Project n° 1C-MED12-87
“CityGoods model – Demo version”
Institute for transport and Logistics Foundation - ITL
Via dei Mille 21, 40121 Bologna – Italy
http://www.fondazioneitl.org/
Alberto Preti apreti@regione.emilia-romagna.it
Giuseppe Luppino gluppino@regione.emilia-romagna.it
Chiara Iorfida ciorfida@regione.emilia-romagna.it
studio associato SISTeMA
Servizi per l’Ingegneria dei Sistemi di Trasporto e della Mobilità
Lungotevere Portuense, 158 – 00153 Roma (RM)
Tel 06.835.115.26 - Fax 06.892.826.80
www.sistema-trasporti.com
Prof. Ing. Guido Gentile
Ing. Lorenzo Meschini
Ing. Domingo Lunardon
CityGoods model is a tool for the analysis of urban freight demand and evaluation of its external
effects developed within the SMILE project. With correct information, it is able to describe
generation and distribution of freight movements in urban areas, for defined supply chains and
traffic zones. The name citygoods is from the first version developed in 2001 within the CityPorts
project, in SMILE it was possible to update it, to add some specific issues and to make it
transferable.
Smile partners decided to share this tool (in demo version) with all the public administrations
interested in order to demonstrate an easier way to start planning activities.
This demo version aims at analysing freight flow in an urban area divided in 5 traffic zones. The
example takes into account:
 2 supply chains, which are (i) fresh food and (ii) dry food, and
 5 commercial activity categories, which represent the disaggregation of the economic
sector. It is recommended to apply the NACE system, the Statistical Classification of
Economic Activities in the European Community, according to Section G (Wholesale and
retail trade; repair of motor vehicles and motorcycles), since it includes the typical
activities involved in urban logistics context.
The tool is implemented through an Excel worksheet.
In the sheet “control”, the user can interface with the model, using some procedure buttons
which allow to execute separately each step of the CityGoods methodology. They are:
 Step 1: Compute Tree
 Step 2: Generation Calibration
 Step 3: Generation Application
 Step 4: Compute OD costs
 Step 5: Distribution Calibration
 Step 6: Distribution Application
 Step 7: Assign OD flows
There are also some shortcut buttons:
 Run All Models (from Step 1 to Step 7)
 Reset Supply
 Clean All Results
The following sheets are structured in two sections, the first one to fill in with input data, the
second one is fed with output data provided by the model.
a) In the sheet “chain”, the supply chains to analyse in the demand model are defined
through:
o A “code”, which is an unique code for the supply chain;
o A “description” (optional).
b) In the sheet “category”, input data are related to the definition of an activity
classification system, which is represented by a tree structure, reflecting the progressive
disaggregation of economic sectors into sub-sectors. The activity categories are described
through:
o A “code”, which is the unique code for the economic sector;
o The economic sector, named “father”, which concerns in the reference to the
code of higher-level economic sector;
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o
A “description” (optional).
c) In a transport planning analysis, the study area should be divided in traffic zones,
coinciding with the main road infrastructure or specific areas of the city (for example the
city center), in order to simulate the interaction of the system with neighboring areas. In
CityGoods model, traffic zones are defined in the sheet “zone”, through:
o A unique numeric code for the zone, defined as “node”;
o A “description” (optional).
d) It is required to estimate the location and relevance of logistic portals (logistic centers, or
access roads to town) for each supply chain analyzed. In CityGoods model, logistic portals
are stored in table named “portal” and defined with:
o A unique numeric code for the zone, defined as “node”;
o A “description” (optional);
o The relative weight among portals in terms of tours for the different supply
chains, named, in the demo version, “wgh & fresh”, “wgh & dry”.
e) Once defined the traffic zones and the activity classification system, it is possible to
collect data for the universe of local units (classified with the activity classification
system) for each traffic zone in which the study area is divided. In CityGoods database
the universe of local units is stored in table “universe”, providing the following
information:
o A description, defined as “info”;
o A “category”, which is the unique alphanumeric code for the economic sector;
o A “dimension”, corresponding to the local unit size, in terms of number of
employees or retail area;
o A “number”, which represents the number of local units with these
characteristics;
o A “zone”, the corresponding zone containing the local units.
