Development of a Model to Evaluate Policy Approaches for Transportation Network Companies and the Private Vehicle to Address Congestion and Promoting Equity in San Francisco
Research Lead: Pravin Varaiya
UC Campus(es): UC Berkeley
Problem Statement: The research team will develop a model to evaluate the impact of regulations on TNCs and private vehicles on congestion and equity in San Francisco. The model has already been validated using data from the City of New York. This project will extend and fit the model to San Francisco using available aggregate data. The model will simulate a range and mix of policies. The regulations that will be analyzed include: (1) a minimum wage for TNC drivers; (2) a cap on the number of TNC vehicles allowed in the city; (3) a tax on TNC trips; (4) a cordon tax on all vehicles; and (5) parking fees on private vehicles.
Project Description: Transportation Network Companies (TNCs) like Uber and Lyft are popular with the public and growing in use. Unfortunately, TNCs have disrupted traffic and increased congestion in San Francisco. Between 2010 and 2016, daily TNC vehicle miles traveled (VMT) increased by 630,000 miles, accounting for 51% of increased delay and 25% of total delay. With 45,000 drivers, TNCs are the city’s largest employer. These drivers earn below the $15 hourly minimum wage and they are beginning to protest their working conditions. The combination of high value to the customer, inferior working conditions for the employees, and negative congestion externalities has prompted cities to consider TNC regulation, including New York City and London, the two largest Uber markets.
Status: In Progress