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Emiliano Fuccio
Tommaso Furlan
Maurizio DeiddaBig Data Analytics (23/01/2017)
Name Description
user_id Unique id related to a car
timestamp
Date and time on the detection of the GPS device mounted on the
car
day_of_week Specifying the day of the week on the recordingade by GPS
time_slot Day parting based on the time recorded by the GPS device
lat Latitude of detection
lon Longitude of detection
GPS detection in Milan in the period between 1° April and April 7 2007
Before Data Preparation
We have approximately 1.800.000 detections (points)
Days analyzed for residents: Sunday – Tuesday – Friday – Saturday
Days analyzed for visitors: Friday (from 1Pm) - Saturday
• Identify the most achieved attractions
(Point of Interest)
• Measuring the intensity of the traffic
according to the zone, the time of day
and to points of interest.
• Get insights thanks to the most
important route’s statistics (length,
duration, speed)
• Detect "behavioral" differences among
residents and visitors.
• Multidimensional analysis with
dimensions: weather - time - traffic
Visitors
Friday (from 1PM)
Saturday
(Split 2)
Residents
Sunday
Tuesday
Friday
Saturday
(Split 1)
Split Dataset into two parts
from Split 2 delete all users having user_id content in Split 1
RESIDENTS
• Milano area: 1575.65 Km2
• Grid with areas: 10 Km2
• Low Flow – High Flow
The trend of high traffic flow in the city center and on high speed
highways, doesn't change with respect to residents.
VISITORS
Min Max AVG
Dom 0.367 368.483 40.56
Mart 0.3 367.983 44.731
Ven 0.25 325.25 43.681
Sab 0.55 290.467 43.098
0-30
30-60
60-90
90-120
120-150
150-180
180-210
210-240
240-270
270-300
300-330
330-360
360-390
1177
457
262
109
56 44 1 3 2 1 1 0 1
Distribuzione delle durate Domenica
56%22%
12%
5%
Composizione delle durate Domenica
0-30
30-60
60-90
90-120
120-150
150-180
180-210
Duration
• < 30 minutes: increase from Friday to Sunday, lower on Tuesday
• 30 – 60 minutes: decrease from Friday to Sunday, high on Tuesday
• >60 minutes: linear trend during the week
Speed
Min Max AVG
Dom 5.002 136.051 31.643
Mart 5.01 133.097 27.782
Ven 5.02 125.157 28.907
Sab 5.032 137.392 30.983
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
244
556
417
287
193
136
103
72
38 18 18 13 5 2
Distribuzione delle velocità Domenica
12%
26%
20%14%
9%
6% 5%
Composizione delle velocità Domenica
0-10
10-20
20-30
30-40
40-50
50-60
60-70
• No significant differences between working days speed and weekend days ones
• Probably why are there especialy urban detections?
Min Max AVG
Dom 0.047 152.287 16.193
Mart 0.059 139.366 15.719
Ven 0.029 126.646 15.28
Sab 0.108 125.017 15.823
Length
0-11
11-22
22-33
33-44
44-55
55-66
66-77
77-88
88-99
99-110
110-121
121-132
132-143
143-154
871
717
336
125
37 10 6 2 3 3 2 1 0 1
Distribuzione delle lunghezze Domenica
41%
34%
16%
6%
Composizione delle lunghezze Domenica
0-10
10-20
20-30
30-40
40-50
50-60
60-70
• Short trips (0-20 Km) have the opposite trend than long trips (>20 Km)
• Descend trend for short trips and ascend trend for long trips
VisitorsDuration
454
79
42
13 3 3
Distribuzione durate dei visitatori Venerdì
1395
227
113
47 26 10
Distribuzione delle dei visitatori Sabato
76%
13%
7%
2%
1%
1%
Composizione delle durate dei visitatori Venerdì
0-30
30-60
60-90
90-120
120-150
150-180
77%
12%
6%
3% 1%1%
