Contemporary Engineering Sciences, Vol. 11, 2018, no. 5, 215 - 227

HIKARI Ltd, www.m-hikari.com

https://doi.org/10.12988/ces.2018.812

New Transportation Infrastructure Impact in

Terms of Global Average Access - Intersection

"La Carola" Manizales (Colombia) Case Study

Diego Julián Perilla Ramírez

Universidad Nacional de Colombia, Departamento de Ingeniería Civil

Manizales, Colombia

Diego Alexander Escobar García

Universidad Nacional de Colombia, Departamento de Ingeniería Civil

Manizales, Colombia

Santiago Cardona Urrea

Universidad Nacional de Colombia, Departamento de Ingeniería Civil

Manizales, Colombia

Copyright © 2018 Diego Julián Perilla Ramírez et al. This article is distributed under the Creative

Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any

medium, provided the original work is properly cited.

Abstract

This study diagnoses the impact of the implementation of the “Carola” Intersection

in global accessibility terms, establishing a comparative into mean travel time

vectors, calculated from vehicle operational speed between the city of Manizales’

existing network and modified network including the new intersection, besides

defining zones and users benefited by the new transport infrastructure.

Keywords: Global Average Accessibility, Geo-Statistics, Road Network, Case

study

1 Introduction

The Manizales municipality (414,906 residents in the metropolitan area), is located

216 Diego Julián Perilla Ramírez et al.

in the department of Caldas at 5°03’58’’N and 75°29’05’’W in the Greenwich

meridian over the Central mountain range at 2150 MASL, near the “Nevado del

Ruiz”, as a part of the Colombian gold triangle (see Figure 1).

Fig. 1: Geographic location of the city of Manizales. Source: Authors.

The administration of the city of Manizales has sought to be consistent with the

national government’s purpose to consolidate transport infrastructure as one of the

most important for economic growth [19] through the execution of high-impact

projects. Manizales has been characterized for promoting projects of great impact

for mobility, such as the intersection of Fuente, inaugurated at the beginning of

2017, strengthening the transit of the Panamericana highway, as well as the transit

of users on their trips to Bogotá or Medellín [20]. Other type of projects with similar

characteristics are being executed in key points for mobility during peak hours, i.e.

the Intersection San Marcel in charge of the National Institute of Roads and the

Carola intersection in charge of the Mayorship of Manizales.

The Carola intersection is established within the current Manizales Development

Plan (2016-2019), proposed in the Physical-Spatial dimension, and framed as a safe,

effective and sustainable road infrastructure, transit and transport project, with the

purpose of making mobility efficient, safe and environmentally compatible [19].

The reason why the research is developed in terms of global average accessibility

is to evaluate the impact that this infrastructure would have on the average travel

times and the new spatial coverage in relation to the current situation.

New transportation infrastructure impact 217

A literary review, a description of the research methodology, discussion on data and

results, as well as a review of the main conclusions, follow this paper’s introduction

2 Literature Review

The concept of accessibility has been frequently used in territory planning and in

transport analysis during the last fifty years. There are records of its use since the

last century in the 1920s. North America was a pioneer in its use associated with

transport networks and travel distribution patterns [2]. However, the most classic

definition of this term was proposed by Hansen in his article "How Accessibility

Shapes Land Uses" published in 1959 where accessibility is defined as "The

potential of opportunities for interaction", also laying the first mathematical bases

of the model. On the other hand, in 1976, Weibull developed an axiomatic approach

for territorial accessibility models, making a meticulous mathematical analysis of

the previously proposed models [7, 16, 18, 26].

Accessibility measures have been classified in different ways over time, according

to study purposes, scope and data availability, which would determine its accuracy

[11]. Generally, the literature defines three types of accessibility: relative, integral

average and global average. Relative accessibility is the measure between two

points of the transport network considering distance or time [18]. Integral average

accessibility refers to different types such as: accumulated opportunities [3, 18],

impedance function [1, 9] and utility as a measure of the economic potential of a

city [5, 11]. Global average accessibility results from the average travel time

between all nodes or zones of an infrastructure network, and is used to determine

network infrastructure quality through average operating speeds and their

directionality [8]. In the literature, global average accessibility was proposed by

Geurs in 2001, who considered accessibility as a measure of infrastructure.

Furthermore, accessibility calculations can take different perspectives and different

factors can be used to enrich the analysis such as: travel mode, purpose of travel,

age, gender, socioeconomic groups, among many others [22].

Accessibility measures have been used for decades by researchers to analyze related

topics such as: urban development planning and land use [12], public transport

analysis [14], equity and social exclusion in transport [24], sustainable transport

development [6], access to health systems [9], economic development [17], social

cohesion [10], provision and location of services [4], re road addressing [8], among

many other studies.

