DATA AUGMENTATION FOR AN INTEGRATED ACITIVITY-TRAVEL DEMAND AND MULTIMODAL TRAFFIC MICROSIMULATION MODEL

综合活动-旅行需求和多模式交通微观模拟模型的数据增强

• 批准号: RGPIN-2014-05190
• 负责人: NurulHabib, Khandker
• 金额: $ 2.04万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=567006
• 关键词: DATA; AUGMENTATION; INTEGRATED; ACITIVITY; TRAVEL

The proposed research will develop an integrated microsimulation model of activity-travel demand and multimodal traffic flow that can allow the minute-by-minute simulation of an urban transportation system at the individual parcel level (postal code) of spatial disaggregation. Such models have extensive data requirements, and this issue will be addressed by developing data augmentation methods that will collect small-scale but detailed and accurate activity-travel data using smartphone-based applications and fusing it with regional household travel survey data. The study area will be the Greater Toronto and Hamilton Area (GTHA) as the region already has an established household travel survey data collection program and a full prototype multimodal traffic microsimulation model. The major objectives of the research are to: 1)develop new methods for data augmentation by fusing multiple sources of data, 2)estimate and calibrate a consistent, coordinated set of probabilistic behavioural models based on the fused data, 3)develop an integrated multimodal travel demand simulation system, and 4)apply the integrated simulation system to the analysis of transportation policy. The first major objective can be further elaborated as follows: (a)Developing a smartphone-based automated activity-travel data collection tool that can accurately collect detailed spatio-temporal movement information. This will reduce the survey response burden and create a truly pervasive travel data collection method. (b)Developing a data augmentation process to supplement regional household travel survey data with small-scale detailed data. This will enrich the large-sample household travel survey by filling in missing and more disaggregate information. The second and third long-term objectives can be further elaborated as follows: (c)Developing a microsimulation framework that seamlessly integrates peoples' demand for activity-travel within a multimodal (road and public transport) transportation network considering temporal variations of traffic flow in the network within a day. (d)Estimating and validating econometric models for all components of this modelling framework by using augmented activity-travel datasets. Component econometric choice models include fully comprehensive activity generation and scheduling models containing dynamic parcel-based activity location choice models and tour-based mode choice models. Models will be household-based and will consider intra-household resource and task allocations. All of these objectives have both short- and long-term implications. In the short-term, a microsimulation framework will be developed and component models will be estimated for the GTHA. In the long-term, the modelling framework will evolve into a standard transportation demand modelling system for regional-scale planning and policy analysis. The regional-scale dynamic passenger travel demand model will be unique in Canada and can be used as a template to develop similar models for other regions in Canada. The model will be useful in evaluating a variety of transportation policies and infrastructure improvement options that are under consideration by various levels of government in Canada. These include road pricing, alternative network infrasture renewal options (e.g., building subway/metro relief lines, replacing old elevated expressways with new expressways or combinations of highways and transit elements) and alternative land use bylaws in urban areas to balance urban systems and minimize social exclusion. The model will also be able to accurately evaluate various travel demand management policies, e.g. carpooling incentives, flexible office hour option, telecommuting options, etc.

拟议的研究将开发一个活动-出行需求和多式联运交通流的集成微观模拟模型，该模型可以在空间分解的单个地块级别(邮政编码)逐分钟模拟城市交通系统。这类模型对数据有广泛的要求，将通过开发数据增强方法来解决这一问题，这种方法将使用基于智能手机的应用程序收集小规模但详细和准确的活动旅行数据，并将其与区域家庭旅行调查数据融合。研究区域将是大多伦多和汉密尔顿地区(GTHA)，因为该地区已经建立了家庭旅行调查数据收集计划和全原型多模式交通微观模拟模型。研究的主要目标是：1)通过融合多源数据开发新的数据增强方法；2)基于融合数据估计和校准一套一致的、协调的概率行为模型；3)开发集成的多式联运出行需求模拟系统；4)将集成模拟系统应用于交通政策分析。第一个主要目标可以进一步阐述如下：(A)开发一个基于智能手机的自动化活动-旅行数据收集工具，该工具可以准确地收集详细的时空移动信息。这将减轻调查回应的负担，并创建一种真正无处不在的旅行数据收集方法。(B)制定数据扩充程序，用小规模详细数据补充区域家庭旅行调查数据。这将通过填写缺失和更多未汇总的信息来丰富大样本家庭旅行调查。第二和第三个长期目标可进一步阐述如下：(C)开发一个微观模拟框架，将人们在多式联运(道路和公共交通)网络中的活动出行需求无缝结合起来，考虑到网络中一天内交通流量的时间变化。(D)利用扩大的活动--旅行数据集，估计和验证这一建模框架所有组成部分的计量经济模型。组件计量经济学选择模型包括完全综合的活动生成和调度模型，其中包含基于动态地块的活动选址模型和基于旅游的模式选择模型。模型将以家庭为基础，并将考虑家庭内部的资源和任务分配。所有这些目标都有短期和长期影响。在短期内，将开发一个微观模拟框架，并将估计GTHA的组件模型。从长远来看，该模型框架将演变为一个标准的交通需求模型系统，用于区域规模的规划和政策分析。区域范围的动态旅客出行需求模型在加拿大将是独一无二的，可以作为模板，为加拿大其他地区开发类似的模型。该模型将有助于评估加拿大各级政府正在考虑的各种交通政策和基础设施改善方案。这些措施包括道路定价、替代网络基础设施更新选择(例如，修建地铁/地铁缓解线路、用新的高速公路或公路和交通要素的组合取代旧的高架高速公路)，以及城市地区的替代土地使用附例，以平衡城市系统和最大限度地减少社会排斥。该模型还将能够准确评估各种出行需求管理政策，例如拼车激励、灵活的办公时间选择、电子通勤选择等。