Smart On-Street Parking: Survey of Actual Implementations in Cities and Insights from Practitioners

Smart solutions for on-street parking, which collect and leverage real-time information about on-street parking space availability to guide drivers or adjust policies, have attracted considerable attention in academia and in the corporate world, but comprehensive feedback on actual implementations was still missing. Here, we survey around 25 smart parking (SP) implementations in cities across the world using online sources. To get more candid insights, we complement this objective review with case studies centred around interviews that we conducted with practitioners from ten cities across continents (San Francisco, Saint Pete Beach, Penang, Douala, Soissons, Grand Paris Seine Ouest, Montpellier, Frauenfeld, Zurich, Perth). Summing up our observations, we underline the broad diversity of SP implementations in terms of contexts and scales, from 2-to-3-year small-scale pilot studies to large deployments that take centre stage in a city’s mobility policy. Technological choices also vary widely, from the ground sensors used in pioneering deployments in the early 2010s and still in use, to static cameras (which cover more spaces per device), and to mobile cameras with automatic licence-plate recognition embarked in roaming cars, a more and more popular solution for parking control. Different attitudes to the role given to smartphone applications are also noticed. But, importantly, not only means, but also goals differ: facilitating parking control and enhancing revenue, or providing data for a curb-pricing strategy, or feeding live data into navigation algorithms to reduce parking search times. Unfortunately, their level of achievement is seldom gauged with robust metrics. Hardware durability issues are mentioned as causes of premature termination, particularly for `first-generation’ ground sensors, but so, too, are fluctuating political will and changing priorities. Smaller-scale, geographically isolated implementations and pilots are particularly vulnerable to these fluctuations, to discontinued funding or defaulting start-ups, and to limited public awareness.

💡 Research Summary

This paper provides one of the first comprehensive examinations of real‑world smart on‑street parking (SP) deployments worldwide. By systematically reviewing roughly 25 implementations identified through online sources and conducting semi‑structured interviews with practitioners from ten cities across five continents, the authors move beyond the technology‑centric focus of previous literature to capture the social, economic, and political dimensions that shape success or failure.

The study first classifies SP solutions into three functional groups: (1) payment‑related systems (traditional meters, smart meters, mobile payment apps), (2) occupancy detection systems (ground/overhead sensors, static cameras, mobile ANPR vehicles), and (3) integrated smart platforms that combine real‑time data, navigation assistance, and, in some cases, reservation services. The authors argue that only detection‑oriented solutions that provide quasi‑real‑time availability qualify as true SP systems for the purpose of this work.

Technologically, the paper highlights three dominant approaches. Ground‑based sensors (ultrasonic, radar, magnetometer) deliver the highest per‑space accuracy (85‑98 %) but suffer from high installation and maintenance costs and, especially for first‑generation devices, durability problems that often trigger premature project termination. Vision‑based static cameras, paired with AI object‑recognition, can monitor many spaces per device, offering a more cost‑effective alternative, yet their performance is sensitive to lighting, weather, and privacy regulations. Mobile ANPR vehicles, originally deployed for illegal‑parking enforcement, have evolved into roaming occupancy collectors; they provide city‑wide coverage with relatively low hardware density but depend heavily on image quality and algorithmic robustness.

The authors find that project scale and objectives vary widely. Some pilots last only two to three years and cover a few streets, while others constitute city‑wide platforms that are integral to mobility policy. Goals range from reducing driver search time and congestion, to increasing parking revenue, to supplying data for dynamic curb‑pricing schemes. However, most implementations evaluate success using a single key performance indicator (KPI), such as average search‑time reduction or revenue growth, which the authors criticize as insufficient. They propose a multi‑dimensional KPI framework that includes traffic flow, emissions, operational cost, data accuracy, and user satisfaction.

Operational risks emerge as a dominant theme. Hardware durability (especially of early sensors), fluctuating political will, unstable funding streams, and the collapse of start‑up vendors are repeatedly cited as causes of project abandonment. Small, isolated pilots are especially vulnerable to these shocks. Interviews reveal a consensus among practitioners that technology alone cannot guarantee success; sustained public awareness campaigns, reliable data quality management, and seamless integration with user‑facing apps are essential. The study also notes divergent attitudes toward smartphone applications: some cities (e.g., San Francisco, Perth) embed real‑time occupancy into navigation apps, achieving high adoption, while others treat apps as optional add‑ons, resulting in low usage.

From a policy perspective, the paper underscores the need for standardised performance testing, long‑term procurement contracts that mitigate start‑up risk, and open data standards that enable interoperability between SP platforms and broader urban traffic management systems. It recommends that municipalities adopt a holistic evaluation model, align SP initiatives with broader sustainability targets, and invest in citizen engagement to improve acceptance.

In conclusion, the research demonstrates that smart parking systems are not merely a collection of sensors and algorithms but socio‑technical ecosystems where hardware choices, governance structures, financial models, and user behavior interact. Future work should focus on longitudinal cost‑benefit analyses, the development of integrated platforms that simultaneously address multiple urban mobility goals, and the establishment of robust, multi‑KPI monitoring frameworks to assess long‑term impact.