Micro-interventions in urban transport from pattern discovery on the flow of passengers and on the bus network
📝 Abstract
In this paper, we describe a case study in a big metropolis, in which from data collected by digital sensors, we tried to understand mobility patterns of persons using buses and how this can generate knowledge to suggest interventions that are applied incrementally into the transportation network in use. We have first estimated an Origin-Destination matrix of buses users from datasets about the ticket validation and GPS positioning of buses. Then we represent the supply of buses with their routes through bus stops as a complex network, which allowed us to understand the bottlenecks of the current scenario and, in particular, applying community discovery techniques, to identify clusters that the service supply infrastructure has. Finally, from the superimposing of the flow of people represented in the OriginDestination matrix in the supply network, we exemplify how micro-interventions can be prospected by means of an example of the introduction of express routes.
💡 Analysis
In this paper, we describe a case study in a big metropolis, in which from data collected by digital sensors, we tried to understand mobility patterns of persons using buses and how this can generate knowledge to suggest interventions that are applied incrementally into the transportation network in use. We have first estimated an Origin-Destination matrix of buses users from datasets about the ticket validation and GPS positioning of buses. Then we represent the supply of buses with their routes through bus stops as a complex network, which allowed us to understand the bottlenecks of the current scenario and, in particular, applying community discovery techniques, to identify clusters that the service supply infrastructure has. Finally, from the superimposing of the flow of people represented in the OriginDestination matrix in the supply network, we exemplify how micro-interventions can be prospected by means of an example of the introduction of express routes.
📄 Content
Micro-interventions in urban transport from pattern discovery on the flow of passengers and on the bus network
Carlos Caminha, Vasco Furtado, Vládia Pinheiro e Caio Ponte Programa de Pós-graduação em Informática Aplicada (PPGIA) Universidade de Fortaleza (Unifor) Brazil
Abstract— In this paper, we describe a case study in a big
metropolis, in which from data collected by digital sensors, we
tried to understand mobility patterns of persons using buses and
how this can generate knowledge to suggest interventions that are
applied incrementally into the transportation network in use. We
have first estimated an Origin-Destination matrix of buses users
from datasets about the ticket validation and GPS positioning of
buses. Then we represent the supply of buses with their routes
through bus stops as a complex network, which allowed us to
understand the bottlenecks of the current scenario and, in
particular, applying community discovery techniques, to identify
clusters that the service supply infrastructure has. Finally, from
the superimposing of the flow of people represented in the Origin-
Destination matrix in the supply network, we exemplify how
micro-interventions can be prospected by means of an example of
the introduction of express routes.
Keywords — Mobility, Complex Networks, Data Mining.
I.
INTRODUCTION
A smart city is known through the ownership of data and
information produced on it to generate knowledge, which,
applied, promotes the well being of citizens. The era of
digital information is characterized by the huge capacity of
the cities of sensing itself through the data collection on its
own dynamic. Within this context, the biggest challenge is to,
from this diverse and the voluminous data, to create means to
generate knowledge and apply it with effectiveness for the
benefit of the collectivity.
One of the areas that best exemplifies the context
described above is the urban mobility. The most diverse
sensors and digital media record daily information on tracks
of people, which becomes a rich input for the carrying out of
studies that support public transport policies. In this article we
describe our experience in a large Brazilian metropolis within
the framework of its project for Smart City. We will show
how, from data collected by digital sensors, we tried to
understand mobility patterns of persons using buses and how
this can generate knowledge to suggest interventions that are
applied incrementally into the transportation network in use.
Our contributions are concentrated on three aspects. First,
we show that, although there is a great variety and volume of
collected data, it is necessary a preparation and refinement
work of the data so that they can be used in prospective
studies. For this we have developed an algorithm to estimate
the Origin-Destination matrix (ODM) of buses users from
datasets on ticket validation and on GPS positioning of buses.
We show that the sample of trips with origin and destination
estimated by our algorithm is statistically significant of the
global behavior of bus users. Thus we ended up producing an
ODM with quantities well superior to those built by survey
that are still the ones that most naturally permeate the work in
the field of transport engineering [1].
From this estimate, we chained in our second contribution,
which consists of representing the scenario of urban mobility
(by making use of the ODM) as complex networks. We built
a complex network that represents the supply of public
transportation in the city considering the vehicles used, the
routes that they follow and the itinerary of the routes with
their bus stops. This network has allowed us to understand the
bottlenecks of the current scenario and, in particular, applying
community discovery techniques, to identify clusters that the
service supply infrastructure has.
Finally, our third contribution consisted of superimposing
to the network of supplies the flow of people represented in
the ODM. This allowed in principle the extension of the
characterization of the transport system, emphasizing the flow
of people inter and intra community as well as has allowed
simulating micro-interventions at the current supply network.
Micro-interventions or urban acupuncture [2] advocates the
introduction of small modifications in urban scenario so that,
with low cost, it is possible to change a local reality and bring
impacts on the organism as a whole (in the case, the city). Our
approach is proved to be useful in this scenario because it
allows not only to intervene locally but also it gives us a
chance to have a global view of the impact of this intervention
in the transport network as a whole. We provide examples of
how this can be done through the introduction of express
routes, which can lead to improved public service by
increasing the convenience and agility at the pathway of
frequent users of an ODM through impr
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