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From EMME to DYNAMEQ
in the city of MALMÖ
THE COMPANY
• Founded in early 2011
• Currently located in Stockholm, Gothenburg and Malmö
• Small company (currently 4 employees) but with many years of experience
AREAS OF BUSINESS
• Supply & demandmodelling and simulation from national strategic levels to separate intersections
• Traffic planning (Road, Public transport, Bicycle and pedestrians)
• Cost-Benefit analysis
• Implementation & developement of models for traffic analysis
• Analysis and studys regarding accessibilty, parking, emission etc.
• Evaluations of infrastructural investments
MODELS (SELECTION)
• Emme
• Sampers/Samkalk
• Dynameq
• Vissim
• ArcGIS
www.m4traffic.se
[email protected]
[email protected]
BACKGROUND
BACKGROUND
City of Malmö
-
Founded the year 1250, became part of Sweden in 1658.
About 300 000 inhabitants
30 % of population represent 170 different countries.
University with 20 000 students.
Every day more than 70 000 people make the 30 minute trip between Malmö
and Copenhagen using the Öresund bridge.
Part of the transnational region of Öresund with 3.5 million inhabitants
Expected increase of population with 33 % in the next 20 years
EXAMPLES OF ONGOING PROJECTS IN THE MALMÖ AREA
Interchange Alnarp
Malmö – Copenhagen Metro
Developement area
Northern Harbour
Interchange Spillepengen
Developement area
Western Harbour
Interchange Flansbjer
Developement area - Sorgenfri
Developement area
Limhamn
Tram
Tram
Developement area
Kalkbrottet
Developement area
Hyllie
Interchange Arena
BACKGROUND
 The city of Malmö is currently going through massive changes in its infrastructural design

New areas developed for living and working - the city prepares for a 33 % increase of population
next 20 years
 To meet the expected increase of travel, the city is planning different measures in the transport
infrastructural design, such as tram, fastlanes for busses, better bike facilitys , motorway
interchanges etc
 Historically the city of Malmö have used static assignment models, such as Emme s a planning
tool for different measures in the road infrastructure on a global level and microsimulation on a
local level
 Due to the expected increase of travel both within the city and commuting to- and from the
growing region of Öresund the need of a planning tool with better possibilities to measure
congestion has grown
 Growing interest in what way different measures will affect route choices, queue lengths, travel
times etc. both in shorter time horizons and in more strategic time horizons (20+ years)
ROAD NETWORK OF THE EMME MODEL
-
1 595 Zones
14 000 Nodes
40 000 Links
1 900 Turn penalties
Includes Själland and Lolland/Falster in
Denmark
- Used by the Swedish Transport administration
- Demand from the Sampers model.
EMME NETWORK IN MALMÖ – SUBAREA OF THE REGIONAL MODEL
-
226 Zones
~1 000 Turn penalties
Demand from local implementation of the
Sampers model
TRANSIT NETWORK OF THE EMME MODEL
National & Regional railways
City public transport system
Number of transitlines in network
Country
Denmark
Helsinborg-Helsingör
Sweden
Öresund bridge
City of Malmö
Bus
169
Ferry
Fast train
S-train
8
14
1
9
Metro
2
Train
43
Expressbus
96
16
90
4
340
66
EMME  DYNAMEQ
Network
EMME
Base data:
• Links
• Centroids
ArcGIS
Group editing:
• Link facility types
• Free flow speeds
• Lanes (not intersections)
DYNAMEQ
Detailed editing:
• Transit lines
• Traffic signals
• Intersection design
DYNAMEQ
Centroids
258
Nodes
1 702
Links
4 321
Transit Lines
66
Intersections
1708
Signalized Intersections
118
EMME  DYNAMEQ
Demand
Peak hours
PM
SAMPERS/
EMME
Peak hours
AM
Converter
24-Hour
Demand
Demand
Time
Time
DYNAMEQ
DTA
Peak
hours PM
Generalized cost = cost + 20 * Length
Peak
hours AM
24-Hour
DYNAMEQ
Results
Delays PM
Travel times
4,500
30
4,000
Hours
35
Minutes
25
3,500
20
3,000
15
2,500
10
2,000
5
1,500
0
1,000
Till
Från
Limhamn
Till
Från
Burlöv
Till
Från
Oxie
Till
Från
500
Mobilia
0
DYNAMEQ
Results
DYNAMEQ
24 – hours
DYNAMEQ
EMME
20 000 v/d
19 000 v/d
19 000 v/d
19 000 v/d
19 000 v/d
21 000 v/d
18 000 v/d
18 000 v/d
16 000 v/d
16 000 v/d
17 000 v/d
20 000 v/d
23 000 v/d
21 000 v/d
16 000 v/d
15 000 v/d
22 000 v/d
22 000 v/d
EMME vs DYNAMEQ
Network traveltimes during AM peak hour: Dynameq versus EMME
OD-relations within the City of Malmö
8000
7000
6000
5000
4000
3000
2000
1000
0
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
Ratio Dynameq/Emme
1.9
2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3
EMME
Network traveltimes with and without the use of tpf in EMME
OD-relations within the City of Malmö
14000
12000
F
10000
r
e
q 8000
u
e 6000
n
c 4000
y
2000
0
1
1.05
1.1
1.15
1.2
1.25
1.3
1.35
1.4
1.45
1.5
Ratio with/without tpf
1.55
1.6
1.65
1.7
1.75
1.8
1.85
EMME
Route choice Without and With Tpf (uncalibrated demand from Sampers)
No Tpf (185 counts)
Y = -426+1.16x; R2 = 0.76
Tpf (185 counts)
Y = 280+0.98x; R2 = 0.82
CONCLUSIONS
From EMME to DYNAMEQ

Network: ArcGIS powerful tool to edit large networks

Demand: Need for more detailed data (time + centroids)

DTA: Peak hours and 24-hours - different aims and challenges

EMME v.s. DYNAMEQ: significant differences in traveltimes
 raises questions about the validity of demand modelling and cost-
benefit analyses based on EMME in congested networks?

EMME: The use of tpf (not default in Sweden) affects route
choice and traveltimes in a significant way
THANK YOU
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