Smart Transit Tech Will Get Cities Moving Again
Bus transit will play a vital role in reviving city economies in the post-pandemic era. But in order to maintain safe, reliable and efficient bus service, cities must ensure dedicated bus lanes remain clear from illegally parked vehicles. Innovative computer vision technology, aided by machine learning, is making it easier than ever for cities to enforce parking and keep buses running on time.
A successful bus system requires proper enforcement, however. Cities must be able to effectively monitor illegal parking to ensure bus lanes remain clear for timely transit and safer streets. Traditionally, that has been done manually, with parking enforcement officers on the street – an inefficient process that’s difficult to scale. Some cities have begun using fixed cameras to aid enforcement, but their scope and efficacy are limited.
For a more modern approach to enforcement, cities are exploring how smart computer vision technology and automated intelligence can help get buses moving again. By mounting these vision devices on buses themselves, transportation leaders can instantly create a citywide enforcement network covering every route in their bus transit systems.
“Smart transit ecosystems and smart cities are not just about pushing the boundaries of technology, but central to the ideas addressing social and environmental issues such as accessibility and sustainability,” says Chris Carson, CEO and founder of Hayden AI, a technology company that provides smart vision solutions to cities. Speaking on a recent webinar, Carson discussed how proper enforcement has a broad impact on cities’ transit goals.
Smart vision technology improves the safety, sustainability and equitable delivery of public transportation, Carson says.
As people return to work in cities and suburbs, transit officials can leverage technology tools to make their infrastructure ready for the future.
“I think the approach transit agencies must take is to embrace technology, seeing it as a growth opportunity – an opportunity to innovate,” Carson says. “As we clear more bus lanes, buses speed up. As buses speed up, more people ride the bus.”
To strengthen and expand enforcement, cities can install AI vision devices not just on transit buses but on school buses, street sweepers, garbage trucks, police cars and other fleet vehicles. Data can be aggregated and insights shared across multiple agencies, creating an even more comprehensive enforcement system.
Aligning with National Infrastructure Goals
The White House has made infrastructure investment a key priority, and technology will play an important role in improving transportation systems, Carson says.
“President Biden is pushing for an overhaul and upgrade to the nation's infrastructure, calling it a transformational effort that could create the most resilient innovative economy in the world,” he says. “It's time to embrace technology to create safer, smarter and more sustainable transit ecosystems.”
Machine learning and computer vision are among the most important emerging innovations that will fuel that transformation effort, says Vaibhav Ghadiok, Hayden AI co-founder and vice president of engineering, who also participated in the webinar.
“Machine learning, especially applied towards computer vision, has made significant leaps in the past decade,” Ghadiok says. With vehicle-mounted devices, “we’re building a rich [three-dimensional] map of the environment that differentiates sidewalks, bus lanes, parking meters, fire hydrants and other components.”
An AI camera system identifies vehicles, via license plates, that are parked in bus lanes. The system integrates enforcement days and times, and can automatically send information on a vehicle to a violation processor at the transit agency for further action. The technology can be updated to account for temporary events such as parades and parameters can easily be changed as needed.
Greater parking enforcement can significantly improve the efficiency of bus transit. In a pilot program of its devices in New York City, Hayden AI saw bus speeds increase by 50 percent or more, Ghadiok says.
“We're improving the on-time performance of these buses [and] reducing passenger wait times, which leads to increased ridership.”
Enforcement is just one use case for AI and computer vision technology. It can also be used to identify parking meters, so cities can improve parking management. In addition, it can be used to alert drivers to available parking spaces nearby, alleviating the problem of driving around continuously looking for parking. The technology can even perform traffic pattern analyses to determine how many pedestrians are walking across an intersection at certain times of the day.
In the future, these systems could be used to schedule curb space, enabling, say, a delivery truck to park in a typically restricted area for 15 minutes to drop off packages.
All those uses will help create a smarter, unified network of enforcement. And as cities invest in new infrastructure technologies, vehicle-mounted computer vision devices – powered by AI and machine learning – will play a critical role in ensuring safe, efficient and effective transit systems for years to come.