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Project

#378 Developing data collection systems to support community-driven integrated mobility services


Principal Investigator
Patrick Carrington
Status
Active
Start Date
July 1, 2021
End Date
June 30, 2022
Research Type
Applied
Grant Type
Research
Grant Program
FAST Act - Mobility National (2016 - 2022)
Grant Cycle
2021 Mobility UTC
Visibility
Public

Abstract

We propose to build data collection systems to support the community-driven design and deployment of innovative, accessible, and integrated mobility services. With our partner, the City of Pittsburgh’s Department of Mobility and Infrastructure, we will build systems to collect community data at mobility hubs and data from individuals to understand mobility patterns throughout the city. This data will help inform planning, testing, and dynamic re-design of mobility services and policy.    
Description
[For optimal viewing, please see the pdf version of the Proposal attached as a Supplemental Information Document.]

Our project objective is to develop and test methods for municipalities to do community-driven design and deployment of innovative, accessible, and integrated mobility services. Today, cities are rethinking their portfolio of mobility services so that they can create systems that are more accessible, sustainable, and equitable. These include providing a variety of options such as public transit, rideshare services, electric scooter- and bike-share programs, ground-based delivery robots, and eventually autonomous vehicles. While private companies often deploy these technologies, regional planners are tasked with considering how to negotiate plans for technology rollouts, how to collect and manage feedback from the community, and ultimately how to develop policy that integrates new mobility services into people’s everyday lives. Successful deployments will balance innovation with community safety, benefit, and access. Effectively, city mobility teams are doing service design [4] for multi-modality community transportation. Moreover, these new deployments should be driven by data from the community. How do people get around now? Where are people challenged with current service offerings? What are the current limitations with public transport? How do pilot deployments of new mobility service offerings actually impact people’s mobility? Thus, there is an opportunity to innovate on best practices from service design and data-driven design to aid in the design of a city’s transportation infrastructure, with the goal of ensuring equitable access to services for all.

We see effective ways for doing data-driven mobility service design as a new core competency for municipalities. Looking at other cities, we can see how rapid rollouts with little design forethought can lead to unforeseen challenges, various stakeholders claiming little responsibility, and animosity from the community. For example, disgruntled residents of San Francisco, Oakland, Los Angeles, and Portland began destroying the Lime and Bird e-scooters that occupied their sidewalks in 2018-2019 [2,7,8,9]. Scooters strewn about the sidewalk blocked paths and riders often disregarded laws requiring they travel in the street. While scooters were a nuisance for able-bodied pedestrians, they presented a significant impediment and safety hazard for those with disabilities [10,14]. In order to thoughtfully incorporate new services into the city, regional planners need methods and processes for collecting feedback and data from the community to help them dynamically re-design and successfully rollout new services [1,15]. 

Responding to this need, we will build systems to collect community data at transit hubs and from individual community members who the city is particularly interested in learning from such as wheelchair users or those from lower socio-economic neighborhoods. We will then analyze this data to inform planning, testing, and dynamically re-designing accessible, safe, and equitable mobility services that better meet residents’ needs. Specifically, we will work with the City of Pittsburgh’s Department of Mobility and Infrastructure (DOMI) in developing a playbook for co-designing new data-driven mobility service deployments with and for city residents. We will work with DOMI to develop a generalized data collection system that can support them in collecting data and community feedback on new mobility services. DOMI has identified two areas where they would like data and community feedback:

1) Understanding how incorporating services such as e-scooters and mobility hubs with public transit and rideshare systems influence people’s travel patterns.
2) Exploring how new transit pass packages integrating multiple services alter and influence people’s transit usage and movement patterns. 

Pittsburgh is a unique testbed in that it does not currently have a fully integrated mobility service system, giving us an opportunity to test new ideas for community-centered mobility service deployment. It also has hilly topology and discrete neighborhoods, some with poor access to services and public transportation. Furthermore, DOMI is working to position Pittsburgh as a model for how to re-design mobility services based on community-generated data. We will help the city develop an integrated mobility service design playbook through data collection systems and analysis tools for helping turn data into actionable plans for policy.

Ongoing and Preliminary Work
Community meetings: Since August 2020, our team has facilitated a series of online meetings with members of the community to better understand concerns, hopes, and needs with regard to accessible autonomous vehicle design. We are building working relationships with people who have a disability, disability advocates, and transportation advocates. We plan to use our current community meetings as a model for conducting meetings throughout this project. We will build on the success of this preliminary work to conduct (online) community meetings in cooperation with Pittsburgh residents, our city partners, and members of the Pittsburgh Mobility Collective. 

