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Detecting vehicles’ relative position on two-lane highways through a smartphone-based video overtaking aid application

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Abstract
In this paper we present a smartphone-based real-time video overtaking architecture for vehicular networks. The developed application aims to prevent head-on collisions that might occur due to attempts to overtake when the view of the driver is obstructed by the presence of a larger vehicle ahead. Under such conditions, the driver does not have a clear view of the road ahead and of any vehicles that might be approaching from the opposite direction, resulting in a high probability of accident occurrence. Our application relies on the use of a dashboard-mounted smartphone with the back camera facing the windshield, and having the screen towards the driver. A video is streamed from the vehicle ahead to the vehicle behind automatically, where it is displayed so that the driver can decide if it is safe to overtake. One of the major challenges is the way to pick the right video source and destination among vehicles in close proximity, depending on their relative position on the road. For this purpose, we have focused on two different methods: one relying solely on GPS data, and the other involving the use of the camera and vehicle heading information. Our experiments show that the faster method, using just the location information, is prone to errors due to GPS inaccuracies. A second method that depends on data fusion from the optical sensor and GPS, although accurate over short distances, becomes more computationally intensive, and its performance significantly depends on the quality of the camera.
Keywords
Computer Networks and Communications, Hardware and Architecture, Software, Information Systems, VANET, ITS, Image processing, Plate recognition, Smartphone application, Android, RECOGNITION, REGRESSION, SYSTEM

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MLA
Patra, Subhadeep, et al. “Detecting Vehicles’ Relative Position on Two-Lane Highways through a Smartphone-Based Video Overtaking Aid Application.” MOBILE NETWORKS & APPLICATIONS, vol. 25, 2020, pp. 1084–94, doi:10.1007/s11036-020-01526-2.
APA
Patra, S., Van Hamme, D., Veelaert, P., Calafate, C. T., Cano, J.-C., Manzoni, P., & Zamora, W. (2020). Detecting vehicles’ relative position on two-lane highways through a smartphone-based video overtaking aid application. MOBILE NETWORKS & APPLICATIONS, 25, 1084–1094. https://doi.org/10.1007/s11036-020-01526-2
Chicago author-date
Patra, Subhadeep, David Van Hamme, Peter Veelaert, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni, and Willian Zamora. 2020. “Detecting Vehicles’ Relative Position on Two-Lane Highways through a Smartphone-Based Video Overtaking Aid Application.” MOBILE NETWORKS & APPLICATIONS 25: 1084–94. https://doi.org/10.1007/s11036-020-01526-2.
Chicago author-date (all authors)
Patra, Subhadeep, David Van Hamme, Peter Veelaert, Carlos T. Calafate, Juan-Carlos Cano, Pietro Manzoni, and Willian Zamora. 2020. “Detecting Vehicles’ Relative Position on Two-Lane Highways through a Smartphone-Based Video Overtaking Aid Application.” MOBILE NETWORKS & APPLICATIONS 25: 1084–1094. doi:10.1007/s11036-020-01526-2.
Vancouver
1.
Patra S, Van Hamme D, Veelaert P, Calafate CT, Cano J-C, Manzoni P, et al. Detecting vehicles’ relative position on two-lane highways through a smartphone-based video overtaking aid application. MOBILE NETWORKS & APPLICATIONS. 2020;25:1084–94.
IEEE
[1]
S. Patra et al., “Detecting vehicles’ relative position on two-lane highways through a smartphone-based video overtaking aid application,” MOBILE NETWORKS & APPLICATIONS, vol. 25, pp. 1084–1094, 2020.
@article{8654543,
  abstract     = {In this paper we present a smartphone-based real-time video overtaking architecture for vehicular networks. The developed application aims to prevent head-on collisions that might occur due to attempts to overtake when the view of the driver is obstructed by the presence of a larger vehicle ahead. Under such conditions, the driver does not have a clear view of the road ahead and of any vehicles that might be approaching from the opposite direction, resulting in a high probability of accident occurrence. Our application relies on the use of a dashboard-mounted smartphone with the back camera facing the windshield, and having the screen towards the driver. A video is streamed from the vehicle ahead to the vehicle behind automatically, where it is displayed so that the driver can decide if it is safe to overtake. One of the major challenges is the way to pick the right video source and destination among vehicles in close proximity, depending on their relative position on the road. For this purpose, we have focused on two different methods: one relying solely on GPS data, and the other involving the use of the camera and vehicle heading information. Our experiments show that the faster method, using just the location information, is prone to errors due to GPS inaccuracies. A second method that depends on data fusion from the optical sensor and GPS, although accurate over short distances, becomes more computationally intensive, and its performance significantly depends on the quality of the camera.},
  author       = {Patra, Subhadeep and Van Hamme, David and Veelaert, Peter and Calafate, Carlos T. and Cano, Juan-Carlos and Manzoni, Pietro and Zamora, Willian},
  issn         = {1383-469X},
  journal      = {MOBILE NETWORKS & APPLICATIONS},
  keywords     = {Computer Networks and Communications,Hardware and Architecture,Software,Information Systems,VANET,ITS,Image processing,Plate recognition,Smartphone application,Android,RECOGNITION,REGRESSION,SYSTEM},
  language     = {eng},
  pages        = {1084--1094},
  title        = {Detecting vehicles’ relative position on two-lane highways through a smartphone-based video overtaking aid application},
  url          = {http://dx.doi.org/10.1007/s11036-020-01526-2},
  volume       = {25},
  year         = {2020},
}

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