Evaluating the Performance of Connected and Automated Vehicles in Fixed Signal-Controlled Conventional Intersections and Superstreets with Platooning-Based Trajectory Planning Article Swipe
Connected and autonomous vehicles (CAVs) are emerging technology that attracts the interests of many transportation professionals and computational scientists. Several recent studies have investigated different model frameworks of CAVs in different transportation environments, such as on freeways and at conventional intersections. Nevertheless, few efforts have been made to investigate the performances of CAVs at innovative intersections, and the lack of knowledge can result in an inaccurate prediction of CAVs performances in the existing transportation network. This research intends to mitigate this research gap by studying the traffic delay and fuel consumption of CAVs in the environment of the superstreet and its equivalent conventional intersection through simulation-based experiments. A real-world superstreet in Leeland, NC, is selected and used. A conventional intersection with equivalent road designs is established in the simulation platform to make a comparison with the selected superstreet. This research develops both platooning and trajectory planning modeling frameworks to examine the implications of CAVs with different capabilities. The Intelligent Driver Model (IDM) is selected and applied to model the CAV behaviors, while Wiedemann 99 (W99) is used to model Human-Driven Vehicles (HDVs). The simulation results demonstrate the efficiency of both platooning and trajectory planning, respectively. Different effects of CAVs in the superstreet and its equivalent conventional intersection are observed. The findings from this research can provide an important reference for transportation planners and policymakers in predicting the influence of CAVs on the existing transportation infrastructure.
Related Topics
Concepts
Intersection (aeronautics)
Trajectory
Intelligent transportation system
Computer science
Fuel efficiency
Traffic simulation
Transport engineering
Transportation planning
SIGNAL (programming language)
Operations research
Simulation
Engineering
Automotive engineering
Astronomy
Physics
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2022/6093217
- https://downloads.hindawi.com/journals/jat/2022/6093217.pdf
- OA Status
- gold
- Cited By
- 4
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4281762752
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4281762752Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2022/6093217Digital Object Identifier
- Title
-
Evaluating the Performance of Connected and Automated Vehicles in Fixed Signal-Controlled Conventional Intersections and Superstreets with Platooning-Based Trajectory PlanningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-06-02Full publication date if available
- Authors
-
Shaojie Liu, Wei FanList of authors in order
- Landing page
-
https://doi.org/10.1155/2022/6093217Publisher landing page
- PDF URL
-
https://downloads.hindawi.com/journals/jat/2022/6093217.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://downloads.hindawi.com/journals/jat/2022/6093217.pdfDirect OA link when available
- Concepts
-
Intersection (aeronautics), Trajectory, Intelligent transportation system, Computer science, Fuel efficiency, Traffic simulation, Transport engineering, Transportation planning, SIGNAL (programming language), Operations research, Simulation, Engineering, Automotive engineering, Astronomy, Physics, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
45Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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