Analysis of pedestrian congestion

1. A method of providing a measure of pedestrian congestion in a given area, the method comprising:

collecting data from a pedestrian moving in said given area;

using said data to determine one or more specified parameters representing a pattern of movement of the pedestrian in the given area; and

from said one or more specified parameters, determining a sinuosity of pedestrian traffic in the given area.

2. The method according to claim 1 , wherein:

said pattern of movement is a walking pattern of the pedestrian; and

said data identifies distances between the feet of the pedestrian.

3. The method according to claim 2 , wherein the one or more specified parameters include:

one parameter, e, representing a lateral gap between the feet of the pedestrian; and

another parameter, l, representing a length of a stride of the pedestrian.

4. The method according to claim 3 , wherein the using the data to identify one or more specified parameters includes:

collecting a first series of values {e i } for said one parameter; and

determining a standard deviation of said first series of values.

5. The method according to claim 4 , wherein the using the using the data to identify one or more specified parameters further includes collecting a second series of values {l i } for said another parameter.

6. The method according to claim 5 , wherein the using the data to identify one or more specified parameters further includes using the second series of values to calculate an average stride length for the pedestrian.

7. The method according to claim 6 , wherein the using the second series of values to calculate an average stride length includes:

using one or more samples of the second series of values to calculate said average stride length; and

using said standard deviation of the first series of values to identify said one or more samples of the second series of values.

8. The method according to claim 5 , wherein the using the data to identify one or more specified parameters includes:

computing a stride and gap series {l i +e i }; and

using said stride and gap series to determine a defined variable representing movement of the pedestrian in the given area.

9. The method according to claim 4 , wherein the determining the sinuosity includes determining said sinuosity by using said standard deviation of the first series of values.

10. The method according to claim 9 , wherein the sinuosity, s, is determined as a function of said standard deviation using the equation:

σ

⁡

(

)

=

1

d

⁢

⁢

s

2

⁡

[

1

⁢

⁢

s

2

+

1

+

e

⁡

(

1

-

s

)

]

where d is a distance between defined obstacles in the walking path of the pedestrian.

11. A system for providing a measure of pedestrian congestion in a given area, the system comprising:

one or more sensors on a pedestrian moving in said given area to generate data from the pedestrian; and

one or more processing units configured for receiving said data, for using said data to determine one or more specified parameters representing a pattern of movement of the pedestrian in the given area, and from said one or more specified parameters, determining a sinuosity of pedestrian traffic in the given area.

12. The system according to claim 11 , wherein:

said pattern of movement is a walking pattern of the pedestrian;

said data identifies a multitude of positions of the feet of the pedestrian; and

the one or more specified parameters include one parameter, e, representing a lateral gap between the feet of the pedestrian, and another parameter, l, representing a length of a stride of the pedestrian.

13. The system according to claim 12 , wherein the using the data to determine one or more specified parameters includes:

collecting a first series of values {e i } for said one parameter;

collecting a second series of values {l i } for said another parameter; and

determining a standard deviation of said first series of values.

14. The system according to claim 13 , wherein the using the data to determine one or more specified parameters further includes using the second series of values to calculate an average stride length for the pedestrian.

15. The system according to claim 14 , wherein the using the second series of values to calculate an average stride length includes:

using one or more samples of the second series of values to calculate said average stride length; and

using said standard deviation of the first series of values to identify said one or more samples of the second series of values.

16. An article of manufacture comprising:

at least one tangible computer readable device having computer readable program code logic tangibly embodied therein to provide a measure of pedestrian congestion in a given area based on data from a pedestrian moving in said given area, the computer readable program code logic, when executing, performing the following:

collecting said data;

using said data to determine one or more specified parameters representing a pattern of movement of the pedestrian in the given area; and

from said specified parameters, determining a sinuosity of pedestrian traffic in the given area.

17. The article of manufacture according to claim 16 , wherein:

said pattern of movement is a walking pattern of the pedestrian; and

said data identifies a multitude of positions of the feet of the pedestrian.

18. The article of manufacture according to claim 17 , wherein:

the one or more specified parameters include one parameter, e, representing a lateral gap between the feet of the pedestrian, and another parameter, l, representing a length of a stride of the pedestrian; and

the using the data to determine one or more specified parameters includes collecting a first series of values {e i } for said one parameter, collecting a second series of values {l i } for said another parameter, and determining a standard deviation of said first series of values.

19. The article of manufacture according to claim 18 , wherein the using the data to determine one or more specified parameters further includes:

computing a stride and gap series {√{square root over (l i +e i )}}; and

using said stride and gap series to determine a defined variable representing movement of the pedestrian in the given area.

20. The article of manufacture according to claim 18 , wherein the determining the sinuosity includes determining said sinuosity by using said standard deviation of the first series of values.