Budapest University of Technology and Economics Faculty of Transportation Engineering and Vehicle Engineering Department of Transport Technology and Economics
„Method of transport data recording. Cross-section transport data recording. Analyzing of traffic flows. Presentation of results Dr. Péter Mándoki associate professor
Traffic data collection Some facts about transport data collection and recording
Transport data collection • • • •
Public transport Individual transport Both together this is the best solution But technically it is most simle to do separatly
Public transport - Traffic survey
Cross section
Aim counting
On a stopping place with counter-proof
On the vehicle
From vider effect
On the vehicle with counter-proof
Questionarrity Second ticket method
Questionarrity
With the Car driver automatical counting on the vechicle Ticket selling automat With „cloud” method
Interview on working place Household interview
Idividual transport - Traffic surway
Cross section
Inductive loop Near the road with couter-proof camera
Aim counting
Intersections
From vider effect
Questionarrity License plate recording With colour paper Camera (following)
Questionarrity Interview on working place Household interview
0. Induktive Loops Vehicle Counter Magyar Közút: the road operator of Hungary
SOME REALIZED TRAFFIC COUNTING IN OUR DEPARTMENT
1. BKSz (Budapest Traffic Association) counting
• Every Year 2004 – 2010 • All Railway Stops in Budapest (MÁV) 41 places • Most of suburban Bus Stops Budapest (Volán) 72 places • Between 6 – 22 hours. Sometimes 4 – 24 hours. • Aim: divide income between the providers • ‘Budapest Season Ticket’ is valid for MÁV, Volán, and BKV. (no other ticket, or validity outside the border of Budapest)
• • • •
11 railway lines 23 Bus lines are leaving Budapest 200 students Both direction
Railway (MÁV)
Out
Bus (Volán)
In
Out
In
Ascendent passenger (6-22)
[passenger]
77 065
7 863
39 160
1 530
Descendent passenger (6-22)
[passenger]
7 087
72 470
936
35 327
Descendent passengers inside Budapest (622) Ascendent passengers inside Budapest (6-22)
[%]
9,20
Average jurney distance
[%]
-
2,39 -
-
-
10,85
4,33
[km]
12,52
12,15
6,67
6,31
Average hurrying
[min]
-0,5
-0,8
-1,6
-4,0
Average delay
[min]
2,9
5,3
3,1
9,1
Delay / hurrying
MÁV
Várakozó utas esetén azon járatok száma, amelyek nem álltak meg
[pcs]
Volán
Out
In
-
-
Out
In 64
213
Népliget Bus Station
1 200 1 000
[passenger]
800
600 400 200 0 6
7
8
9
10
11
12
13 [óra]
14
15
16
17
18
19
20
21
Budapest-Keleti railway station Felszálló utasok KI irányban
Leszálló utasok BE irányban
4000 3500
[passenger]
3000 2500 2000 1500 1000 500 0
6
7
8
9
10
11
12
13
14 [óra]
15
16
17
18
19
20
21
Traffic geo data base
13
2. Újpest (north pest) aim traffic counting
• Before and after the opening the new M0 Bridge („Megyeri Bridge”) • 22. cross section • 18. border point • Between 6-22 • 4 important point 0-24 hours for the calibration • 3 Parking place • Week days and week ends
• • • •
Methodology: Licenc plate number recording Aslo with voice recording Decide the traffic: – – – –
inside the district Going throught the district Starting traffic Aim traffic
• Using questionarity for drivers
B
Újpest C
3. Újpest parking • • • •
All parking places in Újpest Motorola MC70 Roundtrip every half hour Recording program
Motorola MC70
Újpest – parkolás felmérés
The aim of parking count Determinating parkink zones
Parking places capacity Parking car number day and night – weekdays and weekends, Parking regulary and irregularly, Parking time and the habitation of car owner
Újpest – parkolás felmérés
Methodology Division of parking places: Parking zones: depend the distance from metro station: – Újpest-Központ metro station – in 200 meter, – Újpest-Városkapu metro station – in 200 meter, – Both station 200-400 meter.
Parking areas: – Street-sectors, – Parking areas, – Other territories.
Újpest – parkolás felmérés
Parking zones
Újpest – parkolás felmérés
Parking areas
Újpest – parkolás felmérés
Measurements data Date: ▫ Daytime measurement: 2011. apr. 5-7. 7:30-18 hours ▫ Night time measurement : 2011. apr. 5-7-9.
Data collection method: ▫ Roundtrips in every half hours, ▫ University students, ▫ Vehicle register.
