Driverless Cars, Urban Parking and Land Use

Robert A. Simons

• Publisher: Routledge
• Year: 2020
• ISBN:
  9780429891076
• Edition: 1
• Topic: Architecture
• Subtopic: Urban Planning & Landscaping

The subject of driverless and even ownerless cars has the potential to be the most disruptive technology for real estate, land use, and parking since the invention of the elevator. This book includes new research and economic analysis, plus a thorough review of the current literature to pose and attempt to answer a number of important questions about the effect that driverless vehicles may have on land use in the United States, especially on parking. Simons outlines the history of disruptive technologies in transport and real estate before examining how the predicted changes brought in by the adoption of driverless technologies and decline in car ownership will affect our urban areas. What could we do with all the parking areas in our cities and our homes and institutional buildings that may no longer be required? Can they be sustainably repurposed? Will self-driving cars become like horses, used only by hobbyists for recreation and sport?

While the focus is on parking, the book also contains the views of real estate economists, architects, and policymakers and is essential reading for real estate developers and investors, transport economists, planners, politicians, and policymakers who need to consider the implications of a future with more driverless vehicles. Fasten your seat belt: like it or not, driverless cars will begin to change the way we move about our cities within ten years.

1 Introduction

No parking, fine! The effect of driverless vehicles on parking and land use

Robert A. Simons

Automated driverless vehicles (DV) are expected to provide the economic basis for mobility service fleets to thrive, thus generating a paradigm shift in personal mobility. Americans would be able to decouple from their personal vehicles while retaining their independence of movement, and reducing their travel costs and over-investment in idle assets (e.g., personal vehicles parked 95% of the time). Once the trend takes hold, in a decade or three, parking and land use in the urban core would be forever changed. This book sets out a range of intertwined futures that the DV revolution is likely to generate. However, the journey to a changed urban landscape is arduous, and we need to address many technical and behavioral issues before we can broach the land use issues.

I am not the only one working in this area: there are eight books on driverless cars or related topics and one on parking (an anthology of parking topics by Shoup, 2018) since 2015. I stand on the shoulders of these authors to bring the reader the latest and most reasonable DV adoption forecasts possible, given that forecasting itself is a tenuous art. Still, the books vary in quality and relevance. Some are brief and experiential (Jamthe 2017; Simoudis 2017) or deep but limited to technology (Wadhwa, Vivek, and Salkever 2017), and some of the authors are related to parties with a stake in the DV outcome (Burns and Shulgan 2018). I value academic books the highest when the author has no skin in the game (Bridges 2015; Kellerman 2018; Lipsom and Kurman 2016; Sperling 2018). However, most of these books lack data analysis, and I strive to provide as much analytical rigor as possible. Professor Mark Levine, Esq. from the University of Denver has also written on the topic, and I thank him for initially introducing the subject at an American Real Estate Society (ARES) meeting in 2016.

There is very little peer-reviewed literature on the topic, mostly because DVs as a serious research topic only dates from 2015 and, at the time of this writing (early 2019), barely enough time has passed (one to two years is normal for the peer review process) for much to have completed the process. Peer-reviewed work also tends to be narrow and deep, and there are huge gaps in coverage: really, only the modal-choice literature (how people choose to travel – car, bus, etc.) is populated for our benefit. To the extent that there is peer-reviewed literature, I value these sources highly in forming forecasts about DV adoption, which I did recently (Simons, Feltman, and Malkin 2018) and update for this book.

There is also a great deal of popular press and blogs on the topic. Most of it, while interesting, represents the opinions of professionals, many with a stake in the DV outcome, and much of it repeats the same general principles and ideas. For purposes of forecasting DV adoption, there is little value to this information. However, there are four exceptions: RethinkX, Tod Litman, real estate giant CBRE, and a series of analytical pieces that recently appeared in The Economist (UBS Bank, etc.) are rigorous enough to merit increased weight, despite the link between some of the authors and DV outcomes.

On the other side of the DV adoption spectrum are the parking interests that generally deny that DV would be adopted any time in the next 50 years, for obvious reasons. If demand for parking decreases substantially, their business model would be threatened to the core. Change can be hard.

