Data Sharing in Transport

Curated on Posted on by Stefaan Verhulst

Technical Note by the European Investment Board: “Traveller and transport related data are essential for planning efficient urban mobility and delivering an effective public transport services while adequately managing infrastructure investment costs. It also supports local authorities in their efforts towards decarbonisation of transport as well as improving air quality.

Nowadays, most of the data are generated by location-based mobile phone applications and connected vehicles or other mobility equipment like scooters and bikes. This opens up new opportunities in public sector engagement with private sector and partnerships.

This report, through an extensive literature review and interviews, identifies seven Data Partnership Models that could be used by public and private sector entities in the field of transport. It also provides a concise roadmap for local authorities as a guidance in their efforts when engaging with private sector in transport data sharing…(More)”.

Expanding Mobility: The Power of Linked Administrative Data and Integrated Data Systems

Curated on Posted on by Stefaan Verhulst

Brief by Della Jenkins and Emily Berkowitz: “This brief describes how linking administrative data can expand traditional measures of mobility for research and action, provides examples of the types of economic mobility research questions that are only answerable using linked administrative data, and describes how analysis can be deepened using spatial and multi-generational perspectives. In addition, we discuss how the field of economic mobility research benefits when state and local governments are resourced to build systems that enable routine reuse of linked data. Finally, we end with a summary of the opportunities that exist to build on data capacity already developed by state and local governments across the US to better understand the policies that support pathways out of poverty. Now more than ever, governments, research partners, and stakeholders can come together to make use of the data already collected by social service programs to generate evidence-based approaches to expanding mobility…(More)”

Privacy Principles for Mobility Data

Curated on Posted on by Stefaan Verhulst

About: “The Principles are a set of values and priorities intended to guide the mobility ecosystem in the responsible use of data and the protection of individual privacy. They are intended to serve as a guiding “North Star” to assess technical and policy decisions that have implications for privacy when handling mobility data. The principles are designed to apply to all sectors, including public, private, research and non-profit….

Increasingly, organizations in the public, private and nonprofit sectors are faced with decisions that have data privacy implications. For organizations utilizing mobility data, these principles provide a baseline framework to both identify and address these situations. Individuals whose data is being collected, utilized and shared must be afforded proper protections and opportunities for agency in how information about them is used and handled. These principles offer guidance for how to engage in this process.

Human movement generates data in many ways: directly through the usage of GPS-enabled mobility services or devices, indirectly through phones or other devices with geolocation and even through cameras and other sensors that observe the public realm. While these principles were written with shared mobility services in mind, many of them will be applicable in other contexts in which data arising out of individual movement is collected and analyzed. We encourage any organization working with this type of data to adapt and apply these principles in their specific context.

While not all mobility data may present a privacy risk to individuals, all stakeholders managing mobility data should treat it as personal information that is sensitive, unless it can be demonstrated that it doesn’t present a privacy risk to individuals.

These principles were developed through a collaboration organized by the New Urban Mobility (NUMO) alliance, the North American Bikeshare & Scootershare Association (NABSA) and the Open Mobility Foundation (OMF) in 2020. These groups convened a diverse set of stakeholders representing cities, mobility service providers, technology companies, privacy advocates and academia. Over the course of many months, this group heard from privacy experts, discussed key topics related to data privacy and identified core ideas and common themes to serve as a basis for these Principles….(More)”.

Feedback Loops in Open Data Ecosystems

Curated on Posted on by Stefaan Verhulst

Paper by Daniel Rudmark and Magnus Andersson: “Public agencies are increasingly publishing open data to increase transparency and fuel data-driven innovation. For these organizations, maintaining sufficient data quality is key to continuous re-use but also heavily dependent on feedback loops being initiated between data publishers and users. This paper reports from a longitudinal engagement with Scandinavian transportation agencies, where such feedback loops have been successfully established. Based on these experiences, we propose four distinct types of data feedback loops in which both data publishers and re-users play critical roles…(More)”.