Újpest – parkolás felmérés
A parking capacity
Újpest – parkolás felmérés
Daytime
Parking capacity using Újpest-Városkapu
Újpest-Központ 140%
120%
130%
110%
120%
100%
110% 100%
90%
90%
80%
80%
70%
70%
60%
60%
8:00 8:30 9:00 9:30 10:0010:30 11:00 11:3012:00 12:3013:00 13:30 14:0014:30 15:0015:30 16:00 16:3017:00 17:30
8:00 8:30 9:00 9:30 10:00 10:3011:00 11:30 12:0012:30 13:0013:30 14:00 14:3015:00 15:30 16:0016:30 17:00 17:30
200-400 méteres környezet
Teljes terület
95%
100%
90%
95% 90%
85%
85%
80% 80%
75% 75%
70%
70%
65%
65%
60%
60%
8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30
8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:3012:00 12:30 13:00 13:3014:00 14:30 15:00 15:3016:00 16:30 17:00 17:30
Újpest – parkolás felmérés
Daytime
Parking capacity using
Újpest – parkolás felmérés
Daytime
Parking capacity using – non inhabitants
Újpest – parkolás felmérés
Daytime
Parking time 2 500
[jármű]
2 000
1 500
1 000
500
0 0,5
1,0
1,5
2,0
2,5
3,0
3,5
4,0
4,5
5,0
5,5
6,0
6,5
7,0
7,5
8,0
8,5
9,0
9,5 10,0
[óra] Újpest-Központ
Újpest-Városkapu
200-400 méteres környezet
Teljes terület
Újpest – parkolás felmérés
Daytime
Parking time 70% 60% 50% helyi Local
40%
Non local – but living in újpesti Újpest
30%
idegen Non local
20% 10% 0% Újpest-Központ
ÚjpestVároskapu
200-400 méteres környezet
Teljes terület
Whole territory
Minimum 8 hours parking divisaion by habitants
Újpest – parkolás felmérés
Night-time
Parking capacity using
4. Measuring with hand GPS
Measuring with hand GPS
5. Vehicle capacity using – and safity level • How many passengers are in one car • Handy usage (driver) • Safety-belt usage (driver) • (car/hour)
Psion workabout MDA
Vechicle passenger (Petőfi Bridge) vehicle 7000
6000
5000
4000
3000
2000
1000
0 1
2
3
4
5
6
7
8
Passenger
Safety belt usage vehicle 7000
6506
6000
5000
4000
Vechicle
3323
Using safety belt 3000
1908 2000 1157 1000 294 191
60
36
13
8
5
3
0 1
2
3
4
5
6
Passenger
Handy usage 9,00%
8,00%
7,69%
7,64%
7,00%
6,00%
5,00%
3,83%
4,00%
4,08% 3,33%
3,00%
2,00%
1,00%
0,00% 1
2
3
4
5
Passenger
Vechicle types 1994 - 2000 eastern
90%
western
80% 70%
65,42%
75,68%
77,55%
84,42%
88,15%
87,60%
67,45%
60% 50% 40%
34,58%
32,55%
30%
24,32%
22,45% 15,58%
20%
11,85%
12,40%
1999
2000
10% 0% 1994
1995
1996
1997
1998
Taxi types 1994 - 2000 93,33%
100%
eastern
90%
94,35%
96,33%
western
74,49%
80% 70%
94,02%
73,13%
64,67%
60% 50% 40%
35,33% 25,51%
30%
26,87% 6,67%
20% 10%
5,98%
5,65%
3,67%
1998
1999
2000
0% 1994
1995
1996
1997
Colour distribution of vehicles 1000
946
900
red
788
800
white
700
green 600 500
black
506
477
yellow 400
360
365
blue
300
230
200
other
67
100 0 red
white
green
Colour, 2011, Petőfi Bridge
black
yellow
silver
blue
silver
other
Type distribution of vehicles 180 161
160
140
120
114 100
99
100
77
80
73 66
60
54 44
40
42
35 28
25 18
20
19
23 15 8
4 0
2006
22
26
24 15
12
9 4
4
6. „cloud” passenger measuring
7. Tachograf evaluation
Digital tachograf for tramways
(+1) Getting in and out speed measurement
8. Measurement of pedestrian traffic flow
Target of the investigation • Find out the pedestrian traffic and pedestrian habits at intermodal centers, interchange stations, underpasses • Calculate the capacity, the occupancy of the underpass • Investigate the ratio between pedestrian flow on crosswalk and underpass
Investigation features 1. Groups The students measures in four-member groups • 2 people count the pedestrians that cross trough the cross-section (one spots the outward goings one the inward goings) • 2 people investigate the pedestrian move directions with labels which the pedestrian give at the entrance of the underpass (one gives one collects the labels)
Investigation features 2. The label contains:
Kérem, adja le társunknak a kijáratnál, ahol az aluljárót elhagyja!
