Maltinti, Melis and Annunziata - input2012

by F. Maltinti, D. Melis, F. Annunziata

Seventh International Conference on Informatics and Urban and Regional

Planning, University of Cagliari 10-12 May 2012

Introduction

Aim

Describing methodology

input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"

Case study

Conclusion and Further studies.

Transport infrastructures guarantee accessibility

Importance of accessibility during emergency


situations

Knowledge of road network vulnerability is

fundamental to manage risks

Studying a new methodology for assessing road

network vulnerability to:

Identify a vulnerability index correlated to


Identify a vulnerability index correlated to

design and geometric characteristics of roads

Identify critical links of a road network to define

improvements priorities

Guarantee accessibility during emergency

situations

Territorial analysis Road network analysis

Identification of weak

links

Link interruption


Calculation of vulnerability

index

Calculation of shortest paths

matrix

Maps of vulnerability and priority

vulnerktot=vulnerk

glob-norm+vulnerkO/Dresc-norm+vulnerk

shorth-path-norm

The proposed Total vulnerability index is expressed by:

where:

1) vulnerkglob-norm=f[ΣiΣj (tk

ij-t0

ij)]is the normalized indicator for vulnerability assessment

connected to the whole network


2) vulnerkO/Dresc-norm=f[ΣiΣj (tk

ij-t0

ij)]

3) vulnerkshorth-path-norm=f[ΣiΣj (nk

ij)]

connected to the whole network

is the normalized indicator for the vulnerability

assessment connected to the rescue operation

is the normalized indicator for the vulnerability

assessment connected to the number of shortest paths

involved in a link closure

[i, j =urban nodes, k=weak links]

[i, =relief operation centres, j= urban nodes destination

of relief]

nkij=

1 if ∆tkij>0

0 if ∆tkij<0

The index to assess municipality exposure is:

exposurei=f[(ΣkΣj(tkij–t0

ij)]

exposureweii=f[Pi/Ptot,ΣkΣj(t

kij–t0

ij)]

To consider population the function can be rewrite as follows:


We used:

• ArcView GIS, to record georeference and process data, and finally to realize the

network vulnerability map;

• ArcGis Network Analyst extension to calculate the matrix of the shortest paths,

and also to construct the matrix of road distances.

We have obtained travel time by dividing the length by the travel speed of the road

link and travel speed by the design characteristics of the horizontal alignment of the

road to which the link belongs

Hypotheses (coming from Italian Geometric Design Standards of Roads):

• the vehicle is isolated: its speed is not affected by traffic conditions;

• the road gradient does not influence vehicle speed;

• on tangents the vehicle follows the equations of uniformly accelerated linear


• on tangents the vehicle follows the equations of uniformly accelerated linear

motion until it reaches the designed speed limit;

• on curves vehicle speed depends on the radius of the curves and on the road

category.

The first one is not easily verified, but it appears valid for roads located in sparsely

populated areas with low traffic volume.

This road network has been

interrupted because of landslides

and floods on different occasions.

Figure shows the vulnerability map

of the road network.

Central links are the most

vulnerable:

� they belong to different

shortest paths

� they are used for rescue

services for which there are no

alternative routes.

The methodology was

applied to Ogliastra road

network. Ogliastra is a

sparsely populated area

located in Sardinia (Italy).

The situation is

completely different

(see the figure on the

right) using function

These figures show municipality exposure to the event:

The figure on the left shows that more vulnerable municipalities are localized in central-

southern area of the region characterized by low population density.

right) using function

considering local

population: more

vulnerable

municipalities are

localized in north-

eastern and south-

eastern area of the

region because they are

more populated than

central-southern area

exposurei=f[(ΣkΣj(tk

ij–t0ij)] exposurewei

i=f[Pi/Ptot,ΣkΣj(tk

ij–t0ij)]

The proposed methodology:

• expresses vulnerability of a road network considering geometric and design

characteristics of the elements of road.

• attaches more importance to peripheral links which are particularly critical because

they have not alternative paths and their closure can completely isolate an area.


The methodology is specifically effective in areas of low population density and

where traffic flow is poor.

It could represent a new tool for roads administrators to define improvement

priorities and to manage emergency situations.

The study is going on including other road design characteristics (e.g. road gradient),

identifying combinations of link failures and considering different hazards in the

definition of the index.

Seventh International Conference on Informatics and Urban and Regional

Planning, University of Cagliari 10-12 May 2012

F. Maltinti "Gis applications for vulnerability assessment of a road network"

Maltinti, Melis and Annunziata - input2012

Technology

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