Cities get help to orchestrate robotaxi pickup and drop-off

Authors: Bern Grush, Lee St James

Date Published: November 5, 2025

The robotaxi revolution is transforming urban mobility, but without proper coordination driverless vehicles are creating new problems. As more cities deploy robotaxis and automated delivery vehicles, there is an urgent need for a solution to reduce traffic chaos and improve urban safety.

The Urban Robotics Foundation's work on global standards has evolved significantly in recent years to directly address orchestration challenges. As global lead for the ISO 4448 series on public-area mobile robots (Part 1 published in 2024), the Foundation worked with an ISO Working Group to separate aspects related to robotic road vehicles into a dedicated standard series. This led to the development of ISO/WD DTS 25614-1: Intelligent transport systems—Orchestration of vehicles for fixed locations – Part 1: Reservation service. This is targeted for 2026 publication.

Ontario-based startup Pudocity Inc. has built a team and architecture to deploy a patent-pending implementation of this communication and data standard. Their orchestration platform tackles a critical challenge: enabling municipal and/or regional governments to manage autonomous vehicle pick-up and drop-off (PUDO) locations for passengers and goods.

Address a growing safety crisis

The safety implications of uncoordinated robotaxi operations are already visible in cities where autonomous vehicles operate. In San Francisco alone, Waymo accumulated 589 parking violations in 2024, including 138 citations for blocking street cleaning zones. These aren't just nuisance infractions—they represent genuine safety hazards.

Michael Brooks, executive director of the Center for Auto Safety, emphasizes that when robotaxis obstruct traffic flow, they force other drivers to brake suddenly or swerve unexpectedly, increasing crash risk throughout surrounding areas. In Austin, robotaxis have stopped and blocked roadways, while San Francisco has experienced incidents where autonomous vehicles impeded police and fire response, including running through emergency tape and blocking firehouse driveways. Without human judgment to navigate ambiguous situations, these vehicles need explicit coordination to avoid creating cascading safety problems across urban transportation networks. [1-4]

Coordinate PUDO demands using multiple data sources

Effective orchestration requires integrating multiple data sources within a comprehensive management system. The platform must maintain digital inventories of reservable spots with multi-dimensional spatial and feature specifications, operational parameters such as maximum vehicle dimensions and weight limits, and temporal availability schedules. Dynamic PUDO spot availability changes constantly based on construction activities, maintenance requirements, emergency situations, special events, and temporary restrictions.

Real-time traffic condition data helps predict optimal arrival times and buffer periods between sequential reservations. Historical usage patterns reveal demand fluctuations across different times of day, weather conditions, and seasonal variations. Machine learning models trained on accumulated data can predict dwell times, identify potential conflicts before they occur, and continuously refine assignment algorithms. Priority information ensures emergency vehicles, public transit, and utility services receive preferential access when needed.

By synthesizing these diverse data streams, the orchestration system can make intelligent decisions that optimize system-wide efficiency rather than simply matching vehicles to the nearest available spot.

Match beyond simple proximity

Pudocity's orchestration system promises to move beyond conventional proximity-based parking solutions that have proven inadequate at scale. Traditional closest-match approaches fail to account for spatial conflicts when multiple vehicles converge on adjacent spots, temporal issues when sequential reservations are scheduled too closely together, or the broader system impacts of concentrated demand in high-traffic areas. Instead, the platform evaluates potential assignments based on current spatial density, temporal conflicts with existing reservations, historical usage patterns, and the impact on system-wide efficiency.

The system can designate a spot slightly farther from the requested location if doing so reduces bottlenecks, maintains uniform density, or keeps high-demand spots available for priority vehicles. This intelligent allocation prevents the natural clustering that inevitably occurs when each vehicle independently seeks the closest available space.

Resolve spatial and temporal conflicts

Two critical dimensions of Pudocity’s orchestration promise involve managing conflicts in both space and time. When robotaxis are scheduled to arrive at adjacent spots near-simultaneously, the vehicle maneuvering required to settle can slow or block traffic and create congestion that ripples through the local area. The system identifies these potential conflicts and proactively assigns vehicles in ways that minimize these effects to dramatically improve neighborhood traffic flow.

For temporal management, the platform uses predictive models to determine optimal buffer periods between sequential reservations at the same spot, accounting for vehicle size, cargo type, passenger needs, time of day, and even seasonal factors like snow accumulation that can slow parking maneuvers. This prevents situations where delayed departures and early arrivals force incoming vehicles to wait or double-park in travel lanes, blocking through traffic.

