research-article

LookUp: Enabling Pedestrian Safety Services via Shoe Sensing

Authors:

Carlo Borgiattino,

Marco Gruteser,

Carla Fabiana ChiasseriniAuthors Info & Claims

MobiSys '15: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services

Pages 257 - 271

https://doi.org/10.1145/2742647.2742669

Published: 18 May 2015 Publication History

Abstract

Motivated by safety challenges resulting from distracted pedestrians, this paper presents a sensing technology for fine-grained location classification in an urban environment. It seeks to detect the transitions from sidewalk locations to in-street locations, to enable applications such as alerting texting pedestrians when they step into the street. In this work, we use shoe-mounted inertial sensors for location classification based on surface gradient profile and step patterns. This approach is different from existing shoe sensing solutions that focus on dead reckoning and inertial navigation. The shoe sensors relay inertial sensor measurements to a smartphone, which extracts the step pattern and the inclination of the ground a pedestrian is walking on. This allows detecting transitions such as stepping over a curb or walking down sidewalk ramps that lead into the street. We carried out walking trials in metropolitan environments in United States (Manhattan) and Europe (Turin). The results from these experiments show that we can accurately determine transitions between sidewalk and street locations to identify pedestrian risk.

References

[1]

Smart Growth America, Dangerous by Design 2014. http://www.smartgrowthamerica.org/documents/dangerous-by-design-2014/dangerous-by-design-2014.pdf, 2011.

[2]

U.S. Department of Transportation, Traffic Safety Facts, August 2013.

[3]

Reversal in Three-Year Uptick in Pedestrian Fatalities. http://goo.gl/I389KR.

[4]

International Transport Forum, Road Safety Annual Report 2013.

[5]

Peter D. Loeb and William A. Clarke. The cell phone effect on pedestrian fatalities. Transportation Research Part E: Logistics and Transportation Review, 45(1):284--290, 2009.

[6]

Liberty Mutual Insurance, Study shows three out of five pedestrians prioritize smartphones over safety when crossing street. http://goo.gl/5z2DzQ, June 2013.

[7]

Delaware Online, if you text and walk, remember to look up. http://goo.gl/ww5pRc, May 2012.

[8]

The Big Story, NYC Crosswalks urge pedestrians to look! http://bigstory.ap.org/article/nyccrosswalks-urge-pedestrians-look, September 2012.

[9]

U.S. Department of Transportation, Dedicated Short Range Communication. http://www.its.dot.gov/factsheets/dsrc_factsheet.htm.

[10]

Honda. Honda Demonstrates Advanced Vehicle-to-Pedestrian and Vehicle-to-Motorcycle Safety Technologies. http://www.honda.com/newsandviews/article.aspx?id=7352-en, August 2013.

[11]

Tianyu Wang, Giuseppe Cardone, Antonio Corradi, Lorenzo Torresani, and Andrew T. Campbell. Walksafe: a pedestrian safety app for mobile phone users who walk and talk while crossing roads. In Proceedings of the Twelfth Workshop on Mobile Computing Systems; Applications, HotMobile '12, 2012.

Digital Library

[12]

Kazushige Ouchi and Miwako Doi. Indoor-outdoor activity recognition by a smartphone. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp '12, pages 537--537, New York, NY, USA, 2012. ACM.

Digital Library

[13]

Kaustubh Dhondge, Sejun Song, Younghwan Jang, Hyungbae Park, Sunae Shin, and Baek-Young Choi. Video: Wifi-honk: Smartphone-based beacon stuffed wifi car2x-communication system for vulnerable road user safety. In Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys '14, pages 387--387, New York, NY, USA, 2014. ACM.

Digital Library

[14]

Federal Highway Administration, Crash-Type manual for pedestrians, April 1997.

[15]

New York Times, Deaths Rise for Drivers, Bikers and Walkers on City Streets. http://goo.gl/DFhqP, 2012.

[16]

Nike+ Sensor. http://www.apple.com/ipod/nike/, 2012.

[17]

Adidas Speed Cell. http://goo.gl/Xs9CXK.

[18]

Federal Highway Administration, Sidewalk Design Guidelines, July 1999.

[19]

U.S. Department of Transportation announces decision to move forward with vehicle-to-vehicle communication technology for light vehicles. http://goo.gl/UlrBzx, February 2014.

[20]

Openstreetmap. http://www.openstreetmap.org/.

[21]

Shubham Jain, Carlo Borgiattino, Yanzhi Ren, Marco Gruteser, and Yingying Chen. On the limits of positioning-based pedestrian risk awareness. In Proceedings of the 2014 Workshop on Mobile Augmented Reality and Robotic Technology-based Systems, MARS '14, 2014.