3 Methodology

The methodology of the study is based on the development of four consecutive

stages shown in Figure 2 with their description enunciated below.

218 Diego Julián Perilla Ramírez et al.

Fig. 2: Research Methodology. Source: Authors.

3.1 Verification and adjustment of the transport infrastructure network of

Manizales

Geo-referenced information was taken from the network of Manizales, updated

with recent infrastructure changes. Software using geographic information systems

(GIS) with coordinates data of node location, arc lengths (La) and information on

operating speeds (Vprom), which were taken from official reports such as the

Mobility Plan of Manizales in 2017 [23], were used.

3.2 Existing network modification with the implementation of new transport

infrastructure

Based on the existing road network and the geometric design of the new intersection

(Figure 3), the transport infrastructure network is modified by creating the nodes

and arcs necessary for their representation, also changing address attributes, arc

length and expected operating speed according to the design. Prior to the calculation

of the global average accessibility, the updated network is reviewed and evaluated,

verifying the topology between nodes and graph, including the works executed in

the last year. The new intersection gives continuity to the traffic on the Kevin Angel

Avenue that connects the city from East to West, eliminating the existing traffic

signal and increasing the average operation speed to 50 Km/h on said corridor.

New transportation infrastructure impact 219

Fig. 3: Location of the infrastructure project “Intersección de La Carola”

Source: Author´s from [19]

3.3 Calculation of global average accessibility

The matrix of minimum times between all network nodes is calculated with the

information obtained from the existent and modified networks in previous stages,

based on the travel time of each arc; the minimum travel time (tvi) between each

node is measured with the Dkjistra algorithm; and, finally, the average travel time

(Tvi, Expression 1) is determined. [27]. The vector of travel time obtained is related

to the geographic coordinates of each of the nodes obtaining the matrix from which

the isochronous curves of average travel time are generated.

𝑇𝑣𝑖 = ∑ 𝑡𝑣𝑖𝑛

𝑗=1

𝑛 − 1 𝑖 = 1,2,3, … , 𝑛; 𝑗 = 1,2,3, … , 𝑛

(1)

For the geostatistical calculations, the ordinary Kriging Method with linear

semivariogram was used as a prediction model of the average travel times. The

semivariogram characterizes the properties of spatial dependence between points

belonging to an observed sample, which is calculated by Expression (2) [13], where

Z (x) = value of the variable in a site with x, y coordinates; Z (x + h) = another

sample value separated by a distance h; n = number of couples that are separated

by that distance. It is emphasized that, at a lower distance, the similarity or spatial

correlation between the observations is greater.

𝜸(𝒉)

=∑(𝒁(𝒙+𝒉) − 𝒁(𝒙))𝟐

𝟐𝒏

(2)

The ordinary Kriging method proposes that variable value can be predicted as a

linear combination of the n random variables, as presented in Expression (3) [13],

where λ1 = the weights of the original values. This method has been used for

different studies related to the prediction of supply models in transport networks

[25].

𝒁(𝒙𝟎) = 𝝀𝟏𝒁(𝒙𝟏) + 𝝀𝟐𝒁(𝒙𝟐) + 𝝀𝟑𝒁(𝒙𝟑) + 𝝀𝟒𝒁(𝒙𝟒)+. . +𝝀𝒏𝒁(𝒙𝒏) = ∑ 𝝀𝒊𝒁(𝒙𝒊)

𝒏

𝒊=𝟏

(3)

220 Diego Julián Perilla Ramírez et al.

In order to establish the relationship between the isochronous accessibility curves

and the population of the city, the neighborhood division map of the city of

Manizales, which has information on areas, densities and socioeconomic strata, will

be used. It is possible to establish the percentage of the population that will have

the greatest reduction in travel times given the construction of the new transport

infrastructure.

3.4 Calculation of the variation gradient of travel times

Based on the calculation of the global average accessibility of the existing network

(AMGa) and the modified network (AMGf) of the city of Manizales and the use of

software tools (GIS), the gradient percentage variation of travel time in each point

of the network (see Expression 4) is determined (% Gvar). The result will be a map

evidencing the estimated variation in average trip times with the implementation of

the new intersection La Carola.

%𝐺𝑣𝑎𝑟 = ( 𝐴𝑀𝐺𝑎 − 𝐴𝑀𝐺𝑓

𝐴𝑀𝐺𝑎) ∗ 100

(4)

4 Results and discussion

4.1 Global average accessibility in its current scenario, year 2017

The results of the geostatistical calculations, represented by isochronous curves in

ranges of every 5 minutes (See Figure 4), show that the city is covered with average

travel times of between 20 and 65 minutes. It is worth to highlight that the

isochronous curves found between 20 and 35 minutes of average travel time covers

86% of the total study population (358,269 inhabitants).

