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A Comprehensive Survey of Various Localization Methods in Vehicular Ad Hoc Network


Affiliations
1 Department of Electronics and Communication Engineering, St. Joseph’s Institute of Technology, Chennai, Tamil Nadu, India
2 Department of Electronics and Communication Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India
 

Internet of Things (IoT) has had an evolutionary impact in recent days. The various changes in lifestyle and other critical influences have a huge impact on the growth of IoT. IoT in localization-based applications has attained remarkable attention, especially in the localization/positioning of vehicle tracking, health sector, etc. Localization is vital for Vehicular Ad Hoc Networks (VANET) in wireless communication technologies. VANET is prominent for most accident prevention, vehicle tracking, and efficient transportation applications. Most of the existing systems contain GPS technology integrated with vehicles for localization-based applications. The evolution of IoT replaces GPS in the VANET localization application. Various localization solutions are evolved in the literature, but it fails to meet the localization precision according to the consumer needs. In this survey, we have done depth analysis of existing technologies and techniques in the field of localization along with IoT. The analysis includes various parameters like RSU usage, Cooperative Localization methods, VANET localization effects, etc. This study describes that the RSU structures did not improve localization accuracy; instead, it minimizes the required mobile anchor nodes in VANET. Different VANET operations and their results related to real-world scenarios are discussed in detail. Finally, as a result of this potential research, a refined methodology is introduced for future research.

Keywords

Localization, VANET, IoT, GPS Technology, Cooperative Localization Methods.
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  • Amundson I, Koutsoukos XD (2009) A survey on localization for mobile wireless sensor networks. In: Fuller R, Koutsoukos XD (eds) Mobile entity localization and tracking in GPS-less environnments. Springer, Berlin, pp 235–254

  • Al-Sultan S, Al-Doori MM, Al-Bayatti AH, Zedan H (2014) A comprehensive survey on vehicular ad hoc network. J Netw Comput Appl 37:380–392

  • Boukerche A, Oliveira HABF, Nakamura EF, Loureiro AAF (2008) Vehicular ad hoc networks: a new challenge for localization-based systems. Comput Commun 31(12):2838–2849

  • Savarese C, Rabaey JM, Beutel J (2001) Location in distributed ad-hoc wireless sensor networks. In: International conference on acoustics, speech, and signal processing. Proceedings. (ICASSP’01), volume 4, pp. 2037–2040. IEEE

  • Raut SB, Malik LG (2014) Survey on vehicle collision prediction in vanet. In: 2014 IEEE International conference on computational intelligence and computing research, pp 1–5

  • Kuutti S, Fallah S, Katsaros K, Dianati M, Mccullough F, Mouzakitis A (2018) A survey of the state-of-the-art localization techniques and their potentials for autonomous vehicle applications. IEEE Internet Things J 5(2):829–846

  • White CE, Bernstein D, Kornhauser AL (2000) Some map-matching algorithms for personal navigation assistants. Transp Res Part C: Emerg Technol 8(1):91–108

  • Kihei B, Copeland JA, Chang Y (2014) Doppler domain localization for collision avoidance in vanets by using omnidirectional antennas. In: 2014 International conference on connected vehicles and Expo (ICC), pp 331–337

  • Zhu W, Gao D, Foh CH, Zhao W, Zhang H (2016) A collision avoidance mechanism for emergency message broadcast in urban vanet. In: 2016 IEEE 83rd vehicular technology conference (VTC Spring), pp. 1–5

  • Ansari AR, Saeed N, Ul Haq MI, Cho S (2018) Accurate 3d localization method for public safety applications in vehicular ad-hoc networks. IEEE Access 6:20756–20763

  • Deshmuk M, Dinesh D (2014) Challenges in-vehicle ad hoc network (vanet). Int J Eng Technol Manag Appl Sci 2(7):76–88

  • Parkinson BW, Enge P, Axelrad P, Spilker Jr JJ (1996) Global positioning system: theory and applications, Volume II. American Institute of Aeronautics and Astronautics

  • Misra P, Enge P (2006) Global positioning system: signals, measurements and performance, 2nd edn. Ganga-Jamuna Press, Massachusetts

  • Alkan RM, Karaman H, Sahin M (2005) Gps, galileo and GLONASS satellite navigation systems amp;amp; GPS modernization. In: Proceedings of 2nd international conference on recent advances in space technologies, 2005. RAST 2005., pp 390–394

  • Malik Y, Khaliq KA, Abdulrazak B, Tariq MU (2011) Mobile node localization in cellular networks. CoRR, abs/1201.2102

  • Chausse F, Laneurit J, Chapuis R (2005) Vehicle localization on a digital map using particles filtering. In: IEEE Proceedings. Intelligent vehicles symposium, pp 243–248

  • Fogue M, Sanguesa JA, Martinez FJ, Marquez-Barja JM (2018) Improving roadside unit deployment in vehicular networks by exploiting genetic algorithms. Appl Sci 8(1):86

  • Patwari N, Ash JN, Kyperountas S, Hero AO, Moses RL, Correal NS (2005) Locating the nodes: cooperative localization in wireless sensor networks. IEEE Signal Process Mag 22(4):54–69

  • C. Sun, H. Zhao, L. Bai, J. W. Cheong, A. G. Dempster, and W. Feng, “GNSS-5G Hybrid Positioning Based on TOA/AOA Measurements,” in Lecture Notes in Electrical Engineering, vol. 652 LNEE, no. June, 2020, pp. 527–537. doi: 10.1007/978-981-15-3715-8_47.

