Dustin Harber

What Cleveland’s property growth tells us about the value of rapid-transit lines

Can bus rapid transit (BRT) line technology contribute to increased urban mobility and improved property values?

A recent study has revealed that bus rapid-transit lines (BRTs) can actually help increase the property values of multi-family locations in cities. The study was initially located in Ohio, and Cleveland was one of the cities to show this type of property value improvement.

A HealthLine bus travelling down Cleveland’s Euclid Avenue, part of the BRT. (Photo by Raymond Wambsgans/ CC BY 2.0)

Specifically to Cleveland, the study showed that overall residential property values grew by nearly 15% in close proximity to the Greater Cleveland Regional Transit Authority’s seven-mile HealthLine along Euclid Avenue from downtown Cleveland through University Circle to East Cleveland. The rate of value improvement was approximately 41.5% when isolated to the value of multi-family residences.

This is just one example of many urban locations that are making significant investments in transportation and transit systems across the country. These implementations are significant because they can link residents with critical infrastructures, such as schools and universities, hospitals and health networks, employment, retail shopping and recreational activities.

In addition to Cleveland, the study reviewed BRT systems in other regions, including Boston; Chicago; Eugene, Oregon; Everett, Washington; Kansas City, Missouri; Los Angeles; Miami; Oakland, California; Pittsburgh; and Seattle.

Does transit signal priority assist BRTs?

BRT is somewhat different from traditional bus lines since it offers dedicated service lanes, added frequency of routes, traffic signal priority, and elevated platforms and stations that travellers can easily access.

The transit signal priority system plays a significant role in providing the enhanced benefits of BRT. Many urban and municipal leaders today have been inquiring about this technology, what it is and how it works. This interest is now driven by the fact that BRT lanes currently utilise either radio or GPS-based transit signal priority (TSP). However, AI/cloud-based TSP is now leading the way in helping cities improve their mass transit systems to alleviate gridlock and traffic congestion, improve on-time performance of mass transit networks, assist in the arrival of emergency vehicles, and increase rider levels that have socio-economic and environmental benefits. 

How transit signal priority works

Smart traffic light systems and the cloud technology platforms they operate on are now designed to manage and predict traffic more efficiently, which can save a lot of money and create more efficiencies, not only for the cities themselves but also for drivers. Modern AI and machine learning technology can process highly complex data and traffic trends and suggest optimum routing for drivers in real time based on specific traffic conditions. 

Downtown Cleveland: the city has benefitted from its rapid-transit lines. (Photo by drnadig/iStock)

Conventional transit signal priority systems available today typically consist of two parts: a unit in the traffic cabinet and another unit placed on the vehicle. The transit priority logic is the same, regardless of the detection and communication medium. When a vehicle is within predetermined boundaries, the system places a request to the signal controller for prioritisation.

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Since the original systems used fixed detection points, signal controllers were configured with static estimated travel times. Since travel times are dependent on several environmental factors, the industry implemented GPS-based, wireless communication systems. With this method, vehicles found within detection zones replace the static detection points and the vehicle’s speed is used to determine the arrival time.

[Read more: Dar es Salaam’s bus rapid transit: Why it’s been a long, bumpy ride]

As a result of drastically improved processing power, transit system technologies can now take advantage of the huge gains made in the areas of AI and machine learning that were previously reserved for widely known tasks such as image recognition and apply them to long-standing traffic problems to generate insight on the mix of density, traffic and the overall rate of flow in a region. Furthermore, these optimised algorithms can analyse large volumes of data to learn not only local traffic patterns but also cross-region traffic flows, resulting in the ability to redistribute traffic flow more optimally for all users of our roads at all times of the day.

AI-powered transit signal priority systems leverage the power of the cloud to track and learn the patterns of transit vehicles to inform intersections of the arrival of these vehicles, giving them frictionless travel along their routes while minimising disruption to general traffic. Municipal transit systems can access these new insights from these systems to make better decisions that serve riders, their operations and their communities. 

These smart traffic platforms allow cities to build upon current investments in infrastructure to deploy city-wide TSP, avoiding the need to add the bulky and expensive field equipment of conventional signal priority systems. To enable safe and secure connections with traffic signals, each city requires just one device for use, which is a computer that resides at the “edge” and serves as the protective link between city traffic signals and the platform.

It is designed to securely manage the information exchange between traffic lights and the cloud platform. It is the only additional hardware necessary and depending on the existing city network configuration, the platform may receive vehicular data directly or via the city’s network using secure connections. Communities benefit from having smarter infrastructure that adapts to real-time traffic conditions instead of being stuck with statically programmed infrastructure that quickly becomes ill-suited to the dynamic nature of traffic.

Why BRT transit signal priority helps neighbourhoods

The number of US cities currently facing a housing crisis increases by the day, generating movements to demand the densification of single-family zoned neighbourhoods and the shift away from car-centric development patterns. Many densification efforts call for enhanced transit service to encourage residents to ditch cars in favour of transportation options that support denser development. Modern transit signal priority systems can serve as a tool to rapidly expand and enhance transit service without costly transportation infrastructure improvements that might hinder densification efforts. 

Now that transit signal priority systems can run primarily in the cloud, we’re entering a new era where transit agencies and partner traffic agencies can have their cake and eat it too; communities that want to make transit more reliable and accessible to their riders no longer have to disrupt the look and feel of their neighbours by tearing up their roads or sink precious community dollars into expensive signal or transit equipment.

Transit agencies can leverage data from cloud-based transit signal priority systems to show communities where infrastructure improvements make sense. Perhaps most importantly, advanced transit signal priority systems can also empower transit agencies to demonstrate meaningful progress towards climate emissions goals by minimising transit vehicle braking and idling time at red lights and utilising transit vehicles more effectively in operations planning. 

With these advanced transit signal priority technologies in place, urban regions and community hubs can enjoy a renaissance of mobility options, connecting residents with desired transit locations in a more efficient and environmentally friendly way. What’s more, the improved way of life will help these communities flourish in ways that translate into prosperity for everyone.

[Read more: In England, a call to regulate city buses]

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