Composizione delle durate dei visitatori Sabato
0-30
30-60
60-90
90-120
120-150
150-180
Residenti Giorno Visitatori
0 – 30: 54%
30 – 60: 21%
Venerdì
0 – 30: 76%
30 – 60: 13%
0 – 30: 55%
30 – 60: 19%
Sabato
0 – 30: 77%
30 – 60: 12%
Visitors short trips extremely greater than residents short trip
Visitors don’t use own car to move in Milano
Speed
41
102
88
64
41 45
29 24
33
43
35
24 21
4
Distribuzione delle velocità dei
visitatori Venerdì
7%
17%
15%
11%7%
8%
5%
4%
5%
7%
6%
4% 3%
Composizione delle velocità dei visitatori Venerdì
0-10
10-20
20-30
30-40
40-50
50-60
60-70
126
290
253
180
133
115
92 9010293
124116
66
28
10
Distribuzione delle velocità dei
visitatori Sabato
7%
16%
14%
10%
7%6%5%
5%
6%
5%
7%
6%
4%
Composizione delle velocità dei visitatori Sabato
0-10
10-20
20-30
30-40
40-50
50-60
60-70
Residenti Giorno Visitatori
0 – 30: 59%
0 – 50: 82%
+50: 18%
Venerdì
0 – 30: 39%
0 – 50: 57%
+50: 43%
0 – 30: 61%
0 – 50: 81%
+50: 19%
Sabato
0 – 30: 40%
0 – 50: 53%
+50: 47%
Visitors speed extremely lower than residents speed
Visitors park in Milano suburbs and use metro or TrenoNord
train company
Length
193 203
112
66
13 3 3 1
Distribuzione delle lunghezze dei
visitatori Venerdì
32%
34%
19%
11%
Composizione delle lunghezze dei visitatori
Venerdì
0-10
10-20
20-30
30-40
40-50
50-60
603 621
321
219
38
5 5 3 3
Distribuzione delle lunghezze dei
visitatori Sabato
33%
34%
18%
12%
Composizione delle lunghezze dei visitatori
Sabato
0-10
10-20
20-30
30-40
40-50
50-60
Residenti Giorno Visitatori
0 – 20: 73%
0 – 30: 89%
Venerdì
0 – 20: 66%
0 – 30: 85%
0 – 20: 70%
0 – 30: 85%
Sabato
0 – 20: 67%
0 – 30: 85%
On the opposite to duration and speed, length of trips in unchanged between
visitors and residents.
Time Label
00:00 – 05:59 Night
06:00 -08:59 Early Morning
09:00 – 11:59 Morning
12:00 – 13:59 Lunch
14:00 – 17:59 Afternoon
18:00 – 19:59 Early Evening
20:00 – 21:59 Evening
22:00 – 23:59 Late Evening
Time slots inhomogeneous? NORMALIZE!
Night
Early
Mornin
g
Mornin
g
Lunch
Afterno
on
Early
Evening
Dinner
Late
Evening
Domenica 35,5 92 106,3333 130,5 150,75 99,5 84,5 32,5
Martedì 119,1667 250 190 219 296,5 159 132,5 49,5
Venerdì 105,6667 236 189,6667 224,5 239 161,5 118 68,5
Sabato 42 116,6667 117 136,5 141 84 98,5 57,5
0
50
100
150
200
250
300
350
Corsemedieorarieperfasce
Intesità di traffico per fasce orarie
• Average traffic on weekend in each time slot is
always lower than the working days
• Working Cycle: (early morning + morning) is
almost equal to (afternoon + early evening)
Visitors
9%
17%
16%
13%
25%
8%
8% 4%
Composizione del traffico visitatori Sabato
Night
Early Morning
Morning
Lunch
Afternoon
Early Evening
Dinner
Time Slot
# trajectories
visitors
# trajectories
residents
Night 164 252
Early
Morning
307 350
Morning 292 351
Lunch 227 273
Afternoon 459 564
Early
Evening
143 168
Dinner 146 197
Late
Evening
80 115
• Friday not considered
• Decrease of the average trajectories in
visitors
• Trend unchanged
We partition the detection area in this way:
• Center: into the yellow perimeter
• Macroareas neighboring: between the yellow perimeter and mains roads
• Suburbs and airports: Externaly geographic area and intersects red perimeter
Macrozones flows analysis
O/D Matrix zones
The obtained results are equivalent, this highlights similar trend between working
days and holidays ones.
PO flows analysis
Po Rif. Po Rif.