Big data for big issues: Revealing travel patterns of low-income population based on smart card data mining in a global south unequal city

Curated on Posted on by Stefaan Verhulst

Paper by Caio Pieroni, Mariana Giannotti, Bianca B.Alves, and Renato Arbex: “Smart card data (SCD) allow analyzing mobility at a fine level of detail, despite the remaining challenges such as identifying trip purpose. The use of the SCD may improve the understanding of transit users’ travel patterns from precarious settlements areas, where the residents have historically limited access to opportunities and are usually underrepresented in surveys. In this paper, we explore smart card data mining to analyze the temporal and spatial patterns of the urban transit movements from residents of precarious settlements areas in São Paulo, Brazil, and compare the similarities and differences in travel behavior with middle/high-income-class residents. One of our concerns is to identify low-paid employment travel patterns from the low-income-class residents, that are also underrepresented in transportation planning modeling due to the lack of data. We employ the k-means clustering algorithm for the analysis, and the DBSCAN algorithm is used to infer passengers’ residence locations. The results reveal that most of the low-income residents of precarious settlements begin their first trip before, between 5 and 7 AM, while the better-off group begins from 7 to 9 AM. At least two clusters formed by commuters from precarious settlement areas suggest an association of these residents with low-paid employment, with their activities placed in medium / high-income residential areas. So, the empirical evidence revealed in this paper highlights smart card data potential to unfold low-paid employment spatial and temporal patterns….(More)”.

The Mobility Data Sharing Assessment

Curated on Posted on by Stefaan Verhulst

New Tool from the Mobility Data Collaborative (MDC): “…released a set of resources to support transparent and accountable decision making about how and when to share mobility data between organizations. …The Mobility Data Sharing Assessment (MDSA) is a practical and customizable assessment that provides operational guidance to support an organization’s existing processes when sharing or receiving mobility data. It consists of a collection of resources:

  • 1. A Tool that provides a practical, customizable and open-source assessment for organizations to conduct a self-assessment.
  • 2. An Operator’s Manual that provides detailed instructions, guidance and additional resources to assist organizations as they complete the tool.
  • 3. An Infographic that provides a visual overview of the MDSA process.

“We were excited to work with the MDC to create a practical set of resources to support mobility data sharing between organizations,” said Chelsey Colbert, policy counsel at FPF. “Through collaboration, we designed version one of a technology-neutral tool, which is consistent and interoperable with leading industry frameworks. The MDSA was designed to be a flexible and scalable approach that enables mobility data sharing initiatives by encouraging organizations of all sizes to assess the legal, privacy, and ethical considerations.”

New mobility options, such as shared cars and e-scooters, have rapidly emerged in cities over the past decade. Data generated by these mobility services offers an exciting opportunity to provide valuable and timely insight to effectively develop transportation policy and infrastructure. As the world becomes more data-driven, tools like the MDSA help remove barriers to safe data sharing without compromising consumer trust….(More)”.

Real-Time Incident Data Could Change Road Safety Forever

Curated on Posted on by Stefaan Verhulst

Skip Descant at GovTech: “Data collected from connected vehicles can offer near real-time insights into highway safety problem areas, identifying near-misses, troublesome intersections and other roadway dangers.

New research from Michigan State University and Ford Mobility, which tracked driving incidents on Ford vehicles outfitted with connected vehicle technology, points to a future of greatly expanded understanding of roadway events, far beyond simply reading crash data.

“Connected vehicle data allows us to know what’s happening now. And that’s a huge thing. And I think that’s where a lot of the potential is, to allow us to actively monitor the roadways,” said Meredith Nelson, connected and automated vehicles analyst with the Michigan Department of Transportation.

The research looked at data collected from Ford vehicles in the Detroit metro region equipped with connected vehicle technology from January 2020 to June 2020, drawing on data collected by Ford’s Safety Insights platform in partnership with StreetLight Data. The data offers insights into near-miss events like hard braking, hard acceleration and hard corners. In 2020 alone, Ford has measured more than a half-billion events from tens of millions of trips.

Traditionally, researchers relied on police-reported crash data, which had its drawbacks, in part, because of the delay in reporting, said Peter Savolainen, an engineering professor in the Department of Civil and Environmental Engineering at Michigan State University, with a research focus looking at road user behavior….(More)”.

