The FLOW Approach in Munich. Johannes Keller City of Munich, Department of Urban Planning and Building Regulation

Transcription

1 The FLOW Approach in Munich Johannes Keller City of Munich, Department of Urban Planning and Building Regulation

2 2 Local FLOW case study: Art Boulevard Arcisstrasse Located in the Munich Art District Result of Overall Strategy and Bürgergutachten (Citizen Panel) Developped planning guidelines (in the context of FLOW): Improvement of walking and cycling conditions, esp. pedestrian crossings Traffic calming

3 3 Local goals Goals in the context of FLOW Feasibility study for Art Boulevard Improve urban qualities Within Framework conditions Exemplary measures Assessment Apply FLOW multimodal assessment Apply FLOW simulation tools Process requirements WorkFLOW Develop measures in accordance with German planning guidelines (FGSV) Build up VISSIM / VISWALK model and assess measures Feed data into FLOW assessment tools

4 4 Key Research Question To which extent can monetised travel time benefits caused by pedestrian measures (e.g. crossing aids) economically justify the financial investments required for their implementation? AND What s the impact of safety benefits?

5 5 Develop measures in accordance with German planning guidelines (FGSV) Modelling site Main entrance of Technical University Art gallery Alte Pinakothek Arcisstrasse is part of secondary urban network (9-10,000 veh/24h expected after implementation of new traffic scheme) Measures (e.g.) Punctual median refuge Extended median refuge Divided curb extension With or w/o 30

6 Build up VISSIM / VISWALK model and assess measures Vehicle Data Motorized vehicle traffic: Macroscopic transport model, forecast scenario 2025 traffic volumes on links and turns Bicycle traffic: periodic traffic counts at intersections Pedestrian data Survey with two counting cycles: 1) Pedestrian volumes at cross-sections: One day, 7 am 8 pm 2) Origin-destination pairs: - Definition of entry points to study area - Observation of sample at every entry point with regard to destination point Use these datasets as input for doubly constrained trip-distribution model to calculate an Origin-Destination-Matrix Feed matrix into VISSIM / VISWALK model

7 Build up VISSIM / VISWALK model and assess measures Entry points for ped. survey Pedestrian volumes Approx. 100 crossing peds in peak hour Screenshot from simulation model

8 Feed data into FLOW assessment tools Results (Travel time only) Measure Extended kerb extension Investment Annuity [Euro/year] Travel time benefit Yearly surplus Benefit-costcost [Euro] (30 y., 3.0 %) [Euro/year] [Euro] ratio 60,000 3, , Divided kerb extension 30,000 1, , Punctual median refuge 30,000 1, Extended median refuge 75,000 3, , Extended median 75,000 refuge speed limit 30 km/h 3, , , Zebra crossing , , ,000

9 Feed data into FLOW assessment tools Results (Travel time & safety) Measure Avoided light injuries per 10 years 1 Avoided severe injuries per 10 years 0 Traffic safety benefits [Euro/year] 2, Yearly surplus [Euro] Benefit-costratio 2, , , Punctual median refuge , , Extended median refuge , , Extended median 1 refuge speed limit 30 km/h 1 35, , Zebra crossing 0 5, Extended kerb extension Divided kerb extension 2

10 Conclusions Money into pedestrian infrastructure is economically well-spent! Travel time benefits alone (without wider costs and benefits and even safety effects) often amount to benefits that exceed the required investment. Additional investments may be justified for custom-tailored pedestrian solutions. (Here: extended or divided crossing aids) Moderate pedestrian flows may suffice to achieve a benefit-cost-ratio above 1. Positive safety effects on pedestrians have an enormous impact on the assessment and will in many cases marginalize travel time effects. Due to high benefit rates attributed to avoided injuries and fatalities, safety effects justify enormous investments as well as significant time losses for motorized traffic.

11 Reflections Multi-modal models with full implementation of non-motorized modes offer new or extended analysis and assessment opportunities. However, they also need a lot of experience and expertise and are consuming a lot of resources. Data is nice to have, but a lot can be done with limited data: make reasonable assumptions, compare scenarios. I believe: coherence is more important than numerical precision! Even in advanced cities like Munich, planning for pedestrians and cyclists needs to be mostly supplyoriented: low demand does not justify bad infrastructure, quality infrastructure is meant to generate demand! That means: established and ambitious planning standards and guidelines are often more effective than sophisticated models.

12 Outlook FLOW goal was Putting walking and cycling on equal footing with motorized modes This has been fulfilled by improving the integration of these modes into established modeling and assessment frameworks. Mission accomplished? Do we do walking and cycling justice if we assess them with the same methods and critieria (esp. travel time) as motorized traffic? Could it be that this stregthens the case of a planning paradigm that favors higher speeds, longer distances, higher traffic volumes more cars? Could it be that Putting walking and cycling on equal footing with motorized modes (with regard to real-world outcomes) does actually mean that we have to put Walking and cycling on a very different footing than motorized modes (with regard to assessment methods)?

13 Thank you for your attention! Johannes Keller City of Munich, Department of Urban Planning and Building Regulations