The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Research advances in intelligent collision avoidance and adaptive cruise control
Abstract
This paper looks into recent developments and research trends in collision avoidance/warning systems and automation of vehicle longitudinal/lateral control tasks. It is an attempt to provide a bigger picture of the very diverse, detailed and highly multidisciplinary research in this area. Based on diversely selected research, this paper explains the initiatives for automation in different levels of transportation system with a specific emphasis on the vehicle-level automation. Human factor studies and legal issues are analyzed as well as control algorithms. Drivers' comfort and well being, increased safety, and increased highway capacity are among the most important initiatives counted for automation. However, sometimes these are contradictory requirements. Relying on an analytical survey of the published research, we will try to provide a more clear understanding of the impact of automation/warning systems on each of the above-mentioned factors. The discussion of sensory issues requires a dedicated paper due to its broad range and is not addressed in this paper.
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Citations
Cites
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Towards an understanding of adaptive cruise control
Marsden, G., McDonald, M., & Brackstone, M. (2001) · Transportation Research Part C: Emerging Technologies · doi:10.1016/s0968-090x(00)00022-x · Cited by 384
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Collision avoidance analysis for lane changing and merging
Jula, H., Kosmatopoulos, E. B., & Ioannou, P. A. (2000) · IEEE Transactions on Vehicular Technology · doi:10.1109/25.901899 · Cited by 304
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Preview Control for Vehicle Lateral Guidance in Highway Automation
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Drive-by-wire: The case of driver workload and reclaiming control with adaptive cruise control
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Cited by
Milakis, D., van Arem, B., & van Wee, B. (2017) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2017.1291351 · Cited by 963
String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach
Naus, G. J. L., Vugts, R. P. A., Ploeg, J., van de Molengraft, M. J. G., & Steinbuch, M. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2076320 · Cited by 916
Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches
Yasin, J. N., Mohamed, S. A. S., Haghbayan, M.-H., Heikkonen, J., Tenhunen, H., & Plosila, J. (2020) · IEEE Access · doi:10.1109/access.2020.3000064 · Cited by 329
Deb, S., Strawderman, L., Carruth, D. W., DuBien, J., Smith, B., & Garrison, T. M. (2017) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2017.08.029 · Cited by 259
Driver Behavior and Situation Aware Brake Assistance for Intelligent Vehicles
McCall, J. C., & Trivedi, M. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.888388 · Cited by 229
Metadata
- Authors
- Vahidi, A., & Eskandarian, A.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2003-09
- Volume
- 4
- Issue
- 3
- Pages
- 143-153
- ISSN
- 1524-9050 (ISSN-L)
- OpenAlex
- W2107556430
- Cited by
- 836
- References
- 24
- FWCI
- 32.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Vahidi, A., & Eskandarian, A. (2003). Research advances in intelligent collision avoidance and adaptive cruise control. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2003.821292
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
