Seat Assignments With Physical Distancing in Single-Destination Public Transit Settings

Area of Science:

• Public Health
• Operations Research
• Transportation Science

Background:

• Physical distancing is crucial for reducing COVID-19 transmission.
• Current public transit capacity models, like those for school buses, often overlook household groupings, leading to suboptimal efficiency.
• Implementing effective distancing in shared transit environments remains a challenge.

Purpose of the Study:

• To address the limitations of existing physical distancing models in public transit.
• To develop and evaluate models that account for passengers from the same household.
• To improve the efficiency and capacity of public transit vehicles while maintaining safety.

Main Methods:

• Developed a mixed-integer programming model for seat assignment based on vehicle configuration and distancing requirements.
• Introduced a heuristic model incorporating household grouping for passenger assignment.
• Utilized illustrative scenarios to test and validate the proposed models.

Main Results:

• Seating assignments can be generated rapidly, in near real-time.
• The household grouping heuristic significantly increases transit vehicle capacity (e.g., airplanes, school buses, trains).
• The proposed methods maintain or improve safety by not increasing infection risk.

Conclusions:

• Accounting for household groupings in seating arrangements is a more efficient approach for public transit.
• The developed models and heuristic offer practical solutions for optimizing capacity and safety in shared transit.
• Publicly available application and source code encourage widespread adoption and further development.