Traffic event detection framework using social media

This is an accepted manuscript of an article published by IEEE in 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC) on 18/09/2017, available online: https://ieeexplore.ieee.org/document/8038595 The accepted version of the publication may differ from the final published version.© 2017 IEEE. Traffic incidents are one of the leading causes of non-recurrent traffic congestions. By detecting these incidents on time, traffic management agencies can activate strategies to ease congestion and travelers can plan their trip by taking into consideration these factors. In recent years, there has been an increasing interest in Twitter because of the real-time nature of its data. Twitter has been used as a way of predicting revenues, accidents, natural disasters, and traffic. This paper proposes a framework for the real-time detection of traffic events using Twitter data. The methodology consists of a text classification algorithm to identify traffic related tweets. These traffic messages are then geolocated and further classified into positive, negative, or neutral class using sentiment analysis. In addition, stress and relaxation strength detection is performed, with the purpose of further analyzing user emotions within the tweet. Future work will be carried out to implement the proposed framework in the West Midlands area, United Kingdom.Published versio

Planning Catalonia’s Airport System based on Econometric Analysis

The continued growth of the commercial aviation in the world, specifically in Catalonia (only hindered by the outburst of the pandemic), denotes the urge to build resilient and environmentally conscious infrastructures, capable of efficiently absorb the generated demand. Understanding the scope of airports (far more than mere nodes of transport) and their key role is fundamental to tackle its economic growth potential in a sustainable way. Therefore, this thesis presents a holistic study of the demand generation- from structural and economic variables- to help understand, on the one hand, the journey towards the future of commercial aviation in Catalonia, and, on the other hand, the planification and distribution of the airport’s activity flows throughout the territory to achieve maximum economic and logistic efficiency, without losing sight of the Sustainable Development Goals of the UN. Working on statistic and socioeconomic studies, a demand generation model has been created for the three most important airports of Catalonia in the 2035 horizon, as well as the study of different scenarios to understand better the possible configurations of the Catalan airport’s system. With the different results it has been proved that the civil aviation market in Catalonia has rooted strongly (both historically and economically) in the region, with solid forecasting performances for the next years. This increase must be translated into the enhancement of the different airport facilities. Following scientific criteria such as economics and acoustic, environmental and social sustainability, it has been observed that the most resilient configuration of aviation flows goes through a joint one with shared responsibilities between infrastructures. The complementary characteristic of the current infrastructure creates synergies in the region, enabling a more equative distribution of the wealth generated and the environmental impact. The nowadays structure of the commercial and civil aviation market in Catalonia supports this redistribution of powers to balance the region and potentiate it in a holistic, responsible and firm way

From Data to Actions in Intelligent Transportation Systems: A Prescription of Functional Requirements for Model Actionability

Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that are data-driven. Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a “story” intensively producing and consuming large amounts of data. A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers’ personal devices act as sources of data flows that are eventually fed into software running on automatic devices, actuators or control systems producing, in turn, complex information flows among users, traffic managers, data analysts, traffic modeling scientists, etc. These information flows provide enormous opportunities to improve model development and decision-making. This work aims to describe how data, coming from diverse ITS sources, can be used to learn and adapt data-driven models for efficiently operating ITS assets, systems and processes; in other words, for data-based models to fully become actionable. Grounded in this described data modeling pipeline for ITS, we define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation. We deliberately generalize model learning to be adaptive, since, in the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications. Finally, we provide a prospect of current research lines within Data Science that can bring notable advances to data-based ITS modeling, which will eventually bridge the gap towards the practicality and actionability of such models.This work was supported in part by the Basque Government for its funding support through the EMAITEK program (3KIA, ref. KK-2020/00049). It has also received funding support from the Consolidated Research Group MATHMODE (IT1294-19) granted by the Department of Education of the Basque Government

Congestion Pricing in the United States: Principles for Developing a Viable Program to Advance Sustainability and Equity Goals

There is no silver bullet to fix the woes of urban mobility and access, but congestion pricing is a proven, viable, and effective tool. Charging a fee for the parts of the roadway network used the most during the busiest times of day reduces demand. The charges incentivize travelers to switch to other modes of transportation, seek alternative routes, or travel at other times. The charges can help to reduce negative effects of traffic such as air pollution, carbon emissions, road damage, and traffic crashes.This report seeks to accelerate the development of congestion pricing programs in the U.S. that advance sustainability and equity goals. The report is intended for elected officials, civic leaders, advocates, and agency professionals in cities and metropolitan regions. The principles outlined in this report illustrate key concepts, discuss challenges, and share examples and emerging best practices

Demand modeling of successful park and ride planning: multivariate spatial regressive analysis

