The Metropolitan Transportation Authority (MTA), the Port Authority of New York and New Jersey, NJ TRANSIT, NYC Department of Transportation and the Partnership for New York City have launched the fifth iteration of the Transit Tech Lab’s annual competition, calling for tech-driven approaches to support the agencies’ objectives in operational efficiency and human capital utilization.
Applications for the Operational Efficiency Challenge and Utilization of Human Capital Challenge are due March 2 and are accessible at: transitinnovation.org/lab.
Representatives from each participating agency will evaluate startups based on the technology’s impact and the applicant’s product, team, and overall value proposition. Finalists will move forward to conduct a proof-of-concept over an eight-week period; the companies with the most compelling technologies that advance the agencies’ goals can win a yearlong pilot. In the past few years 23 companies have been selected to participate in yearlong pilots, conducting deeper tests to demonstrate the value of their technology to agency partners.
In response to post-pandemic reduced ridership and revenue, NYC regional transit agencies are seeking tools that can reduce costs while increasing efficiency.
Technologies may include:
- Predictive maintenance and analytics on public transit and infrastructure assets, such as track, signal and power systems, to proactively identify possible operational failures before they occur.
- Tools to prevent fare evasion and improve/automate the issuance and processing of fare evasion summonses.
- Tools predicting and mitigating operational disruptions, such as impacts of weather events, delays, platform crowding, excessive wait times, crime, road safety, or EV bus battery electric fires.
- Tools to help prioritize operational staff resources, such as: where to deploy cleaning staff & waste management solutions, manually inspect assets, place human flaggers, or allocate people counters on trains.
- Tools to help automate and improve operations and make them more sustainable, such as: 1:1 customer digital communication, locating buses within a depot, internal employee communication, adaptive bus pick scheduling, automating track inspections to help speed up service, or microgrid and decarbonization optimization.
- Connecting disparate sources of data into one system. Data examples include, tolling data across different locations, cargo and truck movement, and integrating customer feedback.
NYC regional transit agencies, along with other public transportation agencies across North America, are facing a workforce shortage. To meet service needs, agencies are seeking tools to improve employee recruitment and retention through the Human Capital Challenge.
Technologies may include:
- Enhanced training tools to speed up and improve the hiring and onboarding process.
- Tools to help recruit and retain operations staff, especially those with Commercial Driver Licenses (CDL).
- Tools to communicate long-term career paths within agencies.
- Upskilling and training tools for both technical and soft skills to invest in current employees.
- Tools to empower employees by tracking and communicating productivity.
- Tools for workforce and succession planning.
- Tools to improve conductor and bus driver safety.
The Transit Tech Lab is a program of the Transit Innovation Partnership, a public-private initiative created by the MTA and Partnership for New York City to make New York the global leader in public transit. The Transit Tech Lab is supported by the Partnership Fund for New York City, and modeled after the Fund’s successful accelerator program, The FinTech Innovation Lab, which has helped make New York the premier hub for fintech startups.
This is the fifth challenge cycle for the Transit Tech Lab, a process that has yielded substantial success in advancing technological innovation at New York-area transit agencies. To date, the Lab has supported 36 proof of concepts, 23 pilots and six commercial procurements with innovative technologies across its partner transit systems.