Realizing the Autonomous Future with Road Pricing
From The Future of Urban Mobility and How We MOVE
With the MOVE America conference nearly upon us, we’re resharing our piece from MOVE America’s conference book. Note, Paul Salama, our Co-Founder & COO has long been interrogating the link between Autonomy and Pricing for several years; see assumption #8 from his first Medium Post: The 10 Assumptions of Autonomous Vehicles.
A Look Into the Mobility Future
The year is 2030, and, despite the naysayers, the autonomous revolution has arrived. And the version of this future that cities across the country are on their way to realizing is what Zipcar-founder Robin Chase described as Autonomous Heaven: Cars are autonomous and electric; rides are shared; development occurs vertically instead of sprawling, centered around downtowns that have mostly rid themselves of personal cars; and transit, now autonomous, is experiencing a massive resurgence.
Thousands of technologies and innovations have enabled what seemed like a pipe dream only ten years prior, but no single shift did more to facilitate this transition than cities’ fully embracing road pricing. All but the most tech-savvy cities are fighting the last battle with mobility providers, whose ability to optimize and exploit underpriced and under-regulated rights-of-way has kept them one step ahead.
Prior to the widespread adoption of road pricing, autonomous vehicles (AVs) magnified the revealed inadequacy of status quo techniques. While some cities tried banning AVs altogether or capping their number, others tried banning empty or “zombie” trips — all with little success.
21st-Century Digital Tools
The critical insight that led cities to road pricing was AV’s implicit requirement for hyper-accurate location awareness for safe operation. Their precision to the millimeter contrasts with standard GPS signals, which can only guarantee 10-meter accuracy, limiting their usefulness for road pricing applications.
With this innovation in place, the data to manage AVs is generated in real-time and collected by a trusted third-party or entity. And while it’s possible to use that data to simply ban unwanted AV trips, any economist will tell you that itis much simpler and more elegant — not to mention more lucrative — to charge for undesirable travel behavior.
With the adoption of road pricing, neighborhoods, cordon areas, corridors, lanes, and curbside loading zones are all dynamically priced. These prices reflect a vehicle’s contribution to traffic, its degradation of the roadway, and real-time competition for road space, among many other inputs & data points calculated for each leg of the trip.
Despite the multitude of factors that play into a trip’s cost, the passenger experience is seamless:
At the outset of a trip, the passenger is prompted to select route preferences, time constraints, and surcharge tolerance, and receives an estimated trip cost. Along the route, the AV makes hundreds of micro-decisions: whether to pay the surcharge to use the passing lane, take advantage of a slow lane discount in the face of unexpected traffic, reroute around a water main break, or travel down a scenic block that is new to the passenger. Finally, it decides how close to the destination the passenger should be dropped off.
Facilitating Integrated Mobility Planning
Cities soon realized that beyond road pricing’s obvious benefits for cities’ coffers — which was sorely needed with shrunken revenues from parking and enforcement — road pricing was also a mechanism for achieving an endless variety of mobility, equity, accessibility, and social goals. Discounts for low-income passengers’ trips from transit deserts paired with surcharges for trips along transit corridors, a five-minute loading zone grace period for persons with disabilities, negative charges for off-hour deliveries, incremental discounts based on occupancy, or part-time exemptions for vehicle-dependent small businesses are merely some of the policies possible with AV road pricing.
Cities also loved that they could endlessly test and iterate on pricing policies. Initially, they conservatively started with flat fees for all vehicles, akin to congestion pricing in the early 21st Century, and progressing to implement touchscreen (or perhaps holographic) dashboards towards setting targeted, differentiated pricing based on time, fine-grained locations, and later, real-time conditions. Cities were able to see the impact of each variation, via their dashboards, and how responsive vehicle behavior overall was to varying pricing magnitudes.
Cities then started distinguishing between vehicle and trip types: enacting different pricing structures for commercial fleets, MaaS operators, and freight vehicles; and coordinating with stakeholders from each segment, as the private sector was much more responsive to pricing schemes and additional charges. Finally, cities began tying road pricing charges to individual passengers, with specific discounts or transit credits based on their socio-economic status, line of work, or a wide variety of other conditions.
The Future of Road Pricing, Today
While some aspects of this may seem far off or even a fantasy, we can see many of these tools and policies in place today. From the private sector, TNCs like Uber and Lyft already charge passengers based on hyper-localized conditions and demand alongside trip time & distance, vehicle type, and whether it’s a shared ride (see image at left). This is done in real-time with smartphone data & GPS. Meanwhile, scooter companies are restricting access or speed on particular streets and identifying bike lanes and sidewalks using tools such as sub-meter accurate geofencing or cameras. On the other side, the public sector in fact employs a range of mobility policies, such as HOV lanes, dynamic parking prices, weight-based tolls, or low-emission vehicle discounts — although they are usually implemented in siloes and are rarely considered holistically.
This piecemeal approach, lacking any coordination or integration, is untenable. Cities now have a chance to learn from the new mobility providers how best to manage their streets using a singular road pricing system. Many techniques common to mobility companies have public-sector equivalents: surge pricing multipliers are equivalent to congestion charges, pooled rides are a TDM mechanism, siting shared scooters & bikes is equity policy. Private sector customers either accept the calculated prices for these services, or they don’t and attempt to find an alternative. Governments can leverage these same techniques to manage their streets. The future of our cities depends on it.
Interested to learn more about the Road Pricing of the future? Catch ClearRoad COO Paul Salama’s talk on Sept 3 at MOVE America. Get your passes/register here.
