Prior to the pandemic, the ridesharing industry exploded in popularity across the United States. The ability to request a ride from wherever, to wherever, whenever, and through an app so you did not have to speak to a human quickly became popular with consumers. Rideshare companies struggled initially to become profitable based mostly on their cost of revenue expenses. (reference) However, the pandemic affected the market in unexpected ways. As people stayed home, there was much less demand for actual rides and much higher demand for food delivery. Many existing drivers opted to deliver food rather than shuttle passengers to make more money. As the pandemic eased and the passenger demand returned, the subsequent driver supply has been slow to follow. As such, the most popular rideshare companies face a significant shortage in drivers. One potential solution for this is to invest in a fleet of automated vehicles. This project seeks to explore the differences between a rideshare fleet of automated vehicles versus its competitors which consist of traditional taxis and rideshares, public transportation and more non-conventional means of transportation such as shared scooters and bikes. The primary attribute our project focuses on is the automation of the vehicle which also is the primary decision variable for the ridesharing company. Essentially, the question from the consumer perspective is whether the public is ready to ride in automated vehicles and from the corporate perspective is if this will make their platforms profitable.


George Jettson was scripted to have been born in July of 2022. The futuristic depiction of his life predicted flying cars. While we have yet to realize flying cars, self driving cars exist are are only awaiting mainstream implementation. However, while watching the Jettsons as children most people were excited about the prospects of future technology. When faced with it as a viable reality, people seem to shy away from what they do not fully understand. An additional complication for large scale adoption is price. Fully automated vehicles are understandibly expensive. This project seeks to explore the viability automated vehicles as a fleet for a ridesharing company. Ridesharing companies are already facing a manning shortage in a post pandemic economy.

Additionally, in today’s market and technological advancement, the need for automation being a standard feature in vehicles has been a rising need. There has been constant research to make improvements in their abilities & overall reliability along with making strides to completely automate them. In this report/paper we are focused on the challenges in implementing a fleet of automated vehicles as a ridesharing alternative to taxi/Uber/Lyft/ etc. in the Metropolitan D.C. area. As automated vehicles are still a new technology that is relatively untested in a practical environment, the question of the overall safety of the passengers does arise. Our aim through this project is to conduct a mass survey where people provide feedback by answering questions regarding safety, potential features they would like in the technology that would raise their trust in using this mode of transport.

Survey Design

Target Population

Our target population were potential rideshare customers. Given the use of Amazon Mechanical Turk, the audience will already be adults. In addition, the target population are those adults who are in an urban area with established rideshare or taxi options. Part of the demographic collection section of the survey can ask the user if they have used a rideshare within the last month or 6 months. While ideally, the target population are adults in urban areas, we did not have a way to screen out rural participants.

Critical respondent information

Question Response Options
What is your age? Free text.
What is your gender? M / F / Non-Binary / Other
How recently did you ride in a rideshare? Last Week / Last Month / 6 months / Never
How many times a month do you use rideshare services? 10+ / 4-9 / 1-3 / 0
On a scale of 1-5, how likely are you to ride in an automated vehicle if there is an attendant present? 1, 2, 3, 4, 5
On a scale of 1-5, how likely are you to ride in an automated vehicle if there is no attendant present? 1, 2, 3, 4, 5
On a scale of 1-5, how much do you trust an automated vehicle to get you to your destination? 1, 2, 3, 4, 5

Education information

There are several attributes that we will ask you about. Below are quick descriptions of each attribute.

Attribute Definition
Price how much will the ride cost you per mile.
Trip Time given a standard trip, how long will it take.
Wait Time how long it takes for the ride to arrive at pick-up point.
Shared Ride is the ride shared with other paying customers from other parties.
Human Present is there an employee from the rideshare company present such as a driver.

Conjoint questions

Initially, the team had several more attributes that were of interest to include reliability and capacity of the vehicles. Upon further research, these variables were eliminated since their levels did not seem correlated to whether the car was automated or not. Additionally, reducing the number of variables decreases the burden of a expensively large sample size that would provide statistically significant analysis.

The levels for the remaining attributes were selected based on research conducted on the existing rideshare market in the metropolitan D.C. area. These attributes included price, trip time, wait time, whether the ride was shared with a stranger, and whether there was a human present to operate the vehicle. The last two attributes are obviously binary. The levels for the other attributes were selected based on research on the rideshare market in the metropolitan D.C. area. An example of a conjoint question is below and a table with all the possible levels is included in the appendix.

We did not include a no-choice option.

Example of conjoint question: