research-article

P2V and V2P communication for Pedestrian warning on the basis of Autonomous Vehicles

Authors:

Fernando García,

José María Armingol,

Cristina Olaverri-MonrealAuthors Info & Claims

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

Pages 2034 - 2039

https://doi.org/10.1109/ITSC.2016.7795885

Published: 01 November 2016 Publication History

Abstract

The use of smartphones in a road context by drivers and Vulnerable Road Users (VRU) is rapidly increasing. To reduce the risks related to the influence of smartphone usage in a situation where traffic needs to be considered, a collision prediction algorithm is proposed based on Pedestrian to Vehicle (P2V) and Vehicle to Pedestrian (V2P) communication technologies, which increases the visual situational awareness of VRU regarding the nearby location of both autonomous and manually-controlled vehicles in a user-friendly form. The proposed application broadcasts the device's position to the vehicles nearby, and reciprocally, the vehicles nearby broadcast their position to the device in use, supporting pedestrians and other VRU to minimize potential dangers and increase the acceptance of autonomous vehicles on our roads. Results regarding the evaluation of the proposed approach showed a good performance and high detection rate, as well as a high user satisfaction derived from the interaction with the system.

References

[1]

ASIRT, “Annual global road crash statistics”, Association for Safe International Road Travel, Tech. Rep., 2016.

[2]

E. Commission, “Road safety in the European Union: Trends, statistics and main challenges”, European Commission, Tech. Rep., 2015.

[3]

C. Olaverri-Monreal, A. E. Hasan, J. Bulut, M. Körber, and K. Bengler, “Impact of in-vehicle displays location preferences on drivers' performance and gaze”, Intelligent Transportation Systems, IEEE Transactions on, vol. 15, no. 4, pp. 1770–1780, 2014.

[4]

S. Schwarz, D. Sellitsch, M. Tscheligi, and C. Olaverri-Monreal, “Safety in pedestrian navigation: Road crossing habits and route qualityneeds”, in Future Active Safety Technology Towards zero traffic accidents, FAST-zero 2015 Symposium, Gothenburg, Sweden, 2015.

[5]

C. Olaverri-Monreal, “Autonomous vehicles and smart mobility related technologies”, Infocommunications Journal, vol. 8, no. 2, pp. 17–24, 2016.

[6]

A. Allamehzadeh and C. Olaverri-Monreal, “Automatic and manual driving paradigms: Cost-efficient mobile application for the assessment of driver inattentiveness and detection of road conditions”, IEEE Intelligent Vehicles Symposium (IV ' ‘16), pp. 26–31, June 19–22 2016.

[7]

C. Olaverri-Monreal, M. Pichler, G. Krizek, and S. Naumann, “Shadow as route quality parameter in a pedestrian-tailored mobile application”, IEEE Intelligent Transportation Systems Magazine, 2016.

[8]

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection”, IEEE Conference on ComputerVision and Pattern Recognition (CVPR), vol. 1, pp. 886–893, 2005.

[9]

A. Prioletti, A. Mogelmose, P. Grisleri, M. M. Trivedi, A. Broggi, and T. B. Moeslund, “Part-based pedestrian detection and feature-based tracking for driver assistance: Real-time, robust algorithms, and evaluation”, IEEE Transactions on Intelligent Transportation Systems, vol. 14, pp. 1346–1359, 2013.

Digital Library

[10]

C. Hilario, J. Collado, J. M. Armingol, and A. de la Escalera, “Pedestrian detection for intelligent vehicles based on active contour models and stereo vision”, International Conference on Computer Aided Systems Theory (Eurocast), pp. 537–542, 2005.

[11]

M. Bertozzi, A. Broggi, M. Felisa, S. Ghidoni, P. Grisleri, G. Vezzoni, C. H. Gmez, and M. D. Rose, “Multi stereo-based pedestrian detection by means of daylight and far infrared cameras”, Augmented Vision Perception in Infrared, Springer London, pp. 371–401, 2009.

[12]

D. Olmeda, C. Premebida, U. Nunes, J. Armingol, and A. de la Escalera, “Pedestrian detection in far infrared images”, Integrated Computer-Aided Engineering, vol. 20, no. 4, pp. 347–360, 2013.

Digital Library

[13]

U. Lages, K. C. Fuerstenberg, and K. C. Dietmayer, “Laserscanner innovations for detection of obstacles and road”, Advanced Microsystemsfor Automotive Applications (AMAA), pp. 223–247, 2003.

[14]

F. Garcia, J. Garcia, A. Ponz, A. de la Escalera, and J. M. Armingol, “Context aided pedestrian detection for danger estimation based on laser scanner and computervision”, Expert Systems with Applications, vol. 41, no. 15, pp. 6646–6661, 2014.

[15]

C. Premebida, O. Ludwig, M. Silva, and U. Nunes, “A cascade classifier applied in pedestrian detection using laser and image-based features”, International IEEE Conference on Intelligent Transportation Systems (ITSC), 2010.

[16]

A. Lewandowski, S. Bocker, V. Koster, and C. Wietfeld, “Design and performance analysis of an ieee 802.15. 4 v2p pedestrian protection system”, in Wireless Vehicular Communications (WiVeC), 2013 IEEE 5th InternationalSymposium on. IEEE, 2013, pp. 1–6.

[17]

M. Bagheri, M. Siekkinen, and J. K. Nurminen, “Cellular-based vehicle to pedestrian (v2p) adaptive communication for collision avoidance”, International Conference on Connected Vehicles and Expo (ICCVE), pp. 450–456, 2014.

[18]

T. Arai, E. Pagello, and L. E. Parker, “Guest editorial advances in multirobot systems”, IEEE Transactions on Robotics and Automation, vol. 18, no. 5, pp. 655–661, 2002.

[19]

C. Sugimoto, Y. Nakamura, and T. Hashimoto, “Prototype of pedestrian to vehicle communication system for the prevention of pedestrian accidents using both 3g wireless and wlan communication”, International Symposium on Wireless Pervasive Computing (ISWPC), pp. 764–767, 2008.

[20]

F. Schaich, T. Wild, and Y. Chen, “Waveform contenders for 5g - suitability for short packet and low latency transmissions”, IEEE Vehicular Technology Conference (VTC), pp. 1–5, 2015.

[21]

K. David and A. Flach, “Car-2-x and pedestrian safety”, IEEE Vehicular Technology Magazine, vol. 5, no. 1, pp. 70–76, 2010.

[22]

L. Andreone and A. Guarise, “Vulnerable road users thoroughly addressed in accident prevention: The watch-over european project”, World Congress on Intelligent TransportSystems (ITS), vol. 1, pp. 629–636, 2007.

[23]

F. Garcia, F. Jimenez, J. J. Anaya, J. M. Armingol, J. E. Naranjo, and A. de la Escalera, “Distributed pedestrian detection alerts based on data fusion with accurate localization”, Sensors, vol. 13, no. 9, pp. 11687–11708, 2013.

[24]

J. J. Anaya, P. Merdrignac, O. Shagdar, F. Nashashibi, and J. E. Naranjo, “Vehicle to pedestrian communications for protection of vulnerable road users”, in Intelligent Vehicles Symposium Proceedings, 2014 IEEE. IEEE, 2014, pp. 1037–1042.

[25]

K. Dhondge, S. Song, B.-Y. Choi, and H. Park, “Wifihonk smartphone-based beacon stuffed wifi car2x-communication system for vulnerable road user safety”, in IEEE Vehicular Technology Conference (VTC Spring). IEEE, 2014, pp. 1–5.

[26]

F. Garcia, D. Martin, A. de la Escalera, and J. M. Armingol, “In-vehicle sensor fusion methodology for pedestrian detection with danger estimation”, ESTYLF'14, Zaragoza, Spain, 2014.

