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引用次数: 0
摘要
本文提出了英国农村地区的7天旅行需求模型(TDM),以帮助这些地区的电动汽车(EV)过渡。利用英国人口普查调查和英国国家旅行调查(NTS)的数据,对英国峰区国家公园(Peak District National Park)一个乡村的私人乘用车旅行模式进行了建模。这种模式适用于英国的任何农村社区,只需要该社区的家庭和车辆的公开信息。TDM采用一种新颖的方法,通过发展生活方式场景来了解所需的家庭活动,将五种不同的旅行目的作为车辆活动的构建模块。在一周的时间里,49个家庭的84辆汽车行驶了13520英里,这表明为该社区服务的电动汽车车队每周将消耗3562千瓦时的能源。
A data-driven travel demand model to predict electric vehicle energy consumption: focusing on the rural demographic in the UK
ABSTRACT This paper presents a 7-day Travel Demand Model (TDM) for UK rural areas to aid the Electric Vehicle (EV) transition in these regions. Utilising data from both the UK Census Survey and UK National Travel Survey (NTS), private passenger vehicle travel patterns for a rural village in the Peak District National Park (UK), were modelled. This model is adaptable to any rural community within the UK, requiring only publicly available information on households and vehicles for that community. Using a novel approach through the development of lifestyle scenarios to understand the required household activities, the TDM incorporates five different trip purposes as the building blocks for a vehicle’s activity. Over a period of one week, 13,520 miles were driven by 84 vehicles across 49 households, that shows an EV fleet serving this community would consume 3562 kWh energy per week.
期刊介绍:
Transportation Planning and Technology places considerable emphasis on the interface between transportation planning and technology, economics, land use planning and policy.
The Editor welcomes submissions covering, but not limited to, topics such as:
• transport demand
• land use forecasting
• economic evaluation and its relationship to policy in both developed and developing countries
• conventional and possibly unconventional future systems technology
• urban and interurban transport terminals and interchanges
• environmental aspects associated with transport (particularly those relating to climate change resilience and adaptation).
The journal also welcomes technical papers of a more narrow focus as well as in-depth state-of-the-art papers. State-of-the-art papers should address transport topics that have a strong empirical base and contain explanatory research results that fit well with the core aims and scope of the journal.