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Data-driven research aims to solve first / last mile problem


MetroLab Network has partnered with Government Technology to bring to its readers a segment called MetroLab Innovation of the Month Series, which highlights impactful technology, data and innovation projects underway between cities and universities. If you would like to know more or contact the project managers, please contact MetroLab at [email protected] for more information.

In this month’s issue of the Innovation Series of the Month, we explore the work of Georgia Tech and the city of Atlanta on the Socially Conscious Mobility Laboratory (SAM).

Ben Levine of MetroLab spoke with Pascal Van Hentenryck, A. Russell Chandler III Chair and professor at Georgia Tech Milton Stewart School of Industrial and Systems Engineering and head of SAM Lab; Jacob Tzegaegbe, Senior Transportation Policy Advisor for Mayor of Atlanta Keisha Lance Bottoms and Member of the SAM Advisory Board; and Debra Lam, general manager of smart cities and inclusive innovation at Georgia Tech.

Ben Levine: Can you describe the origin and the objective of the socially conscious mobility laboratory, and who participated in the project?

Pascal Van Hentenryck: the Socially aware mobility laboratory (SAM) aims to transform mobility for all segments of the population and to reduce mobility inequalities while tackling problems such as congestion and sustainability, in particular the reduction of greenhouse gas emissions. It focuses on providing new mobility systems to fundamentally improve access to jobs, health care, healthy food and education. It is organized around the concept of on-demand multimodal transport systems which combine on-demand mobility services which serve low density regions and tackle the problem of the first / last kilometer with vehicles with high occupancy, such as buses. or trains, traveling along density corridors. The laboratory has deployed successful pilots in small cities and is now working on mobility in large cities. It is supported by a large NSF Leap HI (Lead Engineering for America’s Prosperity, Health, and Infrastructure) grant to improve American health and prosperity.

Jacob Tzegaegbe: SAM is not a typical research project, but part of a larger research-oriented partnership, Georgia Tech has with the community across the Smart Cities and Inclusive Innovation Initiative. It focuses on the community issue and seeks to contribute to multidisciplinary and innovative research and development. SAM has created an external advisory committee which provides both information on the project and partners willing to implement the research. External partners include the City of Atlanta, the Metropolitan Atlanta Rapid Transit Authority (MARTA), Gwinnett County, the Atlanta Regional Commission, the Georgia Department of Transportation, the Midtown Alliance, the Atlanta-Region Transit Link Authority and the State Road and Tollway Authority.

Levine: What are the first results of this project? Were you surprised or unexpected?

Debra Lam: SAM was able to identify, clean up and aggregate many types of mobility and community data. Preliminary results show that multimodal on-demand transportation systems can improve convenience and significantly reduce costs in Atlanta. In addition, new community carpooling systems could significantly reduce congestion through real-time optimization and machine learning. The project also shows that e-scooters can play a fundamentally positive role in the city.

Levine: Can you tell us a little bit about multimodal transport on demand (ODMTS) systems and how they relate to the SAM laboratory?

Tzegaegbe: ODMTS is a new mobility concept combining the best of public transport and carpooling systems. At a high level, it can be seen as a way to bring public transportation to the 21st century, using mobile apps and data analytics to design mobility systems that pick up passengers from their origins, drop them off at their destinations and use a high vehicle occupancy rate to combat congestion and economies of scale. They significantly improve passenger comfort, are priced as a regular public transportation system and are fully synchronized via mobile apps. The city of Atlanta is ultimately interested in improving the mobility of our residents and in preparing for future trends, such as autonomous vehicles and electrification.

At SAM, we believe that the future of public transportation combines the customer experience with data and technology, such as high performance computing, data mining, machine learning and optimization. ODMTS requires the exploration of compelling research questions and provides a direct link to people and communities having an impact.

Levine: In what ways are data-driven multimodal transport systems driven? What types of data do you use?

Lam: The SAM laboratory uses gigabytes of data collected daily to design new mobility systems. It uses transit data from MARTA and Gwinnett County, including Breeze card transactions, automatic passenger counting and cash transactions. It uses the trajectories of the Atlanta Regional Commission vehicles, which are unique to the United States. It uses the road network of OpenStreetMap, trajectories of Bird e-scooters and aggregated Uber data.

Figure 1: Preliminary design of a multimodal on-demand transportation system for Atlanta.

Levine: Can you guide me through this preliminary ODMTS design? (See Figure 1.) What would a “day in life” look like for someone using ODMTS?

Van Hentenryck: In this design for ODMTS, we show how the existing MARTA system can be supplemented with high frequency bus lines and on demand shuttles. We call the red dots on the map “virtual points,” and they allow passengers to congregate in unique places at the same time, overcoming common barriers to carpooling. The dark blue and orange lines extending from the MARTA card are bus lines, the color indicating the frequency (blue means high frequency). The teal lines represent shuttle services, which greatly extend the reach of the entire public transportation system.

Here is an example of what a user’s experience with the ODMTS mobile app might look like: after entering the app using their smartphone, a cyclist would choose an origin (a virtual stop) and a destination (another virtual stop), one hour of pickup and a number of passengers. The rider’s profile will also specify if he needs a wheelchair accessible vehicle. Once a runner has entered an origin and a destination, they will see a snapshot of their trip, including approximate wait and transit times. They could then request the route. The app would assign a driver and the driver would see a visualization of the upcoming shuttle as well as the scheduled pickup time. The name of the shuttle would be displayed at the top of the screen. When the shuttle arrives, the application would warn the pilot, who could now board the shuttle. Once the driver has been collected, the vehicle changes color in the application and the driver can follow the route visually and in real time until his arrival. If the trip is multimodal, the application would indicate which buses, trains or shuttles to board at a transfer point and the trip would continue with the next step. All synchronization can be managed automatically via the application.

Levine: Which parts of this project are human-oriented and which are technology-oriented? What new or innovative technology are you using?

Lam: Mobility systems are socio-technical systems: they must focus on people and provide services that will be widely adopted and fully meet their needs. Therefore, all design begins with what people do, what they would like to do, and how best to meet those needs in an accessible and affordable way. The technology elucidates these needs, plans the mobility system holistically and works in real time, adapting to needs dynamically. The secret sauce is a tight integration of artificial intelligence and operational research, with optimization, machine learning and massive mobility data sets being the key ingredients.

Figure 2: Need for dedicated bus lanes for suburban counties. Compare rush hour traffic to non-rush hour traffic. Green: no difference; yellow: rush hour causes a delay of up to 13 minutes; orange: rush hour causes a delay of 13 to 26 minutes; red: rush hour causes a delay of 26 to 40 minutes.

Levine: What are the next steps in this project? What goals do you have?

Van Hentenryck: SAM is trying to raise funds to deploy a multimodal on-demand transportation system for Gwinnett County, including its connections to MARTA and downtown and Emory University using rapid transit buses. If we succeed, it will mean that the concept can be applied to many Atlanta suburban communities, fundamentally changing mobility. SAM is currently designing these mobility systems. The other main objective is to design a mobility system centered on electric scooters for downtown and downtown Atlanta and their connected neighborhoods. Finally, we are looking at other places that could use this research, such as military bases and community improvement districts. There are many scales in the city and community to which this research could be applied, and we are delighted with the partnership.

Tzegaegbe: We are delighted to partner with SAM as we continue to think about the future of mobility in Atlanta. Transportation is at the heart of the lives and experiences of the people who live and work in Atlanta and we focus on using these types of mobility approaches to meet a range of priorities: more efficient and cost-effective travel, services better coordinated and integrated, meeting sustainability objectives, leveraging this technology to improve access for underserved communities and improve quality of life.

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