Piazza Duomo 1 Zona Navigli 14
Galleria Vittorio Emanuele 1 Carcere San Vittore 15
Palazzo Reale 1 Basilica Sant'Ambrogio 16
Teatro Scala 1 Università Cattolica 17
Piazza Mercanti 1 Biblioteca Ambrosiana 18
Castello sforzesco 2 Politecnico 19
Parco Sempione 3 Porta Ticinese 20
Pinacoteca Brera 4 Corso Bueno s Aires 21
Orto Botanico 5 Basilica San lorenzo 22
Stadio Giuseppe Meazza 6 Porta Romana 23
Cimitero monumentale 8 Grattacielo Pirelli 24
Università Bocconi 9 Bosco Verticale 25
Stazione Ferroviaria Centrale 10 Museo Nazionale della Scienza 26
Aereoporto Linate 11 Chiesa San Sepolcro 27
Direzione Aereoporto Malpensa 12 Galleria Arte Moderna 28
Ospedale 13
PO Numero di arrivi
Direzione Malpensa 158
Aeroporto Linate 49
Piazza Duomo 9
Ospedale 4
Zona Navigli 3
Corso Buenos Aires 3
Bosco Verticale 2
Stazione Centrale 1
Porta Ticinese 1
Museo Arte Moderna 1
San Vittore 1
Not all PO present in the OD Matrix,
probabily for the difficulty to park in
centers.
To confirm this trend there is the
completely cluster end absence in
the historic centre.
Weather Analysis
FASCIA Martedì Venerdì Media settimanale
23:30 - 00:59 49 78 36
01:00 - 01:59 13 15 22
02:00 - 02:59 21 18 87
03:00 - 03:59 72 70 66
04:00 - 04:59 167 161 162
05:00 - 05:59 398 (Nebbia) 332 (Sereno) 333
06:00 - 06:59 341 (Nebbia) 326 (Sereno) 333
07:00 - 07:59 221 (Nebbia) 208 (Sereno) 232
08:00 - 08:59 184 (Nubi Sparse) 166 (Foschia) 198
09:00 - 09:59 153 (Nubi Sparse) 156 (Sereno) 185
10:00 - 10:59 201 205 238
11:00 - 11:59 208 200 226
12:00 - 12:59 237 225 248
13:00- 13:59 196 220 227
14:00 - 14:59 233 218 256
15:00 - 15:59 304 (Nubi Sparse) 254 (Sereno) 322
16:00 - 16:59 326 (Nubi Sparse) 239 (Sereno) 319
17:00 - 17:59 298 (Nubi Sparse) 235 (Sereno) 311
18:00 - 18:59 185 (Nubi Sparse) 171 (Sereno) 213
19:00 - 19:59 128 (Nubi Sparse) 150 (Sereno) 159
20:00 - 20:59 136 (Nubi Sparse) 134 148
21:00 - 21:59 128 102 131
22:00 - 22:59 67 74 71
23:00 - 00:30 37 80 43
0
50
100
150
200
250
300
350
400
450
23:30-00:59
01:00-01:59
02:00-02:59
03:00-03:59
04:00-04:59
05:00-05:59
06:00-06:59
07:00-07:59
08:00-08:59
09:00-09:59
10:00-10:59
11:00-11:59
12:00-12:59
13:00-13:59
14:00-14:59
15:00-15:59
16:00-16:59
17:00-17:59
18:00-18:59
19:00-19:59
20:00-20:59
21:00-21:59
22:00-22:59
23:00-00:30
Martedì Venerdì Media Settimanale
Analysis specific days
(martedì)
(venerdì)
Traffic flow analysis towards the airport
0
2
4
6
8
10
12
14
16
18
05:00-05:59
06:00-06:59
07:00-07:59
08:00-08:59
09:00-09:59
15:00-15:59
16:00-16:59
17:00-17:59
18:00-18:59
19:00-19:59
Partenze da Linate
Martedì start
Venerdì start
AVG week start
0
2
4
6
8
10
12
14
16
18
05:00-05:59
06:00-06:59
07:00-07:59
08:00-08:59
09:00-09:59
15:00-15:59
16:00-16:59
17:00-17:59
18:00-18:59
19:00-19:59
Arrivi a Linate
Martedì end
Venerdì end
AVG week end
• Despite the centre is very busy, we have mainly passing trajectories
• Denied expectations on the consequences of traffic decrease over the weekend
• average speed don't increase
• average length of shorts routes increase
• Visitors short trips extremely greater than residents short trip
• Visitors don’t use own car to move in Milano
• Visitors speed extremely lower than residents speed
• Visitors park in Milano suburbs and use metro or TrenoNord train
company
• On the opposite to duration and speed, length of trips in unchanged between
visitors and residents
• Average traffic on weekend in each time slots is always lower than the working
days
• The points of interest are not nearly ever reached by car
• The weather affects especially the highway and the roads to Linate Airport.
