systems, Jun. 2010, pp.567-576.

  30. Deshpande P, Kashyap A, Sung C, Das S R. Predictive methods for improved vehicular WiFi access. In Proc. the 7th International Conference on Mobile Systems, Applications, and Services, June 2009, pp.263-276.

  31. Ge Y, Liu C, Xiong H, Chen J. A taxi business intelligence system. In Proc. the 17th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, Aug. 2011, pp.735-738.

  32. Yuan J, Zheng Y, Zhang C et al. T-drive: Driving directions based on taxi trajectories. In Proc. the 18th SIGSPATIAL Int. Conf. Advances in Geographic Information Systems, Nov. 2010, pp.99-108.

  33. Seow K T, Dang N H, Lee D. A collaborative multiagent taxi-dispatch system. IEEE Trans. Automation Science and Engineering, 2010, 7(3): 607-616.

    Article  Google Scholar 

  34. Alshamsi A, Abdallah S, Rahwan I. Multiagent self-organization for a taxi dispatch system. In Proc. the 8th Int. Conf. Autonomous Agents and Multiagent Systems, May 2009, pp.21-28.

  35. Hou Y, Li X, Zhao Y et al. Towards efficient vacant taxis cruising guidance. In Proc. IEEE Global Communications Conference, Dec. 2013.

    Google Scholar 

  36. Zhang D, Li Y, Zhang F, Lu M, Liu Y, He T. coRide: Car-pool service with a win-win fare model for large-scale taxicab networks. In Proc. the 11th ACM Conference on Embedded Networked Sensor Systems, Nov. 2013, Article No.9.

  37. Chen P, Liu J, Chen W. A fuel-saving and pollution-reducing dynamic taxi-sharing protocol in VANETs. In Proc. the 72nd IEEE Vehicular Technology Conf. Fall, Sept. 2010, pp.1-5.

  38. Chen C, Shallcross D, Shih Y et al. Smart ride share with flexible route matching. In Proc. the 13th Int. Conf. Advanced Communication Technology, Feb. 2011, pp.1506-1510.

  39. Hou Y, Li X, Qiao C. TicTac: From transfer-incapable car-pooling to transfer-allowed carpooling. In Proc. IEEE Global Communications Conference, Dec. 2012, pp. 268-273.

  40. Zhao Y, Wagh A, Hulme K et al. Integrated traffic-driving-networking simulator: A unique R&D tool for connected vehicles. In Proc. Int. Conf. Connected Vehicles and Expo, Dec. 2012, pp.203-204.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aditya Wagh.

Additional information

This research was partially supported by the National Science Foundation of USA under Grant No. NSF-CPS-1035733, the Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao of the National Natural Science Foundation of China under Grant No. 61228207, and the Cisco University Research Program.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(PDF 73 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wagh, A., Hou, Y., Qiao, C. et al. Emerging Applications for Cyber Transportation Systems. J. Comput. Sci. Technol. 29, 562–575 (2014). https://doi.org/10.1007/s11390-014-1450-9

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11390-014-1450-9

Keywords

Navigation