Abstract
Smart roads integrate advanced technology to enhance safety, effectiveness, and eco-friendliness, revolutionizing transportation systems. Within this framework, connectivity and automation work together to improve road mobility and energy efficiency. However, there are still uncertainties regarding their effect on road safety and traffic operations, as well as assessment methods, especially for intersections and roundabouts. Navigating roundabouts involves complex decision-making influenced by cooperative and competitive interactions between human-driven vehicles and connected and autonomous driving vehicles (CADVs), affecting gap-acceptance patterns. This research employs Aimsun Next software to simulate the rising market penetration percentages of CADVs by examining assumption-based behavior on single-lane roundabouts. It integrates CADV-based capacity modification factors from the Highway Capacity Manual 2022 and compares adapted capacity curves for CADVs, with simulated capacities for model calibration. Critical model parameters affecting CADVs' ability to enhance roundabout safety and throughput are identified, with a focus on the transition towards cooperative driving in the context of smart roads.
| Original language | English |
|---|---|
| Pages (from-to) | 45-57 |
| Number of pages | 13 |
| Journal | Transport Problems |
| Volume | 19 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Keywords
- cooperative driving
- microscopic simulation
- road intersections
- roundabouts
- smart roads
ASJC Scopus subject areas
- Automotive Engineering
- Transportation
- Mechanical Engineering
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