These trends are valid for both residents and visitors
Other Slides
We used the following SQL query:
0-30
30-60
60-90
90-120
120-150
150-180
180-210
210-240
240-270
270-300
300-330
330-360
360-3902169
1136
467
300
184103 6 2 2 3 0 1 1
Distribuzione delle durate Martedì
50%
26%
11%
7%
Composizione delle durate Martedì
0-30
30-60
60-90
90-120
120-150
150-180
180-210
Duration (continuation)
0-30
30-60
60-90
90-120
120-150
150-180
180-210
210-240
240-270
270-300
1293
436
275
157
93 65
4 5 0 1
Distribuzione delle durate Sabato
55%
19%
12%
7%
4% 3%
Composizione delle durate Sabato
0-30
30-60
60-90
90-120
120-150
150-180
180-210
0-30
30-60
60-90
90-120
120-150
150-180
180-210
210-240
240-270
270-300
300-330
2207
852
447
276
156 127
7 2 2 1 2
Distribuzione delle durate Venerdi
54%
21%
11%
7%
Composizione delle durate Venerdi
0-30
30-60
60-90
90-120
120-150
150-180
180-210
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
601
1268
881
590
359
250
173
110 74 38 15 9 3 3
Distribuzione delle velocità Martedì
14%
29%
20%
13%
8%
6% 4%
Composizione delle velocità Martedì
0-10
10-20
20-30
30-40
40-50
50-60
60-70
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
601
1102
528507
368
228
174
124 75 31 19 13 9
Distribuzione delle velocità Venerdì
16%
29%
14%
13%
10%
6% 5%
Composizione delle velocità Venerdì
0-10
10-20
20-30
30-40
40-50
50-60
60-70
Speed (continuation)
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
358
592
482
290
169
124112
60 56 34 26 13 10 3
Distribuzione delle velocità Sabato
15%
25%
21%
13%
7%
5%
5%
Composizione delle velocità Sabato
0-10
10-20
20-30
30-40
40-50
50-60
60-70
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
1576 1605
712
303
98 36 20 13 3 3 2 2 0 1
Distribuzione delle lunghezze Martedì
36%
37%
16%
7%
Composizione delle lunghezze Martedì
0-10
10-20
20-30
30-40
40-50
50-60
60-70
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
1491 1502
637
287
80 32 24 13 6 3 2 1 1
Distribuzione delle lunghezze Venerdì
36%
37%
16%
7%
Composizione delle lunghezze Venerdì
0-10
10-20
20-30
30-40
40-50
50-60
60-70
Length (continuation)
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
913
732
353
202
63 28 16 13 2 3 2 1 1
Distribuzione delle lunghezze Sabato
39%
31%
15%
9%
Composizione delle lunghezze Sabato
0-10
10-20
20-30
30-40
40-50
50-60
60-70
10%
13%
15%
12%
29%
10%
8% 3%
Composizione del traffico residenti Domenica
Night
Early Morning
Morning
Lunch
Afternoon
Early Evening
Dinner
Fascia Numero traiettorie
Night 213
Early
Morning
276
Morning 319
Lunch 261
Afternoon 603
Early
Evening
199
Dinner 169
Late Evening 65
17%
17%
13%
10%
27%
8% 6% 2%
Composizione del traffico residenti Martedì
Night
Early Morning
Morning
Lunch
Afternoon
Early Evening
Dinner
Fascia Numero traiettorie
Night 715
Early
Morning
750
Morning 570
Lunch 438
Afternoon 1186
Early Evening 318
Dinner 265
Late Evening 99
16%
18%
14%11%
24%
8% 6%
3%
Composizione del traffico residenti Venerdì
Night
Early Morning
Morning
Lunch
Afternoon
Early Evening
Dinner
Fascia Numero traiettorie
Night 634
Early
Morning
