Optimal bus fleet management strategy for emissions reduction
Optimal bus fleet management strategy for emissions reduction
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DOI：
10.1016/j.trd.2015.10.007
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发表时间：
2015-12
影响因子：
7.6
通讯作者：
Lu Li;H. Lo;Xue-kai Cen
中科院分区：
文献类型：
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作者：
Lu Li;H. Lo;Xue-kai Cen
交通运输是废气排放导致环境恶化的主要原因。对于许多以交通为导向的大都市地区，公交车出行通常占据相当大的出行方式份额。因此，管理公交车队，特别是更新公交车以符合新的排放标准，可以对交通引起的空气质量产生重大影响。本文提出了剩余寿命额外效益-成本（RLABC）分析方法，通过提前退役或在现有公交车队的使用寿命内进行改造来最大化总净效益。通过参考 RLABC 分析估算的不同公交车类型的净效益，可以确定对当前公交车队最有利的管理方案。基于 RLABC 分析，为运营商和政府开发了最佳公交车队管理 (BFM) 模型。然后制定政府补贴计划，实现双赢，提供高效、灵活的管理方案。为了说明这一方法，以香港最大的巴士公司为例，该公司的客运量占全港总出行量的 23% 以上。该方法没有采用固定的退休计划，例如目前实行的17岁更换公交车，而是开发了一种最佳的BFM方案，逐步淘汰或改造公交车。这项研究产生了有希望的结果，证明了这种方法对于优化公交车队管理的巨大好处。
Transportation is a major cause for environmental degradation via exhaust emissions. For many transit-oriented metropolitan areas, bus trips often constitute a sizeable mode share. Managing the bus fleet, in particular updating buses to comply with the newer emissions standards, therefore, can have a substantial impact on transportation-induced air quality. This paper presents the approach of remaining life additional benefit–cost (RLABC) analysis for maximising the total net benefit by either early-retiring or retrofitting the current bus fleet within their lifespans. By referring to the net benefits for different bus types estimated by RLABC analysis, the most beneficial management scheme for the current bus fleet can be identified. Optimal bus fleet management (BFM) models based on the RLABC analysis for the operator and the government are developed. Then a government subsidy plan is produced to achieve win–win solutions, which will offer efficient and flexible management schemes. To illustrate the approach, the largest bus company in Hong Kong, which carries more than 23% of the total trips in Hong Kong, is taken as a case study example. Instead of adopting a fixed retirement plan, such as replacing buses at the age of 17 as is currently practised, the proposed method develops an optimal BFM scheme that progressively phases out buses or retrofits them. This study produces promising results to demonstrate the large benefit of this approach for optimal bus fleet management.