Gender gaps in urban mobility


Paper by Laetitia Gauvin, Michele Tizzoni, Simone Piaggesi, Andrew Young, Natalia Adler, Stefaan Verhulst, Leo Ferres & Ciro Cattuto in Humanities and Social Sciences Communications: “Mobile phone data have been extensively used to study urban mobility. However, studies based on gender-disaggregated large-scale data are still lacking, limiting our understanding of gendered aspects of urban mobility and our ability to design policies for gender equality. Here we study urban mobility from a gendered perspective, combining commercial and open datasets for the city of Santiago, Chile.

We analyze call detail records for a large cohort of anonymized mobile phone users and reveal a gender gap in mobility: women visit fewer unique locations than men, and distribute their time less equally among such locations. Mapping this mobility gap over administrative divisions, we observe that a wider gap is associated with lower income and lack of public and private transportation options. Our results uncover a complex interplay between gendered mobility patterns, socio-economic factors and urban affordances, calling for further research and providing insights for policymakers and urban planners….(More)”.

Global Traffic Scorecard


Press Release: “…the 2019 INRIX Global Traffic Scorecard… identified, analyzed and ranked congestion and mobility trends in more than 900 cities, across 43 countries. To reflect an increasingly diverse mobility landscape, the 2019 Global Traffic Scorecard includes both public transport and biking metrics for the first time….

At the global level, Bogota topped the list of the cities most impacted by traffic congestion with drivers losing 191 hours a year to congestion, followed by Rio de Janeiro (190 hours), Mexico City (158 hours) and Istanbul (150 hours). Latin American and European cities again dominated the Top 10, highlighting the rapid urbanisation occurring in Latin America and historic European cities that took shape long before the age of automobile….

INRIX fuses anonymous data from diverse datasets – such as phones, cars, trucks and cities – that leads to robust and accurate insights. The data used in the 2019 Global Traffic Scorecard is the congested or uncongested status of every segment of road for every minute of the day, as used by millions of drivers around the world that rely on INRIX-based traffic services….(More)”

Car Data Facts


About: “Welcome to CarDataFacts.eu! This website provides a fact-based overview on everything related to the sharing of vehicle-generated data with third parties. Through a series of educational infographics, this website answers the most common questions about access to car data in a clear and simple way.

CarDataFacts.eu also addresses consumer concerns about sharing data in a safe and a secure way, as well as explaining some of the complex and technical terminology surrounding the debate.

CarDataFacts.eu is brought to you by ACEA, the European Automobile Manufacturers’ Association, which represents the 15 Europe-based car, van, truck and bus makers….(More)”.

Navigation Apps Changed the Politics of Traffic


Essay by Laura Bliss: “There might not be much “weather” to speak of in Los Angeles, but there is traffic. It’s the de facto small talk upon arrival at meetings or cocktail parties, comparing journeys through the proverbial storm. And in certain ways, traffic does resemble the daily expressions of climate. It follows diurnal and seasonal patterns; it shapes, and is shaped, by local conditions. There are unexpected downpours: accidents, parades, sports events, concerts.

Once upon a time, if you were really savvy, you could steer around the thunderheads—that is, evade congestion almost entirely.

Now, everyone can do that, thanks to navigation apps like Waze, which launched in 2009 by a startup based in suburban Tel Aviv with the aspiration to save drivers five minutes on every trip by outsmarting traffic jams. Ten years later, the navigation app’s current motto is to “eliminate traffic”—to untie the knots of urban congestion once and for all. Like Google Maps, Apple Maps, Inrix, and other smartphone-based navigation tools, its routing algorithm weaves user locations with other sources of traffic data, quickly identifying the fastest routes available at any given moment.

Waze often describes itself in terms of the social goods it promotes. It likes to highlight the dedication of its active participants, who pay it forward to less-informed drivers behind them, as well as its willingness to share incident reports with city governments so that, for example, traffic engineers can rejigger stop lights or crack down on double parking. “Over the last 10 years, we’ve operated from a sense of civic responsibility within our means,” wrote Waze’s CEO and founder Noam Bardin in April 2018.

But Waze is a business, not a government agency. The goal is to be an indispensable service for its customers, and to profit from that. And it isn’t clear that those objectives align with a solution for urban congestion as a whole. This gets to the heart of the problem with any navigation app—or, for that matter, any traffic fix that prioritizes the needs of independent drivers over what’s best for the broader system. Managing traffic requires us to work together. Apps tap into our selfish desires….(More)”.

This essay is adapted from SOM Thinkers: The Future of Transportation, published by Metropolis Books.

Gendering Smart Mobilities


Book edited by Tanu Priya Uteng, Hilda Rømer Christensen, and Lena Levin: “This book considers gender perspectives on the ‘smart’ turn in urban and transport planning to effectively provide ‘mobility for all’ while simultaneously attending to the goal of creating green and inclusive cities. It deals with the conceptualisation, design, planning, and execution of the fast-emerging ‘smart’ solutions.

The volume questions the efficacy of transformations being brought by smart solutions and highlights the need for a more robust problem formulation to guide the design of smart solutions, and further maps out the need for stronger governance to manage the introduction and proliferation of smart technologies. Authors from a range of disciplinary backgrounds have contributed to this book, designed to converse with mobility studies, transport studies, urban-transport planning, engineering, human geography, sociology, gender studies, and other related fields.

The book fills a substantive gap in the current gender and mobility discourses, and will thus appeal to students and researchers studying mobilities in the social, political, design, technical, and environmental sciences….(More)”.