708
Morning 569
Lunch 449
Afternoon 956
Early Evening 323
Dinner 236
Late Evening 137
11%
15%
16%
12%
25%
7%
9%
5%
Composizione del traffico residenti Sabato
Night
Early Morning
Morning
Lunch
Afternoon
Early Evening
Dinner
Fascia Numero traiettorie
Night 252
Early Morning 350
Morning 351
Lunch 273
Afternoon 564
Early Evening 168
Dinner 197
Late Evening 115

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[Slides] Multidimensional Analysis of Milano Mobility

  • 1. Emiliano Fuccio Tommaso Furlan Maurizio DeiddaBig Data Analytics (23/01/2017)
  • 2. Name Description user_id Unique id related to a car timestamp Date and time on the detection of the GPS device mounted on the car day_of_week Specifying the day of the week on the recordingade by GPS time_slot Day parting based on the time recorded by the GPS device lat Latitude of detection lon Longitude of detection GPS detection in Milan in the period between 1° April and April 7 2007
  • 3. Before Data Preparation We have approximately 1.800.000 detections (points)
  • 4. Days analyzed for residents: Sunday – Tuesday – Friday – Saturday Days analyzed for visitors: Friday (from 1Pm) - Saturday • Identify the most achieved attractions (Point of Interest) • Measuring the intensity of the traffic according to the zone, the time of day and to points of interest. • Get insights thanks to the most important route’s statistics (length, duration, speed) • Detect "behavioral" differences among residents and visitors. • Multidimensional analysis with dimensions: weather - time - traffic
  • 5. Visitors Friday (from 1PM) Saturday (Split 2) Residents Sunday Tuesday Friday Saturday (Split 1) Split Dataset into two parts from Split 2 delete all users having user_id content in Split 1
  • 6. RESIDENTS • Milano area: 1575.65 Km2 • Grid with areas: 10 Km2 • Low Flow – High Flow
  • 7. The trend of high traffic flow in the city center and on high speed highways, doesn't change with respect to residents. VISITORS
  • 8. Min Max AVG Dom 0.367 368.483 40.56 Mart 0.3 367.983 44.731 Ven 0.25 325.25 43.681 Sab 0.55 290.467 43.098 0-30 30-60 60-90 90-120 120-150 150-180 180-210 210-240 240-270 270-300 300-330 330-360 360-390 1177 457 262 109 56 44 1 3 2 1 1 0 1 Distribuzione delle durate Domenica 56%22% 12% 5% Composizione delle durate Domenica 0-30 30-60 60-90 90-120 120-150 150-180 180-210 Duration • < 30 minutes: increase from Friday to Sunday, lower on Tuesday • 30 – 60 minutes: decrease from Friday to Sunday, high on Tuesday • >60 minutes: linear trend during the week
  • 9. Speed Min Max AVG Dom 5.002 136.051 31.643 Mart 5.01 133.097 27.782 Ven 5.02 125.157 28.907 Sab 5.032 137.392 30.983 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 130-140 244 556 417 287 193 136 103 72 38 18 18 13 5 2 Distribuzione delle velocità Domenica 12% 26% 20%14% 9% 6% 5% Composizione delle velocità Domenica 0-10 10-20 20-30 30-40 40-50 50-60 60-70 • No significant differences between working days speed and weekend days ones • Probably why are there especialy urban detections?