A word on terminology. The popular press and other scholarly sources usually refer to this issue as automated vehicles (AV) rather than driverless vehicles (DV). Although the terms can be used interchangeably, I use DV in this book because it is the driver’s behavior – not the automation – that has the potential to cause major changes in parking and land use. It is the driver who would choose a fleet mobility service instead of owning a personal, manually-driven vehicle, and it is the driver who does not need to park his own car downtown next to his office. Further, autonomous car is a bit of a misnomer. These vehicles are certainly automated, but DVs would communicate with other vehicles and with traffic signal systems. Thus, they are not actually moving around disconnected from other entities as the name suggests. Successful automation of cars is key, but it is a phase we pass through, a means to an end. At the end of the day, it is the driver (now a passenger) we care about.

We use the generally accepted 5-level driverless vehicle scale as follows: 0 is pure manual driving, and levels 1 and 2 have driver-assist features, such as keeping a safe distance, maintaining safe speed, changing lanes, and parking, while requiring the driver to be otherwise in control of the vehicle. Levels 3 and 4 have the car’s automated system monitoring the external environment with vehicle-to-vehicle (V2V), and infrastructure-to-vehicle (I2V) communication, and with the system driving the car under most conditions. Here, the person in the “driver’s” seat (which may not have driver controls) would have to intervene only in rare instances, or, under ideal weather and road conditions, not at all. At some point, vehicles in this stage would be designed primarily for the passengers, not for the drivers, and would be marketed to mobility fleet (robotaxi) corporations rather than to individual car owners. By level 5, there are not expected to be any driver controls (i.e., steering wheel, gas, or brake pedals) in the vehicle; it is fully automated under nearly all weather conditions, no passenger is expected to intervene, and there are substantial improvements in road congestion, because so many cars on the road are DVs that they are all linked and move in a tightly-packed and efficiently-choreographed pattern. DVs are not assumed to be prevalent in rural areas and some manual drivers would persist even in urban areas for several decades.

This book is divided into four sections. The first includes background trends: technology (there are a dozen inter-related detection, mapping, and controlling technologies that need to work extremely well, in real time, for DVs to function safely) is described in Chapter 2 along with an accounting of current DV testing activity in the United States, and some projected costs-per-mile for various types of travel modes. Incidence and definitions of a dozen types of travel behavior (including driven personal cars, Uber, bicycle, bus, fleet-owned driverless cars, etc.) are addressed in Chapter 3, along with projections on consumer travel costs in the context of annual income. We show that, if properly implemented, DVs could provide annual cost savings equivalent to a 10% pay raise. We also share the results of a survey of more than 200 shared-ride customers on their willingness to ride in a driverless car. The book continues with Chapter 4 on government regulation of DVs in the United States at the federal agency (cars and highway safety, plenty of regulations), federal law (evolving, nothing comprehensive yet), and state levels (more than 30 states have passed laws or prepared executive orders) as of March, 2018. We also briefly address international laws on DV. Chapter 5 considers ethical issues related to DV evolution, including auto-related deaths, economic development potential or detriment, cyber security, the usefulness of human driver assistants, the ethics of data ownership, and who programs the DV to prioritize between pedestrians and passengers. The latter is sometimes known as the “Trolley Problem,” and we rely repeatedly in the book on a database of surveyed preferences collected by the Massachusetts Institute of Technology (MIT).

The second section deals with the transition period. Chapter 6 takes a look at the speed of past technology changes, including horses to cars, land lines to cell phones/smartphones, film cameras to digital cameras/smartphones, online retail shopping, and adoption of Marijuana Legislation in the United States. We use the tech adoption experience of these five industries (how fast they achieved key market penetration threshholds) to guide our own DV adoption forecasts. The next chapter (7) includes the parking industry’s view of the unlikely adoption of DVs in our lifetimes. Its analysis of that position was supplemented by published statements by an outside technology leader and independent system security expert. Next, we look at any early harbingers of stress in the parking realm. We found very little solid evidence of weak parking prices in several major United States markets, only glimmers of possible negative effects when looking at parking investment portfolio data, and we conclude that it is probably too early in the DV adoption cycle to see any systematic real market impacts on current parking prices. Concluding this section, Chapter 9 sets forth our nested tripartite forecasts, considers when DV is likely to be adopted, and provides a more nuanced range of low, medium, and high DV adoption forecasts, through 2050.