Park and ride facilities are designed to efficiently intercept traffic flow toward metropolitan business districts and help relieve traffic congestion in the central business areas. An attempt in this research was made to develop a successful park and ride demand model based on the distribution of park and ride usage, by applying geographic information system (GIS) and other spatial statistical packages. The Minneapolis-St. Paul (Twin Cities) Metropolitan Area was selected as a study area for this research because its park and ride system has grown to become one of the nation\u27s largest systems in terms of the number of facilities and total capacity. Recently, the Twin Cities Metropolitan Area started to consider designating large-scale park and ride facilties in the region. There is a need to conduct a research for achieving successful park and ride planning. This research involves multivariate regression demand forecast, spatial cluster identification, and spatial autoregressive analyses. Factors considered in the model for assessing the success and failure of park and ride facilities include socioeconomic characteristics, transportation network features, user behavior, and spatial statistics. These factors are analyzed for predicting the park and ride usages, i.e., the number of parked lots in the park and ride sites during the last visit in FY 2004. In general, the contribution of this research for successful park and ride facilities demand forecast is to integrate spatial association with quantitative statistics by a series of GIS-based statistical techniques for future practice in the field of transportation facility planning

Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic

This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was validated using a fleet of 100 connected automated vehicles as part of the largest coordinated open-road test designed to smooth traffic flow. The framework includes two main components: a high-level controller deployed on the server side, named Speed Planner, and low-level controllers called vehicle controllers deployed on the vehicle side. The Speed Planner designs and updates target speeds for the vehicle controllers based on real-time Traffic State Estimation (TSE) [1]. The Speed Planner comprises two modules: a TSE enhancement module and a target speed design module. The TSE enhancement module is designed to minimize the effects of inherent latency in the received traffic information and to improve the spatial and temporal resolution of the input traffic data. The target speed design module generates target speed profiles with the goal of improving traffic flow. The vehicle controllers are designed to track the target speed meanwhile responding to the surrounding situation. The numerical simulation indicates the performance of the proposed method: the bottleneck throughput has increased by 5.01%, and the speed standard deviation has been reduced by a significant 34.36%. We further showcase an operational study with a description of how the controller was implemented on a field-test with 100 AVs and its comprehensive effects on the traffic flow

Planning and design of a network of vertiports in the Metropolitan Area of Barcelona (AMB)

This project aims to design a network of vertiports in the Metropolitan Area of Barcelona, Spain. The commitment of technology companies to design eVTOL aircraft suitable for urban areas coupled with the exponential growth of interest in urban air mobility, makes the project to define a well-planned and efficient vertiports infrastructure a smart step for the development of this emerging sector. The design of the vertiport network takes into consideration the following: the geographical layout, existing transportation infrastructure and population density in the Barcelona Metropolitan Area. The objective is to strategically locate the vertiports to maximize public attraction and minimize travel distances for passengers and consequently reduce pollutant emissions. In order to define the frequency of operations to be carried out in each of the vertiports, a study of the demand that this project could attract is required, analyzing the potential market. Based on the forecasts in terms of the number of daily operations carried out at the vertiports, transport lines are established that leave the entire area interconnected. Moreover, the 3D design of one of the vertiports will be carried out, in order to have a more realistic view of its dimensions. It details all the elements required both on the air side of the vertiport and on the land side, establishing the number of pads corresponding to the flight capacity study. Likewise, the passenger terminal must be designed to achieve the most effective passenger flow possible. Furthermore, the design incorporates considerations for noise reduction and environmental impact, aiming to integrate the vertiport network causing the least impact in urban areas. In addition, it is fundamental to develop an economic analysis of the costs and benefits that the construction and implementation of one of the vertiports of the Metropolitan Area of Barcelona would entail, to analyze its viability. Thanks to the implementation of this vertiport network, the city will offer an alternative method of transportation for residents and visitors, making a positive contribution to the environment. The results of this project will provide an innovative design proposal for the vertiport network that could be used as a starting point by other users or companies for a more in-depth development about the creation of vertiports in the city

Cartoons as interdiscourse : a quali-quantitative analysis of social representations based on collective imagination in cartoons produced after the Charlie Hebdo attack

The attacks against Charlie Hebdo in Paris at the beginning of the year 2015 urged many cartoonists – most professionals but some laymen as well – to create cartoons as a reaction to this tragedy. The main goal of this article is to show how traumatic events like this one can converge in a rather limited set of metaphors, ranging from easily recognizable topoi to rather vague interdiscourses that circulate in contemporary societies. To do so, we analyzed 450 cartoons that were produced as a reaction to the Charlie Hebdo attacks, and took a quali-quantitative approach that draws both on discourse analysis and semiotics. In this paper, we identified eight main themes and we analyzed the five ones which are anchored in collective imagination (the pen against the sword, the journalist as a modern hero, etc.). Then, we studied the cartoons at figurative, narrative and thematic levels thanks to Greimas’ model of the semiotic square. This paper shows the ways in which these cartoons build upon a memory-based network of events from the recent past (particularly 9/11), and more generally on a collective imagination which can be linked to Western values.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

A digital response system to mitigate overtourism. The case of Dubrovnik

In order to design effective responses to the complex phenomenon of overtourism, the tourism carrying capacity (TCC) of a destination is an essential reference point. This paper provides in-depth analysis of this correlation through the case study of Dubrovnik. The study applies a TCC calculation model that is able to quantitatively include the main effects of overtourism. The paper illustrates how these results can be used to automate specific decongestion policies by conceptualising a digital response system for real-time intervention to mitigate the undesirable effects of overtourism