High quality, reliable data and robust models are central to the development and appraisal of transportation planning and policy. Although conventional data may offer good ‘content’, it is widely observed that it lacks context i.e. who and why people are travelling. Transportation modelling has developed within these boundaries, with implications for the planning, design and management of transportation systems and policy-making. This paper establishes the potential of passively collected GPS-based “Track & Trace” (T&T) datasets of individual mobility profiles towards enhancing transportation modelling and policy-making. T&T is a type of New and Emerging Data Form (NEDF), lying within the broader ‘Big Data’ paradigm, and is typically collected using mobile phone sensors and related technologies. These capture highly grained mobility content and can be linked to the phone owner/user behavioural choices and other individual context. Our meta-analysis of existing literature related to spatio-temporal mobile phone data demonstrates that NEDF’s, and in particular T&T data, have had little mention to date within an applied transportation planning and policy context. We thus establish there is an opportunity for policy-makers, transportation modellers, researchers and a wide range of stakeholders to collaborate in developing new analytic approaches, revise existing models and build the skills and related capacity needed to lever greatest value from the data, as well as to adopt new business models that could revolutionise citizen participation in policy-making. This is of particular importance due to the growing awareness in many countries for a need to develop and monitor efficient cross-sectoral policies to deliver sustainable communities.

高质量，可靠的数据和可靠的模型对于交通规划和政策的开发和评估至关重要。尽管常规数据可能提供良好的“内容”，但广泛观察到它缺乏上下文，即人们出行的人和原因。运输模型已在这些边界内发展，对运输系统的规划，设计和管理以及政策制定具有影响。本文建立了被动收集基于GPS的“个人追踪”数据集的“跟踪与追踪”（T＆T）数据集的潜力，以增强运输模型和制定政策。T＆T是一种新的和新兴的数据表单（NEDF），属于更广泛的“大数据”范式，通常使用移动电话传感器和相关技术来收集。这些捕获高度颗粒移动性内容，并且可以链接到电话所有者/用户的行为选择以及其他个人情况。我们对与时空移动电话数据相关的现有文献进行的荟萃分析表明，迄今为止，NEDF（尤其是T＆T数据）在应用的交通规划和政策环境中很少提及。因此，我们为决策者，运输建模者，研究人员和广泛的利益相关者提供了合作开发新的分析方法，修改现有模型以及建立从数据中获取最大价值所需的技能和相关能力的机会。以及采用可以彻底改变公民参与决策的新商业模式。由于许多国家对制定和监测有效的跨部门政策以交付可持续社区的需要的意识日益增强，因此这一点尤为重要。