# Evaluating the Capacity Coordination in the Urban Multimodal Transport Network
## 6 Conclusions  
This research put forward a set of evaluation process for an urban multimodal transport network which considers the roadway network, bus transit network, urban rail transit network, and connection network. For the multimodal network, the paper fully considered the impedance of links in different sub-transport networks and constructed the complete path impedance of five different transport modes (namely, car, bus, metro, bus-to-metro, and car-to-metro). To quantify the passenger distribution in a multimodal transport network, the paper adopted the SUE model to solve the problem, and the results were calculated using the MSWA, which provided the necessary basis for further evaluation.  
This research suggested evaluation functions for the indicators from three perspectives. The LOS of the multimodal transport network showed the overall service quality by calculating the v/c ratio of each single network. The Gini coefficient of the network indicated whether most passengers are using a single network, which would result in single-network congestion and disequilibrium of the whole network. The mode share of transport modes reflected the share rate of transit in the multimodal transport network.  
The methodology and the evaluation process proposed in the paper were applied to a real example in Nanjing. In this case, some assumptions were adopted. These assumptions may have caused some potential biases. It was assumed that there was only one OD pair with a demand of 7000 commuting passengers during the morning peak. The feasibility of the proposed evaluation process was well proven by the numerical examples using different OD demands. The results of the numerical examples of OD demand ranging from 3000 to 15,000 indicated that, with a small OD demand, the roadway network would take most of the passengers, whereas the distribution among various networks was unbalanced and the transit sharing rate was low. Accordingly, managers can enhance the appeal and reduce the impedance of transit modes by optimizing the facilities of transit networks (i.e., reducing the walking and waiting time). Similarly, the shortcomings of the network can be recognized, which can provide guidance for network optimization and future improvement.  
Notably, the current study was limited by data acquisition and the complexity of calculation, and it only focused on assumed OD demand. In practical application, the relevant parameters of the impedance function of each link (e.g., fuel fee and speed) should be accurately calibrated according to the actual situation instead of using fixed constants based on the literature, so that the distribution results become more in line with the actual situation and the assignment results calculated by the model are more accurate.  
**Author Contributions:** Conceptualization and study design, Y.Y. and W.W.; data collection, J.C. and Z.D.; analysis and interpretation of results, Y.Y. and Z.D.; writing--original draft preparation, Y.Y.; writing--review and editing, W.W. All authors read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (Grant No. U20A20330) and the National Natural Science Foundation of China (Grant No. 51638004).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.