Digital Library

[22]

Trisha Datta, Shubham Jain, and Marco Gruteser. Towards city-scale smartphone sensing of potentially unsafe pedestrian movements. In Proceedings of the 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems, MASS '14. IEEE Computer Society, 2014.

Digital Library

[23]

European Union Pedestrian Planning. http://goo.gl/r2QNsT.

[24]

E. Foxlin. Pedestrian tracking with shoe-mounted inertial sensors. Computer Graphics and Applications, IEEE, 25(6):38--46, Nov 2005.

Digital Library

[25]

C. Mariotti, V. Lakafosis, M.M. Tentzeris, and L. Roselli. An ipv6-enabled wireless shoe-mounted platform for health-monitoring. In Wireless Sensors and Sensor Networks (WiSNet), 2013 IEEE Topical Conference on, Jan 2013.

[26]

E.S. Sazonov, G. Fulk, J. Hill, Y. Schutz, and R. Browning. Monitoring of posture allocations and activities by a shoe-based wearable sensor. Biomedical Engineering, IEEE Transactions on, 58(4), April 2011.

[27]

Yan Wang, Jie Yang, Hongbo Liu, Yingying Chen, Marco Gruteser, and Richard P. Martin. Sensing vehicle dynamics for determining driver phone use. In Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys '13, pages 41--54, New York, NY, USA, 2013. ACM.

Digital Library

[28]

Shane Colton. The balance filter. http://goo.gl/WR8e6m, 2007.

[29]

Eun Tae Jeung Hyung Gi Min. Complementary filter design for angle estimation using mems accelerometer and gyroscope. http://goo.gl/F2PeSX.

[30]

Invensense. Invensense MPU-9150 product specification. http://www.invensense.com/mems/gyro/documents/PS-MPU-9150A-00v4_3.pdf.

[31]

John-Olof Nilsson, Amit K Gupta, and Peter Händel. Foot-mounted inertial navigation made easy. In International Conference on Indoor Positioning and Indoor Navigation, volume 27, page 30th, 2014.

[32]

Seong Yun Cho and Chan Gook Park. Mems based pedestrian navigation system. Journal of Navigation, 59(01):135--153, 2006.

[33]

Patrick Robertson, Michael Angermann, and Bernhard Krach. Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors. In Proceedings of the 11th International Conference on Ubiquitous Computing, Ubicomp '09, pages 93--96, New York, NY, USA, 2009. ACM.

Digital Library

[34]

A Jimenez, F Seco, F Zampella, J Prieto, and J Guevara. Pdr with a foot-mounted imu and ramp detection. Sensors, 11(10):9393--9410, Oct 2011.

[35]

Oliver Woodman and Robert Harle. Pedestrian localisation for indoor environments. In Proceedings of the 10th International Conference on Ubiquitous Computing, UbiComp '08, pages 114--123, New York, NY, USA, 2008. ACM.

Digital Library

[36]

I. Skog, J.-O. Nilsson, and P. Handel. Evaluation of zero-velocity detectors for foot-mounted inertial navigation systems. In Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on, pages 1--6, Sept 2010.

[37]

S. O. H. Madgwick, A. J. L. Harrison, and R. Vaidyanathan. Estimation of imu and marg orientation using a gradient descent algorithm. In Rehabilitation Robotics (ICORR), 2011 IEEE International Conference on, June 2011.

[38]

T. Gandhi and M. M. Trivedi. Pedestrian protection systems: Issues, survey, and challenges. Intelligent Transportation Systems, IEEE Transactions on, 8(3), 2007.

Digital Library

[39]

Andreas Fackelmeier, Christian Morhart, and Erwin Biebl. Dual frequency methods for identifying hidden targets in road traffic. In Advanced Microsystems for Automotive Applications 2008, pages 11--20. Springer, 2008.

[40]

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. In Wireless Pervasive Computing, 2008. ISWPC 2008. 3rd International Symposium on, 2008.

[41]

K. David and A. Flach. Car-2-x and pedestrian safety. Vehicular Technology Magazine, IEEE, 5(1), 2010.

[42]

A. Flach and K. David. Combining radio transmission with filters for pedestrian safety: Experiments and simulations. In Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd, 2010.

[43]

C. Voigtmann, Sian Lun Lau, and K. David. Evaluation of a collaborative-based filter technique to proactively detect pedestrians at risk. In Vehicular Technology Conference (VTC Fall), 2012 IEEE, 2012.

[44]

A. Flach, A.Q. Memon, Sian Lun Lau, and K. David. Pedestrian movement recognition for radio based collision avoidance: A performance analysis. In Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd, 2011.

[45]

Aktiv project. http://www.aktiv-online.org/english/aktiv-as.html#KAS.

[46]

Audi. Audi: Night vision assistant with highlighting of detected pedestrians. http://goo.gl/2lGD2g.

