Application of CONDUITS-DST in Brussels

Transcription

1 Application of CONDUITS-DST in Brussels CONDUITS training workshop 26 November 2014 Madrid Pierre Schmitz, Brussels Mobility Antonios Tsakarestos, Technische Universität München Ioannis Kaparias, City University London

2 The Brussels Region Population : > 1,1 million inhabitants Surface : 161,4 km² Density : inh/km² Road network Region : 350 km Communes :1400 km PT network Metro : 40 km Tram : 139 km Bus : 445 km Commercial speeds (2009) Tram : 16,8 km/h Bus : 17,0 km/h 2

3 Some actions to be implemented in Brussels The Brussels Mobility Plan IRIS 2 at horizon and particularly 2 of its 9 main actions 2. To improve the PT attractiveness To develop a complete network allowing a good gridding of the Region, with high level service (in other words, fast, regular, mainly by bus, high-frequency) lanes and benefiting from the maximal priority on the traffic lights 9. Improve the Governance to guarantee the IRIS objectives To measure the progress of the realizations on the quantitative and qualitative levels 3

4 Need of a tool to monitor the expected results of the ITS implementations for bus priority Short-term Increase average speed of the buses Increase average speed of the private vehicles displacement parallel to the line Reduction average speed of vehicles crossing the line Increase of air and noise pollution by cars and busses Medium-term Change of route choices for private car drivers Reduction of time losses in the implementation area Long-term Demand shift towards public transport reduces private car rides 4

5 Brussels needs: relevant Key Performance Indicators and a Decision Support Tool (DST) KPI s (already done during the CONDUITS European R&D project) Easy to use and communicate to decision makers and public No or light extra work for the users Clarity for the political decision makers and the public Adapted to cities individuality Geographical scale : sections, roads, zones, network, Adaptability : Ability to use all kind of urban data that are relevant to quantify a performance Weighting possibilities DST (1 st step to be done during the Brussels case study) Easy to use by many cities in order to allow the sharing/dissemination of the results Directly linked to VISSIM and starting with Pollution 5

6 Brussels case study - Evaluation with VISSIM of bus priority systems by using the CONDUITS DST Priority bus line 49 Many intersections with traffic lights 4 VISSIM simulations Morning and evening peak hours Situation before and after implementation 6

7 The CONDUITS Decision Support Tool (DST) 1st step of the CONDUITS DST development: Automatic calculation of the KPI Pollution in VISSIM simulations with KPI Pollution : Pollution Key Performance Indicator W VT : Type of vehicle weighting factor W ET : Type of emission weighting factor Q VT,ET : Emissions by type of pollutant and by type of vehicle 7

8 Results of the Brussels case study (1) The first results reflect the expected short term effects Improvement of the public transport quality: increase average speed of the buses reduction of the stops at intersections before after 16.8 Ave. Speed [km/h] + 3% + 6% Number of Stops [-] -18 % 9 7 before after 4-43 % southbound northbound 0 southbound northbound 8

9 Results of the Brussels case study (2) but increase in pollution + 3% + 7,5 % what is (hopefully) normal! 9

10 Results of the Brussels case study (3) Sensitivity analysis with a pragmatic methodology The given demand levels of the relevant flows are ~ - 1,8% progressively reduced in increments of 1% and the KPI values are recalculated for each ~ - 3,9% scenario. 10

11 Increase in values compared to before -sceario Increase in values compared to before -sceario % Results of the Brussels case study (4) 0 Sensitivity analysis of the single pollutants CO 2 is the dominant emission NO x is the most resistant Adjustment to local city objectives through weights % % 4 % morning peak Traffic load reduction evening peak Traffic load reduction morning peak Traffic load reduction evening peak Traffic load reduction KPI KPI CO 2 NO x PM 10 11

12 KPI value Results of the Brussels case study (5) Scalability improves detailed problem analysis The KPI can be scaled down to smaller parts of the Network single routes junctions Critical spots or times can be identified Comparison morning peak North corridor Network part South corridor 12

13 Weighting factors (1) Vehicle types have different impacts on traffic produce different quantities of pollution and therefore have to be weighed equally in the KPI Weights can be determined on the basis of Passenger Car Units (PCU) equivalents bearing in mind that some vehicle types have zero emissions (e.g. trams, bikes, ), so will have zero weights 13

14 Weighting factors (2) Pollutants may be global (CO 2 ) or local (NO x, PM); have different impacts on human health; become critical at different values; and therefore cannot be weighed equally in the KPI Weights can be determined on the basis of the relative quantities of pollutants on the basis of limit values determined by policy and legislation of countries/cities 14

15 Weighting factors (3) Pollutant limit values: Example weighting scenarios: 15

16 Weighting factors (4) Application of pollutant weighting scenarios: Truly unweighted, where pollutants are determined on the basis of their relative weights only Weighted according to the USA and EU limit values Truly unweighted USA EU 16

17 Brussels evaluation of the KPI s and DST Same methodology for all the indicators Calculation running with all kinds of data Easy weighting of the parameters Automatic calculation before, during and after the implementation of an ITS by using the VISSIM files as they are provided Allow sharing results got in other cities for similar ITS and the possibility to create a common DB with real measurements 17

18 Actual limits of these Indicators It will be necessary to wait a few years before having before and after data based on real measurements Require a cost/benefit analysis to complete the set of KPIs needed to cover the overall sustainability assessment of an ITS KPIs comparison between cities still needs an agreement on common weighting 18

19 Future developments planned in Brussels Further steps : Road traffic prediction module and Road safety prediction module Design of an integrated sustainability module using CONDUITS KPIs for VISSIM micro simulations Implementation of this integrated sustainability module for VISUM macro simulations and OPTIMA simulations + KPI social inclusion 19

20 Thank you! Pierre Schmitz Antonios Tsakarestos Ioannis Kaparias Contact Details Brussels Mobility, Rue du Progrès, 80/1, B-1030 Brussels