Impact of ride-sharing on mobility trends and vehicle stock

Abstract

North American transportation industry is on the verge of a revolutionary change. With the advent of car-sharing services and ride-sharing companies, the transportation industry is experiencing a fundamental way in which people choose to travel. This particular thesis looks at the impact of these disruptive changes in transportation on the way people choose to travel, the car based vehicle miles travelled (VMT) and the national vehicle stock. In particular, this work tries to look at how people choose to make a travel decision when embarking on a particular trip and how that translates to an effect on the national level vehicle stock. When presented with a particular mode of travel, the most relevant aspects associated with that particular mode of travel were explored and evaluated. Each mode was evaluated based on cost, time and comfort associated with the mode.

Multi-attribute utility theory was used to study and evaluate how people make decisions about mode choice when choosing a particular mode for a trip. This work tries to look at the impact of ride-sharing on modal changes and shits that result in a less or more use of personal car travel. Apart from the travel behavior associated with modes, this work also estimates impact of ride-sharing on the total vehicle usage in urban areas. Once the modal share of different modes was estimated, an overall passenger trip demand was generated at the national level. This trip demand was broken down into car-based trips and non-car based trips from the modal share result. Combined with occupancy assumptions, this passenger trip demand was converted into a car based VMT estimate. Finally, combining the car based vehicle miles travelled with the average vehicle utilization, the national vehicle stock was calculated.

In order to measure the impact of these futuristic technologies on modal share, VMT and the national vehicle stock, scenario analysis was the method chosen. In order to have a reference case, a base case scenario was designed assuming the world remains as it is today and nothing changes. A series of progressive scenarios related to ride-sharing were then tested to gauge the impact of ride-sharing. It was found that ride sharing has the most significant impact in the urban areas for short trips. The national level vehicle stock in the year 2050 declined by approximately 1.0% in the improved ride-sharing scenario. Higher-electrification of vehicles along with improvements in ride-sharing did not decrease the stock further by much, as compared to just the improved ride-sharing scenario. In an aggressive scenario, with improved ride-sharing, improved transit and anti-car policies, the national level stock value in year 2050 declined by approximately 6% compared to the base case scenario.

Finally, in the scenario with improved ride-sharing and higher autonomy, the national level VMT increased by 1.3%, but the vehicle stock declined by 9.9%. The results from this work can be further used to inform certain decisions regarding changing travel behaviors or explore questions related to higher level policy analysis.