Estimated Data Production for Urban Goods Transport Diagnosis - Sustainable Urban Logistics: Concepts, Methods and Information Systems - page 130

5.1 Modelling Methodology
The model proposed is the result of a long conceptualization and calibration
process (Ségalou 1999 ; Ségalou et al. 2002 ; Toilier et al. 2005 ; Gonzalez-Feliu
et al. 2010a , b , 2012a , b ). As seen above, the model structure is similar to that of
the IEM module. However, the granularity of the database does not permit pro-
ducing data up to the household or to the retailer, requires the use of aggregated
data in zones. More precisely, the model is organized as follows:
• First, the number of movements (shopping trips at destination) is generated at
each shopping zone (i.e. for each zone of the urban area, the number of shopping
trips attracting private cars is generated).
• Second, this number of movements is distributed in order to link each shopping
zone to each household zone (i.e. to link the shopping destinations to the zones
where the households are located). This is done using a catchment area model.
• Third, the distances travelled are estimated based on a typology of shopping trip
practices and the geographical configuration of the urban area. This is done
empirically on the basis of a shopping-related trip chain database.
5.1.1 Trip Generation
In the shopping trips generation phase the number of trips attracted for purchasing
is generated at each zone. The modelling methodology proposed assumes that
shopping trip generation rates also depend on the type of urban space, classified as
follows:
• The main central urban area (CUA) contains the main city of the urban region
and also the urban suburbs that can be assimilated with the main city, due to the
continuity of the urban landscape. This category of urban space is characterized
by a dense household area, mainly with a variety of proximity retailing and
service activities, and a lack of industrial activity zones. Moreover, the public
transport network is very developed and interconnected.
• The near periphery (NP) includes the suburbs bordering the central urban area.
This category of urban space is characterized by a mix of dense and less dense
household areas. It often also includes industrial and commercial activity zones.
Moreover, the public transport network connecting it to the city centre is well
developed in certain directions (often radially) but public transport in the intra-
zone is less developed.
• The far periphery (FP) contains the rest of the towns of the urban area. This
category of urban space is characterized by low density, predominantly detached
housing and high motorization rates. Indeed, public transport is essentially radial
and closer to interurban rail and bus services than to urban public transport
networks. The far periphery is also a mix of peri-urban industrial and com-
mercial zones and semi-rural agricultural and forest areas.