  • 10. Min Max AVG Dom 0.047 152.287 16.193 Mart 0.059 139.366 15.719 Ven 0.029 126.646 15.28 Sab 0.108 125.017 15.823 Length 0-11 11-22 22-33 33-44 44-55 55-66 66-77 77-88 88-99 99-110 110-121 121-132 132-143 143-154 871 717 336 125 37 10 6 2 3 3 2 1 0 1 Distribuzione delle lunghezze Domenica 41% 34% 16% 6% Composizione delle lunghezze Domenica 0-10 10-20 20-30 30-40 40-50 50-60 60-70 • Short trips (0-20 Km) have the opposite trend than long trips (>20 Km) • Descend trend for short trips and ascend trend for long trips
  • 11. VisitorsDuration 454 79 42 13 3 3 Distribuzione durate dei visitatori Venerdì 1395 227 113 47 26 10 Distribuzione delle dei visitatori Sabato 76% 13% 7% 2% 1% 1% Composizione delle durate dei visitatori Venerdì 0-30 30-60 60-90 90-120 120-150 150-180 77% 12% 6% 3% 1%1% Composizione delle durate dei visitatori Sabato 0-30 30-60 60-90 90-120 120-150 150-180
  • 12. Residenti Giorno Visitatori 0 – 30: 54% 30 – 60: 21% Venerdì 0 – 30: 76% 30 – 60: 13% 0 – 30: 55% 30 – 60: 19% Sabato 0 – 30: 77% 30 – 60: 12% Visitors short trips extremely greater than residents short trip Visitors don’t use own car to move in Milano
  • 13. Speed 41 102 88 64 41 45 29 24 33 43 35 24 21 4 Distribuzione delle velocità dei visitatori Venerdì 7% 17% 15% 11%7% 8% 5% 4% 5% 7% 6% 4% 3% Composizione delle velocità dei visitatori Venerdì 0-10 10-20 20-30 30-40 40-50 50-60 60-70 126 290 253 180 133 115 92 9010293 124116 66 28 10 Distribuzione delle velocità dei visitatori Sabato 7% 16% 14% 10% 7%6%5% 5% 6% 5% 7% 6% 4% Composizione delle velocità dei visitatori Sabato 0-10 10-20 20-30 30-40 40-50 50-60 60-70
  • 14. Residenti Giorno Visitatori 0 – 30: 59% 0 – 50: 82% +50: 18% Venerdì 0 – 30: 39% 0 – 50: 57% +50: 43% 0 – 30: 61% 0 – 50: 81% +50: 19% Sabato 0 – 30: 40% 0 – 50: 53% +50: 47% Visitors speed extremely lower than residents speed Visitors park in Milano suburbs and use metro or TrenoNord train company
  • 15. Length 193 203 112 66 13 3 3 1 Distribuzione delle lunghezze dei visitatori Venerdì 32% 34% 19% 11% Composizione delle lunghezze dei visitatori Venerdì 0-10 10-20 20-30 30-40 40-50 50-60 603 621 321 219 38 5 5 3 3 Distribuzione delle lunghezze dei visitatori Sabato 33% 34% 18% 12% Composizione delle lunghezze dei visitatori Sabato 0-10 10-20 20-30 30-40 40-50 50-60
  • 16. Residenti Giorno Visitatori 0 – 20: 73% 0 – 30: 89% Venerdì 0 – 20: 66% 0 – 30: 85% 0 – 20: 70% 0 – 30: 85% Sabato 0 – 20: 67% 0 – 30: 85% On the opposite to duration and speed, length of trips in unchanged between visitors and residents.
  • 17. Time Label 00:00 – 05:59 Night 06:00 -08:59 Early Morning 09:00 – 11:59 Morning 12:00 – 13:59 Lunch 14:00 – 17:59 Afternoon 18:00 – 19:59 Early Evening 20:00 – 21:59 Evening 22:00 – 23:59 Late Evening
  • 18. Time slots inhomogeneous? NORMALIZE! Night Early Mornin g Mornin g Lunch Afterno on Early Evening Dinner Late Evening Domenica 35,5 92 106,3333 130,5 150,75 99,5 84,5 32,5 Martedì 119,1667 250 190 219 296,5 159 132,5 49,5 Venerdì 105,6667 236 189,6667 224,5 239 161,5 118 68,5 Sabato 42 116,6667 117 136,5 141 84 98,5 57,5 0 50 100 150 200 250 300 350 Corsemedieorarieperfasce Intesità di traffico per fasce orarie • Average traffic on weekend in each time slot is always lower than the working days • Working Cycle: (early morning + morning) is almost equal to (afternoon + early evening)
  • 19. Visitors 9% 17% 16% 13% 25% 8% 8% 4% Composizione del traffico visitatori Sabato Night Early Morning Morning Lunch Afternoon Early Evening Dinner Time Slot # trajectories visitors # trajectories residents Night 164 252 Early Morning 307 350 Morning 292 351 Lunch 227 273 Afternoon 459 564 Early Evening 143 168 Dinner 146 197 Late Evening 80 115 • Friday not considered • Decrease of the average trajectories in visitors • Trend unchanged
  • 20. We partition the detection area in this way: • Center: into the yellow perimeter • Macroareas neighboring: between the yellow perimeter and mains roads • Suburbs and airports: Externaly geographic area and intersects red perimeter Macrozones flows analysis
  • 21. O/D Matrix zones The obtained results are equivalent, this highlights similar trend between working days and holidays ones.