The third section, starting with Chapter 10, finally deals with parking and land use. We cover baseline parking ratios and policy in United States cities, especially at parking minimums and free, on-street parking. With the help of an architect, we address the economics of reuse of a surplus parking structure (very few are suitable for adaptive reuse due to sloped floors) in Chapter 11. Next, Chapter 12 looks back at underlying demand trends for parking in 15 urban areas, especially at use of cars in residential commuting patterns, access to vehicles, and selected parking ratios. There are around three parking spots for each dwelling unit in most metro areas. Just imagine: there is almost as much square footage devoted to parking as to living area! Chapter 13 looks at potential mobility fleet staging areas. Since car fleets would need to be serviced, we posit how big they should be (able to accommodate about one-tenth of total downtown parking), and where they could be located (stadium parking lots and shopping malls), which is addressed for the Cleveland, Ohio market. Chapter 14 is the last chapter in the section, and, with an architect co-author, we look at how DV adoption could change home garages and land use planning for subdivisions in a DV world. We also provide some site layout designs for adaptive reuse of garages in suburban locales.

The last section (entirely written by me, Robert Simons) looks at policy in the transition period (DV adoption with DV penetration rates of 2% at the beginning and up to 30%+ of the market, through about 2035) in Chapter 15. The transition period contains numerous policy recommendations on accelerating technology adoption, buttressing demand, investment, parking and urban planning policy, economic development, and ethical issues. Chapter 16 focuses on the long term (with substantial DV adoption up to 80% of the market, through 2050), and provides more recommendations, plus a detailed look at first-order job creation and losses, by major industry, attributable to DV adoption (also broken down into primary – taxi, truck, and bus drivers, secondary – support industries such as car insurance and body shops, and tertiary effects – re-education, oil refineries, etc.), under three DV adoption scenarios in the United States through 2050. The last policy chapter (17) considers policy outside the USA, primarily in China and Europe. It includes forecasts for DV adoption for about ten leading countries, and a detailed look at vehicle-programming moral choices across the world, from the MIT MoralMachine project.

We also set forth three case study chapters. One (Chapter 18) is a compilation of short abstracts of the eight known adaptive reuse examples of parking structures. Half of these are existing structures in the US, the balance is proposed or under development, or outside the United States. Chapter 19, featuring “The Wedge,” is a detailed look at a clever strategy used in Grand Rapids, Michigan to build a new, six-story plus, public parking deck while piggy-backing onto an existing contiguous structure for access, and also retaining the possibility for future adaptive reuse. Chapter 20 is a case study of the adaptive reuse of a warehouse parking structure into a hotel in Cincinnati, Ohio.

Background trends

Chapter 2 on technology covers the five federally identified stages of driverless vehicle (DV) adoption (where 0 is manually driven rising to 5 with total automation) and the three phases of DV implementation (transition, partial, complete) that weave in the four main threads required for DV to succeed: driverless car technology, electrification, evolution of mobility fleet services, and acceptance of strangers by vehicle passengers. We also introduce the dozen or so technologies (RADAR and similar technologies, inter-related cameras, highly accurate digital maps, artificial intelligence, and the vehicle controlling technology) needed to make it all work reliably. After this primer, we look at testing and adoption of DV systems to date, starting with the United States government’s first tech challenge about 2004. We address the DV activities of Waymo, Tesla, Uber, and some of the big car manufacturers, and look at their bets on the DV future. We spend some time on the compelling case for the feasibility of mobility fleet economics, reducing the per-mile cost of travel in United States urban areas from about $2.50 per mile for an Uber, to $0.85 per mile for an average, privately-owned car, down to $0.25 per mile for a DV. Are cost savings equivalent to a 10% raise enough to lure Americans away from their private cars?