Street Experiments

Curated on Posted on by Stefaan Verhulst

About: “City streets are increasingly becoming spaces for experimentation, for testing “in the wild” a seemingly unstoppable flow of “disruptive” mobility innovations such as mobility platforms for shared mobility and ride/hailing, electric and autonomous vehicles, micro-mobility solutions, etc. But also, and perhaps more radically, for recovering the primary function of city streets as public spaces, not just traffic channels.

City street experiments are:

​“intentional, temporary changes of the street use, regulation and/or form, aimed at exploring systemic change in urban mobility”

​They offer a prefiguration of what a radically different arrangement of the city´s mobility system and public space could look like and allow moving towards that vision by means of “learning by doing”.

The S.E.T. platform offers a collection of Resources for implementing and supporting street experiments. As well as a special section of COVID-19 devoted to the best practices of street experiments that offered solutions and strategies for cities to respond to the current pandemic and a SET Guidelines Kit that provides insights and considerations on creating impactful street experiments with long-term effects….(More)”.

America’s ‘Smart City’ Didn’t Get Much Smarter

Curated on Posted on by Stefaan Verhulst

Article by Aarian Marshall: “In 2016, Columbus, Ohio, beat out 77 other small and midsize US cities for a pot of $50 million that was meant to reshape its future. The Department of Transportation’s Smart City Challenge was the first competition of its kind, conceived as a down payment to jump-start one city’s adaptation to the new technologies that were suddenly everywhere. Ride-hail companies like Uber and Lyft were ascendant, car-sharing companies like Car2Go were raising their national profile, and autonomous vehicles seemed to be right around the corner.

“Our proposed approach is revolutionary,” the city wrote in its winning grant proposal, which pledged to focus on projects to help the city’s most underserved neighborhoods. It laid out plans to experiment with Wi-Fi-enabled kiosks to help residents plan trips, apps to pay bus and ride-hail fares and find parking spots, autonomous shuttles, and sensor-connected trucks.

Five years later, the Smart City Challenge is over, but the revolution never arrived. According to the project’s final report, issued this month by the city’s Smart Columbus Program, the pandemic hit just as some projects were getting off the ground. Six kiosks placed around the city were used to plan just eight trips between July 2020 and March 2021. The company EasyMile launched autonomous shuttles in February 2020, carrying passengers at an average speed of 4 miles per hour. Fifteen days later, a sudden brake sent a rider to the hospital, pausing service. The truck project was canceled. Only 1,100 people downloaded an app, called Pivot, to plan and reserve trips on ride-hail vehicles, shared bikes and scooters, and public transit.

The discrepancy between the promise of whiz-bang technology and the reality in Columbus points to a shift away from tech as a silver bullet, and a newer wariness of the troubles that web-based applications can bring to IRL streets. The “smart city” was a hard-to-pin-down marketing term associated with urban optimism. Today, as citizens think more carefully about tech-enabled surveillance, the concept of a sensor in every home doesn’t look as shiny as it once did….(More)”.

Sustainable mobility: Policy making for data sharing

Curated on Posted on by Stefaan Verhulst

WBCSD report: “The demand for mobility will grow significantly in the coming years, but our urban transportation systems are at their limits. Increasing digitalization and data sharing in urban mobility can help governments and businesses to respond to this challenge and accelerate the transition toward sustainability. There is an urgent need for greater policy coherence in data-sharing ecosystems and governments need to adopt a more collaborative approach toward policy making.

With well-orchestrated policies, data sharing can result in shared value for public and private sectors and support the achievement of sustainability goals. Data-sharing policies should also aim to minimize risks around privacy and cybersecurity, minimize mobility biases rooted in race, gender and age, prevent the creation of runaway data monopolies and bridge the widening data divide.

This report outlines a global policy framework and practical guidance for policy making on data sharing. The report offers multiple case studies from across the globe to document emerging good practices and policy suggestions, recognizing the hyperlocal context of mobility needs and policies, the nascent state of the data-sharing market and limited evidence from regulatory practices….(More)”