Abstract

Models can provide valuable decision support in the ongoing effort to create a sustainable and effective modality mix in urban settings. Modern transportation infrastructures must meaningfully combine public transport with other mobility initiatives such as shared and on-demand systems. The increase of options and possibilities in multi-modal travel implies an increase in complexity when planning and implementing such an infrastructure. Multi-agent systems are well-suited for addressing questions that require an understanding of movement patterns and decision processes at the individual level. Such models should feature intelligent software agents with flexible internal logic and accurately represent the core functionalities of new modalities. We present a model in which agents can choose between owned modalities, station-based bike sharing modalities, and free-floating car sharing modalities as they exit the public transportation system and seek to finish their personal multi-modal trip. Agents move on a multi-modal road network where dynamic constraints in route planning are evaluated based on an agent’s query. Modality switch points (MSPs) along the route indicate the locations at which an agent can switch from one modality to the next (e.g., a bike rental station to return a used rental bike and continue on foot). The technical implementation of MSPs within the road network was a central focus in this work. To test their efficacy in a controlled experimental setting, agents optimized only the travel time of their multi-modal routes. However, the functionalities of the model enable the implementation of different optimization criteria (e.g., financial considerations or climate neutrality) and unique agent preferences as well. Our findings show that the implemented MSPs enable agents to switch between modalities at any time, allowing for the kind of versatile, individual, and spontaneous travel that is common in modern multi-modal settings.

Highlights

  • A smart and varied mobility mix is one of the key issues in developing effective approaches to sustainable urban development [1]

  • We present a multi-modal model of the traffic flow in Hamburg, Germany, around an HVV switch point to study how different participants interact with a set of given multi-modal travel options and plan their trips

  • The results shown here summarize the simulation of 900 agents, repeated 100 times

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Summary

Introduction

A smart and varied mobility mix is one of the key issues in developing effective approaches to sustainable urban development [1]. In the last few years, mobility patterns in urban areas have grown more complex [2]. → work/school → home) has become increasingly broken up into longer chains with multiple subroutes [3]. New mobility solutions such as shared or on-demand vehicles have grown in popularity (e.g., [4]). These developments lead to the concept of Mobility-as-a-Service [5,6]. The growing complexity of mobility provision and its impact on urban development needs to improve by employing intelligent transport systems (ITS) [7]. Germany is an ITS model city and host of the ITS World Congress

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