  • M. U. Liaquat, H. S. Munawar, A. Rahman, Z. Qadir, A. Z. Kouzani, and M. A. P. Mahmud, “Localization of Sound Sources : A Systematic Review,” 2021.

  • M. Wang et al., “Indoor PDR Positioning Assisted by Acoustic Source Localization, and Pedestrian Movement Behavior Recognition, Using a Dual-Microphone Smartphone,” Wireless Communications and Mobile Computing, vol. 2021, pp. 1–16, Jul. 2021, doi: 10.1155/2021/9981802

  • I. Martin-Escalona and E. Zola, “Passive round-trip-time positioning in dense ieee 802.11 networks,” Electronics (Switzerland), vol. 9, no. 8, pp. 1–19, 2020, doi: 10.3390/electronics9081193.

  • W. Shao, H. Luo, F. Zhao, H. Tian, S. Yan, and A. Crivello, “Accurate Indoor Positioning Using Temporal-Spatial Constraints Based on Wi-Fi Fine Time Measurements,” IEEE Internet of Things Journal, vol. 7, no. 11, pp. 11006–11019, 2020, doi: 10.1109/JIOT.2020.2992069.

  • F. Noor, M. A. Khan, A. Al-Zahrani, I. Ullah, and K. A. Al-Dhlan, “A review on communications perspective of flying AD-HOC networks: Key enabling wireless technologies, applications, challenges and open research topics,” Drones, vol. 4, no. 4, pp. 1–14, 2020, doi: 10.3390/drones4040065.

  • I. Martin-Escalona and E. Zola, “Passive round-trip-time positioning in dense ieee 802.11 networks,” Electronics (Switzerland), vol. 9, no. 8, pp. 1–19, 2020, doi: 10.3390/electronics9081193.

  • P. Ssekidde, O. S. Eyobu, D. S. Han, and T. J. Oyana, “Augmented cwt features for deep learning-based indoor localization using wifi rssi data,” Applied Sciences (Switzerland), vol. 11, no. 4, pp. 1–23, 2021, doi: 10.3390/app11041806.

  • J. Wang and J. G. Park, “An enhanced indoor positioning algorithm based on fingerprint using fine-grained csi and rssi measurements of ieee 802.11n wlan,” Sensors, vol. 21, no. 8, 2021, doi: 10.3390/s21082769.

  • Suryawanshi S, Gupta D, Gupta S, Jain S (2015) On the hybrid augmentation of inter-vehicular communication assisted localization using previous path detection. In: Advance Computing conference (IACC), 2015 IEEE International, pp 82–87. IEEE

  • Soatti G, Nicoli M, Garcia N, Denis B, Raulefs R, Wymeersch H (2017) Implicit cooperative positioning in vehicular networks. arXiv preprint arXiv :1709.01282

  • Rezaei S, Sengupta R (2007) Kalman filter-based integration of dgps and vehicle sensors for localization. IEEE Trans Control Syst Technol 15(6):1080–1088

  • Drawil N, Basir O (2008) Vehicular collaborative technique for location estimate correction. In: Vehicular technology conference, 2008. VTC 2008-Fall. IEEE 68th, pp 1–5. IEEE

  • Drawil N, Basir O (2009) Toward increasing the localization accuracy of vehicles in vanet. In: International conference on vehicular electronics and safety (ICVES), pp 13–18. IEEE

  • Mo Y, Dexin Y, Song J, Zheng K, Guo Y (2016) Vehicle position updating strategy based on Kalman filter prediction in vanet environment. Discrete Dyn Nat Soc. https ://doi. org/10.1155/2016/14043 96

  • Rohani M, Gingras D, Vigneron V, Gruyer D (2015) A new decentralized Bayesian approach for cooperative vehicle localization based on fusion of GPS and vanet based inter-vehicle distance measurement. IEEE Intell Transp Syst Mag 7(2):85–95

  • Howard A, Mataric MJ, Sukhatme GS (2003) Putting the’i’in’team’: an ego-centric approach to cooperative localization. In: IEEE International conference on robotics and automation. Proceedings. ICRA’03., volume 1, pp 868–874

  • Fox D, Burgard W, Thrun S (1999) Markov localization for mobile robots in dynamic environments. J Artif Intell Res 11:391–427

  • Howard A, Matark MJ, Sukhatme GS (2002) Localization for mobile robot teams using maximum likelihood estimation. In: IEEE/RSJ International conference on intelligent robots and systems., volume 1, pp 434–439

