This paper will discuss the RAND Europe experience in estimating the coretravel demand models for the Generic Urban Models Phase 2 (GUM) project, sponsored by the UK Department for Transport. The aim of the study is to construct a model applicable to 'large urban areas', i.e. non-metropolitan cities with population over 250,000, which will include land-use, travel demand and assignment models. The model is initially based on Leicester butit will then be generalised to the 12 cities of this type in Great Britain. The primary difficulties in travel demand model estimation in the GUM project stem from deficiencies inherent in the pre-existing household travel survey in Leicester and Leicestershire. This survey was not designed forother travel demand modelling and consequently, the survey covered only asingle individual in the household and omitted the travel of anyone under16 years old. The survey had reasonably detailed information on tour origins but no crisp destination information. Finally, the travel survey lacked information on the time of travel. RAND Europe overcame these obstacles by bringing in additional available sources of data: an extensive roadsideinterview (RSI) study and a survey of public transport users (PT) in Leicester. The paper will discuss two major issues involved in bringing the three data sources together. First, the structure of the model is unusual. The household survey contributes information about mode choice and a "fuzzy" set of destinations, based on the respondent's self-reported travel distance. The RSI and PT data contributes a crisp destination choice and time of day for the tour legs, but limited socio-economic information. The resulting model structure places mode choice at the top of the hierarchy, witha subset of chosen destinations immediately below, followed by individualdestinations and finally time of day alternatives. The second major issueinvolving this amalgamation of data sources is to ensure that the proper weighting and scaling has been done to bring the three data sources into acommon metric, accounting for the survey biases, particularly in the RSI and PT data. The positive outcome of this modelling effort is that RAND Europe has demonstrated that diverse datasets can be combined to produce reasonable model results, provided that a rigorous approach to combine these data sources is implemented. The methods used are expected to be applicable in other contexts of limited data availability. For the covering abstract see ITRD E135582.
Samenvatting