A relatively low-density city designed around the car. Public transportation service that meets its published schedule only 71% of the time, leading to customer satisfaction of only 65%, while the fare recovery is only 15% (passengers only pay 15% of the actual cost with government subsidies making up the difference). Although the above sounds like a description befitting most any U.S. post-World War II city, this is how the creator of a software simulation program and associated white paper describe Canberra, Australia’s current state of public transportation.
A 21st Century Approach to Transportation Design #
Kent Fitch of Project Computing, an Australian software company, states the problem if planners and politicians continue to design transportation networks with a 19th or 20th century approach:
“However, no incarnation of the current bus network nor even an extensive light-rail system can be imagined which meets these goals [decreased traffic, pollution, better health and safety, affordable and efficient public transportation], short of “starting again”: abandoning the 100 sprawling, far-flung suburbs of the “bush capital” for a high-density new city. Hence, both bus and light-rail are distractions from meeting the city’s transport goals, but are being pursued only because no better alternatives are perceived.”
Fitch has created an impressive software simulation that allows anyone to set various parameters of what would be an autonomous vehicle public transit system. Of course it has the limitation of being a model, but the results shout out to planners and city leaders everywhere, that self-driving vehicles need to be a big part of the discussion of both the transport (public and private) and built-environment future.
As shown in his model, the benefits of autonomy increase, as more people choose shared autonomous transport over private vehicles. For instance, his worst-case scenario, where the number of journeys equals that of the current bus system, yields a 90% subsidy reduction, (A$120M to A$12M), elimination of the 92 grams of CO2-e per passenger km attributed to buses, while increasing peak-time congestion (which could be mitigated by increasing wait-time). As the number of journeys increases, costs continue to decrease, while congestion also decreases because of the shared nature of the autonomous vehicles.
‘Traffic congestion is dramatically decreased, particularly during peak periods on major roads. For example, the average occupancy of cars arriving is Civic and Parkes is 2 passengers, compared to an estimate of 1.13 for current journeys to work.”
His work reinforces studies from others (e.g. Fagnant) regarding improved transport efficiency and pollution reduction (elimination of tailpipe emissions) from sharing autonomous vehicles, as well as other societal benefits (Godsmark suggests $2,700 annual net benefit per household (PDF).
The challenge is the transition from today’s scheduled transport world, with its high-fixed costs, to one that is on-demand and where resources can scale much more closely match demand. How does one get the benefits without prematurely abandoning capital or increasing congestion along the way?
A First Step – Bus Feeder with Autonomous Last Mile Transport #
A scenario that could potentially address the transition and that would be a good candidate to add to Fitch’s model is one that combines the existing bus system with lower-cost, last mile autonomous transport. That is, existing, human-driven buses would be used as feeders on major thoroughfares. Bus stops between thoroughfares would be eliminated and replaced with transit plazas at the intersections of the major thoroughfares. Autonomous vehicles would provide last-mile transport.
Being unfamiliar with Canberra, Australia, this author examined a small portion of Silicon Valley to understand what these assumptions might mean:
- Buses would not be eliminated, but routes would be streamlined, such that they would be on major thoroughfares generally traveling East-West or North-South. Bus stops between intersections (now, as often as six per mile) would be eliminated. These two things alone would reduce transit time for riders (fewer stops) and reduce the congestion caused by buses navigating their way into and out of traffic from bus stops. Of course, this approach doesn’t preclude the use of bus-only lanes, but even those type of lanes could be made more efficient by running in half-duplex mode, such that only one lane would be required for both directions (assuming 45 MPH and a mile between transit stations, then it would take less than 2 minutes to travel between plaza stations, which would easily allow up to a 5 minute frequency between buses.
- The ideal transit plaza would be a mixed-use, multi-level development that covers major intersections, such that it doesn’t interrupt the existing traffic flow, but provides a way for the autonomous vehicles to feed passengers to the aforementioned buses (e.g. the buses and autonomous shared ride vehicles would converge on a level above the traffic).
As much as these structures would be about improving traffic flows, they would also be about creating new land in a place where land is extremely valuable. An estimate suggests that 30 acres could be gained in one 3.2 square mile alone. With Silicon Valley land typically ranging from $1 to $4M per acre, this could mean unlocking $30 to $250M of value. Not all of these plaza sites would be able to take advantage of mixed-use and might have limited use (e.g. mini-parks, plazas), while others could support multi-story developments and include things such as housing, businesses and shopping.
Any housing and jobs created at these sites would be at ideal locations, as they would be at transit hubs. Additionally, the government entities that own the underlying land could consider creative ways to create affordable housing above these publicly owned air spaces.
- Autonomous last mile transport is assumed using vehicles such as the one from AuRo Robotics that is being tested with real-world traffic at Santa Clara University. These type of vehicles would most likely be even lower cost than the $40,000 per vehicles cost that Fitch assumed in his model. Given that these are lower speed vehicles (25 MPH maximum), safety is enhanced and it would more easily pass regulatory hurdles than a car designed for highway driving. AuRo Robotics suggests 2016 for commercial introduction for their vehicles, so autonomous vehicles, in some form, will probably be available before society at large is ready.
These sort of vehicles could impact the built environment, freeing up more land for use by people and not their cars. That is, with larger developments, roads for traditional vehicles could be eliminated or reduced. Parking for private cars could be at the aforementioned plazas or at the edge of a development (away from housing). These smaller autonomous vehicles would ferry people and their goods within the development.
Government Transit Agencies Should Build on Fitch’s Work #
One of the really cool things about Fitch’s model is that it is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. That means that anyone (with the right kind of software knowledge, of course) can adapt Fitch’s model to see how variations, such as the one given above, impact the economics and quality of public transport. This is something that transit agencies should be doing as a matter of course to ensure that they are using the public’s money wisely.
Of course, it wouldn’t be surprising to see private companies jump in on this opportunity. For instance, Alphabet (i.e., Google) already runs a bus fleet for their employees and they have their well publicized autonomous vehicles. As written previously, mobility as a service could be a significant business rivaling its traditional search business.
Regardless of whether it is government, private enterprise or combinations of public-private partnerships, autonomy is set to disrupt mobility. Kent Fitch’s model is a good starting point in understanding the potential impact of this disruption.