The DOI matches its Crossref record.
Cooperative Driving at Blind Crossings Using Intervehicle Communication
Abstract
Cooperative driving technology with intervehicle communication has attracted increasing attention recently. It aims to improve driving safety and efficiency using appropriate motion scheduling of all the encountered vehicles. Under cooperative driving control, the motion of individual vehicles could be conducted in a safe, deterministic, and smooth manner. This is particularly useful to heavy-duty vehicles since their acceleration/deceleration capacity is relatively low. Specifically in this paper, cooperative driving at blind crossings (crossings without traffic lights) is studied. A concept of safety driving patterns is proposed to represent the collision-free movements of vehicles at crossings. The solution space of all allowable movement schedules is then described by a spanning tree in terms of safety driving patterns; four trajectory planning algorithms are formulated to determine the driving plans with least execution times using schedule trees. The group communication strategy for intervehicle networks is also analyzed. Finally, simulation studies have been conducted, and results demonstrate the potentiality and usefulness of the proposed algorithms for cooperative driving at blind crossings.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Using connected vehicle technology to improve the efficiency of intersections
Ilgin Guler, S., Menendez, M., & Meier, L. (2014) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2014.05.008 · Cited by 481
A survey of inter-vehicle communication protocols and their applications
Willke, T., Tientrakool, P., & Maxemchuk, N. (2009) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2009.090202 · Cited by 478
Recent advances in connected and automated vehicles
Elliott, D., Keen, W., & Miao, L. (2019) · Journal of Traffic and Transportation Engineering (English Edition) · doi:10.1016/j.jtte.2018.09.005 · Cited by 253
Architecture and key technologies for Internet of Vehicles: A survey
Yang, F., Li, J., Lei, T., & Wang, S. (2017) · Journal of Communications and Information Networks · doi:10.1007/s41650-017-0018-6 · Cited by 129
The impacts of connected autonomous vehicles on mixed traffic flow: A comprehensive review
Pan, Y., Wu, Y., Xu, L., Xia, C., & Olson, D. L. (2024) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.129454 · Cited by 102
Metadata
- Authors
- Li, L., & Wang, F.-Y.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2006-11
- Volume
- 55
- Issue
- 6
- Pages
- 1712-1724
- ISSN
- 0018-9545 (ISSN-L)
- OpenAlex
- W2146363089
- Cited by
- 311
- References
- 0
- FWCI
- 8.38
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cooperative Driving at Blind Crossings Using Intervehicle Communication. https://app.cochat.ai/papers/10.1109/tvt.2006.878730
- The paper
- Li, L., & Wang, F.-Y. (2006). Cooperative Driving at Blind Crossings Using Intervehicle Communication. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/tvt.2006.878730
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.