Modern urban-transport planning requires evidence-based insights into current transport flows to better understand the needs and impacts of policymaking. Urban transport includes passenger and freight vehicles, which have different behavior, and the need for such a separation is often ignored in research and practice [1]. New digital data sources provide an opportunity to better understand urban transport and identify where policy interventions are required. We review the literature on digital counting techniques to monitor transport flows, including loops, Automatic-Number Plate Recognition (ANPR) cameras and floating car data. We further investigate the potential of ANPR cameras, which are widely deployed, and which can be augmented with vehicle category information. This article presents the methodology that we follow for transforming raw augmented ANPR camera data into practical knowledge for city planners. Our is aim is to provide a better understanding of passenger and freight vehicle movements and stops, identifying similarities and differences between vehicle categories. We demonstrate our methodology on a case study for the Mechelen-Willebroek district in Belgium, encompassing augmented data from 122 ANPR cameras for a period of two weeks. Additionally, we also look at the car-reduced zone and how time restrictions affect the different vehicle categories’ actions. The findings are validated with GPS data from heavy-good vehicles in the same period. The potential of augmented ANPR camera data and promising themes and applications of this data source are illustrated through the case study.

中文翻译：

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从自动车牌识别摄像头数据分析客运和货运车辆的运动

现代城市交通规划需要对当前交通流有基于证据的见识，以便更好地了解决策的需求和影响。城市交通包括具有不同行为的客运和货运车辆，在研究和实践中经常忽略这种分隔的需要[1]。新的数字数据源提供了一个机会，可以更好地了解城市交通并确定需要采取政策干预措施的地方。我们回顾了有关数字计数技术以监控运输流程的文献，包括循环，自动车牌识别（ANPR）摄像机和浮动汽车数据。我们将进一步研究ANPR摄像机的潜力，该摄像机已被广泛部署，并且可以通过车辆类别信息进行扩充。本文介绍了将原始的增强型ANPR摄像机数据转换为城市规划人员的实践知识所遵循的方法。我们的目标是更好地了解客运和货运车辆的移动和停止，并确定车辆类别之间的异同。我们在比利时Mechelen-Willebroek地区的案例研究中展示了我们的方法，包括来自122台ANPR摄像机的增强数据，为期两周。此外，我们还研究了汽车禁行区以及时间限制如何影响不同车辆类别的动作。同期的重型车辆GPS数据验证了这一发现。通过案例研究说明了增强型ANPR相机数据的潜力以及该数据源的有前途的主题和应用。