  • 22. PO flows analysis Po Rif. Po Rif. Piazza Duomo 1 Zona Navigli 14 Galleria Vittorio Emanuele 1 Carcere San Vittore 15 Palazzo Reale 1 Basilica Sant'Ambrogio 16 Teatro Scala 1 Università Cattolica 17 Piazza Mercanti 1 Biblioteca Ambrosiana 18 Castello sforzesco 2 Politecnico 19 Parco Sempione 3 Porta Ticinese 20 Pinacoteca Brera 4 Corso Bueno s Aires 21 Orto Botanico 5 Basilica San lorenzo 22 Stadio Giuseppe Meazza 6 Porta Romana 23 Cimitero monumentale 8 Grattacielo Pirelli 24 Università Bocconi 9 Bosco Verticale 25 Stazione Ferroviaria Centrale 10 Museo Nazionale della Scienza 26 Aereoporto Linate 11 Chiesa San Sepolcro 27 Direzione Aereoporto Malpensa 12 Galleria Arte Moderna 28 Ospedale 13
  • 23. PO Numero di arrivi Direzione Malpensa 158 Aeroporto Linate 49 Piazza Duomo 9 Ospedale 4 Zona Navigli 3 Corso Buenos Aires 3 Bosco Verticale 2 Stazione Centrale 1 Porta Ticinese 1 Museo Arte Moderna 1 San Vittore 1 Not all PO present in the OD Matrix, probabily for the difficulty to park in centers.
  • 24. To confirm this trend there is the completely cluster end absence in the historic centre.
  • 25. Weather Analysis FASCIA Martedì Venerdì Media settimanale 23:30 - 00:59 49 78 36 01:00 - 01:59 13 15 22 02:00 - 02:59 21 18 87 03:00 - 03:59 72 70 66 04:00 - 04:59 167 161 162 05:00 - 05:59 398 (Nebbia) 332 (Sereno) 333 06:00 - 06:59 341 (Nebbia) 326 (Sereno) 333 07:00 - 07:59 221 (Nebbia) 208 (Sereno) 232 08:00 - 08:59 184 (Nubi Sparse) 166 (Foschia) 198 09:00 - 09:59 153 (Nubi Sparse) 156 (Sereno) 185 10:00 - 10:59 201 205 238 11:00 - 11:59 208 200 226 12:00 - 12:59 237 225 248 13:00- 13:59 196 220 227 14:00 - 14:59 233 218 256 15:00 - 15:59 304 (Nubi Sparse) 254 (Sereno) 322 16:00 - 16:59 326 (Nubi Sparse) 239 (Sereno) 319 17:00 - 17:59 298 (Nubi Sparse) 235 (Sereno) 311 18:00 - 18:59 185 (Nubi Sparse) 171 (Sereno) 213 19:00 - 19:59 128 (Nubi Sparse) 150 (Sereno) 159 20:00 - 20:59 136 (Nubi Sparse) 134 148 21:00 - 21:59 128 102 131 22:00 - 22:59 67 74 71 23:00 - 00:30 37 80 43
  • 27. Traffic flow analysis towards the airport 0 2 4 6 8 10 12 14 16 18 05:00-05:59 06:00-06:59 07:00-07:59 08:00-08:59 09:00-09:59 15:00-15:59 16:00-16:59 17:00-17:59 18:00-18:59 19:00-19:59 Partenze da Linate Martedì start Venerdì start AVG week start 0 2 4 6 8 10 12 14 16 18 05:00-05:59 06:00-06:59 07:00-07:59 08:00-08:59 09:00-09:59 15:00-15:59 16:00-16:59 17:00-17:59 18:00-18:59 19:00-19:59 Arrivi a Linate Martedì end Venerdì end AVG week end
  • 28. • Despite the centre is very busy, we have mainly passing trajectories • Denied expectations on the consequences of traffic decrease over the weekend • average speed don't increase • average length of shorts routes increase • Visitors short trips extremely greater than residents short trip • Visitors don’t use own car to move in Milano • Visitors speed extremely lower than residents speed • Visitors park in Milano suburbs and use metro or TrenoNord train company • On the opposite to duration and speed, length of trips in unchanged between visitors and residents • Average traffic on weekend in each time slots is always lower than the working days • The points of interest are not nearly ever reached by car • The weather affects especially the highway and the roads to Linate Airport. These trends are valid for both residents and visitors
  • 30. We used the following SQL query:
