Your Driving App Is Leading You Astray


Article by Julia Angwin: “…If you use a navigation app, you probably have felt helpless anger when your stupid phone endangers your life, and the lives of all the drivers around you, to potentially shave a minute or two from your drive time. Or maybe it’s stuck you on an ugly freeway when a glorious, ocean-hugging alternative lies a few miles away. Or maybe it’s trapped you on a route with no four-way stops, ignoring a less stressful solution that doesn’t leave you worried about a car barreling out of nowhere.

For all the discussion of the many extraordinary ways algorithms have changed our society and our lives, one of the most impactful, and most infuriating, often escapes notice. Dominated by a couple of enormously powerful tech monopolists that have better things to worry about, our leading online mapping systems from Google and Apple are not nearly as good as they could be.

You may have heard the extreme stories, such as when navigation apps like Waze and Google Maps apparently steered drivers into lakes and onto impassable dirt roads, or when jurisdictions beg Waze to stop dumping traffic onto their residential streets. But the reality is these apps affect us, our roads and our communities every minute of the day. Primarily programmed to find the fastest route, they endanger and infuriate us on a remarkably regular basis….

The best hope for competition relies on the success of OpenStreetMap. Its data underpins most maps other than Google, including AmazonFacebook and Apple, but it is so under-resourced that it only recently hired paid systems administrators to ensure its back-end machines kept running….In addition, we can promote competition by using the few available alternatives. To navigate cities with public transit, try apps such as Citymapper that offer bike, transit and walking directions. Or use the privacy-focused Organic Maps…(More)”.

Exploring Visitor Density Trends in Rest Areas Through Google Maps Data and Data Mining


Paper by Marita Prasetyani, R. Rizal Isnanto and Catur Edi Widodo: “Rest areas play a vital role in ensuring the safety and comfort of travelers. This study examines the visitor density at the toll and non-toll rest areas using data mining techniques applied to Google Maps Places data. By utilizing extensive information from Google Maps, the research aims to uncover patterns and trends in visitor behavior and pinpoint peak usage times. The findings can guide improved planning and management of rest areas, thereby enhancing the overall travel experience for road users and further research to determine the location of the new rest area.Understanding patterns or trends in visitor density at rest areas involves analyzing the time of day, location, and other factors influencing the density level. Understanding these trends can provide essential insights for rest area management, infrastructure planning, and the establishment of new rest areas.Data from Google Maps provides an invaluable source of real-time and historical information, enabling accurate and in-depth analysis of visitor behavior.Data mining helps identify relationships not immediately apparent in the data, providing a deeper understanding and supporting data-driven decision-making…(More)”.

Artificial Intelligence Opportunities for State and Local Departments Of Transportation


Report by the National Academies of Sciences, Engineering, and Medicine: “Artificial intelligence (AI) has revolutionized various areas in departments of transportation (DOTs), such as traffic management and optimization. Through predictive analytics and real-time data processing, AI systems show promise in alleviating congestion, reducing travel times, and enhancing overall safety by alerting drivers to potential hazards. AI-driven simulations are also used for testing and improving transportation systems, saving time and resources that would otherwise be needed for physical tests…(More)”.

Riders in the smog


Article by Zuha Siddiqui, Samriddhi Sakuna and Faisal Mahmud: “…To better understand air quality exposure among gig workers in South Asia, Rest of World gave three gig workers — one each in Lahore, New Delhi, and Dhaka — air quality monitors to wear throughout a regular shift in January. The Atmotube Pro monitors continually tracked their exposure to carcinogenic pollutants — specifically PM1, PM2.5, and PM10 (different sizes of particulate matter), and volatile organic compounds such as benzene and formaldehyde.

The data revealed that all three workers were routinely exposed to hazardous levels of pollutants. For PM2.5, referring to particulates that are 2.5 micrometers in diameter or less — which have been linked to health risks including heart attacks and strokes — all riders were consistently logging exposure levels more than 10 times the World Health Organization’s recommended daily average of 15 micrograms per cubic meter. Manu Sharma, in New Delhi, recorded the highest PM2.5 level of the three riders, hitting 468.3 micrograms per cubic meter around 6 p.m. Lahore was a close second, with Iqbal recording 464.2 micrograms per cubic meter around the same time.

Alongside tracking specific pollutants, the Atmotube Pro gives an overall real-time air quality score (AQS) from 0–100, with zero being the most severely polluted, and 100 being the cleanest. According to Atmo, the company that makes the Atmotube monitors, a reading of 0–20 should be considered a health alert, under which conditions “everyone should avoid all outdoor exertion.” But the three gig workers found their monitors consistently displayed the lowest possible score…(More)”.

No app, no entry: How the digital world is failing the non tech-savvy


Article by Andrew Anthony: “Whatever the word is for the opposite of heartwarming, it certainly applies to the story of Ruth and Peter Jaffe. The elderly couple from Ealing, west London, made headlines last week after being charged £110 by Ryanair for printing out their tickets at Stansted airport.

