Milos Balac

Evaluating the influence of carsharing stations’ location on potential membership: a Swiss case study

AbstractCarsharing as a mode, in any of its different forms, has the peculiarity of being accessible only to members. The research presented in this paper focuses on round-trip-based carsharing, where vehicles are parked at fixed locations, called in this paper stations. Round-trip-based carsharing has been the first successful form of carsharing, and is still the most diffused one in many countries. Several studies looked at the potential of such a system in various countries but the link between spatial distribution of the stations and potential membership has not been done yet. This paper looks at this question while trying to address other limitations of the existing literature on carsharing potential. The research has two parts. In the first part, a binary logistic model of round-trip based carsharing membership in Switzerland is estimated. The model is based on a large RP dataset (the Swiss national travel diaries survey) where information on carsharing membership is collected. This provides a representative and non-biased sample. The model takes into account accessibility to carsharing at local level introducing a dependency between potential membership and actual availability of the service. The model is then run on a synthetic population representing the whole Swiss population—created based on full census data—and then validated against actual membership data of the Swiss carsharing operator Mobility. It is shown that the model estimated is able to reproduce fairly well the spatial distribution of carsharing members in Switzerland. The second part is aimed at showing that the location of stations actually impacts potential membership. To this purpose an approach to solve the problem of the optimal location of carsharing stations is proposed, where the model estimated in the first part is used as objective function of an optimization algorithm. The region surrounding the city of Zurich is taken as case study for this approach. The proposed technique is suitable to find new constellations of stations so that the number of carsharing members is incremented and can also be seen as an innovative instrument which can help in the planning of carsharing station networks.

Agent-based Simulation of Urban Air Mobility

While a new generation of electric Vertical Take-off and Landing (eVTOL) or Personal Air Vehicles (PAV) projects receive much attention, little research is available on modeling their integration into urban transport systems. An early methodology of the Urban Air Mobility (UAM) extension for the multi-agent transport simulation, MATSim, is being presented, which enables first analyses of system-wide urban transport performance considering the effects of variations in VTOL vehicle properties and dedicated VTOL infrastructure placement.

Modeling Carsharing with the Agent-Based Simulation MATSim

Extensive literature already exists on carsharing and other shared modes, but understanding their effect on the transportation system requires additional work. One main limit of the existing research is that such modes have been analyzed mostly as isolated systems. As these modes were niche products, it was not easy to include them in comprehensive models of transport, and, in a way, it did not even make sense. But the modes’ current popularity and their expected growth completely change the picture. Transport model systems in which such mobility concepts will be explicitly modeled—along with all other modes—will be crucial in the near future to gain an insight into travel behavior effects and to assess possible future scenarios representing the effect of long-term mobility decisions. This paper describes how carsharing demand is modeled in an activity-based multiagent simulation of transport called MATSim (www.matsim.org). The paper draws from a series of papers written by the authors between 2009 and 2015 and is part of a research effort whose ultimate goal is to build a predictive and policy-sensitive model that can be used by practitioners and policy makers to test any type of carsharing scenario. This paper summarizes the work done, provides some examples of applications, addresses current limitations, and briefly reports on ongoing and planned developments.

A first look at bridging discrete choice modeling and agent-based microsimulation in MATSim

Abstract The agent-based transport simulation framework MATSim allows for the simulation of dynamic transport scenarios with agents, that adaptively make travel choices. Regarding mode choice, a heavily randomized process is used to date, which allows for very unrealistic mode decisions in the short run to arrive at consistent mode shares after a large number of iterations. The authors show that implementing a discrete mode choice model may drastically increase the convergence speed of the simulation, but point out that considerable future research is necessary to make travel decisions consistent and to back the process with a strong theoretical foundation.

Initial analysis of urban air mobility’s transport performance in Sioux Falls

While numerous Personal Air Vehicle (PAV) and next-generation Vertical Take-off and Landing (VTOL) vehicle projects are being developed, the potential of their introduction within an urban environment has yet to be understood and applied. Thus, an Urban Air Mobility (UAM) extension for the transport simulation, MATSim, is being utilized on the test case of Sioux Falls. The results provide an outlook on the transport performance of UAMwith varying parameters. Within the limitations of the current simulation, UAM access/egress and process times prove to be highly influential on passenger adoption.

Equity Effects of Congestion Charges: An Exploratory Analysis with MATSim

This paper shows an application of the multiagent, activity-based transport simulation MATSim to evaluate equity effects of a congestion charging scheme. A cordon pricing scheme was set up for a scenario of the city of Zurich, Switzerland, to conduct such an analysis. Equity is one of the most important barriers toward the implementation of a congestion charging system. After the challenges posed by equity evaluations are examined, it is shown that agent-based simulations with heterogeneous values of time allow for an increased level of detail in such evaluations. Such detail is achieved through a high level of disaggregation and with a 24-h simulation period. An important difference from traditional large-scale models is the low degree of correlation between travel time savings and welfare change. While traditional equity analysis is based on travel time savings, MATSim shows that choice dimensions not included in traditional models, such as departure time changes, can also play an important role in equity effects. The analysis of the results in light of evidence from the literature shows that agent-based models are a promising tool to conduct more complete equity evaluations not only of congestion charges but also of transport policies in general.

Activity rescheduling within a multi-agent transport simulation framework (MATSim)

Peoples desire or the need to perform certain activities during the day drives their activity-scheduling decisions. However, these decisions are dependent on the state of the transportation system, its supply and demand. The need for the tools able to deal with the kind of adaptations to the daily plans that come with these decisions, is ever growing. The introduction of new modes and services and the fast approaching era of autonomous vehicles, among other things, has increased the need for suitable tools to look at the induced/suppressed demand effects on the activity schedules. The work in this paper presents a methodology for the adaptation of the activity schedules inside of the multi-agent transport simulation (MATSim), based on the changes of supply in the system. The first results show that the proposed methods are able to adapt people?s schedules when they are faced with shorter or longer travel times and this with only 10% in the computation time. However, further development is needed in order to more realistically represent human behavior, which is discussed at the end of this paper.

Implementation of vehicle relocation for carsharing services in the multi-agent transport simulation MATSim

Operators of free-floating carsharing systems typically encounter the problem of imbalances in their vehicle fleets, caused by demand fluctuations over the course of one day, or from one day to the following. In order to provide a high level of accessibility to their service with a minimum number of vehicles, they must consider relocating unused vehicles. While some strategies to accomplish this have been successfully implemented, both in simulation and in practice, the set of tools required to represent carsharing in agent-based simulations is still incomplete. Agent-based simulations are particularly well suited to this task, because they allow modeling the interaction of supply and demand at individual level. This paper describes the implementation of the relocation agents within MATSim framework as an extension to the previous work on carsharing. The implementation was tested using a simple operator-based relocation strategy.