Skip to main content

South Nevada RTC provides bus crowding data 

Transit's app will help passengers make decisions about socially-distanced journeys
By Ben Spencer January 19, 2021 Read time: 2 mins
Transit shows current crowded levels listed as ‘many seats', ‘some seats’ or ‘very limited seats’ (© Sharaf Maksumov | Dreamstime.com)

The Regional Transportation Commission of Southern Nevada (RTC) has entered an agreement to provide customers with real-time crowding information via the Transit app. 

RTC says the new feature helps riders make informed decisions about trip planning and social distancing.

Transit is an app that allows users to navigate public transit with real-time predictions, tip planning, navigation and payments. It also integrates bike-sharing, scooters, car-sharing and ride-hailing. 

MJ Maynard, RTC chief executive officer, says: “As we continue to navigate through this pandemic, we are operating our transit vehicles at a 50% capacity to allow riders to practice safe social distancing."

"We’ve made this safety commitment to our passengers, and we are taking that commitment a step further by providing our riders with valuable real-time information so they can make educated decisions about how and when to travel.”

Transit provides a map showing live locations of transit vehicles along the route. The vehicle icon is expected to display the last update of the vehicle's location but also its current crowding level listed as 'many seats', 'some seats' or 'very limited seats'. 

A vehicle below 50% of the Covid-19 capacity is classified in the app as 'many seats'.

Buses between 50-90% appear as 'some seats' while those above 90% are shown as 'very limited seats'. 

David Block-Schachter, chief business officer at Transit, describes this kind of information as a “huge step” in helping riders feel confident getting on the bus. 

“And not just during the pandemic: it also makes a big difference if you use a wheelchair, you’re carrying big luggage or you just want to feel more comfortable,” he continues.

“Even after the pandemic, crowding information is sure to benefit RTC customers.”

Riders can also share how crowded they perceive the bus to be by using Transit’s Go step by step navigator. 

Comparing the crowdsourced reports against passenger count data from the RTC will provide important insights into how customers feel about crowding levels onboard, the RTC adds. 

Transit is available to download for iPhone and Android phones. Customers can purchase their pass within Transit or via the rideRTC app.
 

For more information on companies in this article

Related Content

  • What Citizen Kane can teach transportation engineers
    July 14, 2023
    Andy Boenau suggests that one of the most famous movies of all time might have lessons for our industry. And they’re all about not knowing things...
  • IBTTA 2011 Annual Meeting highlights developing trends in tolling
    January 26, 2012
    Alain Estiot, chief meeting organiser of this year's IBTTA Annual Meeting and Exhibition, talks about hot topics for discussion. The IBTTA's 79th Annual Meeting and Exhibition, which takes place this year in Berlin in September, will once again take many of the developing trends from around the world and look at their effects on the tolling sector. Host organisation Toll Collect's Alain Estiot, chief meeting organiser, says that the event has to be viewed against a backdrop of major global change.
  • How can US transportation be ‘re-envisioned’?
    October 17, 2019
    In her address to this year’s ITS America Annual Meeting, congresswoman Eleanor Holmes Norton, chair of the House Subcommittee on Highways and Transit, called for a ‘re-envisioning’ of transportation. Her speech is below – and ITS International asks a number of US experts what they would like to see ‘re-envisioned’…

    I would like to welcome  ITS America to the nation’s capital.

  • Here: AI has place in ‘privacy by design’
    June 23, 2020
    Artificial intelligence may improve traffic in cities and keep location data private, but Here Technologies shows that it only takes four points of anonymous data to predict your identity.