Even allowing for the exorbitant cost of inkjet printer ink, 55 quid for each sheet of paper is a shockingly creative example of punitive pricing.

The Jaffes, aged 79 and 80, said they had become confused on the Ryanair website and accidentally printed out their return tickets instead of their outbound ones to Bergerac. It was the kind of error anyone could make, although octogenarians, many of whom struggle with the tech demands of digitalisation, are far more likely to make it.

But as the company explained in a characteristically charmless justification of the charge: “We regret that these passengers ignored their email reminder and failed to check-in online.”…

The shiny, bright future of full computerisation looks very much like a dystopia to someone who either doesn’t understand it or have the means to access it. And almost by definition, the people who can’t access the digitalised world are seldom visible, because absence is not easy to see. What is apparent is that improved efficiency doesn’t necessarily lead to greater wellbeing.

From a technological and economic perspective, the case for removing railway station ticket offices is hard to refute. A public consultation process is under way by train operators who present the proposed closures as means of bringing “station staff closer to customers”.

The RMT union, by contrast, believes it’s a means of bringing the staff closer to unemployment and has mounted a campaign heralding the good work done by ticket offices across the network. Whatever the truth, human interaction is in danger of being undervalued in the digital landscape…(More)”.

Primer on Data Sharing


Primer by John Ure: “…encapsulates insights gleaned from the Inter-Modal Transport Data Sharing Programme, a collaborative effort known as Data Trust 1.0 (DT1), conducted in Hong Kong between 2020 and 2021. This initiative was a pioneering project that explored the feasibility of sharing operational data between public transport entities through a Trusted Third Party. The objective was to overcome traditional data silos and promote evidence-based public transport planning.

DT1, led by the ‘HK Team’ in conjunction with Dr. Jiangping Zhou and colleagues from the University of Hong Kong, successfully demonstrated that data sharing between public transport companies, both privately-owned and government-owned, was viable. Operational data, anonymised and encrypted, were shared with a Trusted Third Party and aggregated for analysis, supported by a Transport Data Analytics Service Provider. The data was used solely for analysis purposes, and confidentiality was maintained throughout.

The establishment of the Data Trust was underpinned by the creation of a comprehensive Data Sharing Framework (DSF). This framework, developed collaboratively, laid the groundwork for future data sharing endeavours. The DSF has been shared internationally, fostering the exchange of knowledge and best practices across diverse organisations and agencies. The Guide serves as a repository of lessons learned, accessible studies, and references, aimed at facilitating a comprehensive understanding of data sharing methodologies.

The central aim of the Guide is twofold: to promote self-learning and to offer clarity on intricate approaches related to data sharing. Its intention is to encourage researchers, governmental bodies, commercial enterprises, and civil society entities, including NGOs, to actively engage in data sharing endeavours. By combining data sets, these stakeholders can glean enhanced insights and contribute to the common good…(More)”.

Unleashing the power of data for electric vehicles and charging infrastructure


Report by Thomas Deloison: “As the world moves toward widespread electric vehicle (EV) adoption, a key challenge lies ahead: deploying charging infrastructure rapidly and effectively. Solving this challenge will be essential to decarbonize transport, which has a higher reliance on fossil fuels than any other sector and accounts for a fifth of global carbon emissions. However, the companies and governments investing in charging infrastructure face significant hurdles, including high initial capital costs and difficulties related to infrastructure planning, permitting, grid connections and grid capacity development.

Data has the power to facilitate these processes: increased predictability and optimized planning and infrastructure management go a long way in easing investments and accelerating deployment. Last year, members of the World Business Council for Sustainable Development (WBCSD) demonstrated that digital solutions based on data sharing could reduce carbon emissions from charging by 15% and unlock crucial grid capacity and capital efficiency gains.

Exceptional advances in data, analytics and connectivity are making digital solutions a potent tool to plan and manage transport, energy and infrastructure. Thanks to the deployment of sensors and the rise of connectivity,  businesses are collecting information faster than ever before, allowing for data flows between physical assets. Charging infrastructure operators, automotive companies, fleet operators, energy providers, building managers and governments collect insights on all aspects of electric vehicle charging infrastructure (EVCI), from planning and design to charging experiences at the station.

