Journal Publications

@article{Lenfers2021b,
title = {Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg},
author = {Ulfia Annette Lenfers and Nima Ahmady-Moghaddam and Daniel Glake and Florian Ocker and Jonathan Ströbele and Thomas Clemen},
editor = {Simon Elias Bibri},
url = {https://www.mdpi.com/2073-445X/10/11/1179/htm},
doi = {10.3390/land10111179},
issn = {2073-445X},
year = {2021},
date = {2021-11-03},
journal = {Land 2021},
volume = {11},
number = {10},
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. },
keywords = {adaptive behavior, agent-based model, decision support systems, multimodal travel, sohh, urban planning},
pubstate = {published},
tppubtype = {article}
}

@article{Lenfers2018b,
title = {Firewood Collection in South Africa: Adaptive Behavior in Social-Ecological Models},
author = {Ulfia A Lenfers and Julius Weyl and Thomas Clemen},
url = {http://www.mdpi.com/2073-445X/7/3/97},
doi = {10.3390/land7030097},
issn = {2073-445X},
year = {2018},
date = {2018-08-01},
journal = {Land},
volume = {7},
number = {3},
pages = {97},
publisher = {Multidisciplinary Digital Publishing Institute},
abstract = {Due to the fact that the South Africa's savanna landscapes are under changing conditions, the previously sustainable firewood collection system in rural areas has become a social-ecological factor in questions about landscape management. While the resilience of savannas in national parks such as Kruger National Park (KNP) in South Africa has been widely acknowledged in ecosystem management, the resilience of woody vegetation outside protected areas has been underappreciated. Collecting wood is the dominant source of energy for rural households, and there is an urgent need for land management to find sustainable solutions for this complex social-ecological system. However, the firewood collection scenario is only one example, and stands for all “human-ecosystem service” interactions under the topic of over-utilization, e.g., fishery, grazing, harvesting. Agent-based modeling combined with goal-oriented action planning (GOAP) can provide fresh insights into the relationship between individual needs of humans and changes in land use. At the same time, this modeling approach includes adaptive behavior under changing conditions. A firewood collection scenario was selected for a proof-of-concept comprising households, collectors, ecosystem services and firewood sites. Our results have shown that, even when it is predictable what a single human agent will do, massive up-scaling is needed in order to understand the whole complexity of social-ecological systems. Under changing conditions, such as climate and an increasing population, fair distribution of natural goods become an important issue.},
keywords = {adaptive behavior, Bushbuckridge, Canyon Biosphere, firewood collection, goal, Kruger, social, to},
pubstate = {published},
tppubtype = {article}
}