利用旅行时间拥堵指数检验拥堵定价计划的有效性

Naveed Farooz Marazi, B. B. Majumdar, P. Sahu
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摘要

本研究在印度海得拉巴使用拥堵评估工具--旅行时间拥堵指数(TTCI)调查了拥堵定价(CP)的有效性。首先,根据陈述偏好(SP)实验,设计了一组 CP 方案下的假设模式选择情景,以收集汽车用户的看法。在陈述偏好调查数据的基础上,开发了离散出行行为模型,以估算在生成的 CP 方案下小汽车、两轮车和公交车之间可能的模式权衡。利用研究城市中最拥堵走廊的现有交通、几何和土地使用数据,估算了基本条件和未来条件下的 TTCI 值,然后利用车辆乘载系数估算了不同条件下的通勤量。此外,根据 CP 方案下的模式权衡得出的通勤量被转换为已确定的拥堵走廊的交通量。最后,使用最终交通量重新估算 TTCI 值,并对基准年和未来年份的最差、最差(中间)和最佳 CP 方案进行比较。考虑到交通流量每年平均增长 5%。结果表明,在实施氯化石蜡方案后,所有已确定的走廊的 TTCI 值都有明显改善,这表明氯化石蜡方案在缓解交通拥堵方面非常有效。对拥堵城市而言,氯化石蜡的这种有效性证明可在使氯化石蜡成为成功的出行需求管理措施方面发挥重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining Congestion Pricing Scheme Effectiveness Using the Travel Time Congestion Index
This study investigated the effectiveness of congestion pricing (CP) using the travel time congestion index (TTCI), a congestion assessment tool, in Hyderabad, India. Initially, a set of hypothetical mode choice scenarios under the CP scheme were designed to collect car users’ perceptions based on a stated preference (SP) experiment. Based on the SP survey data, discrete travel behavior models were developed to estimate the probable modal trade-off among cars, two-wheelers, and public buses under the generated CP scenarios. Using the existing traffic, geometric, and land-use data from the most congested corridors of the study city, TTCI values were estimated for the base and future conditions, followed by commuter volume estimation for the different conditions using vehicle occupancy factors. Further, the commuter volume derived from modal trade-off under CP scenarios was converted into traffic volume for the identified congested corridors. Finally, the TTCI values were re-estimated using the final traffic volume and compared across worst, best-worst (intermediate), and best case CP scenarios for the base and future years. An annual average growth of 5% in traffic volume was considered. The results show a significant improvement in TTCI values across all identified corridors under CP implementation, indicating its effectiveness toward congestion alleviation. Such demonstration of CP effectiveness could play a major role in making CP a successful travel demand management measure for cities burdened with congestion.
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