Manage priority and emergency responses

Not all vehicles have equal claims to limited curb space, and effective orchestration must reflect such legitimate hierarchies. The Pudocity system implements priority schemes that ensure emergency vehicles receive immediate access during crises, public transit buses maintain reliable access to designated stops, and construction or utility vehicles can park near work sites.

When an ambulance of firetruck needs immediate curb access, the system identifies lower-priority reservations nearby and reassigns them to alternative locations—enabling emergency vehicles to arrive at required locations even before they reach the scene.

For public transit, the system maintains buffer zones around bus stops, preventing robotaxis from encroaching on transit infrastructure during scheduled arrival windows. This coordinated approach addresses one of the most significant current problems: autonomous vehicles do not reliably respond to gestured instructions from emergency personnel or transit operators.

Seek economic and environmental benefits

The economic implications extend far beyond avoided parking tickets. For robotaxi operators, eliminating time spent circling for available spots translates directly to increased vehicle utilization and revenue—a robotaxi that spends five minutes less per trip searching for locations can complete significantly more trips per day.

Cities stand to benefit even more dramatically through increased utilization of existing curb space, dynamic pricing mechanisms that discourage inefficient behaviors, and the recovery of monetary value from historically underpriced public space.

Environmental benefits accompany these economic gains: reduced circling means lower emissions, less congestion means improved air quality, and more efficient operations mean better energy utilization across the entire fleet. Pudocity’s orchestration system promises to capture value that currently goes unrealized while simultaneously improving transportation efficiency and environmental outcomes.

Use continuous learning while scaling regionally

Perhaps the most powerful promise of the Pudocity platform is its ability to learn and improve over time. Machine learning models trained on historical usage data identify patterns invisible to human planners—which locations experience highest demand during different times, how weather affects dwell times, what buffer periods are optimal for different vehicle types.

The system detects when particular spots consistently generate delays and adjusts assignment decisions accordingly, identifies underutilized locations and balances load across regions, and even learns inter-fleet operator differences to improve reliability. As autonomous vehicle deployments scale from dozens to thousands of vehicles across metropolitan regions with multiple competing operators, regional orchestration becomes not merely beneficial but essential.

No individual operator can solve system-wide coordination problems, and only a neutral third-party manager with visibility across participating fleets can optimize for collective benefit rather than individual advantage.

Conclusion: Focus digital infrastructure for urban autonomous future

The autonomous vehicle industry stands at a critical juncture where technical capability has already outpaced operational coordination. Pudocity's orchestration system, built on the emerging ISO 25614 standard, represents the missing infrastructure layer to unlock the full potential of autonomous mobility. Just as traffic signals coordinate vehicle movements and air traffic control manages aircraft landings on shared runways, this platform promises to coordinate access to limited urban infrastructure before uncoordinated growth creates unmanageable problems.

The technology exists, the economic case is compelling, and the safety benefits are substantial. The question isn't whether robotaxis will transform our cities, but whether that transformation will be chaotic or coordinated.

For more detailed information about Pudocity's patent-pending orchestration platform, reach out to bern@urbanroboticsfoundation.org for a copy of the Pudocity white paper.

Bern is the CEO of Pudocity and will be presenting Pudocity’s work live in Hamilton, Ontario, at the Future of Transportation and Mobility Series: “Rethinking Resilience for the Next Era of Mobility” on November 12, 2025. See more here:  https://ftms.citm.ca/

To stay up to date on developments with Pudocity, please fill in the contact form on their website: https://pudo.city/

[1] Dnistran, I, (2025) “Waymo’s Robotaxis Racked Up $65,000 In Fines Just In San Francisco” https://insideevs.com/news/754841/waymo-traffic-violations-fines-2024/

[2] Anderson, B. (2025) “Waymo Robotaxis Racked Up 589 Parking Tickets In A Year” https://www.carscoops.com/2025/03/waymo-cars-have-racked-up-over-65k-in-parking-violations-in-san-francisco/

[3] Chase, C. (2025) “Statement on New Automated Vehicle Framework” (Advocates for Highway and Auto Safety) https://saferoads.org/2025-nhtsa-av-framework-statement/

[4] https://www.youtube.com/watch?v=H9KCBAbsiWU

Image credit; image clipped from: AP Archive (2023) “Driverless Taxis navigate complex road to future” https://www.youtube.com/watch?v=Z9JpFdP8-B8