Understanding the Social Functions of Subway Stations (Beihang University)
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Transcript of Understanding the Social Functions of Subway Stations (Beihang University)
Understanding the Social Understanding the Social Functions of Subway StationsFunctions of Subway Stations
based on Metro Ridershipbased on Metro Ridership
Beihang UniversityBeihang UniversityBiao LengBiao Leng
Beijing Municipal Commission of Urban Planning
Supported by
Beijing Municipal Commission of Transportation
Ministry of Science and Technology
Beijing Metro Network Control Center
Beijing Transportation Information Center
Beijing Mass Transit Railway Operation Corporation Limited
Beijing MTR Corporation
Data Description——Study area
Over 10% population
“China statistical yearbook”, Chinese Statistical Bureau, 2012
in 2012.5
15 lines 372 km of track 188 stations 7.5 million average
diurnal ridership
Data Description——Study area
Data Description——Empirical datasets
The intensity of daily overall ridership
DongZhiMen
CBD
XiErQi
XiZhiMenXiDan
Intensity of average morning peak ridership for exit
Tidal Characteristics: Morning Peak — 22.20% of daily volume Afternoon Peak — 18.90% of daily volume
Data Description——Empirical datasets
Result & Analysis——General result
Class Meaning
Residential Area The area where large number of people live together.
Work Area The area where large number of people work together.
Commercial Area The area where people go shipping and relax.
Mixed Area The combination of residential and work function, or residential and commercial functions.
Tourist Area The area where people visit.
Station port The area transiting people among cities, such as airport, railway station, inter-city bus station.
Different functional classes with large, medium or small group:
Result in May 2012
Most at the end of lines
Widely in the center; A few sparsely on the
suburban lines
Mainly around Chaoyangmen, Fuxingmen etc. Some small-
scale among other areas
Coincide with commercial centers;NO small
Around attractions; NO large
Near airport, stations
Result & Analysis——Cluster membership at system level
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
500
1000
1500
2000
2500(a)
Time
Ave
rage
Rid
ersh
ip
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
500
1000
1500
2000
2500(b)
Time
Ave
rage
Rid
ersh
ip
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23�200
0
200
400
600
800
1000
1200
1400(c)
Time
Ave
rage
Rid
ersh
ip
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
200
400
600
800
1000
1200
1400
1600(d)
Time
Ave
rage
Rid
ersh
ip
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
100
200
300
400
500
600
700(e)
Time
Ave
rage
Rid
ersh
ip
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230
200
400
600
800
1000
1200
1400(f)
Time
Ave
rage
Rid
ersh
ip
Daily entrance ridership pattern (in line) for six function areas
Great morning peak; Flat curve during the
others.
One afternoon peak, Opposite to residential areas.
Flat before afternoon peak
One afternoon peak Margin of peak >> Work’s Bigger curve slope before
peak
One afternoon peak No sudden increase Change of SD > Work’s
& Commercial’s
No visible peak Biggest SD, even over mean
→ discrete & unsteadily
Two peaks
Smart City
Urban Planning -- current vs. planned social function
July 2013
Smart City
Urban Planning -- the change of social function Liuliqiao Station – from station port (2012) to
residential region (2013)
Smart City
Transport Planning -- the schedule of trains
Smart City
Transport Planning -- the optimized passenger guiding
Thanks!