Author: Jayden Carter, Dixon Resources Unlimited

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In recent years, there has been an increase in the technology utilized in the parking industry. While parking had traditionally been a static element of urban mobility, within recent years, there has been a vast increase in the availability of parking transaction data, sensors, license plate recognition (LPR) systems, and mobile parking applications. These advances have opened the door to new opportunities for smarter parking management. Through data, the parking industry is shifting towards a proactive approach – using data to understand current conditions and forecast future trends to optimize operations (Into Tesler 2021).

One of the most valuable applications of data in parking is the ability to display occupancy trends. By analyzing historical meter transactions, LPR data, time of day, and special events, data models can forecast where and when parking demand will peak. These trends allow operators to prepare in advance by adjusting pricing strategies, deploying enforcement staff more effectively, or communicating availability to the public. In the same way that the public can use Apple and Google Maps to forecast predicted drive times based on historical trends and current conditions, the data can be harnessed to predict the availability and demand of parking on a given day, location, and time.

This approach has a multitude of benefits: drivers can save time, and operators will improve space utilization. Reducing the time that drivers spend searching around for parking will also reduce vehicle emissions, which aligns with sustainability goals. According to a study from UCLA, it is estimated that cruising for curb parking in just the 15 blocks of Westwood Village creates about 950,000 vehicle miles per year. This is equivalent to 47,000 gallons of gasoline and 730 tons of carbon dioxide per year (Hurst 2014). This represents merely a 15-block portion of the expansive Los Angeles County area. It is necessary to minimize the parking search for drivers to lower vehicle emissions.

Current data applications in parking operations focus on real-time monitoring, historical trend analysis, and compliance monitoring. This technical infrastructure requires systems capable of processing large volumes of information from diverse sources, with data quality and consistency being substantial factors in achieving proper results. While building up the infrastructure to handle vast quantities of data is a hurdle, DIXON is rapidly evolving alongside the increased data demand.

Data analytics, machine learning, and predictive modeling are unstoppable forces that will continue to revolutionize the parking and transportation industries. It is unlikely that real-time parking data will become accessible to the masses within the coming years. Despite this, taking a proactive approach by forecasting parking occupancy is fully within grasp. As the parking industry continues to evolve, DIXON continues to evolve with it. The DIXON Data Suite® provides cities with the analytical foundation necessary to transform parking operations towards strategic optimization. This foundation provides the basis for continued innovation and improvement in parking operations across diverse environments.

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Into Tesler. (2021). No Parking? No Problem! Intetics Creates a Predictive Modeling Solution to Alleviate Parking Congestion. Retrieved from https://intetics.com/blog/no-parking-no-problem-intetics-creates-a-predictive-modeling-solution-to-alleviate-parking-congestion/

Hurst, M. (2014). Q&A: UCLA’s parking Guru Donald Shoup. Retrieved from newsroom.ucla.edu/stories/q-a-ucla-s-parking-guru-donald-249859

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