While a great deal has been made of rebuilding international and local air travel over the last few months, a gradual return to commuter traffic is underway in many parts of the world. With a renewed focus on passenger health, rail travel is increasingly in the spotlight. It is no longer enough to ensure safety, overcrowding, and passenger processing in one area — the entire transit ecosystem needs to be viewed as a whole to minimize risks, maximize throughput, and plan effectively for the future.

Traveler safety — the top priority

Over the last two decades, safety has been under scrutiny. From terrorism threats to disease outbreaks, commuters have needed safeguarding — but it seems the goalposts are continuously shifting. Wherever the risk comes from,  certain immutable factors need to be considered: crowd management, smooth traveler flow, and efficient resource management.

And then, there is the ever-more critical factor of commuter confidence. In a world where passengers must place their lives and trust in transport decisionmakers, commuters want to know that everything has been done to keep them safe, and these measures need to be visible to the traveler.

Understanding how people behave is vitally important in these circumstances. When operators have detailed insights of how and when travelers arrive, move, dwell, and leave, they can more accurately predict show-up times and areas where crowding is likely to occur. This, in turn, allows for mitigating actions, like additional staff resources, redirecting passengers to less-busy areas, and even sharing travel information with commuters.

Managing crowds

No crowd exists in isolation. They do not appear from nowhere. They are a function of movement. When we look closely at how crowds form and shift, we begin to understand that it is near-impossible to pinpoint any single cause. For example, several external factors could cause capacity to exceed expectations. These could range from a change in weather to delays at a different station, or even something as unexpected as protest action or a road traffic incident. 

With such wild variations in causality, how can operators realistically hope to consistently manage the flow and minimize crowding? While it may feel like an overwhelming task, it all comes down to collecting, sorting, and analyzing a vast amount of data, and using it both live and predictively. 

Supporting modal shifts 

Disruptions can occur unexpectedly. At any given time, a train could be delayed, or arrive early, leaving extra passengers on the platform. Employee disruptions and sanitation issues can cause plans to deviate from expectation. And, even if absolutely everything within one station is running smoothly and efficiently, an upset at any other point in the network can have a knock-on effect.

It is therefore essential to understand the entire rail network and consider anything that affects passenger arrival and departure times, crowd management, and safety when making resourcing or people-distribution plans. Only when operators have holistic insight into both past and current movement patterns, can they begin to accurately and adequately plan their operations.

Problem-solving data

By implementing a system that connects to and transforms any data source — including sensors, turnstiles, ticketing, and actual train schedules — into actionable insight, operators can make the right decisions for their station, network, and passenger safety.

Blending this input with historical data also proves useful to understand the impacts of unexpected events on operations. As a result, operators can plan their resourcing more effectively while distributing and managing the flow of people more efficiently.

With a clear understanding of the impact of delays and external influences, operators can more easily predict the effects of external events and adjust plans to effectively mitigate them. They can offer increased levels of service, thanks to improved forecasting and resource planning. Space and safety are much easier to manage.

Improving the passenger experience

One of the best ways travelers can feel safer is through real-time information-sharing and guidance. For example, operators can share live journey information — like entrance congestion, platform and carriage density levels, and which stations are least busy — using a combination of dynamic digital signage and mobile apps. Armed with this information, commuters can make more informed travel choices, like choosing a less-crowded platform or station, or alter their travel time.

Not only does this provide travelers with more choice and control, but transit use also becomes better distributed, further minimizing the risk of bottlenecks, and ultimately improving the experience for all.

Seamless, validated movement insights

While recent months have proven that extraordinary circumstances can derail even the best planning, they have also provided even more valuable insight into people's movement and behavior. Several stations have noticed significant changes in individual passenger arrival and dwell times, as passengers try to minimize social contact, for instance. 

Human behavior is variable, which means operators need an ongoing flow of live, up-to-the-minute input, as well as sophisticated analysis and predictive functionality. 

With end-to-end insights and improved operational visibility, operators can take control and make timely, proactive decisions, consistently and accurately matching the demand for a seamless, safe, and stress-free journey.