# Data-Driven Approach for Defining Demand Scenarios for Shared Autonomous Cargo Bike Fleets +
## 4 Demand Scenario Generation
### OSABS Base Demand and Beliefs
#### 4.3.2 Assessment of OSABS Base Demand  
The evaluation of the previously described survey on mobility needs in Magdeburg showed that about 16.67% of all trips by foot, 16.49% by bike, 14.47% by public transport, and 15.65% by car are likely to be replaced by using autonomous cargo bikes. Below, these values are referred to as probability of use per mode of transport \(p_{mode_{e}}\). In addition, a large proportion of respondents indicated they would travel a maximum of 10 km on an autonomous cargo bike. The exact distance distribution is shown in Table 1.  
To determine the traffic volume of autonomous cargo bikes for a statistical day, we calculated the number of trips replaced with OSABS by multiplying the previously obtained usage probabilities per mode of transport with OD-trips from the respective OD-matrices \(n_{OD_{i}}\). In order to provide a wide range of input for any subsequent simulation models, we conducted this while distinguishing between two different scenarios:  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Distance [km]** & \
\begin{tabular}{c} **Proportion of** \\ **Respondents [\%]** \\ \end{tabular} & **Distance [km]** &
\begin{tabular}{c} **Proportion of** \\ **Respondents [\%]** \\ \end{tabular} \\ \hline \((0,1]\) & 5.09 & (11, 12) & 0.85 \\ \((1,2]\) & 7.07 & (12, 13) & 0.14 \\ \((2,3]\) & 11.03 & (13, 14) & 0.14 \\ \((3,4]\) & 4.53 & (14, 15) & 4.24 \\ \((4,5]\) & 25.04 & (15, 16) & 0.14 \\ \((5,6]\) & 4.38 & (16, 17) & 0.00 \\ \((6,7]\) & 4.53 & (17, 18) & 0.00 \\ \((7,8]\) & 4.81 & (18, 19) & 0.00 \\ \((8,9]\) & 0.28 & (19, 20) & 5.66 \\ \((9,10]\) & 21.92 & \textgreater{}20 & 0.00 \\ \((10,11]\) & 0.14 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Stated OSABS distance limits.  
* High scenario: A share of trips from all modes of transport, namely, foot, bike, car, and public transport, will be replaced with OSABS.
* Low scenario: A share of trips by only foot, bike, and public transport will be replaced with OSABS.  
For each OD-pair, we then multiplied the resulting number of OSABS trips by the probability of use, which we derived from the trip distance \(s_{OD}\) and the stated distance limits \(l(s_{OD})\) from Table 1. In the following, this probability will be referred to as distance-dependent probability of use \(p_{dist_{OD}}\). Since no information was available on the actual starting and ending locations within origin and destination districts, it was necessary to estimate trip distances. Therefore, using shapefile and the software packages sf [65] and stplanr [66], we determined the Euclidean distance between the centroids of the respective OD-districts \(s_{E_{OD}}\) and multiplied it by a factor of 1.3. According to [PERSON] [67], this factor has proven to be a sound approximation of actual distances traveled within cities. To calculate intrazonal trips (i.e., trips within a district), for which the distance-dependent probability of use would be zero according to the above calculation, a distance of one kilometer was assumed.  
In conclusion, the calculation of OSABS trips per OD-pair \(n_{OSABS_{OD}}\) can be expressed via the following equations:  
\[p_{dist_{OD}}=s_{OD}\cdot l(s_{OD})\text{ with }s_{OD}=\begin{cases}1&\text{if }O=D \\ 1.3&\text{if }O\
eq D\end{cases} \tag{1}\]  
\[n_{OSABS_{OD,high}}=\sum_{i}(p_{mode_{i}}\cdot n_{OD_{i}})\cdot p_{dist_{OD}} \text{ with }i\in\{\text{foot, bike, car, pt}\} \tag{2}\]  
\[n_{OSABS_{OD,low}}=\sum_{i}(p_{mode_{i}}\cdot n_{OD_{i}})\cdot p_{dist_{OD}} \text{ with }i\in\{\text{foot, bike, car}\} \tag{3}\]  
Since most of the calculated traffic flows were non-integer values, it was then necessary to apply an algorithm that allows for rounding the results to integer values while preserving their overall sum. To achieve this, after rounding every number down in the first step, we incrementally rounded up those numbers with the highest fractional parts until the desired sum was reached. The total OSABS demand for a statistical traffic day is 8322 trips for the high scenario and 5435 trips for the low scenario.