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VIPER: an adaptive guidance and notification service system in internet of vehicles

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Abstract

In recent years, Internet of Vehicles has attracted increasing research attention, especially from the viewpoint of establishing effective information transmission methods to aid drivers and road users. Drivers can currently receive numerous types of assisted information. However, too much and cluttered information may affect their driving performance. Thus, effective guidance and notification services should be provided to drivers according to time, location, and events. For this purpose, we propose a Message Queue Telemetry Transport-based adaptive guide and notification service system called VIPER to provide driving assistance information. VIPER adaptively provides information to drivers and road users based on five conditions: Vehicle, points of Interest, People, Environment, and Roads. First, we establish a hierarchical grid architecture that is used to provide location-based services. Second, we collect information from the vehicles, roads, and environmental sensors to produce a weighted road network. Then, guide and notification services are provided based on this network. Thus, we can provide real-time driving assistance and help drivers to increase their safety and avoid traffic jams. We also analyze historical traffic data collected from vehicle detectors and accident data to estimate the safety and accident risk degrees of roads. To verify the feasibility of the proposed system, a system prototype is implemented to provide guidance and notification services. The experimental results show that our system can effectively assist drivers and road users and that it has a low system response time.

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References

  1. Bandyopadhyay, S., Bhattacharyya, A.: Lightweight Internet Protocols for Web Enablement of Sensors Using Constrained Gateway Devices. In: Proceedings of International Conference on Computing, Networking and Communications, San Diego, CA, USA (2013)

  2. Bormann, C.: CoAp-Constrained Application Protocol|Overview. http://coap.technology/ (2016). Accessed 2 Mar. 2017

  3. Caro, N.D., Colitti, W., Steenhaut, K., Mangino, G., Reali, G.: Comparison of Two Lightweight Protocols for Smartphone-based Sensing. In: Proceedings of the 20th IEEE Symposium on Communications and Vehicular Technology in the Benelux, Namur, Belgium. 1–6 (2013)

  4. Chang, K.C., Wang, K.H.: Design and Implementation of Traffic Safety Guardian System for Android Based on OpenCV. In: Proceedings of the International Conference on Connected Vehicles and Expo, Beijing, China. 288–289 (2012)

  5. Chang, K.C., Wang, K.H.: Enhancing Performance of Traffic Safety Guardian System on Android by Task Skipping Mechanism. In: Proceedings of IEEE 17th International Symposium on Consumer Electronics, Hsinchu, Taiwan. 115–116 (2013)

  6. Chen, Y.H., Chen, C.Y.: Service Oriented Cloud VM Placement Strategy for Internet of Things. IEEE Access PP(99), 1–11 (2017)

  7. Chu, W.T., Huang, W.H.: Cultural difference and visual information on hotel rating prediction. World Wide Web. 20(4), 595–619 (2017)

    Article  Google Scholar 

  8. Chu, W.T., Tsai, Y.L.: A hybrid recommendation system considering visual information for predicting favorite restaurants. World Wide Web. 20(6), 1313–1331 (2017)

    Article  Google Scholar 

  9. Dow, C.R., Nguyen, D.B., Wang, S.C., Tsai, M.F.: A geo-aware taxi carrying management system by using location based services and zone queuing techniques on internet of things. Mob. Inf. Syst. 2016(5), 1–10 (2016). https://doi.org/10.1155/2016/9817374

    Google Scholar 

  10. Dow, C.R., Nguyen, D.B., Chen, H.C., Hwang, S.F.: An adaptive and hotspot aware taxi zone queuing system on internet of vehicles. Int. J. Semantic Web Info. Syst. 13(3), 89–106 (2017)

    Article  Google Scholar 

  11. Foundation, W.: A* search algorithm. https://en.wikipedia.org/wiki/A*_search_algorithm (2017). Accessed 1 May. 2017

  12. Gupta, V.: Invited Talk: IoT Protocols War and the Way Forward. In: Proceedings of the 28th IEEE International Conference on VLSI Design, Bangalore, India. 28 (2015)

  13. Gupta, K., Wable, G., Batra, T.: Collision Detection System for Vehicles in Hilly and Dense Fog Affected Area to Generate Collision Alerts. In: Proceedings of International Conference on Issues and Challenges in Intelligent Computing Techniques, Ghaziabad, India. 38–40 (2014)

  14. Han, C., Shao, X.: Double Signal Double Display Intersection Vehicle Terminal System for Parking Navigation. In: Proceedings of the IEEE International Conference System Science and Engineering (ICSSE), Shanghai, China. 103–107 (2014)

  15. Jaffey, T.: MQTT and CoAP, IoT Protocols. https://eclipse.org/community/eclipse_newsletter/2014/february/article2.php (2014). Accessed 1 Mar. 2014

  16. Jo, H.C., Jin, H.W.: Adaptive Periodic Communication over MQTT for Large-Scale Cyber-Physical Systems. In: Proceedings of the 3rd IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, Hong Kong, China. 66–69 (2015)

  17. Kharchenko, V., Illiashenko, O., Boyarchuk, A., Sklyar, V., Phillips, C.: Emerging Curriculum for Industry and Human Applications in Internet of Things. In: Proceedings of 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Bucharest, Romania, Romania. 918–922 (2017)

  18. Lee, S., Kim, H., Hong, D.K., Ju, H.: Correlation Analysis of MQTT Loss and Delay According to QoS Level. In: Proceedings of International Conference on Information Networking, Washington, DC, USA. 714–717 (2013)