Chapter 3 addresses behavioral change, tastes, and preferences for car ownership. Written jointly with three co-authors (Jon Richmond, Daniel Simons, and Howard Goldberg), we identify several DV-related issues. First, we address eight transportation modes. Six exist today – walking, driving a personal car, public bus/train, bicycle, taxi/hired vehicle, and other (scooters, jet packs, etc.). Three modes are emerging: driverless personal vehicles (e.g., Tesla), solo-use hired vehicles (Uber/Lyft or driverless, overtaking taxis), and shared hired vehicles, also driverless (key to cost reduction). The chapter also examines the peer-reviewed literature on model choice published since 2010, mostly using survey research or simulation modeling. We also address “I love driving,” especially among Millennials, who show a surprising willingness to move away from personal vehicle use. After review of the peer-reviewed literature, and an analysis of the cost of personal travel, we also report the results of a survey of 214 shared-ride service customers (e.g., Uber, Lyft, etc.) in North Carolina, primarily on what activities they engage in when they are in a shared-ride vehicle, and if they would consider riding in a driverless car under a few scenarios. My co-authors for Chapter 3 are transportation planning Professor Jon Richmond, Howard Goldberg, and Daniel J. Simons, who ran the statistics on the survey.

Chapter 4 covers government regulation for DVs in the United States. Written jointly with lawyer Tod Northman and law student Jeffrey Carr, we systematically cover the United States federal and state laws and executive orders pertaining to DVs. Since laws are essentially embodied societal ethical values, we seek to look at the regulations through the lens of two competing claims: safety and economic development. We find some substantial progress made at the federal level (e.g., the NHTSB) in terms of agency definitions of what a driver and vehicle are, and pertaining to highway safety. However, there is no overarching federal legislation on driverless vehicles, either allowing or forbidding it. At the US state level, however, there is a wide digression. As of November 2018, 26 US states had passed DV legislation, seven had executive orders, and four had both. California, Arizona, and a few other states lead in allowing DV on-road testing, and, therefore, also lead in DV industry development. Analysis of these regulations shows they are primarily driven by both safety and economic development. We also briefly address the overseas DV regulatory environment, which is generally more conservative than the United States in prohibiting testing on public streets.

Chapter 5 addresses the ethics of the DV transition. Authored with Tod Northman, Jeffrey Carr, and Alexandra Malkin, it looks at a grab-bag of ethical topics related to DV evolution. These include underlying principles of equity economics, vehicular mortality and safety trends, ethics of job losses for taxi and truck drivers, car manufacturers, mortuaries, insurance, and other industries related to DV technology (potentially about 7% of the US economy could be directly or indirectly affected), the disposability of the car’s occupants (MIT has a great website on this moral dilemma) and who programs/decides who lives and dies in the event that a DV faces a horrible set of choices in a lose–lose situation. From the insurance angle, we address who would likely be responsible for an accident involving the vehicle (likely, primarily the software company), including shared responsibility of the vehicle owners and passengers or driver-assist operator. Fina...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• List of exhibits
• List of tables
• Notes on contributors
• Preface
• Acknowledgments
• Abbreviations
• 1. Introduction: no parking, fine! The effect of driverless vehicles on parking and land use
• 2. Identification of major vehicle-related hardware and technological trends
• 3. Tastes and preferences and behavioral change in transportation modal choices and car ownership
• 4. Government regulation of the transition to driverless/autonomous cars
• 5. Ethical issues from the transition to driverless/automated cars
• 6. The past adoption and transition time periods of five disruptive technologies
• 7. A road too steep and too long: the scientific case against plausible evolution of driverless cars
• 8. Any early signs of softness in the parking markets in capital markets and parking sale prices?
• 9. The forward-looking adoption timeline for driverless cars and corporate owned fleets
• 10. Current parking regulations and parking market standards in the United States
• 11. Urban adaptive reuse potential from the architect’s perspective
• 12. A breakdown of parking spaces by type in 15 US metropolitan areas
• 13. Where would the driverless car fleet rest during the day?
• 14. Parking at home: transformational changes at the unit and subdivision levels
• 15. Policy implications: transition period
• 16. Policy implications: in the long run
• 17. Policy implications and generalizability to large European and Asian cities, plus some final thoughts on DV adoption
• 18. Introduction to parking structure adaptive reuse case studies
• 19. The Wedge: a parking expansion and adaptive reuse case study in Grand Rapids, Michigan
• 20. The Summit, a Dolce Hotel: an adaptive reuse of a parking structure in Cincinnati, Ohio
• Index