f)
Now it is possible to start with the integration of the following data from a random
sample of local units, to collect in the sheet “sample”, which are:
o An extended description, named “info”;
o A “category”, which is the unique code for the economic sector;
o A “dimension”, which is the local unit size, in terms of number of employees or
retail area;
o A “weight”, which describes the reliability of data;
o Movements (loading and unloading operations) required by the local unit for
each supply chain, within the specific time horizon (mandatory), in the demo
version they are defined as “rev fresh”, “rev dry”.
g) It is possible to fill in the sheet “tour” with the acquisition of the following data from a
random sample of delivery tours made by logistic operators, which are:
o A unique numeric code for the tour, named “tour”;
o The supply chain served by the tour, with the supply chain name;
o The order sequence of stops of the delivery tour (mandatory), defined as “stop”.
h) Once defined traffic zones, it is required to estimate the average transport impedance
between zones for each supply chain. The impedance can be calculate as a combination
of some relevant attributes of the path between zone centroids: travel time, distance,
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economic cost. In CityGoods database transport impedance between zones for each
supply chain is stored in table named “ODcost”.
In the sheet “link”, the transportation graph of the study area is represented with the
main information related to:
o The code of the origin zone, defined as “tail”;
o The code of the destination zone, defined as “head”.
In the sheet “ODflow”, the origin-destination matrices of the logistics trips for each
supply chain are modeled, which represent the output data of the model.
i)
Once collected all input data, it is possible to execute the model with the buttoms in the
sheet “control”.
STEP 1: “Compute Tree”
This procedure allows to count for each element of the category tree, defined in
the sheet “category”, the total number of local units in the study area. The output
of this procedure is the Column “occ tree”, in the sheet “category”.
STEP 2: “Generation Calibration”
With this step, it is possible to estimate the demand for goods of local units
according to data reviled from a simple of local units, collected in the sheet
“sample”. It gives in output the columns of the sheet “category”: “cum tree”, the
total number of local units for the economic sector in the study area, “occ
sample”, the total number of local units for the economic sector in the analyzed
sample, “cum sample”, the total number of local units for the economic sector in
the analyzed sample, and, in the demo version, the columns “(a) mov fresh”, “(a)
mov dry” and “(+ b * dim) mov fresh”, “(+ b * dim) mov dry”, which are
coefficients of generation model.
STEP 3: “Generation Application”
The procedure allows to estimate the demand for goods of each chain and zone,
giving as output of the demo the columns “mov fresh”, “mov dry” of the sheet
“category”, which represent the total number of movements (for given supply
chains) required by the entire economic sector in the study area, the columns
“mov fresh”, “mov dry” of the sheet “sample”, which estimate movements
(loading and unloading operations) for the local unit, the columns “mov fresh”,
“mov dry” of the sheet “universe”, which estimate movements (loading and
unloading operations) for the local units for the supply chain, the columns “mov
fresh”, “mov dry” of the sheet “zone”, which represent movements (loading and
unloading operations) estimated by the model for the zone.
STEP 4: “Compute ODcosts”
This step allows to calculate the travel costs of each pair of zones in the model.
The travel costs are estimated as minimum path on a given graph (table “link”). It
generates the columns “origin”, code of the origin zone, “destination”, code of
the destination zone, and, in the example, the columns “cst fresh”, “cst dry”, of
the sheet “ODcosts”, which represent transport impedence between zones for
given supply chain.
STEP 5: “Distribution Calibration”
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It allows to estimate the logistic distribution system according to data reviled
from a simple of logistic operator (table “tour”), giving in output the columns
“stops, the average number of stops, and “beta”, the impudence coefficient of
the sheet “chain”.
STEP 6: “Distribution Application”
The procedure generates a complete representation of the delivery tour system
in the study area, giving as output of the example the column “flw fresh”, “flw
dry”, of the sheet “portal”, which represents the relative weight among portals in
terms of tours for the different supply chains, and the column “flw fresh”, “flw
dry”, of the sheet “ODflow”, i.e. the logistics trips between zones.
STEP7: “Assign ODflows”
This step assigns the OD flows on the network according to a minimum path
selection of the routes, giving as output of the demo the columns “flw fresh”,
“flw dry” of the sheet “link”, which represent the logistics trips on the link.
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