TY  - JOUR
PY  - 2020//
TI  - Revealing personal activities schedules from synthesizing multi-period origin-destination matrices
JO  - Transportation research part B: methodological
A1  - Ballis, Haris
A1  - Dimitriou, Loukas
SP  - 224
EP  - 258
VL  - 139
IS  - 
N2  - Over the last decades, technological advances have allowed the capturing of travel behaviour at large-scale. Despite the unprecedented volume and the variety of personal mobility data, aggregate Origin-Destination (OD) matrices are still the most widespread means to organise and represent travel demand. Nonetheless, standard ODs cannot adequately capture significant elements affecting travel behaviour such as trip-interdependency and trip-chaining, therefore they are not particularly suitable for travel behaviour analysis at person-level. The currently presented modelling framework enables the in-depth study of personal mobility by firstly combining the trips present in OD matrices into home-based trip-chains (i.e. tours) and subsequently into sequences of activities (activity schedules). The above-mentioned process is completed based on advanced graph-theoretical and combinatorial optimisation concepts. The applicability of the methodology is meticulously verified through a large-scale test case where a set of multi-period, purpose dependant ODs is converted into realistic activity schedules able to incorporate more than 99% of the inputted travel demand. The accurate and highly detailed results showcase the significant potential of the proposed methodology to support the comprehensive analysis of travel behaviour at person level.<p />  <p>Language: en</p>
LA  - en
SN  - 0191-2615
UR  - http://dx.doi.org/10.1016/j.trb.2020.06.007
ID  - ref1
ER  -