How Autonomous Vehicles Will Influence the Future of Travel

by Aug 29, 2018Mobility

Ronald T. Milam and William (Billy) Riggs

Ronald T. Milam, AICP, PTP is the director of evolving the status quo with Fehr & Peers and co-leads the firm’s research and development. In addition to consulting and research, he teaches transportation planning and advanced transportation analytics courses for UC Berkeley Tech Transfer, UC Davis Extension, and UC San Diego Extension.

William (Billy) Riggs, Ph.D., AICP, LEED AP is a global expert and thought leader in the areas of future mobility and smart transportation, housing, economics and urban development. He is a professor at the University of San Francisco School of Management, and a consultant and advisor to multiple companies and start-ups on technology, smart mobility and urban development.

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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 policy makers 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, and then wrap up with some suggestions of what communities can do now 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:

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 further reduce individual traveler costs and is made convenient by app-based technology through smart phones.


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 now available for other purposes.


Reduced potential for collisions.

AV technology offers the potential of computer and sensor-aided travel that is 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.


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 (see image below).  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.

UBER vehicle choice and service offerings in a suburban market. Source: UBER app accessed April 2018 in Roseville, CA.

These changes create strong possibilities for increased traffic generation, loss of transit ridership, reduced parking needs but increased curb space demands, raising important decision-points for public agencies. To date, public agency action has been limited. Although some municipalities like London have restricted new mobility services, public agencies in the U.S. have largely accommodated disruptive transport. Evidence includes things like 1) the explosive growth of TNCs and 2) the openness to AV testing on public streets. This is happening around the world, in states such as California (where recent laws are focused on reducing vehicle travel and encouraging more active transportation), but also in multimodal havens like the Netherlands.

In light of this, a key policy question is, “What motivates this accommodation?“ This is a central question because, 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 currently incentivized to increase the use of vehicles while the public sector in many cities and states like 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 unknown reactions below.

  • 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 US 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 (i.e., carpooling).

The general expectation from testing AV effects was that vehicle travel would likely to 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 on Meeting of the Minds during the week of September 3rd, 2018.


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  1. AV will change the purchasing habits of the South. Pickup trucks are the biggest profitable products for automobile manufacturers. AV will separate the pickup truck bed from the cab as now the bed alone can navigate as a ground drone and bring home any larger object that can be carried in the pickup truck bed. This without adding tremendous aerodynamic drag to the people-moving half of a pickup truck. An eight times improvement in energy efficiency can be had by AV running ground drones instead of Southerners firing up a diesel dually to go pick up a pack of cigarettes and the convenience store. AV will allow the vehicle to be on the human scale saving tremendous energy and cleaning up our air to healthy levels once again. MIT study says 200,000 Americans die 10 years or more early from air pollution. 53,000 of those being from automobiles, pickup trucks, SUVs, big rigs and diesel buses. Oh and VW diesel cheaters.

  2. The potential impacts of AV on and from Public Transportation agencies will become important as their fleet penetration rates increase. Without some policy guidance from legislators and possibly utility regulators we can have widely varying regulations placed on AV’s.

  3. As with so much written about this subject, the assumptions on which this article is based are tendentious and unlikely outcomes. There is nothing about how the transformation to AVs will occur, nor whether ultimately it is technically feasible. There is no shortage of barriers to this Nirvana/Dystopia – read my book Driverless Cars: On a road to nowhere (London Partnership Publishing ) or an analysis of some of them.


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