Isochronous curves between 20 and 25 minutes cover 15% of the study area and are

located in the downtown area (Central Bussiness District - CBD) and areas adjacent

to the two main arterial roads that connect the city, which are Kevin Angel Avenue

and Santander Avenue.

In contrast, the curves showing the highest average travel times are found in the

peripheries of the city: the 55-minute curves cover the Maltería and Gallinazo

sectors east of the city and within the same curve to the southwest of the city are

the sectors of Bajo Tablazo and Villamaría, as shown in the boxes of Figure 4. The

area with the least favorable average travel times are located northwest of the city

in the sector of La Linda with curves greater than 60 minutes.

New transportation infrastructure impact 221

Figure 4: Isochronous curves current scenario, year 2017. Source: Authors.

4.2 Global average accessibility future scenario, including La Carola

intersection

Once the global average accessibility with the modified network was estimated,

isochronous curves were obtained in the same ranges of accessibility calculation

made in the existing network; between 20 and 65 minutes, but with noticeable

changes mainly in the curve of 20 to 25 minutes, area that increases significantly.

Figure 5 shows the results of the global average accessibility calculation to the

network in the future scenario. The reduction of average travel times is more

noticeable on Kevin Angel Avenue, this corridor communicates the city from East

to West. This change is shown in detail in the red box, which also shows the

modification to the existing network with the start of operation of the new

intersection.

4.3 Global average accessibility gradient

Figure 6 shows the gradient curves of the areas where an increase or savings in the

average travel time will take place, measured as a percentage of change between

the current and future scenario. It is evident that some areas of the periphery, such

as the La Linda sector (northeast), had savings between 5% and 10% in the average

travel times. Sectors close to the intersection are observed with savings of up to

30% (see Fig. 6). Likewise, there is a small increase in the average travel time in

certain sectors of the La Carola neighborhood (next to the intervention).

222 Diego Julián Perilla Ramírez et al.

Fig.5: Isochronous curves future scenario. Source: Authors

Fig.6: Gradient Saving (%). Source: Authors.

This is due to the fact that the average travel time is directly related to the length of

the arches. However, this means that users, despite having more mobility options

in the sector, will have to travel longer lengths, but without representing

disturbances due to traffic or waiting times for turns at intersections.

New transportation infrastructure impact 223

Figure 7 shows the saving percentage and its effect on the population. Up to 8%

perceive savings between 5% and 10% of their mean travel times, which equals to

5000 families favored in the city. Moreover, up to 6% of the population obtain

savings of 15%. Finally, it should be noted that 2% of the population receives

savings in their average travel times of up to 20%, which indicates that this road

infrastructure alternative will benefit a large number of inhabitants.

Fig.7: Covered Population per saving percentage of travel time. Source: Authors.

With information obtained from the accessibility calculations in the average travel

time matrix, it is possible to classify the covered population into socioeconomic

strata. This classification consists of assigning a category from 1 to 6 to the areas

depending on dwellings conditions, access to basic services and income per family,

1 indicating the lowest and 6, the highest. Figures 8 and 9 show the variation

between the current situation and the future one by socioeconomic stratum. As can

be seen, the most benefited stratum 5, located in close proximity to the curve whose

average travel time is close to 30 minutes for about 99% of the population of the

same stratum.

5 Conclusions

The methodology used to calculate global average accessibility can also be used in

developing countries and intermediate cities with similar contexts, allowing to

determine the impacts that new infrastructure works can generate.

The impact generated with the implementation of the new intersection mainly

covers Kevin Angel Avenue. Coverage percentage of the 25-minute curve increases

from 5.15% to 5.71% and the 30-minute curve of 28.10 % to 29.90%, decreasing

the average travel times for Laureles, Los Rosales and La Leonora neighborhoods,

with socioeconomic strata 4-5.

224 Diego Julián Perilla Ramírez et al.

Fig.8: Coverage distribution by socioeconomic strata. Current situation. Source:

Authors.

Fig.9: Coverage distribution by socioeconomic strata. Future situation. Source:

Authors.

According to the analysis, 7.2% of the population save from 5% up to 25% in their

mean travel times, which translates into a benefit to a considerably large group in

the city.

Acknowledgements. The authors thank the research center of sustainable mobility

of the National University of Colombia, campus Manizales.

New transportation infrastructure impact 225

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Received: January 20, 2018; Published: February 27, 2018