MOBILE DATA-BASED DEMAND MODELLING FOR THE CITY OF CHELMSFORD



MOBILE DATA-BASED DEMAND MODELLING FOR THE CITY OF CHELMSFORD

Authors

Csaba Kelen, Jacobs, Pablo Vilarino, Jacobs

Description

The paper describes the mobile-phone and mobile app-based demand data collection, verification and processing toward the development of a fully multi-modal transport model in Chelmsford, UK.

Abstract

Mobile-phone based movement data have all but replaced traditional revealed preference data collection methods for the development of trip matrices in the UK. Event data produced by Mobile Network Operators provides adequate information to identify time and location of trip origin and destination, but only limited information on transport mode, vehicle type or trip purpose.

This paper describes the mobile-phone and mobile app-based demand data collection, verification and processing toward the development of a fully multi-modal transportation model in Chelmsford, UK. The mobile data was collected for a period of 30 days from INRIX, an O2 company, and was processed by Jacobs to develop time-of-day, vehicle type and purpose-specific motorized trip matrices. During the data processing, various algorithms were used to identify vehicle type and trip purpose.

The raw trip matrices were verified against third party data in order to establish the suitability of the algorithms for vehicle type and trip purpose identification. Year 2011 Census population and journey to work data, Tempro tripend data, Traffic Masters and National Travel Survey data were used to this end. The limitations of mobile-phone based trip mode, vehicle type and purpose identification were hence established.

Taking into account the limitation of mobile-phone based data to capture non-motorized modes, a Cycle App was developed for Chelmsford to facilitate cycle demand data collection. Via the app, user-specific, route-specific and trip-specific data was collected. In combination with other data sources, the panel data was used to (1) develop cycle trip matrices and to (2) develop a cycling route choice model. Established econometric models were used to develop a route choice model and to generate a set of generalised cost functions by trip purpose and/or user type.

The above data sources were combined with previous RP and SP surveys to develop a variable demand model for Chelmsford, including destination, mode choice and time-of-day choice components. The fully multi-model strategic model is expected to be delivered to Essex County Council by the June 2016.

Publisher

Association for European Transport