Industry and Public Sector Leaders Partner to Launch the Mobility Data Collaborative


Press Release: “The Mobility Data Collaborative (the Collaborative), a multi-sector forum with the goal of creating a framework to improve mobility through data, launches today…

New mobility services, such as shared cars, bikes, and scooters, are emerging and integrating into the urban transportation landscape across the globe. Data generated by these new mobility services offers an exciting opportunity to inform local policies and infrastructure planning. The Collaborative brings together key members from the public and private sectors to develop best practices to harness the potential of this valuable data to support safe, equitable, and livable streets.

The Collaborative will leverage the knowledge of its current and future members to solve the complex challenges facing shared mobility operators and the public agencies who manage access to infrastructure that these new services require. A critical component of this collaboration is providing an open and impartial forum for sharing information and developing best practices. 

Membership is open to public agencies, nonprofits, academic institutions and private companies….(More)”.

Road Traffic Accidents Analysis in Mexico City through Crowdsourcing Data and Data Mining Techniques


Paper by Gabriela V. Angeles et al: “Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current.

However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze.

The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS….(More)”.

Mobility Data Sharing: Challenges and Policy Recommendations


Paper by Mollie D’Agostino, Paige Pellaton, and Austin Brown: “Dynamic and responsive transportation systems are a core pillar of equitable and sustainable communities. Achieving such systems requires comprehensive mobility data, or data that reports the movement of individuals and vehicles. Such data enable planners and policymakers to make informed decisions and enable researchers to model the effects of various transportation solutions. However, collecting mobility data also raises concerns about privacy and proprietary interests.

This issue paper provides an overview of the top needs and challenges surrounding mobility data sharing and presents four relevant policy strategies: (1) Foster voluntary agreement among mobility providers for a set of standardized data specifications; (2) Develop clear data-sharing requirements designed for transportation network companies and other mobility providers; (3) Establish publicly held big-data repositories, managed by third parties, to securely hold mobility data and provide structured access by states, cities, and researchers; (4) Leverage innovative land-use and transportation-planning tools….(More)”.

Traffic Data Is Good for More than Just Streets, Sidewalks


Skip Descant at Government Technology: “The availability of highly detailed daily traffic data is clearly an invaluable resource for traffic planners, but it can also help officials overseeing natural lands or public works understand how to better manage those facilities.

The Natural Communities Coalition, a conservation nonprofit in southern California, began working with the traffic analysis firm StreetLight Data in early 2018 to study the impacts from the thousands of annual visitors to 22 parks and natural lands. StreetLight Data’s use of de-identified cellphone data held promise for the project, which will continue into early 2020.

“You start to see these increases,” Milan Mitrovich, science director for the Natural Communities Coalition, said of the uptick in visitor activity the data showed. “So being able to have this information, and share it with our executive committee… these folks, they’re seeing it for the first time.”…

Officials with the Natural Communities Coalition were able to use the StreetLight data to gain insights into patterns of use not only per day, but at different times of the day. The data also told researchers where visitors were traveling from, a detail park officials found “jaw-dropping.”

“What we were able to see is, these resources, these natural areas, cast an incredible net across southern California,” said Mitrovich, noting visitors come from not only Orange County, but Los Angeles, San Bernardino and San Diego counties as well, a region of more than 20 million residents.

The data also allows officials to predict traffic levels during certain parts of the week, times of day or even holidays….(More)”.

Stop the Open Data Bus, We Want to Get Off


Paper by Chris Culnane, Benjamin I. P. Rubinstein, and Vanessa Teague: “The subject of this report is the re-identification of individuals in the Myki public transport dataset released as part of the Melbourne Datathon 2018. We demonstrate the ease with which we were able to re-identify ourselves, our co-travellers, and complete strangers; our analysis raises concerns about the nature and granularity of the data released, in particular the ability to identify vulnerable or sensitive groups…..

This work highlights how a large number of passengers could be re-identified in the 2018 Myki data release, with detailed discussion of specific people. The implications of re-identification are potentially serious: ex-partners, one-time acquaintances, or other parties can determine places of home, work, times of travel, co-travelling patterns—presenting risk to vulnerable groups in particular…

In 2018 the Victorian Government released a large passenger centric transport dataset to a data science competition—the 2018 Melbourne Datathon. Access to the data was unrestricted, with a URL provided on the datathon’s website to download the complete dataset from an Amazon S3 Bucket. Over 190 teams continued to analyse the data through the 2 month competition period. The data consisted of touch on and touch off events for the Myki smart card ticketing system used throughout the state of Victoria, Australia. With such data, contestants would be able to apply retrospective analyses on an entire public transport system, explore suitability of predictive models, etc.

The Myki ticketing system is used across Victorian public transport: on trains, buses and trams. The dataset was a longitudinal dataset, consisting of touch on and touch off events from Week 27 in 2015 through to Week 26 in 2018. Each event contained a card identifier (cardId; not the actual card number), the card type, the time of the touch on or off, and various location information, for example a stop ID or route ID, along with other fields which we omit here for brevity. Events could be indexed by the cardId and as such, all the events associated with a single card could be retrieved. There are a total of 15,184,336 cards in the dataset—more than twice the 2018 population of Victoria. It appears that all touch on and off events for metropolitan trains and trams have been included, though other forms of transport such as intercity trains and some buses are absent. In total there are nearly 2 billion touch on and off events in the dataset.

No information was provided as to the de-identification that was performed on the dataset. Our analysis indicates that little to no de-identification took place on the bulk of the data, as will become evident in Section 3. The exception is the cardId, which appears to have been mapped in some way from the Myki Card Number. The exact mapping has not been discovered, although concerns remain as to its security effectiveness….(More)”.