  • Ghaleb FA, Zainal A, Rassam MA, Abraham A (2017) Improved vehicle positioning algorithm using enhanced innovation- based adaptive Kalman filter. Pervasive Mob Comput 40:139–155

  • Kulkarni PS, Labade RP (2017) Vehicle positioning using Kalman filter for dedicated short range communication. Int J Eng Technol Sci Res 4(5):608–613

  • Najah Abu Ali and Mervat Abu-Elkheir (2015) Improving localization accuracy: successive measurements error modeling. Sensors 15(7):15540–15561

  • Nabil Mohamed Drawil and Otman Basir (2010) Intervehiclecommunication- assisted localization. IEEE Trans Intell Transp Syst 11(3):678–691

  • Cruz SB, Abrudan TE, Xiao Z, Trigoni N, Barros J (2017) Neighbor-aided localization in vehicular networks. IEEE Trans Intell Transp Syst 18(10):2693–2702

  • Hoang GM, Denis B, Härri J, Slock DT (2017) Robust data fusion for cooperative vehicular localization in tunnels. In: Intelligent vehicles symposium (IV), 2017 IEEE, pp 1372–1377. IEEE

  • Ali Ufuk Peker and Tankut Acarman (2017) Vanet-assisted cooperative vehicle mutual positioning: feasibility study. IEICE Trans Fundam Electron Commun Comput Sci 100(2):448–456

  • Jensfelt P (2001) Approaches for mobile robot localization in indoor environments. Ph. D. thesis, Royal Institute of Technology, Stockholm, Sweden

  • Rekleitis I (2003) Cooperative localization and multi-robot exploration. Ph. D. thesis, School of Computer Science, McGill University, Montreal, Quebec, Canada

  • Chausse F, Laneurit J, Chapuis R (2005) Vehicle localization on a digital map using particles filtering. In: Intelligent vehicles symposium, 2005. Proceedings. IEEE, pp 243–248. IEEE

  • Hoang GM, Denis B, Härri J , Slock DTM (2016) Cooperative localization in GNSS-aided vanets with accurate ir-uwb range measurements. In: Positioning, navigation and communications (WPNC), 2016 13th Workshop on, pp 1–6. IEEE

  • Peker AU, Acarman T, Yaman C, Yuksel E (2014) Vehicle localization enhancement with vanets. In: Intelligent vehicles symposium proceedings, 2014 IEEE, pp 661–666. IEEE

  • Boukerche A, Rezende C, Pazzi RW (2009) Improving neighbor localization in vehicular ad hoc networks to avoid overhead from periodic messages. In: Global telecommunications conference, 2009. GLOBECOM 2009. IEEE, pp 1–6. IEEE

  • Montgomery J (2005) A real-time traffic and weather reporting system for motorists. In: Second IEEE consumer communications and networking conference. CCNC., pp 580–581

  • Jiangfeng W, Feng G, Fei Y, Shaoxuan S (2009) Design of wireless positioning algorithm of intelligent vehicle based on vanet. In: Intelligent vehicles symposium, 2009 IEEE, pp 1098–1102. IEEE

  • Reza TA, Barbeau M, Alsubaihi B (2013) Tracking an on the run vehicle in a metropolitan vanet. In: Intelligent vehicles symposium (IV), 2013 IEEE, pp 220–227. IEEE

  • Reza TA, Barbeau M, Lamothe G, Alsubaihi B (2013) Noncooperating vehicle tracking in vanets using the conditional logit model. In: 16th International IEEE conference on intelligent transportation systems-(ITSC), pp 626–633.


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  • A Comprehensive Survey of Various Localization Methods in Vehicular Ad Hoc Network

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Authors

Maria Christina Blessy A
Department of Electronics and Communication Engineering, St. Joseph’s Institute of Technology, Chennai, Tamil Nadu, India
S. Brindha
Department of Electronics and Communication Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India

Abstract


Internet of Things (IoT) has had an evolutionary impact in recent days. The various changes in lifestyle and other critical influences have a huge impact on the growth of IoT. IoT in localization-based applications has attained remarkable attention, especially in the localization/positioning of vehicle tracking, health sector, etc. Localization is vital for Vehicular Ad Hoc Networks (VANET) in wireless communication technologies. VANET is prominent for most accident prevention, vehicle tracking, and efficient transportation applications. Most of the existing systems contain GPS technology integrated with vehicles for localization-based applications. The evolution of IoT replaces GPS in the VANET localization application. Various localization solutions are evolved in the literature, but it fails to meet the localization precision according to the consumer needs. In this survey, we have done depth analysis of existing technologies and techniques in the field of localization along with IoT. The analysis includes various parameters like RSU usage, Cooperative Localization methods, VANET localization effects, etc. This study describes that the RSU structures did not improve localization accuracy; instead, it minimizes the required mobile anchor nodes in VANET. Different VANET operations and their results related to real-world scenarios are discussed in detail. Finally, as a result of this potential research, a refined methodology is introduced for future research.

Keywords


Localization, VANET, IoT, GPS Technology, Cooperative Localization Methods.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F210729