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CICAPS: a cooperative intersection collision avoidance persistent system for cooperative intersection ADAS

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Abstract

Dangerous collisions happen at traffic intersections and cause dire effects. So, numerous systems based on Vehicular ad hoc networks (VANET) have been introduced to prevent collisions and enhance users’ safety at intersections. However, these systems may engender several problems since they do not store data in appropriate databases, while VANET cannot currently guarantee the reception of all messages. To improve the safety in the intersections without stop signs and traffic lights, we propose in this paper a new system, entitled cooperative intersection collision avoidance persistent system (CICAPS). This system is based on real-time databases (RTDB), the notion of Quality of Data (QoD) and a hybrid architecture using vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications. The introduction of RTDB makes CICAPS able to manage real-time data, which are characterized by very rapid evolution and limited temporal validity, and to leverage these data to better control intersection situations. Moreover, it helps CICAPS respect the time constraints of transactions, knowing that late orders are likely to cause accidents. As for the notion of QoD, it allows decreasing the numbers of data updates and exchanged messages, and so the risk of congestion of messages and loss of data. Regarding the hybrid architecture, it allows implementing both a central driving control and a distributed driving control, and so increasing the operational reliability and the failure tolerance. Finally, CICAPS can deal with different forms of intersections and not only four-way perfect-intersections. Simulations of various driving scenarios at urban intersections, under the vehicles in network simulation (VEINS) framework, confirm that CICAPS ensures a robust and efficient intersection management safety.

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References

  1. U.S. Departement of Transportation, Federal Highway Administration. https://highways.dot.gov/research-programs/safety/intersection-safety. Accessed Mar 2020

  2. Scanlon JM, Kusano KD, Sherony R, Gabler HC (2015) Potential of intersection driver assistance systems to mitigate straight crossing path crashes using us nationally representative crash data. In: 2015 IEEE intelligent vehicles symposium (IV), pp 1207–1212. IEEE

  3. Peng S, Chen Y, Mengmeng L (2022) Smart city information processing under internet of things and cloud computing. J Supercomput 78(3):3676–3695

    Article  Google Scholar 

  4. Dahiya A, Chauhan RK (2010) A comparative study of manet and vanet environment. J Comput 2(7):87–92

    Google Scholar 

  5. Sleem L, Noura HN, Couturier R (2020) Towards a secure its: overview, challenges and solutions. J Inf Secur Appl 55:102637

    Google Scholar 

  6. Dominguez JML, Sanguino TJM (2019) Review on v2x, i2x, and p2x communications and their applications: a comprehensive analysis over time. Sensors 19(12):2756

    Article  Google Scholar 

  7. Fouchal H, Bourdy E, Wilhelm G, Ayaida M (2017) A validation tool for cooperative intelligent transport systems. J Comput Sci 22:283–288

    Article  Google Scholar 

  8. Malik RQ, Alsattar HA, Ramli KN, Zaidan BB, Zaidan AA, Kareem ZH, Ameen HA, Garfan S, Mohammed A, Zaidan RA (2019) Mapping and deep analysis of vehicle-to-infrastructure communication systems: coherent taxonomy, datasets, evaluation and performance measurements, motivations, open challenges, recommendations, and methodological aspects. IEEE Access 7:126753–126772

    Article  Google Scholar 

  9. Elleuch I, Makni A, Bouaziz R (2017) Cooperative intersection collision avoidance persistent system based on v2v communication and real-time databases. In: 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA), pp 1082–1089. IEEE

  10. Nellore K, Hancke G (2016) A survey on urban traffic management system using wireless sensor networks. Sensors 16(2):157

    Article  Google Scholar 

  11. Mohar SS, Goyal S, Kaur R (2022) Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics. J Supercomput 1–49

  12. Rios-Torres J, Malikopoulos AA (2017) A survey on the coordination of connected and automated vehicles at intersections and merging at highway on-ramps. IEEE Trans Intell Transp Syst 18(5):1066–1077

    Article  Google Scholar 

  13. Kumar RR, Begum SW, Manikandan M, Student PG (2014) Distance based accident prevention in intersection using vanet. Int J Innov Res Comput Commun Eng 2

  14. Wuthishuwong C, Traechtler A, Bruns T (2015) Safe trajectory planning for autonomous intersection management by using vehicle to infrastructure communication. EURASIP J Wirel Commun Netw 2015(1):33