[47]

Volvo. Volvo car corporation's emergency brake assist. http://www.volvocars.com/intl/top/corporate/volvo-sustainability/pages/sustainability-news.aspx?itemid=280, 2011.

[48]

Toyota. Toyota develops new pedestrian safety technology. http://www.toyota.com/esq/safety/activesafety/toyota-develops-new-pedestriansafety-technology.html, 2013

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https://dl.acm.org/doi/10.1145/3676490
Merzougui SLimani XGavrielides AReiter PPalazzi CMarquez-Barja J(2024)Leveraging Edge Computing and Orchestration Platform for Enhanced Pedestrian Safety Application: The DEDICAT-6G Approach2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454879(380-383)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454879
Shiraishi YWakazono YWakabayashi YIshida S(2023)Estimation of Sidewalk Surface Condition with Insole Devices2023 Fourteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)10.23919/ICMU58504.2023.10412165(1-6)Online publication date: 29-Nov-2023
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LookUp: Enabling Pedestrian Safety Services via Shoe Sensing
1. Information systems

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cover image ACM Conferences

MobiSys '15: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services

May 2015

516 pages

ISBN:9781450334945

DOI:10.1145/2742647

General Chairs:
Gaetano Borriello
University of Washington, USA
,
Giovanni Pau
UPMC-LIP6, France / UCLA, USA
,
Program Chairs:
Marco Gruteser
Rutgers University, USA
,
Jason Hong
Carnegie Mellon University, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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New York, NY, United States

Publication History

Published: 18 May 2015

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National Science Foundation
Regione Piemonte (Italy)
Qualcomm University Relations

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MobiSys'15

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SIGMOBILE

MobiSys'15: The 13th Annual International Conference on Mobile Systems, Applications, and Services

May 18 - 22, 2015

Florence, Italy

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MobiSys '15 Paper Acceptance Rate 29 of 219 submissions, 13%;

Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Cited By

Stefanidi HTatzgern MMeschtscherjakov A(2024)Augmented Reality on the Move: A Systematic Literature Review for Vulnerable Road UsersProceedings of the ACM on Human-Computer Interaction10.1145/36764908:MHCI(1-30)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3676490
Merzougui SLimani XGavrielides AReiter PPalazzi CMarquez-Barja J(2024)Leveraging Edge Computing and Orchestration Platform for Enhanced Pedestrian Safety Application: The DEDICAT-6G Approach2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454879(380-383)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454879
Shiraishi YWakazono YWakabayashi YIshida S(2023)Estimation of Sidewalk Surface Condition with Insole Devices2023 Fourteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)10.23919/ICMU58504.2023.10412165(1-6)Online publication date: 29-Nov-2023
https://doi.org/10.23919/ICMU58504.2023.10412165
Wu SLi JSousa MGrossman T(2023)Investigating Guardian Awareness Techniques to Promote Safety in Virtual Reality2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR55154.2023.00078(631-640)Online publication date: Mar-2023
https://doi.org/10.1109/VR55154.2023.00078
Wu RChen H(2023)The Effect of Visual and Auditory Modality Mismatching between Distraction and Warning on Pedestrian Street Crossing Behavior2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR59233.2023.00121(1045-1054)Online publication date: 16-Oct-2023
https://doi.org/10.1109/ISMAR59233.2023.00121
Arafat MLarue GDehkordi S(2023)Effectiveness of interventions for mobile phone distracted pedestrians: A systematic reviewJournal of Safety Research10.1016/j.jsr.2022.11.00884(330-346)Online publication date: Feb-2023
https://doi.org/10.1016/j.jsr.2022.11.008
Thoma MPartaourides HSreedharan ITheodosiou ZMichael LLanitis A(2023)Performance Assessment of Fine-Tuned Barrier Recognition Models in Varying ConditionsComputer Analysis of Images and Patterns10.1007/978-3-031-44240-7_17(172-181)Online publication date: 20-Sep-2023
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Tomitsch MEllison A(2023)A Human-Centred Technology Approach to Pedestrian Safety in Smart CitiesResilient and Responsible Smart Cities10.1007/978-3-031-20182-0_2(19-32)Online publication date: 31-Mar-2023
https://doi.org/10.1007/978-3-031-20182-0_2
Hasan RHoque MKarim YGriffin RSchwebel DHasan R(2022)Someone to Watch Over You: Using Bluetooth Beacons for Alerting Distracted PedestriansIEEE Internet of Things Journal10.1109/JIOT.2022.31879659:22(23017-23030)Online publication date: 15-Nov-2022
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Hasan RHasan R(2022)Pedestrian safety using the Internet of Things and sensors: Issues, challenges, and open problemsFuture Generation Computer Systems10.1016/j.future.2022.03.036134(187-203)Online publication date: Sep-2022
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