BESTUFS II WP3, round table n 3 Application fields, use cases and opportunities Bruxelles,

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1 BESTUFS II WP3, round table n 3 Application fields, use cases and opportunities Bruxelles, Modelling city logistics in Emilia-Romagna: from the CityPorts project to the CityGoods software Guido GENTILE DITS - Rino ROSINI Regione Emilia-Romagna Daniele VIGO DEIS - Università di Bologna

2 ER City logistic surveys In the years Emilia-Romagna performed an extensive survey of City Logistics phenomenon for all ER towns CityPorts, Merope, Regional programmes Huge and fine-grained data source Quite homogeneous (CityPorts survey model) 3 main surveys: Demand Generation, Attraction and flows/operations A unique modeling opportunity!

3 Demand Generation Models General survey: Russo & Comi (2004) gravitational, 4 Phases (Hutchinson 1974, Odgen 1992, List & Turnquist 1994, Taylor 1997, He & Crainic 1998, Gorys & Hausmanis 1999 ) input-output (Harris & Liu, 1998) spatial price equilibrium (Oppenheim 1994, Nagurney, 2002) the first is more suited to a urban scale

4 Demand Generation Models Some problems: Generation: intrinsic approximation introduced by aggregating many economic activities into few categories a given economic activity generates movements belonging to different Supply Chains Distribution: a vehicle performs many deliveries/pickups in a tour

5 Other experiences FRETURB (L.E.T., Lyon, Fr): general model for the evaluation of the impact of Logistic Actions Based on 3 detailed surveys on French towns (Marseilles, Bordeaux and Dijon) Regression-based model Software tool distributed by French Ministry of Transport to all French Municipality VISEVA (Friedrich et al 2003), Good Trips (Boerkamps, 1999)

6 NACE classification tree 5 Digits code with hierarchic structure

7 NACE classification tree (2) Mapping of the Universe into the NACE tree gives immediate indicators of town structure (overall and spatial=per Zone) Bologna Universe

8 Main assumption NACE-Based Model The n. of operations generated by a specific NACE code (e.g. 502 Vehicle Maintenance) should take into account: Those generated by the descendant codes (5020, 5021, 50201,,50205) Those generated by parent classes (50, 5) Measured by two contributes: the relative weight (n. of elements in the Universe) of the subtree rooted at the code relative weight of the path to the tree root

9 Model Formulation NACE tree structure: N set of NACE codes f(i) father of code i N FS(i) = {j N: f(j) = i} i N r root tree FS(j) j=f(i) i M i s number of yearly operations of the supply chain s S generated by code i N (model output) m i s number of yearly operations associated to the link entering i N (parameters to be determined by calibration)

10 M is = W is + H i s W i s H i s Model Formulation (2) i N contrib. to M i of the subtree with root i contrib. to M i of the path from i to r (for leaves M is = H is ) H is = m is + H s f(i) i N (computed in topological order) W is = j FS(i) β j (W js + m js ) i N (computed in reverse topological order) β i probability that the child of f(i) is i N (computed statistically from the Universe)

11 CityGoods is a GIS application based on an Access DataBase

12 with specific tools for the analysis of freight urban demand

13 Import the NavTeq street network as a ShapeFile of polylines

14 Import the traffic zones as a ShapeFile of areas

15 GeoCode (from address to point) e.g. the sample of interviews

16 but more important the universe of local units economic activities

17 GeoRefer (from coordinates to point) e.g. the logistic portals

18 Calibrate the generation model Each local unit has a unique NACE code but generates movements (deliveries) from different supply chains as a function of the activity dimension (e.g. the number of employs) Starting from the interviews, we adjust the model coefficients through a least square approach Problem: few interviews, many codes (about 1700) Fact: the codes comply to a hierarchal structure (a tree) with successive specifications of the activity Solution: we can assume a correlation among the movements generated by related codes

19 With a survey we measure the movements produced by each supply chain and other operative attributes

20 Result of the calibration for each code and supply chain the annual movements

21 Apply the generation model to the universe after determining the zone of each local unit

22 find out the zone-supply chain matrix

23 Add the fiend of movements to the zone table in structure mode

24 populate it with the estimated movements from the model with an sql query

25 and produce a thematic chart based on the color of the zones

26 Create the graph from the street network and connect the centroids to it automatically

27 Compute the distances among the centroids (zone and portals) on the graph

28 Apply for each supply chain the gravitational model suitably modified to consider tours

29 obtaining the peak hour freight vehicle od matrix for each supply chain

30 Assign the freight od matrices to the road graph jointly with the people demand

31 obtaining the flow on each arc useful to evaluate congestion and pollution

32 Data are directly utilized with other application (e.g. ArcGis)

33 or for further analysis within CityGoods

34 The z-s matrix allows to extend the attributes observed in the survey to the universe zone attributi filiere

35 Duration of delivery stops 0,6 0,5 0,4 0,3 durata (min) bologna ravenna faenza 0,2 0,1 0 0 (0,5] (5,10] (10,15] (15,20] (20,30] (30,45] (45, ]

36 Type of parking 0,6 0,5 0,4 0,3 sosta bologna ravenna faenza 0,2 0,1 0 0 privata piazzola strada divieto doppiafila

37 Day of delivery 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 giorno bologna ravenna faenza 0 lunedì martedì mercoledì giovedì venerdì sabato domenica

38 Hour of delivery 0,3 0,25 0,2 ora bologna ravenna faenza 0,15 0,1 0, h06-07 h07-08 h08-09 h09-10 h10-11 h11-12 h12-13 h13-14 h14-15 h15-16 h16-17 h17-18 h18-19 h19-20 h20-21 h21-22 h22-23 h23-24 h00-01 h01-02 h02-03 h03-04 h04-05 h05-06

39 Typical use of CityGoods Building and managing of the freight demand model for a specific city organization of the survey data interpretation of information through GIS Calibration of the model to obtain Its optima parameters Application of the model to obtain the zone supply chain matrix the origin destination matrices for freight vehicles Application of the zone supply chain matrix to extend the observed attributes to the universe Assignment of the o-d matrices to the road network to evaluate congestion and pollution

40 Alternative use of CityGoods Possible application of a mix of models calibrated on some typical cities to other cities without further surveys Data required are easily available Universe of local units (statistical institutions, chamber of commerce) Zoning (possible, the same used in traffic planning) Commercial street database (Navteq, TeleAtlas)

41 Conclusions Data required by the model are easily available and standardized High granularity of results At the same time, synthesis through indicators Robustness of estimation based on tests relative to the cities of Bologna and Ravenna Easy portability of the model to other cities without further surveys Integration of the model chain in a GIS like software

42 and future developments Use of the models City planning in Emilia-Romagna Application and validation in other contexts Extensions Modeling of people trips for buying goods