study on foot traffic flows on pedestrian routes in underground traffic system
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Study on Foot Traffic Flows on Pedestrian RoutesIn Underground Traffic System
1 Moscow State University of Civil Engineering 2 Academy of State Fire Service of Russia, UNK PPBS, EMERCOM
3 Ulyanovsk State Technical University
Academy of State fire service of Russia
Prof Valery Kholshevnikov1, Dr Dmitry Samoshin2, Dr Irina Isaevich3
Moscow State university of civil
engineering
Ulyanovsk State Technical University
Study outline:
Moscow underground traffic system:
- 9 millions of passengers daily:
- normal operation gives max load (compare to emergency evacuation): simultaneous multidirectional pedestrian movement: contra flows, flows crossings;
- issues under discussion:
• particular technique of actual observations;• relations between travel speed and density of human flows;• metro car traffic capacity and station platform design;• a mutual impact of escalator installations and pedestrian
flows on efficiency of daily operation;• an impact of automatic turnstile on evacuation route traffic
capacity;
Traffic routes in underground station
Blue arrows – towards trains
Green arrow – towards exits
EntranceTicket hall
Platform
Platform
Trains
Bridge to changing station
Station hall
Esc
alat
ors
Tic
ket
cont
rol
Trains
Data sample volume
5957 counts total: 3380 – travel speed measurements at different flow density range; 1379 – escalator traffic capacity depending upon flow density and flow speed; 396 – ticket machines traffic capacity; 301 – “widening” flows; 261 – flow density on platform;
244 – car door traffic capacity;
Methods of actual observations – video analysis
Scale grid drawing Videotape analysis based on scale grid. An example.
Travel speed (without density impact). Empirical data.
Non Rush-hour Rush-hour
Average free travel speed 69.4 m/min
Average free travel speed 106.2 m/min
Travel speed and emotional state
Relationship between emotional state and activity:1 – attention; 2 – control;
3 – activity.
Relation between unimpeded travel speed and psychological stress
level
Quiet
Active
Of increased
activity
General law for V=f(D)
-is the average travel speed of pedestrians in a
flow, m/s;
-is the average travel speed of pedestrians on a
route without the influence of density, m/s;
aj -is an empirical constant for each type of
pathway);
Di -is the prevailing density of the flow, persons/m2
(or m2/m2);
Doj -is a threshold value of flow density on the j-the
pathway, persons/m2 (or m2/m2 if pedestrians are
measured based on their horizontal projection) );
E -is an indicator of the emotional state of the
pedestrian (the category of movement);
J -is an indicator of the type of route traversed;
j
jjjjD D
DаVV
0
E0
E ln1
E, jDV
__
,0E
jV
D, person/m2
V,
m/m
in
Horizontal plane
Door opening
D, person/m2
V,
m/m
in
0 1 2 3 4 5 6 7 8 9 1 0
10
2 0
30
40
50
60
70
V , м /м ин
D , ч ел ./м
5
5
6
6
4
4
4
7
7
1
1
2
2
3
3
8
8
2
0 1 2 3 4 5 6 7 8 9
10
20
30
40
50
V , м /м ин
4
5
5
4
4
3
3
6
6
1
1
2
2
7
7
D , че л ./м2
Stairs downward
Stairs upwards
D, person/m2
V,
m/m
in
D, person/m2
V,
m/m
in
Relation between travel speed, emotion level and density of flow in underground traffic system.
Of increased
activity
0
10
20
30
40
50
60
70
80
90
100
110
120
0 1 2 3 4 5
Active
V=106.2*(1-0.4*Ln(D/0.56))
V=69.4*(1-0.4*Ln(D/0.65))
D, persons/m2
V, m/min
Pedestrians on platform
Camera
Pedestrians Camera marks
•Car door traffic capacity – 50 persons/min (at door width 1.2m);
•Max platform density – 5 persons/m2;
•Comfortable inter-person distance: face to face – 0.49m, face to back – 0.58m, side by side – 0.8m.
1 – station hall; 2 – movement through escalator’s guiding handrails; 3 – handrails in front of escalator; 4 – escalator entrance; 5 – escalator.
