Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

Multi-modal interactions at the network-level remain unexplored due to lack of high-resolution data for all transportation modes involved. The current work investigates effect multi-modal space-mean network speed each mode using dataset from pNEUMA experiment that was carried out in a congested city centre Athens, Greece. Explanatory variables considered are accumulation and stopped fraction vehicles mode. Firstly, mean MFD is by assuming can be expressed terms accumulations modes. quality fits compared uni-modal ones, where given assumed function only. Secondly, classical two-fluid model extended networks. An analysis on ergodicity assumption context also presented. This introduces dynamic uses vehicles. so-called trip-based simulates stop-and-go pattern thereby reproducing evolution congestion. first explore this direction. results models validated with empirical data.