published journal article

Regulating TNCs: Should Uber and Lyft set their own rules?

Abstract

We evaluate the impact of three proposed regulations of transportation network companies (TNCs) like Uber, Lyft and Didi: (1) A minimum wage for drivers, (2) a cap on the number of drivers or vehicles, and (3) a per-trip congestion tax. The impact is assessed using a queuing theoretic equilibrium model which incorporates the stochastic dynamics of the app-based ride-hailing matching platform, the ride prices and driver wages established by the platform, and the incentives of passengers and drivers. We show that a floor placed under driver earnings can push the ride-hailing platform to hire more drivers and offer more rides, at the same time that passengers enjoy faster rides and lower total cost, while platform rents are reduced. Contrary to standard competitive labor market theory, enforcing a minimum wage for drivers benefits both drivers and passengers, and promotes the efficiency of the entire system. This surprising outcome holds for almost all model parameters, and it occurs because the wage floor curbs TNC labor market power. In contrast to a wage floor, imposing a cap on the number of vehicles hurts drivers, because the platform reaps all the benefits of limiting supply. The congestion tax has the expected impact: fares increase, wages and platform revenue decrease. We also construct variants of the model to briefly discuss platform subsidy, platform competition, and autonomous vehicles.

research report

A Futures Market for Demand Responsive Travel Pricing

Abstract

Dynamic toll pricing based on demand can increase transportation revenue while also incentivizing travelers to avoid peak traffic periods. However, given the unpredictable nature of traffic, travelers lack the information necessary to accurately predict congestion, so dynamic pricing has minimal effect on demand. Dynamic toll pricing also poses equity concerns for those who lack other travel options. This research explores a potential remedy to these concerns by using a simple “futures market” pricing mechanism in which travelers can lock in a toll price for expected trips by prepaying for future tolls, with the future price increasing as more travelers book an overlapping time slot. This approach encourages travelers to avoid driving during the peak periods when pricing increases toward capacity or to purchase trips in advance when the price remains low or discounted, thus using infrastructure capacity more efficiently. Travelers that do not prepurchase their trip are subject to the real-time market price, which is determined by dynamic congestion pricing. This futures-market mechanism can augment existing toll collection technologies and provide travelers with sufficient pricing information and purchasing options to preplan their travel and avoid excessive prices.

policy brief

Toll Pricing “Futures” Market Could Reduce Congestion and Increase Revenue

Abstract

Transportation agencies are increasingly relying on tolls to raise revenue and to mitigate congestion, but conventional fixed tolls do not necessarily encourage offpeak use of infrastructure, and high tolls can dampen economic productivity. Dynamically adjusting pricing based on demand can incentivize travelers to avoid peak traffic periods and shift it to other modes, but given the unpredictable nature of traffic, travelers lack the information necessary to accurately predict congestion, so dynamic pricing has minimal effect on demand. Dynamic toll pricing also poses equity concerns for those who lack other travel options, such as access to transit. A simple “futures market” pricing mechanism has the potential to address these concerns—travelers can lock in a price for expected trips by prepaying for future tolls, with the future price increasing as more travelers book an overlapping time slot. To evaluate the effectiveness of a futures market to impact travel demand, trip density, traffic flow, and revenue, this research conducted a sensitivity analysis of elasticity and pricing constraints.

published journal article

Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Abstract

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

research report

Mitigating Exposure and Climate Change Impacts from Transportation Projects: Environmental Justice-Centered Decision-Support Framework and Tool

Abstract

California must operate and maintain an effective and efficient transportation infrastructure while ensuring that the health of communities and the planet are not compromised. By assessing transportation projects using a life-cycle perspective, all relevant emission sources and activities from the construction, operation, maintenance, and end-of-life phases can be analyzed and mitigated. This report presents a framework to assess the life-cycle of human health and climate change impacts from six types of transportation projects: (1) Roadways; (2) Marine ports; (3) Logistical distribution centers; (4) Railyards; (5) Bridges and overpasses; and (6) Airports. The framework was applied using an integrated model to assess fine particulate matter (PM2.5) and greenhouse gas (GHG) emissions, noise impacts, and monetized damages (Value of Statistical Life, Social Cost of Carbon) from two case studies: routine resurfacing and vehicle operations on road segments within the San Francisco Bay Area using 2019 data, and annual marine, cargo, rail, trucking, and infrastructure maintenance operations at the Port of Oakland in 2020. The results suggest that emission sources in a project’s supply chain and construction (material production and deliveries, construction activities, fuel refining) can significantly contribute to the full scope of impacts from transportation systems. Equitable mitigation policies (e.g., electrification, pollution control technologies) need to be tailored to address the sources that impact communities the most.

published journal article

Does Bike-share Enhance Transport Equity? Evidence from the Sacramento, California Region

