## 5 Discussion  
The daily activity plans of shoppers and workers were simulated using the MATSim tool. In the simulation, the travel time, travel distance, and AV fleet size were optimized. The transport mode of the first scenario was driving conventional cars, and the second scenario was using AVs. The third scenario was driving cars and using public transport (intermodal), while the third scenario was using AVs and Public transport (intermodal). Table 6 presents the results of the four scenarios, where scenarios (1) and (2) present the results of the existing activity plans where existing conventional private cars and AVs were used. On the other hand, in scenarios (3) and (4), representing the new activity chain plans (a P&R system integrated into existing activity plans), the results of the MATSim simulation of the new daily activity chain plans of both shoppers and workers are presented in Table 6.  
The obtained benefits of using AVs are clearly presented in Table 6, which showed a reduction in the travel time. The travel time was reduced from 69.5 to 39.5 min when conventional cars were \begin{table}
\begin{tabular}{|c|c|c|c|} \hline
**Scenario** & \begin{tabular}{c} **Total Average Daily** \\ **Trip Time (Minutes)** \\ \end{tabular} & \
\begin{tabular}{c} **Total Average Waiting** \\ **Time (Minutes)** \\ \end{tabular} &
\begin{tabular}{c} **Total Parking Time** \\ **(Minutes)** \\ \end{tabular} \\ \hline \multicolumn{3}{|c|}{(1) Existing condition} & 69.5 & - & 7 \\ \hline \multicolumn{3}{|c|}{(2) Existing condition with AVs} & 39.5 & 11.4 & - \\ \hline \multicolumn{3}{|c|}{(3) Existing condition with P\&R} & 105.1 & - & 4.5 \\ \hline \multicolumn{3}{|c|}{(4) P\&R and AVs} & 54.8 & 10.2 & - \\ \hline \end{tabular}
\end{table} 
Table 6: Trip time comparison of conventional modes and AVs. Figure 5: Time profile of 750 AVs, when the AVs replaced conventional cars in scenario (4). replaced by AVs (fleet of 450 AVs), which means that AVs can increase the utility of travelers, because they are more likely to decrease their travel time. Moreover, users of AVs can obtain other benefits, compared with users of personal cars, because travelers have the opportunity to conduct more activities on-board AVs than driving personal cars. Additionally, a traveler would be exposed to 11.4 min of waiting time during the day on average, and they have to wait at their place, rather than on the street or at a specific location. Additionally, AV travelers are not required to care about parking the AVs, because they park themselves or go to serve another order, which means savings in terms of the time spent in the parking process. Scenario (3) showed an increase in the travel time, compared to scenario (1). This increase was produced because the travelers used the public transport mode (slow mode) and diverted to the shortest path to the destination, and the parking process time was added. Moreover, the utility of travelers in scenario (1) is not bad, because the parking price (which was set by the municipality) inside the city is high, and travelers are interested in avoiding it. As a result, using P&R would be a good choice for people who travel from outside the city center. The extra 4.5 min can be reduced by managing the P&R facilities. For example, an agent can take a traveler's car and park it on behalf of the traveler, or the design of the P&R system could determine the required time for parking. Finally, the simulation of scenario (4) showed that the travel time of scenario (2) could be reduced if personal cars were replaced by AVs. The reduction in travel time was 50.3, based on a fleet size of 750 AVs, and the total waiting time per day for each traveler was on average 10.2 min. As a summary, the simulation of the existing transport modes produced an average daily travel time of 69.5 min, which includes the total time of all trips conducted in the day and a parking process time of 9 min.