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 With the Car driver automatical counting on the vechicle Ticket selling automat With cloud method Questionarrity Second ticket method Questionarrity Interview on working place Household interview
Idividual transport - Traffic surway Cross section Aim counting Intersections From vider effect Inductive loop Near the road with couter-proof camera 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) Bus (Volán) Out 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 (6- [%] 9,20-2,39-22) Ascendent passengers inside Budapest (6-22) [%] - 10,85-4,33 Average jurney distance [km] 12,52 12,15 6,67 6,31 Delay / hurrying Average hurrying [min] -0,5-0,8-1,6-4,0 Average delay [min] 2,9 5,3 3,1 9,1 Várakozó utas esetén azon járatok száma, amelyek nem álltak meg MÁV Volán Out In Out In [pcs] - - 64 213
[passenger] Népliget Bus Station 1 200 1 000 800 600 400 200 0 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 [óra]
[passenger] Budapest-Keleti railway station Felszálló utasok KI irányban Leszálló utasok BE irányban 4000 3500 3000 2500 2000 1500 1000 500 0 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 [óra]
13 Traffic geo data base
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 Újpest B 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-Központ Újpest-Városkapu 120% 140% 110% 100% 130% 120% 110% 90% 100% 80% 70% 90% 80% 70% 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 60% 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% 85% 90% 80% 75% 70% 85% 80% 75% 70% 65% 65% 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 60% 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 2 000 [jármű] 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% 40% 30% 20% helyi Local újpesti Non local but living in Újpest idegen Non local 10% 0% Újpest-Központ Újpest- Városkapu 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
vehicle Vechicle passenger (Petőfi Bridge) 7000 6000 5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 Passenger
vehicle 7000 6506 Safety belt usage 6000 5000 4000 3000 3323 Vechicle Using safety belt 2000 1908 1157 1000 0 294 191 60 36 13 8 5 3 1 2 3 4 5 6 Passenger
Handy usage 9,00% 8,00% 7,64% 7,69% 7,00% 6,00% 5,00% 4,00% 3,83% 4,08% 3,33% 3,00% 2,00% 1,00% 0,00% 1 2 3 4 5 Passenger
Vechicle types 1994-2000 90% 80% eastern western 75,68% 77,55% 84,42% 88,15% 87,60% 70% 65,42% 67,45% 60% 50% 40% 34,58% 32,55% 30% 24,32% 22,45% 20% 10% 15,58% 11,85% 12,40% 0% 1994 1995 1996 1997 1998 1999 2000
Taxi types 1994-2000 100% 90% eastern western 93,33% 94,02% 94,35% 96,33% 80% 74,49% 73,13% 70% 64,67% 60% 50% 40% 30% 35,33% 25,51% 26,87% 20% 6,67% 10% 5,98% 5,65% 3,67% 0% 1994 1995 1996 1997 1998 1999 2000
Colour distribution of vehicles 1000 946 900 800 700 600 500 400 300 200 100 477 360 365 67 506 788 230 red white green black yellow blue silver other 0 red white green black yellow blue silver other Colour, 2011, Petőfi Bridge
180 Type distribution of vehicles 160 161 140 120 114 100 99 100 80 77 66 73 60 54 40 20 4 18 25 35 19 15 8 12 28 23 22 26 4 4 24 44 42 15 9 0 2006
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: Please give it to our colleague at the exit where you leave the underpass! Kérem, adja le társunknak a kijáratnál, ahol az aluljárót elhagyja! Budapesti Műszaki és Gazdaságtudományi Egyetem Side1 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 The aim of the investigation shortly: The aim of our practise to investigate the pedestrian traffic in the underpass. A BME Közlekedésmérnöki és Járműmérnöki Kar hallgatói vagyunk. Mérési gyakorlatunk célja az aluljáró gyalogos forgalmának felmérése. Köszönjük, hogy közreműködésével segítette munkánkat! Thank you for helping our work! Number of entrance. Side2
Investigation features 3. Measuring Page Helyszín/ mérőcsoport Gyalogos mérőlap Negyedórás idő Mérést végezte: bontás Dátum: Place of measure / Number of measuring group Date Time in quarter-hour Name Sum of quarter-hour results
Investigation features 4. Site Plan: Tram Sign of measuring group Metro station Exit Name of the Street or 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: c i j c i e i,le where: i: place of distribution; j: place of collecting; c i j : number of tickets given place i and counted at place j; c i j c j e j,fel c i : number of all tickets that given at place i; c j : number of all tickets collected at place j; e i,le : number of people that enter at i; e j,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 E h = 1 0 1 1 0 1 1 1 1 0 0 0 1 0 1 FIT 1 megállók 10 00 0 11 01 (E x ) (E 1 ) 1. pont 2. pont 3. pont 4. pont (E 2 ) 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 (E h 1 ) 1. gyerek 1 0 1 0 0 1 1 1 1 0 1 0 1 0 1 (E h ) 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 Profit modelling TSP heurisztika MAX! Listening for the maximal travel time!
Mátészalka (25 minutes) New bus line Existing bus line Profit modelling: 86 000 Ft/running 9% +Line 56% +Profit Profit modelling: 55 000 Ft/running
Jászberény (25 minutes) New bus line Existing bus line Profit modelling : 77 000 Ft/running 25% +Line 27% +Profit Profit modelling : 60 000 Ft/running