  19. Li, C., Feng, H., Zhi, X., Nale, Z.: Intelligent Guidance System for Foggy Area Traffic Safety Operation. In: Proceedings of the 14th IEEE International Conference on Intelligent Transportation Systems, Washington, DC, USA. 428–432 (2011)

  20. Li, H., Zhang, Y., Chen, Y.: PSTEP-A Novel Probabilistic Event Processing Language for Uncertain Spatio-temporal Event Streams of Internet of Vehicles. In: Proceedings of IEEE International Conference on Software Quality, Reliability and Security-Companion, Vancouver, BC, Canada. 161–168 (2015)

  21. Maevsky, D., Bojko, A., Maevskaya, E., Vinakov, O., Shapa, L.: Internet of Things: Hierarhy of Smart Systems. In: Proceedings of the 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Bucharest, Romania, Romania. 821–827 (2017)

  22. Mosquitto: An Open Source MQTT v3.1 Broker. https://mosquitto.org/ (2017). Accessed 2 Sep. 2017

  23. MQTT: MQTT. http://mqtt.org/ (2014). Accessed 2 Aug. 2017

  24. Nafi, N.S., Khan, J.Y.: A VANET Based Intelligent Road Traffic Signalling System. In: Proceedings of Australasian Telecommunication Networks and Applications Conference, Brisbane, QLD, Australia. 1–6 (2012)

  25. OASIS: OASIS | Advancing open standards for the information society. https://www.oasis-open.org/ (2017). Accessed 2 Apr. 2017

  26. Ota, K., Kumrai, T., Dong, M., Kishigami, J., Guo, M.: Smart infrastructure Design for Smart Cities. IT Prof. 19(3), 42–49 (2017)

    Article  Google Scholar 

  27. Pandit, K., Ghosal, D., Zhang, H.M., Chuah, C.N.: Adaptive traffic signal control with vehicular ad hoc networks. IEEE Trans. Veh. Technol. 62(4), 1459–1471 (2013)

    Article  Google Scholar 

  28. Paul, A., Daniel, A., Ahmad, A., Rho, S.: Cooperative cognitive intelligence for internet of vehicles. IEEE Syst. J. 11(3), 1249–1258 (2017)

    Article  Google Scholar 

  29. Shah, M.A., Kulkarni, D.B.: Storm Pub-Sub: High Performance, Scalable Content Based Event Matching System Using Storm. In: Proceedings of IEEE Parallel and Distributed Processing Symposium Workshop, Hyderabad, India. 585–590 (2015)

  30. Smida, E.B., Fantar, S.G., Youssef, H.: Video Streaming Challenges Over Vehicular Ad-hoc Networks in Smart Cities. In: Proceedings of International Conference on Smart, Monitored and Controlled Cities (SM2C), Sfax, Tunisia, Tunisia. 12–16 (2017)

  31. Szabó, R., Farkas, K.: Publish/Subscribe Communication for Crowd-Sourcing Based Smart City Application. In: Proceedings of the 2nd International Conference of Informatics and Management Sciences, Zilina, Slovak Republi. 25–29 (2013)

  32. Thangavel, D., Ma, X., Valera, A., Tan, H.X., Tan, C.K.Y.: Performance Evaluation of MQTT and CoAP via a Common Middleware. In: Proceedings of the 9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Singapore. 1–6 (2014)

  33. Wang, H., Luo, T.: A Safety Message Broadcasting Scheme with QoS Guarantee for VANET. In: Proceedings of World Automation Congress (WAC), Puerto Vallarta, Mexico. 1–4 (2012)

  34. Wei, N., Weiyang, Q., Fangqi, Z., Yu, Y., Decun, D.: Contract Strategy Design in Early Stage of Implementing Pay-How-You-Drive Policy with Traditional Commercial Vehicle Insurance Coexisted. In: Proceedings of the 12th IEEE International Conference on Service Systems and Service Management, Guangzhou, China. 1–4 (2015)

  35. Yang, F., Wang, S., Li, J., Liu, Z., Sun, Q.: An overview of internet of vehicles. Comm. Chin. 11(10), 1–15 (2014)

    Article  Google Scholar 

  36. Zhang, X., Yu, L., Wang, Y., Xue, G., Xu, Y.: Intelligent Travel and Parking Guidance System Based on Internet of Vehicle. In: Proceedings of the 2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China. 2626–2629 (2017)

  37. Zheng, K., Zheng, B., Xu, J., Liu, G.F., Liu, A., Li, Z.: Popularity-aware spatial keyword search on activity trajectories. World Wide Web. 20(4), 749–773 (2017)

    Article  Google Scholar 

  38. Zhu, J., Jiang, W., Liu, A., Liu, G.F., Zhao, L.: Effective and efficient trajectory outlier detection based on time-dependent popular route. World Wide Web. 20(1), 111–134 (2017)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan

    Chyi-Ren Dow, Duc-Binh Nguyen, Syuan Cheng, Po-Yu Lai & Shiow-Fen Hwang

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  1. Chyi-Ren Dow
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  2. Duc-Binh Nguyen
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  3. Syuan Cheng
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  5. Shiow-Fen Hwang
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Correspondence to Chyi-Ren Dow.

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Dow, CR., Nguyen, DB., Cheng, S. et al. VIPER: an adaptive guidance and notification service system in internet of vehicles. World Wide Web 22, 1669–1697 (2019). https://doi.org/10.1007/s11280-018-0617-7

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  • DOI: https://doi.org/10.1007/s11280-018-0617-7

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