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Vehicle motion intention reasoning using cooperative perception on urban road
Abstract
As autonomous vehicles are venturing on the urban road, reasoning other vehicles' motion intention is always essential for anticipatory decision-making. This paper considers a new class of motion intention reasoning problem using cooperative perception. Specifically, thanks to the extended perception range contributed by cooperative perception, we can explicitly consider the behavior correlations among multiple vehicles, where each vehicle's motion intention can be inferred using both the temporal observations and the other vehicles' motion intention expectation. As such, a Simplified variant of Coupled Hidden Markov Model (S-CHMM) is proposed for motion intention inference. The experiment on an autonomous vehicle shows that the proposed algorithm can improve the motion intention accuracy and provide efficient overtaking triggering for autonomous driving on urban road.
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In [22], cooperative vehicle sensing increases perception range, offering better perception quality and sufficient response time for autonomous triggered actions.
“With the vehicles cooperative sensing, the perception range is increased, offering better perception quality and sufficient response time for autonomous triggered actions.”
From A Review of Machine Learning and IoT in Smart Transportation (2019) · cites this paper as [22]
[22] developed a method for cooperative vehicle perception using a CHMM so that information can be shared among vehicles in a timely manner to avoid accidents.
“The authors in [22] developed a method for cooperative vehicle perception, using a CHMM method so that information can be shared among vehicles in a timely manner to avoid accidents.”
From A Review of Machine Learning and IoT in Smart Transportation (2019) · cites this paper as [22]
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Cited by
Sorted by citations
A Review of Machine Learning and IoT in Smart Transportation
Zantalis, F., Koulouras, G., Karabetsos, S., & Kandris, D. (2019) · Future Internet · doi:10.3390/fi11040094 · Cited by 625
Metadata
- Authors
- Liu, W., Kim, S.-W., Marczuk, K., & Ang, M. H.
- Affiliations
- National University of Singapore (SG)
- Seoul National University (KR)
- Venue
- 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
- Publisher
- IEEE
- Published
- 2014-10
- Pages
- 424-430
- OpenAlex
- W2046457978
- Cited by
- 33
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 4 · 2022: 4 · 2021: 7 · 2020: 3 · 2019: 3 · 2018: 3 · 2017: 1 · 2016: 1 · 2015: 4
- FWCI
- 2.57
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Intelligent Transportation Systems (ITSC) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Keywords
- cooperative perception, autonomous vehicles, urban streets, coupled hidden Markov models, anticipatory decision-making, intention inference
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