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Highway Capacity Benefits from Using Vehicle-to-Vehicle Communication and Sensors for Collision Avoidance
Abstract
Several automobile manufacturers are offering assisted driving systems that use sensors to automatically brake automobiles to avoid collisions. Before extensively deploying these systems, we should determine how they will affect highway capacity. The goal of this paper is to compare the highway capacity when using sensors alone and when using sensors and vehicle-to-vehicle communication. To achieve this goal, the rules for using both technologies to prevent collisions are proposed, and highway capacity is estimated based on these rules. We show that both technologies can increase highway capacity. The increase in capacity is a function of the fraction of the vehicles that use a technology. If all of the vehicles use sensors alone, the increase in highway capacity is about 43%. While if all of the vehicles use both sensors and vehicle-to-vehicle communication, the increase is about 273%.
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An increase in road capacity can be expected due to the introduction of autonomous vehicles, mainly attributed to reduced headways.
“An increase in road capacity can be expected due to the introduction of autonomous vehicles, mainly attributed to reduced headways”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Tientrakool et al., 2011
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Research works printed but not linked: 11
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Cited by
Sorted by citations
Shared autonomous vehicle services: A comprehensive review
Narayanan, S., Chaniotakis, E., & Antoniou, C. (2020) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2019.12.008 · Cited by 691
Autonomous vehicles: The next jump in accessibilities?
Meyer, J., Becker, H., Bösch, P. M., & Axhausen, K. W. (2017) · Research in Transportation Economics · doi:10.1016/j.retrec.2017.03.005 · Cited by 371
Using an Activity-Based Model to Explore the Potential Impacts of Automated Vehicles
Childress, S., Nichols, B., Charlton, B., & Coe, S. (2015) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.3141/2493-11 · Cited by 319
Annu, & Rajalakshmi, P. (2024) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2024.3368240 · Cited by 73
Metadata
- Authors
- Tientrakool, P., Ho, Y.-C., & Maxemchuk, N. F.
- Affiliations
- Columbia University (US)
- Venue
- 2011 IEEE Vehicular Technology Conference (VTC Fall)
- Publisher
- IEEE
- Published
- 2011-09
- Pages
- 1-5
- ISSN
- 1090-3038 (ISSN-L)
- OpenAlex
- W2113523706
- Cited by
- 235
- References
- 0
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 17 · 2023: 32 · 2022: 20 · 2021: 30 · 2020: 24 · 2019: 25 · 2018: 20 · 2017: 13 · 2016: 11 · 2015: 9 · 2014: 8 · 2013: 9 · 2012: 1
- FWCI
- 9.63
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Vehicular Technology Conference (publishedVersion)
- IMDEA Networks Institute Digital Repository (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Keywords
- road capacity, vehicle-to-vehicle communication, collision avoidance, automated braking, automotive sensors, traffic flow, technology adoption, collision avoidance rules
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