Location, Location, Location
Optimizing Multi-Space Meter Placement with Analytics
Recently, the City of Cincinnati embarked on an aggressive parking modernization plan, Cincy EZPark, a vision for making parking more convenient for motorists. In addition to matching rates to demand, implementing pay-by-cell options, and improving meter uptime, the city installed more than 100 multi-spaced parking meters (“MSMs”) to make parking easier and reduce on-going maintenance costs.
An initial challenge faced by Cincinnati was determining just where the new MSMs should go. There are some common-sense guidelines for installing parking kiosks (such as do not block ingress or egress points). But other than a quick cost-benefit analysis and location survey, the industry hasn’t provided much guidance for determining the best location for parking meters, let alone prioritizing their installation. Cincinnati resolved to tackle this challenge using data.
In addition to revenue, productivity, and cost savings, one measure of success is convenience, or expedience.
The Queue Breakthrough
In solving this problem, Cincinnati started with the premise that every block is different. That may sound like common sense, but all too often meter technologies are installed without thought to how curbside spaces are differentiated. Take, for instance, 100 W. McMillan Street (“Block A”) and 1000 Delta Avenue (“Block B”) in Cincinnati.
Block A is characterized by a few spaces spread over a long distance. The metered spaces serve a few local restaurants as well as a number of residences. Demand is fairly evenly distributed across the day.
Block B, on the other hand, has many contiguous spaces. Serving mostly taverns, restaurants, theaters, and fitness centers, parking demand fluctuates significantly by hour of the day.
While both Blocks A and B may have similar average paid use (or the average percentage of metered hours paid), the hourly demand patterns—volume and occupancy—vary significantly, as do the hourly rates and time limits.
These differences matter. Curbside utilization, block length, and the number of spaces can influence the optimal curbside use of hardware, including:
• The prime location of the MSM on the block
• The prioritization of blocks in a neighborhood or across a city
To improve customer convenience when considering the installation of MSMs, conscientious parking planners should weigh the block length, the number or curbside parking spaces, transaction volume, peak use per hour, highest use in an hour, and transactions per minute. The table below demonstrates the relationship between these factors and how they might affect the placement of MSMs.
In addition to revenue, productivity, and cost savings, one measure of success is convenience, or expedience. Time is crucial to motorists, and, with that in mind, Cincinnati applied time as a metric in determining the placement
For example, the distance between the first and last space on a block determines how far a driver may need to walk to make payment, so the user experience can differ drastically from one block to the next. Someone parking at the end of a parking zone that’s 200 feet long will spend 15 to 20 seconds walking to the MSM (assuming the device is positioned at the block’s mid-point, which, as we’ll discuss below, shouldn’t necessarily be a given), while a motorist parking at the end of a 900 feet block (a standard block in Manhattan) will spend four to six times longer walking. The customer with less distance to travel is likely to have the better experience.
Factoring convenience into decisions about MSM placement can be difficult using standard reports. Consequently, data scientists built a proprietary platform using comparative data, weighing various considerations to prioritize blocks across the city and helping to identify the best locations for MSMs.
The platform accounts for a number of factors, among them:
• Utilization, including the average number of payment transactions per hour and the peak hours for transactions to reduce queuing, or long lines at the MSM
• The number of parking spaces and the length of the block to avoid long hikes to the MSM and reduce the likelihood of erroneous parking tickets
• Street views capturing ingress and egress points to inform installation decisions
After identifying a block as a prime candidate for an MSM, the team reviewed the street layout and transaction histories across the pre-existing single space meters (“SSMs”) to determine the best location for the device. Often, MSMs are placed in the middle of a block based on the assumption that usage trends from space to space are uniform (see “Case One”). Demand, though, is frequently uneven across parking spaces. Parking behavior is driven by proximity to merchants, restaurants, and other attractions, as well as characteristics of the space itself. Is the space protected by the shade of a tree on a hot summer day? Can the driver exit easily after parking there?
These considerations shape payment trends along the curb. Cities can optimize the location of MSMs to benefit more users, installing or relocating the devices to minimize the time it takes to pay for the majority of users.
Governing with—and in the Face of—Data
There are, of course, exceptions. While using data to drive parking policies provides transparency to the public, press, and elected officials, additional criteria may come into play from time to time. Municipal decision-making is an exercise in weighing the trade-offs between multiple objectives, including those that are seemingly subjective and incapable of measurement.
Data may suggest that an MSM be pushed to the north end of a street, but the type of use and uniqueness of stakeholders might suggest a different approach. For example, the MSM may need to be located farther south if placing it in the optimized position would:
• Interfere with a restaurant’s ability to have an outdoor café
• Hinder a merchant from holding sidewalk sales
• Inconvenience the elderly or infirm by locating the device too far from facilities like clinics or rehabilitation centers.
Using the prioritization analysis, the City has installed 111 MSMs in recent years (MSMs are denoted in blue; SSMs are represented in orange).
Properly managing transportation is data intensive. Parking is no different. This fact is underscored when one accounts for how interconnected parking policy is to the greater objectives of transportation, including achieving Vision Zero goals, mitigating congestion, and providing access.
The City of Cincinnati has made significant strides in moving from the basic level of data collection and reporting to the ultimate goal of using data to drive decisions and promote beneficial behavioral changes. Data can be used to manage every area of parking operations, and Cincinnati endeavors to continue to do so.
Specific to parking meters, the city has used data to guide decisions about hourly rates, hours of operation, and time limits. Cincinnati uses data to improve maintenance and reduce meter downtime and, in the future, the city plans to use meter data to study and optimize meter purchases, shifting the default purchase values up or down to match the requirements of customers, ultimately reducing button pushes and wear on the equipment. All the while the city will continue to install and monitor the locations of the MSMs, working to optimize their locations and policies as the neighborhoods where they’re located keep evolving.
Dan Fortinberry, CAPP, CPP, is Parking Facilities Division Manager, Cincinnati Department of Community and Economic Development; Eduardo Cardenas, MS, is Senior Data Scientist, Parking and Mobility Solutions, Conduent Transportation; Matt Darst, JD, is Senior Director, Parking and Mobility Solutions, Conduent Transportation They can be reached at: email@example.com; firstname.lastname@example.org; email@example.com