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

TL;DR

The paper investigates real-world on-street SP deployments by surveying ~25 implementations and conducting semi-structured interviews with practitioners from ten cities. It provides a three-way SP taxonomy (Payment Systems, Occupancy Detection Systems, Integrated Smart Platforms) and analyzes deployment scales, technologies (ground sensors, cameras, and ANPR), data delivery to drivers, and governance models. The findings reveal wide contextual variation in goals, technology mixes, and outcomes, with robust before–after metrics available only in a minority of cases; sustainability hinges on funding, maintenance, and policy integration rather than technology alone. The study offers practical guidance for researchers and practitioners on persistent data governance, scalable sensing strategies, and the need for transparent, policy-driven use of SP data to reduce cruising, improve revenue, and inform curb management.

Abstract

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.

Figures (10)

• Figure 1: Steps followed in this paper.
• Figure 2: A variety of SPS: Pictures of smart parking cameras & sensors.
• Figure 3: Geographic distribution of the cities whose SP implementations were globally reviewed and/or used as case studies.
• Figure 4: Evolution of the academic literature about SPS between 1999 and 2025 (July, 2nd)
• Figure 5: Evolution of Service Providers and Milestones. The thick coloured lines start at the foundation of the company or the first implementation and terminate at its end. There may occasionally be an uncertainty of one or two years about these dates.