The real value of data lies in its aggregationThis will require breaking down siloes across industries and enabling digital collaboration. A digital action framework released by WBCSD, in collaboration with Arcadis, Fujitsu and other member companies and partners, introduces a set of recommendations for companies and governments to realize the full potential of digital solutions and accelerate EVCI deployments:

  • Map proprietary data, knowledge gaps and digital capacity across the value chain to identify possible synergies. The highest value potential from digital solutions will lie at the nexus of infrastructure, consumer behavior insights, grid capacity and transport policy. For example, to ensure the deployment of charging stations where they will be most needed and at the right capacity level, it is crucial to plan investments within energy grid capacity, spatial constraints and local projected demand for EVs.
  • Develop internal data collection and storage capacity with due consideration for existing structures for data sharing. A variety of schemes allow actors to engage in data sharing or monetization. Yet, their use is limited by mismatched use of data standards and specification and process uncertainty. Companies must build a strong understanding of these structures internally by providing internal training and guidance, and invest in sound data collection, storage and analysis capacity.
  • Foster a policy environment that supports digital collaboration across sectors and industries. Digital policies must provide incentives and due diligence frameworks to guide data exchanges across industries and support the adoption of common standards and protocols. For instance, it will be crucial to integrate linkages with energy systems and infrastructure beyond roads in the rollout of the European mobility data space…(More)”.

Destination? Care Blocks!


Blog by Natalia González Alarcón, Hannah Chafetz, Diana Rodríguez Franco, Uma Kalkar, Bapu Vaitla, & Stefaan G. Verhulst: “Time poverty” caused by unpaid care work overload, such as washing, cleaning, cooking, and caring for their care-receivers is a structural consequence of gender inequality. In the City of Bogotá, 1.2 million women — 30% of their total women’s population — carry out unpaid care work full-time. If such work was compensated, it would represent 13% of Bogotá’s GDP and 20% of the country’s GDP. Moreover, the care burden falls disproportionately on women’s shoulder and prevents them from furthering their education, achieving financial autonomy, participating in their community, and tending to their personal wellbeing.

To address the care burden and its spillover consequences on women’s economic autonomy, well-being and political participation, in October 2020, Bogotá Mayor Claudia López launched the Care Block Initiative. Care Blocks, or Manzanas del cuidado, are centralized areas for women’s economic, social, medical, educational, and personal well-being and advancement. They provide services simultaneously for caregivers and care-receivers.

As the program expands from 19 existing Care Blocks to 45 Care Blocks by the end of 2035, decision-makers face another issue: mobility is a critical and often limiting factor for women when accessing Care Blocks in Bogotá.

On May 19th, 2023, The GovLabData2X, and the Secretariat for Women’s Affairs, in the City Government of Bogotá co-hosted a studio that aimed to scope a purposeful and gender-conscious data collaborative that addresses mobility-related issues affecting the access of Care Blocks in Bogotá. Convening experts across the gender, mobility, policy, and data ecosystems, the studio focused on (1) prioritizing the critical questions as it relates to mobility and access to Care Blocks and (2) identifying the data sources and actors that could be tapped into to set up a new data collaborative…(More)”.

Understanding the relationship between informal public transport and economic vulnerability in Dar es Salaam


WhereIsMyTransport Case Study: “In most African cities, formal public transport—such as government-run or funded bus and rail networks—has limited coverage and fails to meet overall mobility demand. As African cities grow and densify, planners are questioning whether these networks can serve the economically vulnerable communities who benefit most from public transport access to opportunities and services.

In the absence of formal public transport or private vehicles, low-income commuters have long relied on informal public transport—think tro tros in Accra, boda bodas in Kampala, danfos in Lagos—to meet their mobility needs. Yet there is little reliable data on the relationship between informal public transport and economic vulnerability in and around Africa’s cities, making it challenging to understand:

  • Which communities are the most vulnerable?
  • What opportunities and services do people typically attempt to access?
  • What routes do informal public transport operators follow?
  • What are the occupation and gender-related impacts?

Addressing these questions benefits from combining data assets. For example, pairing data on informal public transport coverage with data on the socioeconomic characteristics of the communities that rely on this type of transport…(More)”.

Data for Environmentally Sustainable and Inclusive Urban Mobility


Report by Anusha Chitturi and Robert Puentes: “Data on passenger movements, vehicle fleets, fare payments, and transportation infrastructure has immense potential to inform cities to better plan, regulate, and enforce their urban mobility systems. This report specifically examines the opportunities that exist for U.S. cities to use mobility data – made available through adoption of new mobility services and data-based technologies – to improve transportation’s environmental sustainability, accessibility, and equity. Cities are advancing transportation sustainability in several ways, including making trips more efficient, minimizing the use of single-occupancy vehicles, prioritizing sustainable modes of transport, and enabling a transition to zero and low-emission fuels. They are improving accessibility and equity by planning for and offering a range of transportation services that serve all people, irrespective of their physical abilities, economic power, and geographic location.
Data sharing is an important instrument for furthering these mobility outcomes. Ridership data from ride-hailing companies, for example, can inform cities about whether they are replacing sustainable transport trips, resulting in an increase in congestion and emissions; such data can further be used for designing targeted emission-reduction programs such as a congestion fee program, or for planning high-quality sustainable transport services to reduce car trips. Similarly, mobility data can be used to plan on-demand services in certain transit-poor neighborhoods, where fixed transit services don’t make financial sense due to low urban densities. Sharing mobility data, however, often comes with certain risks,..(More)”.