By Valeria Riso

“These are unprecedented times”. This has been said quite widely and everywhere. We are perhaps (hopefully?) now experiencing the last stage of it, although I wonder whether or when we will be able to go back to normality as we remember it. In particular, what is going to be the impact on transport and travelling? Are we going to be able to move freely? What are the changes in transport going to look like? How long will they need to be in place for? And can the transport system cope with the changes?

As a transport planner, but mainly as a simple human and with her family in a different country, I have been wondering all of this. As a microsimulation modeller I have tried to find some answers.

Assuming we have the same flow, walking space, origins/destinations and routes, I have considered three different scenarios (Test 1):

  1. Pedestrians move freely within the space available.
  2. Pedestrians keep a 2m distance from each other whenever possible.
  3. Pedestrians keep a 2m distance from each other all the time.

These three scenarios are indicated below, where every image is a snapshots of the pedestrian model1 taken at a distance of 30 seconds.

Images-T1

The images from Test 1 indicate that while in scenarios A and B opposite flow of pedestrians (with red being the left-to-right flow and blue being the right-to-left flow) get completely past each other at similar time (i.e. by 00:03:00 there is a clear separation between red and blue flows in both scenarios), scenario C takes pedestrians to a situation of standstill as, since they need to obey the distancing rule, they are not able to move.

But what happens when the space available is reduced? The images below indicate the impact of this change on the three scenarios (Test 2).

Images-T2

The images from Test 2 indicate that while scenario C is again taking pedestrians to a standstill situation due to the rule of distance, scenario B is far beyond scenario A with regard to the time by when opposite flows are past each other (i.e. before 00:02:30 for scenario A and after 00:03:00 for scenario B).

Both tests concentrated on the impacts of the rule of distance within a certain area. But what is the impact that any spacing rule within an area would have onto the spaces leading to the areas in question?

In pedestrian planning we use different parameters to indicate the quality of a walking area; to classify pedestrians’ experience in terms of freedom of movement and comfort, we use densities of pedestrians per square metre and classify them by levels (i.e. Level of Service2(LoS)). A LoS A represents free-flow conditions whilst a LoS F indicates a very congested situation; congestion is assumed to start from LoS D.

The next images show pedestrians colour coded3 based on the before mentioned LoS. The focus now is on the leading spaces to the areas affected by the spacing rule. It is assumed that pedestrians move freely within these leading spaces.

Images-T3

Images-T4

What actually happens is that the congestion in the leading spaces is experienced from the very start of the model in all scenarios and tests. Aren’t these leading spaces the places where people are expected to queue before entering a certain area (i.e. office, supermarket, station, airport, etc.)? Therefore, with the above in mind, how should we configure these spaces?

Thinking about this ‘unprecedented times’ and the impacts on transport made me ask myself more questions than gave me answers for. Perhaps something I should now try to investigate…

 

1 PTV Viswalk 11 was used

2 LoS used in this example are in according with Fruin’s study, Pedestrian Planning and Design, John J. Fruin, 1987

3 Pedestrians coloured in dark blue have LoS A, those in yellow have LoS D, and those in red have LoS F

Join the conversation! 2 Comments

  1. Hi, are you able to share the pedestrian behaviour parameters used in the three scenarios?

    Like

    Reply
    • Hi Simon, I have used the default PTV Viswalk walking behaviour’s parameters for A, have then increased the ASocIso parameter for B, and have also decreased the Tau parameter for C.

      Like

      Reply

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Category

Transportation, Uncategorized, Valeria Riso

Tags

, , ,