As employers, suppliers, and transport providers, organisations generate a large portion of traffic flows on transport networks. However, despite the significance of business travel to overall mobility, the underlying activity compositions of the movement and decision-making processes within organisations are not well understood. In this study, a new method is developed based on GPS data to identify typical business activity-travel patterns and characterise the travel behaviour of a specific vehicle and corresponding drivers.

Using GPS data collected from the real operation of 6,500 commercial vehicles over a period of three months, the proposed method was tested. In total, five profiles were constructed, accommodating activity-travel patterns associated with vans, cars, trucks-35 t (light trucks), trucks-3ax (medium trucks), and buses. Similarities and differences in these profiles across vehicle types were revealed, and specific locations corresponding to the activities of the patterns were further examined. Moreover, using these profiles as a reference, the travel practice of a specific vehicle was evaluated. The experimental results demonstrate the potential and effectiveness of the approach in depicting business travel patterns, providing a deep understanding of business travel behaviour, and assisting the design and evaluation of policies for more sustainable business transport.

作为雇主，供应商和运输提供商，组织在运输网络上产生很大的流量。但是，尽管商务旅行对整体流动性具有重要意义，但对于组织内部流动和决策过程的基本活动组成却知之甚少。在这项研究中，基于GPS数据开发了一种新方法，以识别典型的业务活动-旅行模式并表征特定车辆和相应驾驶员的行驶行为。

使用在六个月内从6500辆商用车的实际运行中收集的GPS数据，对所提出的方法进行了测试。总共构造了五个轮廓，以适应与货车，小汽车，35吨卡车（轻型卡车），-3卡车卡车（中型卡车）和公共汽车相关的活动旅行模式。揭示了这些类型在不同车辆类型之间的异同，并进一步检查了与模式活动相对应的特定位置。此外，使用这些配置文件作为参考，评估了特定车辆的行驶实践。实验结果证明了该方法在描述商务旅行模式方面的潜力和有效性，可深入了解商务旅行行为，