Casebook of related deployments: Alongside community meetings, we are developing a comparative casebook of mobility service deployments from across different cities. Drawing on media materials (e.g., news coverage, industry trade press), municipal policy, and existing reports from advocacy organizations and think tanks, we will develop a descriptive analysis of existing deployments and how they have been interpreted and received by the public. This casebook will provide a valuable baseline in defining what has gone well in terms of networked mobility and identifying challenges that have arisen in existing deployments. The casebook will serve as an open resource hosted on our project website, allowing other researchers, municipalities, and industry representatives to draw from it and extend its contents over time.

Research Plan 
We will develop a set of data collection systems to capture feedback from the community, usage patterns of mobility services, and individualized mobility data from specific populations. We will conduct a pilot deployment with the City of Pittsburgh to collect and analyze community data to help the city inform new mobility service policy. Our research project will include the following data collection activities:

1) Designing and building feedback stations around the city: There are current challenges to collecting in-person feedback from community members due to current social distancing measures. Furthermore, traditional methods of gathering community feedback (phone, email) are limited because they often capture general sentiment rather than specific experiences that happen day to day with mobility services. Given these challenges, we believe there is a need for distributed, automated, and self-managed community data collection. To address this need, we will design and build physical feedback stations that can be located around town and will allow people to capture their experiences and feedback via video and audio. The feedback collection will be facilitated by an automated question asking system and will use natural language understanding to analyze and preprocess qualitative data for use by the city. This will build upon PI Matelaro’s research on real-world feedback systems that leverage digital agents for capturing observations and thoughts on user experience [12]. We will also leverage prototype systems that have been designed in PI Forlizzi’s research group. These stations will be designed following guidelines on accessible public kiosks [11] to ensure that all members of the community can readily participate. We plan to put these stations near e-scooter deployment locations so that we can tightly link people’s experience on the ground with their comments, helping us to better pinpoint and respond to challenges as they occur. Furthermore, the City is also looking to develop plans with the Pittsburgh Mobility Collective for mobility hubs, where various mobility services are brought together in central locations. We will use our feedback stations to begin scouting locations for the mobility hubs, giving us a lightweight way to test what locations may be best suited for a future hub deployment. 

2) Designing and building personal physical sensing systems: To further augment our community-centered data, we will also build physical sensing systems that can be used by individual community members to better capture specific kinds of user experience data. For example, we will build upon PI Carrington’s SpokeSense system [3] to understand how wheelchair users navigate the city, how they manage challenges, and how specific changes to a mobility service deployment can alter their experiences for the better. The data collected from these systems can be used to better guide how a deployment is conducted by engaging individuals through their complete journeys. We will also use these systems as a way to explore how to conduct research that balances understanding the needs of individual community members while respecting their privacy and agency (see Ethical Considerations). Toward this goal we will implement a mobile application which will integrate data from both smartphone-based and peripheral sensors. The peripheral sensors will include a custom sensor to capture motion data from individual mobility devices such as wheelchairs and a more generalized tag for devices such as e-scooters. Both types of devices will capture motion and vibration data as users travel through the city. This data can also be used to assess the conditions of roads and pathways experienced by users across multiple transportation modalities.

3) Bridging from data and deployment to policy design: As we collect and analyze data from across our empirical engagements, we will simultaneously develop methods and tools for city planners to incorporate these findings into their policy design and regulatory decision making. We will employ methods from service design such as customer journey maps and value flow models to map the legislative and technological landscapes with our partners in the Department of Mobility and Infrastructure, we will draw out and distill techniques for charting preferred futures and critically evaluating design ideas and deployments. Furthermore, building on the City of Pittsburgh’s newly released interactive online portal for community participation, Engage PGH, we will include methods for continued, asynchronous engagement with the community so that these mobility services can co-evolve over time to continually meet residents' needs. This work builds upon PI Fox’s research bridging tech design, data, policy, and activism through participatory design methods [5,6].

Ethical Considerations
We recognize that this work comes with a set of important ethical considerations — namely, the collection of data around mobility usage among residents and visitors to the city. We will work closely with our partners in the Department of Mobility and Infrastructure, city residents (through our ongoing community meetings), and legal advocates, to ensure that residents’ and visitors’ privacy and anonymity are preserved throughout the research process, as well as to convey individuals’ privacy rights. We will also evolve our procedures over the course of the project to ensure that the data collected is handled with the utmost care. At present, we’re considering a data trust model or a value exchange, which both focus on developing responsible data sharing standards at the municipal level and providing individuals with a share in the benefits derived from the data gathered about them [13,16]. 

