Cited by 27IoT and GPS-based Vehicle Safety SystemsTraffic and Road SafetyContext-Aware Activity Recognition Systems

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

SaferCross: Enhancing Pedestrian Safety Using Embedded Sensors of Smartphone

Open access

Abstract

The number of pedestrian accidents continues to keep climbing. Distraction from smartphone is one of the biggest causes for pedestrian fatalities. In this paper, we develop SaferCross, a mobile system based on the embedded sensors of smartphone to improve pedestrian safety by preventing distraction from smartphone. SaferCross adopts a holistic approach by identifying and developing essential system components that are missing in existing systems and integrating the system components into a “fully-functioning”mobile system for pedestrian safety. Specifically, we create algorithms for improving the accuracy and energy efficiency of pedestrian positioning, effectiveness of phone activity detection, and real-time risk assessment. We demonstrate that SaferCross, through systematic integration of the developed algorithms, performs situation awareness effectively and provides a timely warning to the pedestrian based on the information obtained from smartphone sensors and Direct Wi-Fi-based peer-to-peer communication with approaching cars. Extensive experiments are conducted in a department parking lot for both component-level and integrated testing. The results demonstrate that the energy efficiency and positioning accuracy of SaferCross are improved by 52% and 72% on average compared with existing solutions with missing support for positioning accuracy and energy efficiency, and the phone-viewing event detection accuracy is over 90%. The integrated test results show that SaferCross alerts the pedestrian timely with an average error of 1.6sec in comparison with the ground truth data, which can be easily compensated by configuring the system to fire an alert message a couple of seconds early.

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Crossref · 10.1109/access.2020.2980085

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Citations

Cites

Show all 30 references

Research works printed but not linked: 13

  1. wi-fi alliance, 2018, Wi-Fi Peer-to-peer (P2P) Technical Specification Version 1 1
  2. bumgardner, 2018, Brisk Walking Speed
  3. rivers, 2006, Evidence in Traffic Crash Investigation and Reconstruction Identification Interpretation and Analysis of Evidence and the Traffic Crash Investigation and Reconstruction Process
  4. 2019, If You’re Not Careful Your Smartphone May Kill You
  5. times, 2012, A Reminder to Look(!) Both Ways
  6. news, 2019, Tel Aviv Deploys ‘Zombie Lights’ for Mobile-Obsessed Walkers
  7. tribune, 2019, Look Up From Your Phone Pedestrian Deaths Have Spiked
  8. 2019, Pedestrian Deaths Could Hit a 30-Year High
  9. 2018, Power Monitor
  10. 2019, If You’re Not Careful Your Smartphone May Kill You
  11. castillo, 2012, CBS News
  12. 2019, Inattention is Leading Cause of Deadly Pedestrian Accidents in el Paso
  13. 2015, Traffic safety facts

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Metadata

Authors
Won, M., Shrestha, A., Park, K.-J., & Eun, Y.
Affiliations
  • University of Memphis (US)
  • South Dakota State University (US)
  • Daegu Gyeongbuk Institute of Science and Technology (KR)
Venue
IEEE Access
Published
2020
Volume
8
Pages
49657-49670
ISSN
2169-3536 (ISSN-L)
OpenAlex
W3012345026
Cited by
27
References
30
Citations by year
2026: 3 · 2025: 4 · 2024: 4 · 2023: 2 · 2022: 7 · 2021: 5 · 2020: 2
FWCI
1.97
Type
journal article
Language
en
Open access
Locations
  • IEEE Access (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • arXiv (Cornell University)
Funders
  • South Dakota Board of Regents
  • Global Research Laboratory Program through the NRF (2013K1A1A2A02078326)
  • Ministry of Science, ICT and Future Planning
Topics
  • Physical Sciences › Engineering › Automotive Engineering › IoT and GPS-based Vehicle Safety Systems
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
pedestrian safety, smartphone distraction, embedded sensors, pedestrian positioning, energy efficiency, situational awareness, real-time risk assessment

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