Movement through escalator
Pedestrian flow in front of escalator
EscalatorStation hallTrains: 500 pers
t=0.15 min
t=2.02 min
t=4.20 min
Escalator traffic capacity
Maximum escalator traffic capacity obtained at close values between pedestrian speed 42.37 m/min (at density 5 persons/m2)
and escalator speed 42 m/min (0.7 m/sec)
Movement through ticket machines
Ticket machines
Area of observation
Passengers
In rush-hour 17.00-19.00 and normal operation 15.00-16.00 time to overcome ticket machines, their traffic capacity and flow density
impact were investigated
Time losses moving through ticket machines
Flow density and psychological state impact passage time: the higher the density the more time takes to pass through ticket machine due to physical contacts between people and stress factor. In normal condition at 2-3 persons/m2 time decreases because passengers aimed to overcome uncomfortable type of route. Average traffic capacity is 1187 persons per hour.
Pedestrian flow modeling
Based of study results, valid computer programs were developed. On this diagram, comparison of actual observation and flow modeling at control point is presented.
Distinguishing features of pedestrian movement in underground traffic system
1. Seasons (i.e. winter, summer etc) do not influence pedestrian movement.
2. Psychological state of pedestrians (i.e. rush-hour, normal conditions) change parameters of their movement.
3. Rush–hour movement fit “of increased activity movement” category of movement, and non-rush hour movement fit “active” category of movement.
4. Pedestrians in rear of the flow moves in “quiet” category of movement in rush hour and in normal conditions. Pedestrians in head of flow moves in “of increased activity” category of movement in rush hour and in normal conditions
5. It was noticed “widening” of the flow as they exit on a wide hall. Flow widening caused with pedestrian intention to move in a low density extending length of their route. Balance between uncomfortable movement in a dense flow and roundabout route observed at density value about 1,2 pers/m2 (range 0,3-1,9 pers/m2) – flow does not widening any more.
General conclusions
• Observations were undertaken on all consecutive route sectors based on unified technique and analytical methods aimed to get the most precise data.
• Experimental data were fully statistically treated in each density range.
• Unimpeded travel speed (i.e. without density impact), as an indictor of emotional state, confirmed established earlier scale of emotional states (categories of movement) and relation between parameters of pedestrian flow based on Weber-Fechner law.
• Reliable data, describing human flows development and movement were obtained during these experiments. Validated against available data computer models were also developed and they used in practice nowadays.
Computer model ADLPV (Analysis of Pedestrian Flow, Probability)
М ом е н т в р ем е н и t0
i
D N b li i i
= / t
0t
0t
0Ni
t0
i + 1 i - 1
Di + 1
Di - 1
t0
Ni - 1
t0 N
i + 1
t0
V Di i- 1 - 1
= ( )
t0
V Di i- 1 - 1
= ( )t
0t
0t
0t
0
bi + 1
bi - 1
j
l l
N j
D j , V j = D j ( )t
0 t
0 t
0
b j
М ом е н т в р ем е н и t = t + t1 0
D N N N N b l V Di i i , i i i j , i i i + 1 - 1 ,
= ( - + + ) / ; = ( ) t
1t
1t
1t
1t
1t
1t
1
N j,i
V
AV
B
A B
VC
V D Di i- 1
, е сли < t
0t
0q
V D Di i
, е с ли > t
0t
0
VA
=t
0V D D
i i +, е с ли <
1
t0
t0
V D Di + i +1 1
, е с ли >t
0t
0
VB
=t
0
A BCC
Ni , i + 1
Ni - i1 ,
t0
t1
V j D D, е сли < i
t0
t0
V D Di i
, е сли > t
0t
0
VC
=t
0
N N N V t li i , i i B
- = (1 - / );- 1
t
0t
1t
0t
0
N N V t l N D b V ti - , i i A j , i j j C 1 - 1
= / ; = t
1t
0t
0t
1t
0t
0
Д о л я уч а с ти я п р и о бр а зова н и и с коп л ен и я на у ч аст ке i
N N P P D V b D V bi j i j i i i j j j- 1 - 1 - 1 - 1 - 1
/ = / = / t
1t
1t
1t
1t
1t
1t
1t
1
m a x
qm ax
qm a x
qm a x
qm ax
qm a x
lb
NNNND
i
tjj
tii
tii
tit
i
1110
0 ,,11,
tVbDN перiti
tii
o1
1,
;...,
;...,
00
00
11
1
ma
ma
qti
ti
qti
ti
crDDеслиV
DDеслиVV
0ti
пер V
lt
Changes in consequent time intervals Basic equations
Density of flow:
Number of pedestrians, passing to next sector of route:
Transition travel speed:
Transition time:
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