Research Team
Success in this project requires a tightly integrated interdisciplinary team with expertise in service design, HCI, context-aware technologies, and accessible mobility. Our team builds atop existing collaborations, and we have designed our research to take advantage of individual expertise while integrating knowledge across disciplines. PI Carrington will be responsible for managing the design and building of sensing systems to support journey mapping and analysis. PI Fox will be responsible for overseeing the community engagements and policy design activities, as well as qualitative analysis and drawing out insights across each of the field sites. PI Martelaro and Forlizzi will co-manage the design and development of the feedback stations and data analysis. Ph.D. student Li will manage the overall project operations, communications, data collection, and development schedules.

References
1.	Cynthia Bennet, Emily Ackerman, Patrick Carrington, and Sarah Fox. in submission. The Crowded Sidewalk: The (In)Accessibility of Micromobility. Proceedings of the ACM on Human-Computer Interaction (CSCW).
2.	Jack Blocker. 2018. There’s an Instagram Devoted to Destroying Rideshare Scooters. Vice. Retrieved September 27, 2020 from https://www.vice.com/en_us/article/vbj7xb/theres-an-entire-instagram-account-devoted-to-destroying-rideshare-scooters.
3.	Patrick Carrington, Gierad Laput, and Jeffrey P. Bigham. 2020. SpokeSense: developing a real-time sensing platform for wheelchair sports. ACM SIGACCESS Accessibility and Computing 124: 2:1.
4.	Jodi Forlizzi and John Zimmerman. 2013. Promoting service design as a core practice in interaction design. Proc. of IASDR13.
5.	Sarah E. Fox, Kiley Sobel, and Daniela K. Rosner. 2019. Managerial Visions: Stories of Upgrading and Maintaining the Public Restroom with IoT. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, 1–15.
6.	Sarah Fox, Catherine Lim, Tad Hirsch, and Daniela K. Rosner. 2020. Accounting for Design Activism: On the Positionality and Politics of Designerly Intervention. Design Issues 36, 1: 5–18.
7.	April Glaser. 2018. People Keep Throwing Electric Scooters Into Lakes and Rivers. Slate Magazine. Retrieved September 27, 2020 from https://slate.com/technology/2018/12/electric-scooter-bird-lime-lakes-rivers-environment-vandalism.html.
8.	Corey D. Harper, Chris T. Hendrickson, Sonia Mangones, and Constantine Samaras. 2016. Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions. Transportation Research Part C: Emerging Technologies 72: 1–9.
9.	Vivian Ho. 2018. Stolen, burned, tossed in the lake: e-scooters face vandals’ wrath. The Guardian. Retrieved September 27, 2020 from https://www.theguardian.com/us-news/2018/dec/28/scooters-california-oakland-los-angeles-bird-lime.
10.	Dara Kerr. Disability rights group sues scooter companies over clogged sidewalks. CNET. Retrieved September 27, 2020 from https://www.cnet.com/news/disability-rights-group-sues-scooter-companies-bird-and-lime-over-clogged-sidewalks/.
11.	Jonathan Lazar, J. Bern Jordan, and Gregg Vanderheiden. 2019. Toward unified guidelines for kiosk accessibility. Interactions 26, 4: 74–77.
12.	Nikolas Martelaro and Wendy Ju. 2018. The Needfinding Machine. In The Social Internet-of-Things. Springer.
13.	Stuart Mills. 2019. Who Owns the Future? Data Trusts, Data Commons, and the Future of Data Ownership. Social Science Research Network, Rochester, NY.
14.	Morris. 2018. Scooters Blocking Wheelchair Access to Sidewalks. Wheelchair Travel. Retrieved September 27, 2020 from https://wheelchairtravel.org/electric-scooters-blocking-wheelchair-access-sidewalks/.
15.	Meg Young, Lassana Magassa, and Batya Friedman. 2019. Toward inclusive tech policy design: a method for underrepresented voices to strengthen tech policy documents. Ethics and Information Technology 21, 2: 89–103.
16.	Meg Young, Luke Rodriguez, Emily Keller, et al. 2019. Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing. Proceedings of the Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 191–200.

    
Timeline
[For optimal viewing, please see the pdf version of the Proposal attached as a Supplemental Information Document.]

Our 12-month timeline is shown below. We will conduct community meetings through the course of the project, providing the public with consistent engagement on our progress. We will develop our data collection systems over the summer semester. We will then deploy our system in the Fall and Winter while co-developing our analysis tools. During the Spring we will focus on analyzing our data with our community partners and developing methods for converting data into policy recommendations. We will complete our project by co-authoring a data-driven mobility service design playbook with DOMI. This playbook will be shared broadly with municipalities across the US and the world.
    