Abstract

This study examines the rate of bike-share adoption by individuals from different socio-demographic groups and living in different bicycling contexts, as well as how individuals incorporate bike-share service into their travel patterns for different travel purposes and change their use of other modes. Data are from a two-wave survey of bike-share users and a parallel household survey of residents in the Sacramento region. Modeling results for bike-share adoption and use frequency show that low-income individuals are less likely to adopt bike-share but use the service more frequently than other income groups when they do adopt. Low-income users, people of color, and non-auto owners are more likely than other groups to use bike-share frequently for many trip purposes. Individuals living in areas with a stronger biking culture and surrounded by bike infrastructure are less likely to adopt the service and less likely to use it for purposes other than commuting. All users change their use of other modes when they incorporate bike-share into their travel patterns, but low-income individuals, people of color, and non-auto owners would be more severely impacted if the service were to stop.

published journal article

Pavement resurfacing and supply chains are significant contributors to PM2.5 exposure from road transportation: evidence from the San Francisco Bay Area

Abstract

There are hundreds of millions of kilometers of paved roads and many people live in proximity. Pollution from road transportation is a well-documented problem potentially leading to chronic health impacts. However, research on the raw material production, construction, operation, maintenance, and end-of-life phases of paved roads, and corresponding supply chains, is generally limited to energy consumption and greenhouse gas emissions. No previous research efforts on the life-cycle stages of pavements and road operation connect pollutant emission inventories to the intake of inhaled pollutants and resulting damages to exposed populations. We have developed a first-of-its-kind model quantifying human exposure to fine particulate matter (PM2.5) due to emissions from routine pavement resurfacing and vehicle operation. We utilize the Intervention Model Pollution Source-Receptor Matrix to calculate marginal changes in ground-level PM2.5 concentrations and resulting exposure intake from a spatially resolved primary and secondary PM2.5 emission precursors inventory. Under a scenario of annual road-resurfacing practices within the San Francisco Bay Area in California (population: 7.5 million), resurfacing activities, material production and delivery (i.e. cement, concrete, aggregate, asphalt, bitumen), and fuel (i.e. gasoline, diesel) supply chains contribute almost 65% to the annual PM2.5 intake from all the sources included in the study domain (the remaining 35% being due to on-road tailpipe emissions). Exposure damages range from $170 to $190 million (2019 USD). Complete electrification of on-road mobile sources would reduce annual intake by 64%, but a sizable portion would remain from material supply chains, construction activities, and brake and tire wear. Future mitigation policies should be enacted equitably. Results show that people of color experience higher-than-average PM2.5 exposure disparities from the emission sources included in the study, particularly from material production.

policy brief

Could Transportation Network Companies help Improve Rail Commuting?

Abstract

Commuter rail is known to have a “first- and last-mile” problem (i.e., a lack of options for getting commuters to and from a rail station). The first- and last-mile dilemma creates inequalities in access. For example, high-income commuters drive to work (forgoing transit altogether), middle-income commuters drive to a rail station and pay to park, and low-income commuters rely on feeder buses or walking to reach a rail station. Transportation network companies (TNCs), like Uber and Lyft, are a viable option for connecting travelers to rail stations, especially for those who don’t own a car, however, their high fares make them attractive only to higher-income travelers. To close this equity gap, subsidies could be provided for TNC rides that connect travelers to commuter rail. To explore this concept further, we developed idealized (but physically realistic and rational) models to describe communities in the San Francisco Bay Area, and simulated the effects of various subsidization policies (i.e., providing subsidies for TNC rides to and from rail stations, increasing rail stations parking fees) using real-world data representative of Bay Area commuter populations.

research report

Subsidizing Transportation Network Companies to Support Commutes by Rail

Abstract

The research team explores how rail transit’s first- and last-mile issues might be addressed by partnering with transportation network companies (TNCs) like Uber and Lyft. The goal is to lure high-income commuters to shift from cars to TNCs and rail. The team also explores how rail and TNC partnerships can improve travel for low-income commuters who currently rely on low-frequency bus services. The researchers parametrically test subsidizing TNC fares for feeder services in the San Francisco Bay Area in an idealized fashion. Inputs such as the residents’ value of time and vehicle ownership were taken from various local data sources. The communities that were selected for the study are served to different degrees by the BART rail system. The research includes that the optimal policy must be tailored to the characteristics of the community it serves. In dense, walkable communities with strong bus service near rail stations, TNC subsidies should be targeted to less accessible neighborhoods and low-income commuters to not compete with bus transit and active modes like walking. For lower-density communities with limited dedicated bus feeder service, TNC subsidization can be applied more broadly, although disincentives, like increasing rail parking fees, must be considered carefully because they can induce commuters to drive directly to work instead. The research paper concludes with a discussion of how subsidies might be covered by reallocating existing resources in different ways.