„Please give it to our colleague at the exit where you leave the underpass!” Logo and name of Budapest University of Technology and Economics Short introduction of the students: „We are students of BUTE, Transportation engineering and Vehicle Engineering Faculty”
Side1
Budapesti Műszaki és Gazdaságtudományi Egyetem
A BME Közlekedésmérnöki és Járműmérnöki Kar hallgatói vagyunk.
Side2
Mérési gyakorlatunk célja az aluljáró gyalogos forgalmának felmérése. Köszönjük, hogy közreműködésével segítette munkánkat!
The aim of the investigation shortly: „The aim of our practise to investigate the pedestrian traffic in the underpass.”
Number of entrance.
„Thank you for helping our work!”
Investigation features Gyalogos mérőlap
3. Measuring Page Place of measure / Number of measuring group
Helyszín/ mérőcsoport
Negyedórás idő bontás
Mérést végezte:
Dátum:
Date ∑
Time in quarter-hour ∑
Name ∑
Sum of quarter-hour results
∑
Investigation features 4. Site Plan:
Sign of measuring group
Exit
Name of the Street or Station
Tram
Metro station
Investigation features 5. Purpose: The purpose of the exercise is calculating the capacity and the traffic volume of the underpass group by exits. Leaders task: We should collect the data from all measuring groups and send back the merged data
Investigation features 6. How to calculate: where: • 𝑖: 𝑝𝑙𝑎𝑐𝑒 𝑜𝑓 𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛; 𝑐𝑖−𝑗 ∗𝑒 𝑐𝑖−∑ 𝑖,𝑙𝑒
• 𝑗: 𝑝𝑙𝑎𝑐𝑒 𝑜𝑓 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑛𝑔; • 𝑐𝑖−𝑗 : 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑖𝑐𝑘𝑒𝑡𝑠 𝑔𝑖𝑣𝑒𝑛 𝑝𝑙𝑎𝑐𝑒 𝑖 and 𝑐𝑜𝑢𝑛𝑡𝑒𝑑 𝑎𝑡 𝑝𝑙𝑎𝑐𝑒 𝑗;
𝑐𝑖−𝑗 ∗𝑒 𝑐∑−𝑗 𝑗,𝑓𝑒𝑙
• 𝑐𝑖−∑ : number of all tickets that given at place i; • 𝑐∑−𝑗 : number of all tickets collected at place j; • 𝑒𝑖,𝑙𝑒 : number of people that enter at i;
• 𝑒𝑗,𝑓𝑒𝑙 : number of people that exit at j.
Results These results are given from students’ reports:
Results These results are given from students’ reports:
Results These results are given from students’ reports:
Results These results are given from students’ reports:
(+2) Simple cross section counting
Székesfehérvár
Szeged
Optimalizing of own coach service for costumers TESCO-Globál Supermarkets.
Geo-coding of road networks
Pl. Mátészalka
Geocoding of the bus stops
TESCO Pl. Mátészalka
Optimalizing FIT Eh =
1
0
1
1
0
1
1
1
1
0
0
0
1
0
1
1
00 0 01
megállók
10 11
(E x )
(E1 )
(E2 )
(E h1 )
(E h )
1. pont
2. pont
3. pont 4. pont
1. szülő
1
0
1
1
0
1
1
1
1
0
0
0
1
0
1
2. szülő
0
0
1
0
0
1
1
0
1
0
1
0
1
0
1
maszk
0
0
1
1
1
1
0
0
0
1
1
0
0
0
0
1. gyerek
1
0
1
0
0
1
1
1
1
0
1
0
1
0
1
2. gyerek
0
0
1
1
0
1
1
0
1
0
0
0
1
0
1
Objektiv function calculation Spending power modelling
Cost of the bus line modelling
TSP heurisztika
Profit modelling
MAX! Listening for the maximal travel time!
Mátészalka (25 minutes) New bus line
Existing bus line
Profit modelling: 86 000 Ft/running
Profit modelling: 55 000 Ft/running
9% +Line 56% +Profit
Jászberény (25 minutes) New bus line
Existing bus line
Profit modelling : 77 000 Ft/running
Profit modelling : 60 000 Ft/running
25% +Line 27% +Profit
