Applying Public Participation Approach to Black Spot Identification Process

A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-In this work we introduce a fast big data approach for road incident hot spot identification using Apache Spark. We implement an existing immuno-inspired mechanism, namely SeleSup, as a series of MapReduce-like operations. SeleSup is composed of a number of iterations that remove data redundancies and result in the detection of areas of high likelihood of vehicles incidents. It has been successfully applied to large datasets, however, as the size of the data increases to millions of instances, its performance drops significantly. Our objective therefore is to re-conceptualise the method for big data. In this paper we present the new implementation, the challenges faced when converting the method for the Apache Spark platform as well as the outcomes obtained. For our experiments we employ a large dataset containing hundreds of thousands of Heavy Good Vehicles incidents, collected via telematics. Results show a significant improvement in performance with no detriment to the accuracy of the method.

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“…Government and public [10] also contribute to the knowledge, however it also results in inaccuracies [11]. Two main reviews compare HSID methods.…”

Section: A Related Work On Hot Spot Identificationmentioning

confidence: 99%

Vehicle Incident Hot Spots Identification: An Approach for Big Data

Triguero

Figueredo

Mesgarpour

et al. 2017

2017 IEEE Trustcom/BigDataSE/Icess

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“…Tal y como se mencionó anteriormente, hoy en día no existen muchas experiencias de aprendizaje-servicio en la formación universitaria en gestión de la seguridad vial, pero hay ejemplos de cómo la participación pública (Kowtanapanich et al, 2006;Masuri et al, 2015) ha demostrado promover el concepto de "responsabilidad compartida" en este escenario. Kowtanapanich et al (2006) muestran cómo se puede utilizar un enfoque de concienciación social para ayudar a identificar la ubicación de puntos negros a través de un Programa de Participación Pública en Accidentes en la ciudad de Khon Kaen, Tailandia. La seguridad vial está directamente relacionada con el bienestar social, ya que la reducción del número de accidentes graves y la sensación de seguridad aumentan el nivel de bienestar.…”

Section: Contexto De La Experienciaunclassified

La implementación de metodologías de Aprendizaje –Servicio en el campo de la seguridad vial: la experiencia universitaria en Ingeniería Civil

Guirao¹,

Casado-Sanz²,

Quesada³

2019

Aprendizaje, Innovación Y Cooperación Como Impulsores Del Cambio Metodológico

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Resumen-El aprendizaje servicio es una metodología educativa en la que el estudiante adquiere una responsabilidad cívica al mismo tiempo que progresa en el aprendizaje de una determinada materia. Este artículo está centrado en la implementación de una experiencia de aprendizaje-servicio en el campo de la seguridad vial con alumnos de Ingeniería Civil. Trabajar con Asociaciones de Víctimas de accidentes de tráfico puede ayudar a comprender mejor los indicadores de siniestralidad, los tipos de lesiones causadas por estos accidentes y sus consecuencias físicas y legales. Este documento contribuye a la literatura existente con la evaluación de las experiencias positivas y negativas percibidas por los estudiantes al acometer por primera vez un proyecto de aprendizaje-servicio en el campo de la seguridad vial. La metodología se basó en una campaña de encuestas a los 61 estudiantes matriculados en la

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“…Like transportation services or infrastructure, public participation needs to be designed for a particular context. Various researches have been carried out in different fields of transportation, including the traffic planning (Wahl 2012), (Li 2013), safety programming (Kowtanapanich et al 2006), intelligent transportation (Ali et al 2012), (Lu 2009), routing (Shah et al 2011), (Efentakis et al 2012), (Stenneth et L. 2011) and environmental impact assessment (Alagan 2007). Table 2 demonstrates these research domains in public participation for transportation and describes their usage.…”

Section: Public Participation In Transportationmentioning

confidence: 99%

Enriching Spatial Data Infrastructure (Sdi) by User Generated Contents for Transportation

Shakeri

Alimohammadi

Sadeghi‐Niaraki

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Spatial data is one of the most critical elements underpinning decision making for many disciplines. Accessing and sharing spatial data have always been a great struggle for researchers. Spatial data infrastructure (SDI) plays a key role in spatial data sharing by building a suitable platform for collaboration and cooperation among the different data producer organizations. In recent years, SDI vision has been moved toward a user-centric platform which has led to development of a new and enriched generation of SDI (third generation). This vision is to provide an environment where users can cooperate to handle spatial data in an effective and satisfactory way. User-centric SDI concentrates on users, their requirements and preferences while in the past, SDI initiatives were mainly concentrated on technological issues such as the data harmonization, standardized metadata models, standardized web services for data discovery, visualization and download. On the other hand, new technologies such as the GPS-equipped smart phones, navigation devices and Web 2.0 technologies have enabled citizens to actively participate in production and sharing of the spatial information. This has led to emergence of the new phenomenon called the Volunteered Geographic Information (VGI). VGI describes any type of content that has a geographic element which has been voluntarily collected. However, its distinctive element is the geographic information that can be collected and produced by citizens with different formal expertise and knowledge of the spatial or geographical concepts. Therefore, ordinary citizens can cooperate in providing massive sources of information that cannot be ignored. These can be considered as the valuable spatial information sources in SDI. These sources can be used for completing, improving and updating of the existing databases. Spatial information and technologies are an important part of the transportation systems. Planning, design and operation of the transportation systems requires the exchange of large volumes of spatial data and often close cooperation among the various organizations. However, there is no technical and organizational process to get a suitable data infrastructure to address diverse needs of the transportation. Hence, development of a common standards and a simple data exchange mechanism is strongly needed in the field of transportation for decision support. Since one of the main purposes of transportation projects is to improve the quality of services provided to users, it is necessary to involve the users themselves in the decision making processes. This should be done through a public participation and involvement in all stages of the transportation projects. In other words, using public knowledge and information as another source of information is very important to make better and more efficient decisions. Public participation in transportation projects can also help organizations to enhance their public supports; because the lack of public support can lead to failure of technic...

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Applying Public Participation Approach to Black Spot Identification Process

Cited by 18 publications

References 5 publications

Vehicle Incident Hot Spots Identification: An Approach for Big Data

Vehicle Incident Hot Spots Identification: An Approach for Big Data

La implementación de metodologías de Aprendizaje –Servicio en el campo de la seguridad vial: la experiencia universitaria en Ingeniería Civil

Enriching Spatial Data Infrastructure (Sdi) by User Generated Contents for Transportation

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