    Article  Google Scholar 

  15. Budan G, Hayatleh K, Morrey D, Ball P, Shadbolt P (2018) An analysis of vehicle-to-infrastructure communications for non-signalised intersection control under mixed driving behaviour. Analog Integr Circ Sig Process 95(3):415–422

    Article  Google Scholar 

  16. Cho H, Kim B (2014) Study on cooperative intersection collision detection system based on vehicle-to-vehicle communication. Adv Sci Technol Lett 121–124

  17. Azimi R (2015) Co-operative driving at intersections using vehicular networks and vehicle-resident sensing

  18. Medina AIM, van de Wouw N, Nijmeijer H (2018) Cooperative intersection control based on virtual platooning. IEEE Trans Intell Transp Syst 19(6):1727–1740

    Article  Google Scholar 

  19. Idoudi N, Duvallet C, Sadeg B, Bouaziz R, Gargouri F et al (2010) A framework to model real-time databases. Int J Comput Inf Sci 6(1):19–28

    Google Scholar 

  20. Elleuch I (2016) Définition d’un modèle de système de bases de données temps réel pour les systèmes d’aide à la conduite coopératifs. In: Proceedings of the 34th conférnce francophone en informatique des organisations et systèmes d’Information et de décision (INFORSID),Grenoble, France, 31 May–3 June

  21. Eom M, Kim B-I (2020) The traffic signal control problem for intersections: a review. Eur Transp Res Rev 12(1):1–20

    Article  Google Scholar 

  22. Li W, Zhang H, Huang Z, Li C (2022) Human-vehicle intersection traffic lights timing optimization research. J Adv Transp 2022

  23. Behrisch M, Bieker L, Erdmann J, Krajzewicz D (2011) Sumo–simulation of urban mobility. In: The Third International Conference on Advances in System Simulation (SIMUL 2011), Barcelona, Spain, vol 42, pp 55–60. IARIA

  24. Sommer C, German R, Dressler F (2011) Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans Mob Comput 10(1):3–15

    Article  Google Scholar 

  25. Varga A, Hornig R (2008) An overview of the OMNeT++ simulation environment. In: The 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops, 03–07 Mar, Marseille, France, pp 1–10. ICST, Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (2008)

  26. Wang S, Li J, Jiang S, Wei Z, Zhang J, Xu S (2012) Study of real-time data collection and release with in-vehicle system. In: In 2nd international conference on computer application and system modeling. Atlantis Press, Paris, France, pp 1472–1475

  27. Li YJ (2010) An overview of the DSRC/WAVE technology. In: International conference on heterogeneous networking for quality, reliability, security and robustness. Springer, pp 544–558

  28. Wymeersch H, de Campos GR, Falcone P, Svensson L, Ström EG (2015) Challenges for cooperative ITS: improving road safety through the integration of wireless communications, control, and positioning. In: 2015 international conference on computing, networking and communications (ICNC), pp 573–578. IEEE

  29. Lai W, Ni W, Wang H, Liu RP (2018) Analysis of average packet loss rate in multi-hop broadcast for VANETs. IEEE Commun Lett 22(1):157–160

    Article  Google Scholar 

  30. Ma X, Andréasson I (1965) Driver reaction delay estimation from real data and its application in gm-type model evaluation. Transp Res Rec 130–141:2006

    Google Scholar 

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Author notes

  1. Achraf Makni and Rafik Bouaziz have contributed equally.

Authors and Affiliations

  1. MIR@CL Laboratory, Faculty of Economics and Management of Sfax, Sfax University, Sfax, Tunisia

    Islam Elleuch & Rafik Bouaziz

  2. MIR@CL Laboratory, National School of Electronics and Telecommunications of Sfax, Sfax University, Sfax, Tunisia

    Achraf Makni

Authors
  1. Islam Elleuch
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  2. Achraf Makni
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  3. Rafik Bouaziz
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Correspondence to Islam Elleuch.

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Elleuch, I., Makni, A. & Bouaziz, R. CICAPS: a cooperative intersection collision avoidance persistent system for cooperative intersection ADAS. J Supercomput 79, 6087–6114 (2023). https://doi.org/10.1007/s11227-022-04849-x

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