4.1.2 Input Parameters for the Barcelona case study
Inputs are summarized in Table 16. The first group – Area Characteristics – shall best describe a region and its particularities. It reflects the region geography (i.e. region size, central area, slopes) and demand patterns. The second, the User behavior, indicates their parameters of user characteristics (e.g. walking speed) and how will they respond to the system (depending on the VoT, for example). The last three are related to the Agency parameters on infrastructure, operation and repositioning.
The estimation process for each parameter is detailed in Appendix 1, devoted to parameter estimation. In the table there is also an assumption on the variability of each parameter, from Low (L) to High (H). A low variability will mostly vary up to ± 20%; a medium, ± 50%; while a high variability could be factors or even magnitudes higher/lower in some cases. The last ones are the most critical to be adapted.
The first group – Area Characteristics – shall best describe a region and its particularities. It reflects the region geography (i.e. region size, central area, slopes) and demand patterns. The second, the User behavior, indicates their parameters of user characteristics (e.g. walking speed) and how will they respond to the system (depending on the VoT, for example). The last three are related to the Agency parameters on
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Table 16 – General parameters.
Groups Parameter Notation Value Unit Variability
Area Characteristics Service region R 50 km² H
4.1.3 Scenarios Typologies variations
The scenarios proposed will be depart from Barcelona’s Bicing as a calibration and then the mentioned parameters will be varied according to Table 17. For a clear comparison, population, and therefore demand, are always the same (around 1,5 million inhabitants and 45 thousand daily trips). What will change is: the density-area relation from each region (depicting low density regions); the value of time of the citizens (reflecting different economic purchase power from different cities/countries); and the center-periphery factors such as demand concentration within the central region in relation to the periphery or their resulting unbalance. With this proposal, Barcelona is placed as the densest case possible, with a relatively high VoT and an average central demand concentration.
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Table 17 – Parameters range for the scenarios.
Parameter Barcelona BSS Baseline Minimum Maximum
Demand [trips/km2]:
(Density [ppl./km2] – Area [km])
44 (28.000 – 50)
5,5 (3.500 – 400)
44 (28.000 – 50)
Value of time [€/h] 11,4 3,0 15,0
Central / Peripheric Demand [-] 3,0 1,0 5,0
Central / Peripheric Unbalance [%] 2 0 20
4.2 Calibration
4.2.1 Finding a center
To explore the feasibility region to place the BSS center, data of population, job and city dimensions are considered. As the systems gains strength with density rather than just absolute numbers, numbers are divided by their district areas. As result, the population is treated as density. For the jobs, it is considered the office surface of each region as a proxy of jobs that characterizes the CBD. Again, dividing by the area, one reaches the density of office surface within each district. The final point to define the feasibility boundary is the geographic center where the position of each district is averaged to arrive to the city center.
Figure 31 illustrates the region formed by these three factors where a possible center could be placed. The region is rather small compared to the city area, a 0,7 km2 compared to the city’s 102 km2 (0,68%).
The system actual slots center is placed outside this region, 0,7 km from this region average center or 0,6 km from its closest point, the office density center. Proportionality the difference is meaningful, but when compared to the expected BSS dimensions, around 50 km2 (approx. 7,1 km x 7,1 km), it falls to a less than 10% of one of these dimensions.
Having in mind the importance of the CDB to a BSS operation and knowledge of Barcelona’s Eixample neighborhood relevance to the city’s dynamic the office density center is considered in the following steps of this work of calibration.
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Figure 31 – Feasibility for system centers.
4.2.2 Areas extension
Each district center is ordered from the closest to the furthest from the center in order to orient which ones should be considered in the system and have a center-periphery orientation. As a filter, an elevation threshold was stablished to exclude in a first moment districts that were too high or low compared to the stablished center. The center is at a 55 m elevation from the sea level and a + 10 % is considered, so the threshold is ± 60 m, resulting in regions acceptance from – 5 m to 115 m. As a consequence, 57 from the 73 districts remained to be analyzed and included in the BSS area. In the actual Bicing, there are 51 which are part of the BSS.
On its analysis, bacc (2016) also saw the possibility of expanding Bicing a further to 10 other districts despite their complex orography (Vall d’Hebron, La Clota, sur de Horta, La Font d’en Fargues, Can Peguera, El Turó de la Peira, La Guineueta, Verdun, La Prosperitat y sur de Trinitat Nova), in particular with the e-bicycle aid.
To differentiate the centric region in these 57 districts, two parameters were considered with the accumulated area ordered from the closest to the proposed center: population and office areas (Chart 7). Over 85% of the population live within 50% of the territory and can be considered a possible feasible area for the system.
There is reasonable linearity in its evolution and no major change can be noticed until the 42% of the accumulated area (80% of the population), where there is a sudden slope drop. No significant centrality pattern emerged from it since this number does not allow
Geographic Pop. Dens. Off. Dens. Bicing Slot 0,6 km
0,8 km
64 a clear division due to the small representability of the remaining area. Therefore, the accumulated population analysis does not solve the clarify the areas limits.
On the accumulated office area, the patterns are clearer. The 60% of it is located within the 20% of the territory, while the approximate 80% is in 30%. The following 20% of the city area brings only 15% more of the office areas, which allows to see two possible cutlines for the CDB, at 20 or 30% of the territory. As the focus in on the expanded CBD, for the following steps it is considered the 30% accumulated area, which is around 60%
of the total Bicing area.