Cities are continuously expanding: increasing population and vehicles result in rising pollution, occupied public spaces, and growing complexity of public services planning.

Think about this: when was the last time you walked to a grocery shop? In many cases, it’s nearly impossible due to insufficient pedestrian infrastructure.

Similarly, despite reduced traffic due to lockdowns, we still experience congested roads during peak-times. Therefore it remains essential to improve the efficiency of urban areas, optimize public transportation system and private mobility especially when preparing for the new normal. The foundation for this is the understanding of human movement in various scenarios.

The COVID-19 crisis also has shown that it is crucial to design systems that quickly respond and adapt to the emergency needs in terms of the logistics of goods, services, and public transits. Location intelligence is a powerful tool to achieve this goal.

Using the data extracted from millions of mobile devices throughout the country and correlating it with different events, such as seasonal changes, natural disasters, weather, local events, etc., helps transportation planners to develop accurate models and forecasts for people movements.

The rapid changes in population travel behavior and movement patterns developed the new definition of the “efficient transportation systems”.

Photo by Les Corpographes

Let’s look at how urban and transportation planners can use AirSage location insights for 2021-2022 transportation forecasting and modeling.

Reducing urban congestion

One of the biggest problems in the cities is traffic congestion. According to the Urban Mobility Report released in 2019  by the Texas A&M Transportation Institute, the average American commuter wastes 54 extra hours a year in traffic delays.

The statistics of some of the most congested US metro areas are impressive:
·       San Francisco-Oakland: 103 hr/year
·       Washington, DC: 102 hr/year
·       New York-Newark: 92 hr/year
·       Boston: 80 hr/year
·       Seattle: 78 hr/year
·       Atlanta: 77 hr/year
·       Houston: 75 hr/year
·       Chicago: 73 hr/year
·       Miami: 69 hr/year

Of course, the coronavirus crisis has changed the situation as in the first half of 2020, the number of vehicle miles traveled by US drivers fell by 16.6 percent.

According to a survey presented by Prof. Deborah Salón of Arizona State University, many respondents would reconsider their daily travel behavior after the pandemic once restrictions and stay-home orders were lifted. More than 10% of respondents are willing to limit their use of personal vehicles, ride-hailing, and transit services in favor of cycling and walking.

Expected change in daily travel among respondents. D. Salon, Deborah Salon, School of Geographical Sciences and Urban Planning, Arizona State University, 2020

Changing population behavior and expectations require incisive solutions. The traditional surveys are important to understand general people incentives, but in many cases, they are not sufficient for optimal transportation planning. Survey focus groups often fail to represent the critical mass and usually present the best people’s opinion about themselves. It might happen that instead of choosing sustainable modes of transportation (bikes, e-scooters, etc.) as stated by the survey respondents, many of them will realize that using private motor vehicles is more time-efficient, therefore preferable.

On the other hand, the big data solutions that collect and analyze mobile data in near real-time make it possible to extract useful information about traffic trends and analyze people movement with the seasonal, weekly, daily, and hourly distribution. Analyzing the data of the population, urban, and transportation planners can identify the cause of congestion and find remedy. By studying time, origins and destinations, length of stay, and routes of real trips, planners can evaluate and identify poorly timed traffic signals increasing commercial transportation, new vitiation trends, and changes in the popular destinations.

This will allow to reduce and optimize traffic congestion and improving mobility systems without wasting time and money on inadequate surveys.

Building people-centric bike and pedestrian infrastructure

Consider a scenario when the pandemic actually changes our long-term travel and commute behavior. A situation in which more people make alternative choices in by using bikes and e-scooters. Municipalities and cities would have to provide the appropriate infrastructure to ensure their safety.

If we look at our current urban environment, we quickly realize that infrastructure was not designed with pedestrians and bikers in mind. Sidewalks are often interrupted. Crosswalks sometimes end nowhere. And the bike lanes are often missing, so bikers need to share the road with other motor vehicles, which is often is dangerous.

Mobile data can help examine the roads and create the routes for bike lanes and pedestrian infrastructure according to people needs, forecast their impact on the traffic, and assess return on investments examining before-and-after results.

Increasing reliability and efficiency of public transportation

According to multiple sources, US travelers reduce their use of public transportation mainly because of its unreliability. Overcrowded subways, bus delays, issues during the transfers, and unavailability in some rural areas are important reasons why public transportation is considered inefficient.

Moreover, today, the increasing number of passengers expect to get public transportation updates, including delays, cancellations, prices change and even live occupancy, in close to real-time. A study reported on shows that a majority of US rider say they’d be willing to pay more for daily updates on prices and delays, for completely paperless journeys or smartphone ticketing.

Ridership and Community Context Analysis. City of Winnipeg Transit Master Plan. AirSage data visualized by Stantec.

People movement data generated by AirSage provides insights on gaps in public transportation and intercity transit systems. It allows tracking traveling patterns down to specific bus stops. It helps transportation planners accurately model and forecast demand for certain routes, stops, transit stations, and even estimate the best places for bike-sharing stations. Besides, understanding the real needs of transit passengers helps prioritize projects and optimize budget spend.

These are only a few examples of how mobile data can help to solve urban and public transportation planning challenges. The beauty of people movement insights provided by AirSage is its simplicity. The data speaks for itself, and any transportation planning professional can work with it immediately to save time and to deliver better results.

Let’s make our cities and transportation systems more efficient together!

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