Analysing the effect of bus service quality improvements on transport energy demand using micro-scale models

社会经济和行为因素是能源需求的重要驱动因素，但很少在运输-能源模型中得到考虑。运输能源模型往往以技术为中心，在行为方式上是静态的，尽管有证据表明，需要在需求方面作出重大改变，以实现减排目标。除了新方法之外，挑战的规模表明需要新的框架。本研究建议开发一种可重复和可扩展的方法，用于（a）估计城市交通排放和能源需求的数量和空间分布，以及（B）模拟有针对性的当地干预措施对英国各县模式转变、排放和能源需求的影响。研究结果将提供坚实的证据基础，以支持英国客运主管或联合当局在全国范围内实现运输系统脱碳。更具体地说，这项研究将试图回答以下问题：在多大程度上可以改善巴士服务质量导致减少运输能源需求，通过模式转变，从私人汽车旅行？在此过程中，将探讨以下子问题：1。根据社会经济特征、模式选择、出行模式和出行结构限制等因素的组合，可以创建什么样的个人和社区分类？2.如何使用基于活动的模型来估计个人层面客运的能源需求和排放？3.如何改善当地的公交网络，以鼓励从汽车转向交通方式？如何通过考虑行为因素来现实地模拟与上述改进相关的模式转变？如何使用情景模型来比较当地公交网络中不同服务质量改进所导致的模式转变和相关能源需求减少？

Socioeconomic and behavioural factors are vital drivers of energy demand and yet are seldom accounted for in transport-energy models. Transport energy models tend to be technocentric and static in their approach to behaviour, despite evidence suggesting that dramatic changes on the demand side are needed to meet emission reduction targets. Beyond new methods, the scale of the challenge indicates that new frameworks are needed. This research proposes to develop a reproducible and scalable methodology for (a) estimating the quantity and spatial distribution of emissions and energy demand from urban transport and (b) modelling the impact of targeted local interventions on mode shift, emissions and energy demand in UK counties. The results will provide a solid evidence base to support Passenger Transport Executives or Combined Authorities in the UK to decarbonise transport systems nationwide. More specifically, the research will attempt to answer the following question:To what extent can improvements in bus service quality lead to a reduction in transport energy demand through a mode shift away from private car travel?In doing so, the following sub-questions will be explored:1. What categorisation of individuals and neighbourhoods can be created based on combinations of factors such as socioeconomic characteristics, mode choice, travel patterns, and structural constraints to travel?2. How can activity-based models be used to estimate energy demand and emissions from passenger transport at an individual level?3. How can local bus networks be improved to encourage a mode shift away from cars? How can mode shift associated with said improvements be modelled realistically by accounting for behavioural factors? How can scenario modelling be used to compare mode shift and associated energy demand reduction resulting from different service quality improvements in the local bus network?