Deployment Plan
[For optimal viewing, please see the pdf version of the Proposal attached as a Supplemental Information Document.]

The proposed research holds great potential to bring data-driven decision making methods and social benefits to regions, municipalities, cities, and local communities throughout the Commonwealth. Our plan is to conduct our field-based data collection service design research at deployment locations around the city and with groups of specific individuals. These locations and individuals will be decided in collaboration with our partners in the Department of Mobility and Infrastructure. We will deploy our feedback stations at locations where e-scooter are being deployed. For example, our partners have identified Hazelwood as a possible location for deploying a suite of new mobility services. We will also deploy our individual physical and mobile-phone based sensing systems with specific individuals that DOMI is interested in. Specifically, we are interested in exploring the experience of people with disabilities so that we can manage and mitigate known harms of micro-mobility deployments while also seeing how new micro-mobility can improve their travel around the city. 

In addition to the e-scooter deployment locations, we will also work with our partners to deploy feedback stations at candidate locations for mobility hubs. These deployments will also incorporate our physical and mobile-phone based sensing systems to help us understand the needs of specific community members. For example, the recent challenges of COVID-19 have prompted the city to understand the commute patterns of essential workers. The city is also seeking to understand and address gaps in mobility offerings that affect underemployed Black men in our community. Our goal will be to work with our partners to develop plans for conducting these more targeted studies and collecting data through our suite of data collection tags and mobile app.     
Expected Accomplishments and Metrics
[For optimal viewing, please see the pdf version of the Proposal attached as a Supplemental Information Document.]

In developing novel methods of public input and engagement into the mobility service design process, we will contribute the following: 

Lightweight sensing systems for robust deployment in the real world. Our work will contribute technical designs for real-world sensing systems to collect community feedback around the city and from community members, with a focus on individuals with disabilities. We plan to open-source our designs and provide guidelines for deploying different systems around the city.

Datasets. We will compile the qualitative and quantitative data we collect into publicly available, anonymized datasets that can be used to support city planners in answering questions about people’s concerns, thoughts, and behaviors around new mobility services (specifically, e-scooters and mobility hubs). This data can also be used to help policymakers in their regulatory decision making as the transportation landscape becomes more diverse.

Novel policy development methods and considerations. We also see this work contributing model policy development methods that could transfer to other domains of transportation management. We will connect with the City of Boston’s Office of New Urban Mechanics, the Chicago Department of Transportation, and Atlanta’s Center for Civic Innovation to share insights and resources. We will also share a report of our findings with local and national policymakers to inform the legislative debate around transportation policy. For example, we will reach out to US Representatives Ayanna Pressley, Jesús García, and Mark Takano, who recently formed the future of transportation caucus.

Mobility service design playbook. Our collection of methods, tools, and deployment examples will serve as an extensible, replicable process for engaging with communities when deploying and designing new mobility service portfolios. Paired with our casebook, this playbook will be a resource that can be shared with and built upon in other mobility service deployments and by other municipalities. We intend to make this playbook open-source and accessible from our project webpage, and circulate through our project listserv which includes members of national legal advocacy groups, municipal departments of transportation, and industry representatives. Our partners in the Department of Mobility and Infrastructure will send the playbook to their counterparts in other cities, regions, and states. 

Public dissemination We will develop academic publications (e.g., CHI, Facct, Transactions on Intelligent Transportation Systems) and public press articles (e.g., CityLab) for the benefit of the greater community. In addition, we will develop publications of use to the city, such as the casebook, memos and white papers, and the mobility service design playbook.
    

Individuals Involved

Email Name Affiliation Role Position
pcarrington@cmu.edu Carrington, Patrick Human-Computer Interaction Institute PI Faculty - Untenured, Tenure Track
forlizzi@cs.cmu.edu Forlizzi, Jodi SCS Co-PI Faculty - Tenured
sarahfox@cmu.edu Fox, Sarah SCS Co-PI Faculty - Untenured, Tenure Track
nikmart@cmu.edu Martelaro, Nikolas Human-Computer Interaction Institute Co-PI Faculty - Untenured, Tenure Track

Budget

Amount of UTC Funds Awarded
$100000.00
Total Project Budget (from all funding sources)
$200000.00

Documents

Type Name Uploaded
Data Management Plan 378-Data-Management-Plan.pdf March 19, 2021, 7:49 a.m.

Match Sources

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Partners

Name Type
Department of Mobility and Infrastructure Deployment & Equity Partner Deployment & Equity Partner