Scholarlink

<p>This study develops and calibrates an empirical capacity model for single-lane roundabouts in Hungary, integrating geometric characteristics and Connected and Automated Vehicle (CAV) market penetration levels (MPLs). Field data were collected from 16 entries across five urban roundabouts, with traffic volumes observed under stable queuing conditions. Regression analysis identified central island diameter and splitter island width as statistically significant geometric predictors of entry capacity, contributing to capacity increases of 20.34–23.01%, respectively. To assess technological impacts, Highway Capacity Manual (2022) adjustment factors were integrated into the model to simulate CAV adoption scenarios. At 100% CAV penetration, entry capacity increased by 29.75%, highlighting the substantial operational benefits of full automation. A simplified model using two key factors—central island diameter and CAV MPL—was derived to support practical applications while maintaining predictive robustness. Sensitivity analyses demonstrated that CAV adoption has a stronger influence on capacity than geometric adjustments, particularly under low to moderate congestion. Comparative validation with German, HCM, and Jordanian models showed deviations below 7.5%, confirming external consistency. The proposed model offers a reliable, context-sensitive tool for roundabout capacity estimation, supporting infrastructure planning under increasing automation and providing guidance for similar urban settings.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The influence of geometry and connected automated vehicles on single-lane roundabout capacity

  • 期刊论文

  • 发表日期：

    2025年8月20日

查看全文
  • Haitham A. Al Hasanat,
  • Omar Alharasees

摘要

This study develops and calibrates an empirical capacity model for single-lane roundabouts in Hungary, integrating geometric characteristics and Connected and Automated Vehicle (CAV) market penetration levels (MPLs). Field data were collected from 16 entries across five urban roundabouts, with traffic volumes observed under stable queuing conditions. Regression analysis identified central island diameter and splitter island width as statistically significant geometric predictors of entry capacity, contributing to capacity increases of 20.34–23.01%, respectively. To assess technological impacts, Highway Capacity Manual (2022) adjustment factors were integrated into the model to simulate CAV adoption scenarios. At 100% CAV penetration, entry capacity increased by 29.75%, highlighting the substantial operational benefits of full automation. A simplified model using two key factors—central island diameter and CAV MPL—was derived to support practical applications while maintaining predictive robustness. Sensitivity analyses demonstrated that CAV adoption has a stronger influence on capacity than geometric adjustments, particularly under low to moderate congestion. Comparative validation with German, HCM, and Jordanian models showed deviations below 7.5%, confirming external consistency. The proposed model offers a reliable, context-sensitive tool for roundabout capacity estimation, supporting infrastructure planning under increasing automation and providing guidance for similar urban settings.