ARTÍCULO
TITULO

Advanced demand data collection technologies for multi modal strategic modelling

Csaba Kelen    
Pablo Vilarino    
Georgios Christou    

Resumen

New data collection technologies have all, but replaced traditional, site-based data collection methods for trip matrix development in the UK. Event data produced by Mobile Network Operators provides adequate information to identify time and location of trip origin and destination (OD), but only limited information on transport mode, vehicle type or trip purpose. In addition, GPS-based data provides another source of OD and user data. This paper describes the mobile phone and app-based demand data collection, verification and processing toward the multi-modal strategic transportation model of Chelmsford, UK. The mobile data was collected during 30 days by INRIX, and was processed by Jacobs to develop time-of-day, vehicle type, mode and purpose-specific motorised trip matrices. The mobile phone- trip matrices were verified and adjusted against various third party data. A cycle app was developed for Chelmsford to facilitate non-motorised OD data collection by engaging a voluntary user group. Together with other data sources, the data was used to develop cycle OD matrices and to calibrate a cycling route choice model. The paper concludes that the use of mobile phone data provides greater quantity and coverage to develop OD matrices. However, the new data source requires significant effort in post processing and model data segmentation by mode, trip purpose and vehicle type, via applying third party information. The quality and efficiency of this process is likely to improve in the near future, resulting in a step change in the modelling practice. The model was delivered to Essex County Council in April 2017.

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