Quick-Response Research on Long-Term Strategic Issues. Task 34. The Effects of Vehicle Automation on the Public Transportation Workforce

In the past few decades, the U.S. economy has undergone tremendous structural transformations. The workforce has been impacted by notable trends, including the emergence of the digital economy, and the forces of globalization and interconnected trade. As the economy moves forward, automation and robotics present both a disruptive reality and a potential opportunity to the U.S. labor work force. Released by the National Bureau of Economic Research (NBER) in March 2017, “Robots and Jobs: Evidence from U.S. Labor Markets” found that between 1990 and 2007 each additional robot per thousand workers reduced employment by 0.18-0.35 percentage points. With increased automation, this figure could increase. At this pace, middle-class jobs could become obsolete. Still, observers of past technological innovation realize the potential for the creation of new positions, and that lower marginal costs can enhance further job creation. For example, bank teller positions increased even after the ATM was introduced due to the expansion of bank branches. While cross-country trucking jobs may seem prone to automation replacement, an article by Brookings argues that the skills and duties of drivers are underestimated, and that advancements in automation will create complementary jobs. Furthermore, some public transportation agencies struggle to attract enough labor for operations to the point where service is jeopardized. The public transportation industry is particularly exposed to the coming technological changes. Automakers have shown willingness to participate in the mobility sector by collaborating with Transportation Network Companies (TNCs) in advancing self-driving technology. Innovative public transportation agencies have begun testing Low Speed Automated Vehicles (LSAV) as shuttles. These pilot programs may eventually develop into automated trunk line testing (see FTA’s request for comment relating to automated transit buses https://www.transit.dot.gov/research-innovation/vehicle-automation-requests-comment ), which would have a direct effect on labor. Labor transitions that automation will bring are approaching. Increased knowledge and awareness can help the public transportation industry plan for and adapt to new labor realities and skillset demands. The objective of this research is to provide the public transportation industry with information that will help it become more aware of automation’s effects on the labor work force. The research should emphasize the effects of Society of Automotive Engineers (SAE) automation levels 4 and 5 (Preparing for the Future of Transportation Automated Vehicles 3.0, US Department of Transportation, October, 2018, page vi, https://www.transportation.gov/sites/dot.gov/files/docs/policy-initiatives/automated-vehicles/320711/preparing-future-transportation-automated-vehicle-30.pdf). Analysis should focus on the following areas: (1) Status quo analysis of transit labor market that assess current labor market segments/jobs and the current demographics, pay, and skills required for these jobs. (2) Ranking of jobs within the public transportation industry that are most and least susceptible to replacement (or conversion to another agency role based on additional training and/or revisions to the organizational chart) via automated technologies. (3) An overall estimation of total public transportation jobs at risk of replacement, along with potential job opportunities created because of automation in transit. (4) A description of the skills that the public transportation workforce will need to handle the new technologies. (5) A timeframe estimate for when the autonomous vehicles (AV) technologies could have an impact on the workforce. (6) A generalized description of how public transportation agencies are currently working with organized labor in implementing current technology and training programs and what barriers exist in doing so. (7) A set of historic and real-time data and metrics to be collected and monitored on an ongoing basis to track the effect of automation on the workforce; recommend ideal entities for collection and analysis of such data. (8) Recommendations for workforce transitioning, re-training, partnerships, and additional steps that public transportation agencies can take to anticipate technological change as it relates to its labor force, noting current successful transit apprenticeship programs.

• Record URL:
  http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4658

Language

• English

Project

• Status: Completed
• Funding: $100000
• Contract Numbers:

  Project J-11, Task 34

• Sponsor Organizations:

  Transit Cooperative Research Program

  Transportation Research Board
  500 Fifth Street, NW
  Washington, DC    20001

  Federal Transit Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Project Managers:

  Garcia-Colberg, Mariela

• Performing Organizations:

  Texas Transportation Institute

  Texas A&M University System
  3135 TAMU
  College Station, TX  United States  77843-3135
• Principal Investigators:

  Walk, Michael

• Start Date: 20190325
• Expected Completion Date: 0
• Actual Completion Date: 20190325

Subject/Index Terms

• TRT Terms: Automation; Autonomous vehicles; Impacts; Jobs; Public transit; Training; Workforce
• Subject Areas: Administration and Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01698959
• Record Type: Research project
• Source Agency: Transportation Research Board
• Contract Numbers: Project J-11, Task 34
• Files: TRB, RIP
• Created Date: Mar 18 2019 4:21PM