montreal, 18. -20th october, 2006 20th international emme users’ conference the modelling of 2...

20th International EMME Users’ Conference Montreal, 18. -20th October, 2006

The modelling of 2 different cases of the trip distribution in EMME in the Czech

Republic Jiri Dufek,

Transport Research Centre Brno, Czech Republic

[email protected]


Regional level: Urban agglomeration: Middle Bohemian region Brno city

The modelling on regional and urban level


Basic information:

The Middle – Bohemian Region

• data of National population census used for trip generation

• 574 zones, 512 internal (cities, towns , villages), 62 external)

• zone groups (ga) system corresponding to the administrative units, former “districts”

Ensembles defined: - ga “districts” - 14 zone groups - gb “capitals” - 2 groups (Prague

gb2 and others gb 1)


Demand between districts (ga):


• knowledge of demand between individual district based on National Population Census - 3D trip distribution

• all OD pairs were assigned to specific categories, depending on a district which they belong to = 3rd dimension

Demand from district capitals (gb1) to the Prague (gb2)

Node label – town nameNode number – total production

This is not aggregated demand (only between district capitals)




- between district capitals (gb1)

- depends ON districts

- depends NOT ONLY ON travel time and zones attractivity

DISPLAYED DEMAND:

• Strong demand inside each district (ga), small demand between outlying districts

- insufficient 2D distribution, suitable 3D distribution

• 3rd dimension – sorted matrix by origin and destination district

• 3rd dimension totals – district to district demand from population census




- result of the 3D modelling

-strong impact of 3rd dimension (demand between districts)

- displayed with a help of intrinsic function “which”

DISPLAYED DEMAND:

• differences between demand within a district and outside a district


Model network information:


• done by data exchange between ArcView and EMME,

• very detailed: 4711 regular nodes, 14268 links,

• interactive adjustments of the input from GIS: (highway exits, big intersections),

• intersection and turn definition.

Example of the intersection done interactively:

- blue – one way links

- red – two way links

- in circles – all allowed turns


Temporary results of assignment:


• equilibrium assignment, BPR volume / delay function

• demand matrix – resulted from 3D trip distribution

• VDF variables: free flow speed, link capacity

• until now only commuting

Detailed view - assigned volumes on the intersection (example)


Conclusion remarks:


• only 1 scenario until now, not finished

• now it is only commuting, shopping demand is being modeled

• the development scenarios containing planned actions will be tested

• the model is 1-modal (auto), planned to be multimodal

• public transport lines will be put in

• a modal split between individual and public transport will be modeled


Model upgrade:

The Brno city and surrounding

• new zoning system: zones are urbanistic units

• knowledge of delatied socioeconomic data about population in individual zones, from National Population census: inhabitants age, employment, sex, householsd equipment, car ownership, etc..

• totally 315 zones: 278 urbanistic units of Brno, 11 nearest villages and 26 external zones

The whole network with urbanistic units and displayed centroids of nearest villages

Detailed view – city centre


Model upgrade:


• The Integrated of public transport system (IDS JMK)

• 57 urban lines (13 tram, 11 trolleybus, 33 bus lines)

• new 27 regional bus lines and 5 train lines

The whole network with zone bonudaries, train links and regional bus lines

Regional bus lines usually end in significant city transport stops, for the passengers transfers.


Determination of transport production and atractivity


Production:

Data source – population census

• No. of people leaving the zone for commuting

• No. of pupils and students leaving the zone

Data source – web sites

•The capacity of student colleges in Brno

Attractivity:

• No. of jobs in individual companies and institutions in Brno

• Data about shops- estimation of No. of the customers per a day from companies incomes (data source commercial statistics)

• The capacity of all secondary and higher schools in Brno (data source – Internet, personal interviews)


Overeview of production and attraction matrices in the system


mo md

mo1 – total commuting md1 – No. of jobs

mo2 – students leaving homes md2 – No. of shopping persons

mo22 – students leaving colleges md3 – No. of school attendants (secondary and higher)

mo3 – men commuting md4 – No of customers of big shopping centres

mo4 – women commuting md5 – external zones – people living outside Brno travelling home

mo5 – production of external zones md6 – total of all atractivities

mo9 – shopping production


Examples of the production and attraction plots:


mo1 - commuting




mo2 – students from home mo2 – students from colleges




md1 – No. of jobs




md2 – shopping


Types of the trips considered:


HWH home – work – home

HWShH home – work – shopping – home

HShH home – shopping – home

H(C)SchH home (+college) – school * - home

* - only secondary and hogh schools, primary schools transport is considered to be within a zone



* - only secondary and high schools, primary schools transport is considered to be within a zone

HWH gravity (entropy) model, production - mens commuting, attractivity – No. of jobs

HWShH 3-leg trip chain (macro tchain3 used), production – women commuting (typical in Czech Republic), atractivities: Aq – No. of jobs, Br – No. of customers in shops

HShH gravity (entropy) model – proportional distribution of No. of shopping centres customers between all zones

according to No. of inhabitants

H(C)SchH gravity (entropy) model *

Calculations of trip distribution:• input matrix = negative exponential function of distances between zones

• production data is more reliable the attractivity data – scaled by production (except HSH)



Dealing with external zones32 external zones: entries to/from the model area

• 19 zones – car and bus entry

• 7 zones – car entry only

• 6 zones train entry only



Dealing with external zones

Total production splited to 3 mo matrices: car, car+bus and train

Data souces:

• car transport: traffic volumes from National Traffic Census

• No. of passenges: lack od surveys – estimation.

Attractivity = total od previous attractivities (work, shops, schools, ...)



Resulted full demand matrices

mf2 from home or college to school

mf11 1st leg of trip chain calculation (movement of employed women)

mf12 2nd leg - work – shop

mf13 3rd leg – shop – home

mf14 from home to work (employed men)

mf19 from home to shopping centre

mf22 from external zones (auto)

mf23 from external zones (auto and transit)

mf24 from external zones (transit)



Modal split and auto assignment

Calculation od the modal split (matrix mf20): not finished yet, utility functions are not definitemf20 =e^ f (mf3, mf9, mo12, md12) / (e^f (mf3, mf9, mo12, md12)) + (e^f(mf4, mf1, mo12, md12))

mf3 auto travel time (min)

mf9 auto costs ( CZK)

mo12 No. of cars per a worker

md12 parking costs (only in central zones)

mf4 transit time

mf1 transit rate

Calculation of all day auto demand (matrix mf16): (mf19+mf19'+mf22+mf22')+(mf11+mf12+mf13+mf14+mf14'+mf24+mf24')*mf20

explanations to matrices / see previous slide



Modal split and auto assignment

assigned auto demand (mf16)

volumes must be calibrated



Conslusions:

Next plans in Brno

• calibration of modal split functions (in Brno: 55 % cars, 45 %)

• calculation and assignment of urban transport matrix

• development of scenarios (some already are in older model)

• construction of Big City Circle and other planned roads

• two high – speed tramway lines

• a shift of Central railway Station

• the Park and Ride system.

montreal, 18. -20th october, 2006 20th international emme users’ conference the modelling of 2...

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