What if public agencies don’t change transportation policies or regulations as autonomous vehicles (AVs) enter the market and expand their presence on American roadways? This is one of many questions we investigate in assessing the potential risks that AVs present to the desired future outcomes that cities, regions and states have established through their land use and transportation plans. We use the term “risks” purposefully. This is because our research and modeling reveal the potential for substantial increases in vehicle travel and decreases in transit ridership if AVs operate under current policy and regulatory frameworks.
So, what can policymakers and local agencies do? We will get to that in the second article of this series, but first it is important to understand how private sector market forces are changing travel decisions and behavior. We follow this exploring a new model of behavior and the results, then wrap up with some suggestions of what communities can do to influence these trends.
Changes in behavior
In an era of disruptive trends and new mobility, travel behavior is changing in ways that directly influence how we model traffic implications. Specifically, these include:
1. Reduced cost of vehicle travel (in both money and time).
The concept of mobility or transportation as a service (MAAS or TAAS) relies on only paying for the cost of travel when a trip is made. Sharing trips can reduce individual traveler costs further and is made convenient by app-based technology through smart phones.
2. Eliminated burden of driving.
Autonomous vehicles (AVs) complement the MAAS model by removing the driver from transportation network company (TNC) services or by allowing private vehicle owners to avoid the driving task. For TNCs, eliminating the driver lowers the cost of service. For private individuals, time otherwise spent driving is available for other purposes.
3. Reduced potential for collisions.
AV technology offers the potential of computer and sensor-aided travel designed to avoid collisions. If connected vehicle (CV) technology is also included, vehicle travel can occur with even greater awareness of environmental conditions to minimize the risk of collisions.
4. Vehicle travel made more convenient.
TNCs today provide door-to-door service, eliminate the chore of parking and offer a variety of vehicle choices and services including wheelchair assistance and Spanish-speaking drivers. However, TNC trips are expensive enough that few people that rely on vehicle travel are willing to forgo owning their own vehicles. The transition to AVs will change the cost equation and vehicle design flexibility may result in even greater vehicle and service choices in addition to providing more travel options for the young, elderly and those with a range of disabilities.
In light of this, a key policy question is “What motivates this accommodation?” Without government action, the private sector business model for TNCs and MAAS generates revenue based on miles of travel, minutes of travel, demand levels and choice of vehicle/service. Hence, the private sector is incentivized to increase the use of vehicles while the public sector in many cities and states such as California has spent the past couple of decades focused on reducing vehicle miles of travel (VMT) to improve sustainability.
To grapple with this dichotomy between what the market wants and the sustainable and equitable vision that most cities are trying to achieve, we used regional travel forecasting models to test potential future outcomes with and without the influence of new government policies and regulations.
Modeling disruptive trends
Disruptive trends extend beyond just the technology changes in transportation. While not a complete list, we identified 16 factors related to trends including, but not limited to, job market health, fuel prices, social networking, vehicle ownership, AVs and internet shopping. The potential outcome for the future travel associated with these factors is difficult to predict because of the following unknown reactions:
- Government regulation of AVs, TNCs and new modes.
- Public transit agency responses to TNCs and AVs.
- Public acceptance and use of AVs and sharing them for regular travel.
- Public acceptance and use of new modes such as e-bike and e-scooters.
Despite the unknowns, we tested the potential AV effects using traditional regional travel forecasting models. In our case, we tested scenarios using models from seven regions across the United States combined with similar test results from two additional regions. All model runs include full market penetration of AVs in the horizon year of the models, which was 2035 or later, and AV-related changes to the following travel forecasting model variables related to travel behavior.
- Terminal time — Travel models define the time needed to park your car and walk to a destination as “terminal time.” The higher a terminal time, the less likely a person will choose an auto for a particular trip. AVs are likely to reduce terminal times by eliminating the need to park and providing on-demand door-to-door service.
- Parking cost — Most models include a variable for parking cost in areas where costs are imposed. AVs have the potential to lower or even eliminate these traditional parking costs.
- Value of time — Travel models also incorporate the value of time, but in different ways. Travelers using AVs will have lower values of time because the opportunity cost of driving will be reduced.
- Auto availability — Models generally have variables tied to trip rates and auto availability. AVs may increase trip rates due to their greater convenience and ready availability. Greater convenience could lead to more discretionary vehicle trips for shopping, social, leisure or recreational purposes. Additionally, people not licensed to drive will be able to make vehicle trips.
- Roadway capacity — As vehicles become more automated and connected, they offer greater potential to increase roadway capacity especially on freeways. The increase in capacity will come from shorter headways, less weaving and more stable traffic flows. Roadway capacity will increase first on freeways and expressways, then on major arterials.
- Auto operating costs — Vehicle travel has costs associated with purchasing or leasing, operating and maintaining the vehicle. Travel decisions tend to focus on the operating costs such as fueling the vehicle and can be expressed in a model as a per mile cost to capture higher costs for longer distance trips. For AVs, operating costs are expected to be lower due to electrification of vehicles and potential for vehicle sharing.
- Auto occupancy — Auto occupancy is the number of persons per vehicle and it has a substantial effect on the number of vehicle trips and related effects on how the roadway network operates. We test traditional levels of auto occupancy and a scenario with higher levels of shared trips (carpooling).
The general expectation from testing AV effects was that vehicle travel likely would increase and transit ridership would decrease for the main reasons cited at the beginning of this article.
- AVs will reduce the cost of vehicle travel (in both money and time).
- AVs eliminate the task of driving.
- AVs will reduce the potential for collisions.
- AVs will make vehicle travel more convenient.
This is the first article in a two-part series. Look for the next article to be published in the next week.