Method of transport data recording. Cross-section transport data recording. Analyzing of traffic flows. Presentation of results

Átírás

1 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

2 Traffic data collection Some facts about transport data collection and recording

3 Transport data collection Public transport Individual transport Both together this is the best solution But technically it is most simle to do separatly

4 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

5 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

6 0. Induktive Loops Vehicle Counter Magyar Közút: the road operator of Hungary

7 SOME REALIZED TRAFFIC COUNTING IN OUR DEPARTMENT

8 1. BKSz (Budapest Traffic Association) counting Every Year 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)

9 11 railway lines 23 Bus lines are leaving Budapest 200 students Both direction

10 Railway (MÁV) Bus (Volán) Out In Out In Ascendent passenger (6-22) [passenger] Descendent passenger (6-22) [passenger] 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]

11 [passenger] Népliget Bus Station [óra]

12 [passenger] Budapest-Keleti railway station Felszálló utasok KI irányban Leszálló utasok BE irányban [óra]

13 13 Traffic geo data base

14 2. Újpest (north pest) aim traffic counting

15 Before and after the opening the new M0 Bridge ( Megyeri Bridge ) 22. cross section 18. border point Between important point 0-24 hours for the calibration 3 Parking place Week days and week ends

16 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

17 3. Újpest parking All parking places in Újpest Motorola MC70 Roundtrip every half hour Recording program Motorola MC70

18 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

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20 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 meter. Parking areas: Street-sectors, Parking areas, Other territories.

21 Újpest parkolás felmérés Parking zones

22 Újpest parkolás felmérés Parking areas

23 Újpest parkolás felmérés Measurements data Date: Daytime measurement: apr :30-18 hours Night time measurement : apr Data collection method: Roundtrips in every half hours, University students, Vehicle register.

24 Újpest parkolás felmérés A parking capacity

25 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: 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

26 Újpest parkolás felmérés Daytime Parking capacity using

27 Újpest parkolás felmérés Daytime Parking capacity using non inhabitants

28 Újpest parkolás felmérés Daytime Parking time [jármű] ,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 méteres környezet Teljes terület

29 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 méteres környezet Teljes terület Whole territory Minimum 8 hours parking divisaion by habitants

30 Újpest parkolás felmérés Night-time Parking capacity using

31 4. Measuring with hand GPS

32 Measuring with hand GPS

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35 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

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37 vehicle Vechicle passenger (Petőfi Bridge) Passenger

38 vehicle Safety belt usage Vechicle Using safety belt Passenger

39 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% Passenger

40 Vechicle types % 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%

41 Taxi types % 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%

42 Colour distribution of vehicles red white green black yellow blue silver other 0 red white green black yellow blue silver other Colour, 2011, Petőfi Bridge

43 180 Type distribution of vehicles

44 6. cloud passenger measuring

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47 7. Tachograf evaluation

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50 Digital tachograf for tramways

51 (+1) Getting in and out speed measurement

52 8. Measurement of pedestrian traffic flow

53 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

54 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)

55 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

56 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

57 Investigation features 4. Site Plan: Tram Sign of measuring group Metro station Exit Name of the Street or Station

58 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

59 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.

60 Results These results are given from students reports:

61 Results These results are given from students reports:

62 Results These results are given from students reports:

63 Results These results are given from students reports:

64 (+2) Simple cross section counting

65 Székesfehérvár

66 Szeged

67 Optimalizing of own coach service for costumers TESCO-Globál Supermarkets.

68 Geo-coding of road networks Pl. Mátészalka

69 Geocoding of the bus stops TESCO Pl. Mátészalka

70 Optimalizing E h = FIT 1 megállók (E x ) (E 1 ) 1. pont 2. pont 3. pont 4. pont (E 2 ) 1. szülő szülő maszk (E h 1 ) 1. gyerek (E h ) 2. gyerek

71 Objektiv function calculation Spending power modelling Cost of the bus line modelling Profit modelling TSP heurisztika MAX! Listening for the maximal travel time!

72 Mátészalka (25 minutes) New bus line Existing bus line Profit modelling: Ft/running 9% +Line 56% +Profit Profit modelling: Ft/running

73 Jászberény (25 minutes) New bus line Existing bus line Profit modelling : Ft/running 25% +Line 27% +Profit Profit modelling : Ft/running