  • 31. 0-30 30-60 60-90 90-120 120-150 150-180 180-210 210-240 240-270 270-300 300-330 330-360 360-3902169 1136 467 300 184103 6 2 2 3 0 1 1 Distribuzione delle durate Martedì 50% 26% 11% 7% Composizione delle durate Martedì 0-30 30-60 60-90 90-120 120-150 150-180 180-210 Duration (continuation)
  • 32. 0-30 30-60 60-90 90-120 120-150 150-180 180-210 210-240 240-270 270-300 1293 436 275 157 93 65 4 5 0 1 Distribuzione delle durate Sabato 55% 19% 12% 7% 4% 3% Composizione delle durate Sabato 0-30 30-60 60-90 90-120 120-150 150-180 180-210 0-30 30-60 60-90 90-120 120-150 150-180 180-210 210-240 240-270 270-300 300-330 2207 852 447 276 156 127 7 2 2 1 2 Distribuzione delle durate Venerdi 54% 21% 11% 7% Composizione delle durate Venerdi 0-30 30-60 60-90 90-120 120-150 150-180 180-210
  • 33. 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 130-140 601 1268 881 590 359 250 173 110 74 38 15 9 3 3 Distribuzione delle velocità Martedì 14% 29% 20% 13% 8% 6% 4% Composizione delle velocità Martedì 0-10 10-20 20-30 30-40 40-50 50-60 60-70 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 601 1102 528507 368 228 174 124 75 31 19 13 9 Distribuzione delle velocità Venerdì 16% 29% 14% 13% 10% 6% 5% Composizione delle velocità Venerdì 0-10 10-20 20-30 30-40 40-50 50-60 60-70 Speed (continuation)
  • 34. 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 130-140 358 592 482 290 169 124112 60 56 34 26 13 10 3 Distribuzione delle velocità Sabato 15% 25% 21% 13% 7% 5% 5% Composizione delle velocità Sabato 0-10 10-20 20-30 30-40 40-50 50-60 60-70
  • 35. 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 130-140 1576 1605 712 303 98 36 20 13 3 3 2 2 0 1 Distribuzione delle lunghezze Martedì 36% 37% 16% 7% Composizione delle lunghezze Martedì 0-10 10-20 20-30 30-40 40-50 50-60 60-70 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 1491 1502 637 287 80 32 24 13 6 3 2 1 1 Distribuzione delle lunghezze Venerdì 36% 37% 16% 7% Composizione delle lunghezze Venerdì 0-10 10-20 20-30 30-40 40-50 50-60 60-70 Length (continuation)
  • 36. 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100-110 110-120 120-130 913 732 353 202 63 28 16 13 2 3 2 1 1 Distribuzione delle lunghezze Sabato 39% 31% 15% 9% Composizione delle lunghezze Sabato 0-10 10-20 20-30 30-40 40-50 50-60 60-70
  • 37. 10% 13% 15% 12% 29% 10% 8% 3% Composizione del traffico residenti Domenica Night Early Morning Morning Lunch Afternoon Early Evening Dinner Fascia Numero traiettorie Night 213 Early Morning 276 Morning 319 Lunch 261 Afternoon 603 Early Evening 199 Dinner 169 Late Evening 65 17% 17% 13% 10% 27% 8% 6% 2% Composizione del traffico residenti Martedì Night Early Morning Morning Lunch Afternoon Early Evening Dinner Fascia Numero traiettorie Night 715 Early Morning 750 Morning 570 Lunch 438 Afternoon 1186 Early Evening 318 Dinner 265 Late Evening 99
  • 38. 16% 18% 14%11% 24% 8% 6% 3% Composizione del traffico residenti Venerdì Night Early Morning Morning Lunch Afternoon Early Evening Dinner Fascia Numero traiettorie Night 634 Early Morning 708 Morning 569 Lunch 449 Afternoon 956 Early Evening 323 Dinner 236 Late Evening 137 11% 15% 16% 12% 25% 7% 9% 5% Composizione del traffico residenti Sabato Night Early Morning Morning Lunch Afternoon Early Evening Dinner Fascia Numero traiettorie Night 252 Early Morning 350 Morning 351 Lunch 273 Afternoon 564 Early Evening 168 Dinner 197 Late Evening 115