[27]

G. Johansson and K. Rumar, “Drivers' brake reaction times”. Human Factors, vol. 13, no. 1, pp. 23–27, 1971.

[28]

H. Makishita and K. Matsunaga, “Differences of drivers' reaction times according to age and mental workload.” Accident analysis and prevention, vol. 40, no. 2, pp. 567–575, 2008.

[29]

D. Gomez, P. Marin-Plaza, A. Hussein, A. Escalera, and J. M. Armingol, “Ros-based architecture for autonomous intelligent campus automobile (icab)”, UNED Plasencia Revista de Investigacion Univer-sitaria, vol. 12, pp. 257–272., 2016.

[30]

A. Hussein, P. Marin-Plaza, D. Martin, A. de la Escalera, and J. M. Armingol, “Autonomous off-road navigation using stereo-vision and laser-range-finder fusion for outdoor obstacles detection”, IEEE Intelligent Vehicles Symposium (IV), pp. 1–6, 2016.

[31]

F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS quarterly, pp. 319–340, 1989.

Digital Library

Cited By

Tran TParker CYu XDey DMartens MBazilinskyy PTomitsch M(2024)Evaluating Autonomous Vehicle External Communication Using a Multi-Pedestrian VR SimulatorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785068:3(1-26)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678506
Yu XHoggenmüller MTran TWang YTomitsch M(2024)Understanding the Interaction between Delivery Robots and Other Road and Sidewalk Users: A Study of User-generated Online VideosACM Transactions on Human-Robot Interaction10.1145/367761513:4(1-32)Online publication date: 23-Oct-2024
https://dl.acm.org/doi/10.1145/3677615
Clérigo ASchrapel MTeixeira PRito PSargento SVinel A(2024)SafeARCross: Augmented Reality Collision Warnings and Virtual Traffic Lights for Pedestrian SafetyProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675734(63-73)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3640792.3675734
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Index Terms

P2V and V2P communication for Pedestrian warning on the basis of Autonomous Vehicles
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Information systems
  1. Information systems applications

Index terms have been assigned to the content through auto-classification.

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2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

2678 pages

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IEEE Press

Publication History

Published: 01 November 2016

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Cited By

Tran TParker CYu XDey DMartens MBazilinskyy PTomitsch M(2024)Evaluating Autonomous Vehicle External Communication Using a Multi-Pedestrian VR SimulatorProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785068:3(1-26)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678506
Yu XHoggenmüller MTran TWang YTomitsch M(2024)Understanding the Interaction between Delivery Robots and Other Road and Sidewalk Users: A Study of User-generated Online VideosACM Transactions on Human-Robot Interaction10.1145/367761513:4(1-32)Online publication date: 23-Oct-2024
https://dl.acm.org/doi/10.1145/3677615
Clérigo ASchrapel MTeixeira PRito PSargento SVinel A(2024)SafeARCross: Augmented Reality Collision Warnings and Virtual Traffic Lights for Pedestrian SafetyProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675734(63-73)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3640792.3675734
Pan RJie LZhang XPang SWang HWei Z(2022)A V2P Collision Risk Warning Method based on LSTM in IOVSecurity and Communication Networks10.1155/2022/75075732022Online publication date: 1-Jan-2022
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Wang YHespanhol LWorrall STomitsch MJi YJeon M(2022)Pedestrian-Vehicle Interaction in Shared Space: Insights for Autonomous VehiclesProceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3543174.3546838(330-339)Online publication date: 17-Sep-2022
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Colley MLi SRukzio E(2021)Increasing Pedestrian Safety Using External Communication of Autonomous Vehicles for Signalling HazardsProceedings of the 23rd International Conference on Mobile Human-Computer Interaction10.1145/3447526.3472024(1-10)Online publication date: 27-Sep-2021
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Colley MWalch MGugenheimer JAskari ARukzio EBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Towards Inclusive External Communication of Autonomous Vehicles for Pedestrians with Vision ImpairmentsProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376472(1-14)Online publication date: 21-Apr-2020
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