Will Uber dominate NYC in 2025?
Self-driving rides will radically change the NYC transit landscape
Cabs, Uber and Lyft in NYC circa 2015
Todd Schneider put together an informative post regarding the taxi industry in New York City. He used data from the New York City Taxi and Limousine Commission’s (TLC) summary reports.
Some key statistics. Between Yellow Taxis, Uber, and Lyft, there are approximately 600,000 rides hailed every day. Although much of Uber and Lyft’s growth has come at the expense of Yellow Taxi services, these ride hailing services are also growing the total market. This is a nod to the growing trust and preference of on-demand ride services over other transportation options.
KEY STATISTIC: 600,000 rides hailed a day
Yellow Taxis provides the best insight into current daily yield per vehicle
Rides per day per medallion
There are 13,000 taxi medallions issued in NYC. The TLC estimates that the average medallion is in use 29 days a month, 14 hours a day. Note that multiple drivers can share one medallion. If we assume a baseline of 400,000 rides hailed a day for Yellow Taxis, that puts yield at 30.8 rides per day or 2.2 rides per hour. See Figure 1 in the appendix below.
KEY STATISTIC: 30.8 Rides/Day per medallion
Average cost per ride, approximate travel distance, and approximate trip time
The average Yellow Taxi ride in 2015 was $14. Yellow Taxis charge $2.50/ride plus $2.50/mile or $.50 per minute idle time. Based on this pricing model, I estimated the average ride to be 2.6 miles long w/ 10 minutes of idle time. Based on this information, an approximate pick-up to drop-off ride is 15 minutes. See Figure 2 in the appendix below.
KEY STATISTICS: $14/average ride cost, 2.6 mile/average ride length
Annual miles per vehicle and usable lifespan
Based on the above figures, the average Yellow Taxi is logging 28,000 miles/year. Yellow Cabs are retired as they reach 300,000 lifetime miles.
KEY STATISTIC: 300,000 miles average retirement age for taxi
Now close your eyes and visualize robotic cars roaming the streets of Manhattan
Future scenario 1: An Uber world
Fast-foward to 2025. The Uberization of New York is nearly complete. The Yellow Taxis companies are in their last death throws. Google|Lyft is playing catch-up. Uber has drastically dropped prices to a level that is moving customers away from public transportation options. For example, city buses are being decommissioned every day due to low ridership. More and more commuters are staying above ground to get across town.
Uber sets fares are $3 for rides under 3 miles, $5 for rides between 3–5 miles, and $1 per mile for rides over 5 miles.
The introduction of the Uber Narrow vehicles with 2 or 4 in-line seats have helped to throttle more vehicles per lane, but that has only served to increase demand. Ridership has crossed to 2 million rides a day for Uber and Google|Lyft.
The shift towards on-demand, self-driving vehicle rides are thinning the herds of private vehicles and human-powered, on-demand vehicles from the streets. The city is considering radically changing traffic and infrastructure of surface streets to optimize for narrow self-driving vehicles.
KEY PROJECTION: 2,000,000 rides per day*
- huge rideshare increase projection based on demand increase due to aggressive per ride pricing to compete with city buses and subway tickets.
Uber’s fleet, with 80% of the total ride-share market, has expanded to 27,000 vehicles. Uber’s purchase cost per vehicle is $40,000 per vehicle. The average vehicle is completing 60 rides a day. The average ride is 3.2 miles. The average self-driving Uber is in service 18 hours a day. Each Uber Narrow is logging 70,000 miles annually. After 280,000 miles, Uber is retiring the vehicles. See Figure 4 in the appendix below.
KEY PROJECTIONS: 60 rides/day and 280,000 mile retirement age
The cost of maintenance, insurance and electricity is $20,000 per vehicle per year. Including amortization of initial purchase cost, each Uber Narrow costs $30,000/year to keep operational.
At an average fare of $3.5 per ride, Uber’s New York City revenues are $2 billion a year. Their gross profit for NYC are over $1.2 billion/annually. See Figures 3, 4 & 5 in the appendix below.
Future scenario 2
Successfully projecting 10 years into the future for a disruptive technology is extraordinarily difficult. It is worthwhile to consider the infrastructure, political, regulatory, competitive, and economic obstacles that could delay or alter the above Uber-ized future scenario.
#1 challenge: Public sector take-over
Although Uber has high-powered lobbyist and lawyers, they have also developed a combative relationship with many municipal regulatory agencies. That being said, the benefits of self-driving vehicle transportation are too compelling to ignore. Metro transportation agencies have no choice but to approve self-driving ride services in order to provide a sustainable and convenient transportation layer.
Historically, large scale transportation services such as high-speed rail and buses have been run by the NYC Transit Department. Prior to Uber and Lyft, NYC controlled fare pricing and supplies of taxi and limo companies with its regulations and medallions. Today, we are witnessing the destruction of the regulated Yellow Taxi companies with the popularity of on-demand ride services of Uber and Lyft. As the NYC transit planners and regulators contemplate how best to take advantage of self-driving vehicle technology, they may be interested in regaining control of this service layer.
The NYC Transit Department has two likely pathways forward.
- Set well-defined regulatory rules for private on-demand, self-driving services to follow. The transit agency could set guidelines for rate schedules, service levels, maintenance and safety guidelines for self-driving ride services.
- Partner with a self-driving technology provider to run its own self-driving, on-demand service.
In the second scenario, the NYC Transit Department may contract with a company like Google for a subscription-based service. Google could provide a fleet of self-driving vehicles, or at a minimum the software. In this scenario, the NYC Transportation Department could create a public offer and restrict or prohibit private competitors.
Obstacles for self-driving ride services
Infrastructure Bottleneck
Can the streets of NYC accommodate a huge surge in demand for on-demand vehicle transportation? Even with narrow self-driving cars lane-splitting and dedicated lanes and drop-off spots, the congestion could overwhelm the grid.
NYC Subway and Metro Buses employees block self-driving ride services
The biggest losers in a self-driving transportation world are the employees who run the metro bus services. If Uber were to drop prices to the cost of a bus fare, why would anyone choose to ride a bus? Bus employees and their unions will fight tooth and nail against such an eventuality.
Subway services will also feel the pain if the prices of self-driving vehicle fares drop precipitously. Although ridership for the subway is less threatened by self-driving ride services, a major price drop would still lead to customer defections. As long as the subway saves riders time over the gridlock-challenged ride services, the subway will be a popular transportation option. Short commutes will transition to self-driving ride options, while the longer rides will remain underground.
99 problems, but the technology ain’t one of them
Self-driving technology for a dense and well-mapped city like NYC is not particularly difficult. Sure, there are crazy pigeons, pedestrians, cab drivers and bikers to contend with. In these action-packed streets, the vehicle speeds are often that of a fast-walking pace. The modest average speed of a ride greatly reduces the risks of bodily and property damage. The high volume of rides allow for rapid capture, learning and optimization for unaccounted edge cases.
Final thoughts
Make no mistake, self-driving vehicles are coming to large metros in the near future. Uber will have a prominent role to play. The question is whether these cities will allow a private sector winner, run their own service, or something in between.
The math
All the projections are based on the author’s assumptions only. Projections for market size, market share, Uber pricing, fleet costs are merely speculative and in no way represent Uber’s projections or assumptions.
