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\begin{document}

\title{Network Fundamental Diagram Based Routing of Vehicle Fleets in Dynamic
Traffic Simulations}



\author[1]{Florian Dandl }%
\author[2]{Gabriel Tilg }%
\author[2]{Majid Rostami-Shahrbabaki }%
\author[2]{Klaus Bogenberger }%
\affil[1]{Technical University of Munich}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\begin{abstract}
The growing popularity of mobility-on-demand fleets increases the
importance to understand the impact of mobility-on-demand fleets on
transportation networks and how to regulate them. For this purpose,
transportation network simulations are required to contain corresponding
routing methods. We study the trade-off between computational efficiency
and routing accuracy of different approaches to routing fleets in a
dynamic network simulation with endogenous edge travel times: a
computationally cheap but less accurate Network Fundamental Diagram
(NFD) based method and a more typical Dynamic Traffic Assignment (DTA)
based method. The NFD-based approach models network dynamics with a
network travel time factor that is determined by the current average
network speed and scales free-flow travel times. We analyze the
different computational costs of the approaches in a case study for
10,000 origin-destination (OD) pairs in a network of the city of Munich,
Germany that reveals speedup factors in the range of 100. The trade-off
for this is less accurate travel time estimations for individual OD
pairs. Results indicate that the NFD-based approach overestimates the
DTA-based travel times, especially when the network is congested.
Adjusting the network travel time factor based on pre-processed DTA
results, the NFD-based routing approach represents a computationally
very efficient methodology that also captures traffic dynamics in an
aggregated way.%
\end{abstract}%



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