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The Multi-Agent Transport Simulation MATSim, ISBN:978-1-909188-77-8, ISBN:978-1-909188-75-4, ISBN:978-1-909188-78-5, ISBN:978-1-909188-76-1

From the transport economic literature, it is known that optimal pricing of (environmental) externalities improves the urban system. In contrast to theory-based optimal pricing strategies, real-world policy setting often follows so-called “backcasting” approaches where certain targets are set, and policy measures are implemented in order to reach those targets. An example for the latter approach is the EU goal to reduce global greenhouse gas emissions in the transport sector by 20% until 2020 with respect to 1990 levels. This article aims to (i) compare optimal pricing and backcasting approaches for a specific case study in a simulation environment by identifying the contribution of each approach in EU’s 2020 emission reduction target, and (ii) to determine the costs required to reach the desired targets. For this purpose, an optimal emission pricing strategy is applied to a real-world scenario of the Munich metropolitan area in Germany. The highly differentiated tolls relate to individual exhaust emissions, i.e. they are calculated using damage cost estimates from the literature and vary over time of day, with traffic situation, and with vehicle type. The results indicate that the desired reduction in CO2 emissions is not reached for optimal pricing approach, and that the initial damage costs estimates need to be multiplied by a factor of 5 in order to reach the target, yielding a price of 350 EUR/ton CO2. When aiming at a decrease of the overall emission costs by 20% (CO2 and local pollutants), the initial cost estimates need to be multiplied by a factor of 10. Furthermore, it is shown that the major contribution to the overall emission reduction stems from behavioral changes of commuters and reverse commuters rather than from urban travelers; under some circumstances, urban travelers even increase their CO2 emission levels. Hence, the study rises awareness that conflicting trends for different types of pollutants and different types of individuals are very likely: an increase in non-methane hydrocarbon levels for urban travelers and freight depicts that pricing emissions does not necessarily result in a reduction of all pollutants or of the emissions levels of all travelers. It is shown how agent-based simulations can be used to provide valuable insights and decision support in such possibly counter-intuitive situations.

Die Berliner Taxiflotte weist aktuell nur eine geringe Anzahl an barrierefreien Fahrzeugen auf, welche von RollstuhlfahrerInnen genutzt werden können, ohne den Rollstuhl zu verlassen. In diesem Kurzpapier wird anhand eines Simulationsmodells untersucht, wie viele Fahrzeuge der stadtweiten Taxiflotte mindestens barrierefrei zugänglich sein müssten. Dafür wird zunächst eine Abschätzung der Nachfrage vorgenommen und sodann die notwendige Flottengröße ermittelt. Die Ergebnisse zeigen auf, dass eine Flottengröße von 250 Fahrzeugen eine hinreichend gute Angebotsqualität liefern können.

The Multi-Agent Transport Simulation MATSim, ISBN:978-1-909188-77-8, ISBN:978-1-909188-75-4, ISBN:978-1-909188-78-5, ISBN:978-1-909188-76-1

The Multi-Agent Transport Simulation MATSim, ISBN:978-1-909188-77-8, ISBN:978-1-909188-75-4, ISBN:978-1-909188-78-5, ISBN:978-1-909188-76-1

The Multi-Agent Transport Simulation MATSim, ISBN:978-1-909188-77-8, ISBN:978-1-909188-75-4, ISBN:978-1-909188-78-5, ISBN:978-1-909188-76-1

Many authors argue that issues related to interpretability, lack of data availability, and limited applicability in terms of policy analysis have hindered a more widespread use of accessibility indicators. Aiming to address these aspects, this paper presents two accessibility computation approaches applied to Nelson Mandela Bay in South Africa. The first approach, a household-based accessibility indicator, is designed to account for the high diversity both among the South African society and in terms of settlement patterns. Besides OpenStreetMap (OSM) as its main data source, this indicator uses a census and a travel survey to create a synthetic population of the study area. Accessibilities are computed based on people's daily activity chains. The second approach, an econometric accessibility indicator, relies exclusively on OSM and computes the accessibility of a given location as the weighted sum over the utilities of all opportunities reachable from that location including the costs of overcoming the distance. Neither a synthetic population nor travel information is used. It is found that the econometric indicator, although associated with much lower input data requirements, yields the same quality of insights regarding the identification of areas with low levels of accessibility. It also possesses advantages in terms of interpretability and policy sensitivity. In particular, its exclusive reliance on standardized and freely available input data and its easy portability are a novelty that can support the more widespread application of accessibility measures.

This chapter lists modules that were important for several projects in the past, but which are no longer being developed.

This section presents MATSim’s technical tools for initial input generation.

Traffic assignment models are crucial for traffic planners to be able to predict traffic distributions, especially, in light of possible changes of the infrastructure, e.g., road constructions, traffic light controls, etc. The starting point of the seminar was the observation that there is a trend in the transportation community (science as well as industry) to base such predictions on complex computer-based simulations that are capable of resolving many elements of a real transportation system. On the other hand, within the past few years, the theory of dynamic traffic assignments in terms of equilibrium existence and equilibrium computation has not matured to the point matching the model complexity inherent in simulations. In view of the above, this interdisciplinary seminar brought together leading scientists in the areas traffic simulations, algorithmic game theory and dynamic traffic assignment as well as people from industry with strong scientific background who identified possible ways to bridge the described gap.

Road pricing is a controversial policy measure (e.g., Button and Verhoef, 1998). Its implementation in MATSim is conceptually straightforward (Rieser et al., 2007a, 2008; Grether et al., 2008): Essentially, for each vehicle entering a link at a given time, the appropriate toll is computed and charged to the vehicle’s driver.

Traffic assignment models are crucial for traffic planners to be able to predict traffic distributions, especially, in light of possible changes of the infrastructure, e.g., road constructions, traffic light controls, etc. The starting point of the seminar was the observation that there is a trend in the transportation community (science as well as industry) to base such predictions on complex computer-based simulations that are capable of resolving many elements of a real transportation system. On the other hand, within the past few years, the theory of dynamic traffic assignments in terms of equilibrium existence and equilibrium computation has not matured to the point matching the model complexity inherent in simulations. In view of the above, this interdisciplinary seminar brought together leading scientists in the areas traffic simulations, algorithmic game theory and dynamic traffic assignment as well as people from industry with strong scientific background who identified possible ways to bridge the described gap.

This chapter explains how to set up and run MATSim and describes the requirements for building a basic scenario. Updated information may be available from http://matsim.org, in particular from http://matsim.org/docs.

This chapter explains how MATSim’s agent-based framework can be interpreted from a microeconomic perspective and how it can be used for the economic evaluation of transport policies, e.g., for BCA (Benfit-Cost Analysis). The text of this chapter is partly taken from Kickhöfer (2014, Section 2.3). Typically, the process of economic policy evaluation consists of three steps: First, forecasting changes in the system by modeling users’ reactions to a policy (Section 51.1). Second, assigning some (potentially monetary) valuation to these changes (Section 51.2). And third, applying an appropriate aggregation rule (Section 51.3). As will be shown in the next sections, these steps are neither completely independent nor completely dependent on each other.

This last book part summarizes MATSim scenarios, as located on the map in Figure 52.1 and listed at http://matsim.org/scenarios.

The network container was already described in Section 4.1.1. An important additional feature of the network module is using time-dependent network attributes. Network state changes can thus be considered, as e.g., implied by accidents, or adaptive traffic control, with varying speed limits or driving directions of lanes on multi-lane roads with heavily unbalanced loads over the course of a day. Attributes that can be adapted are “free speed”, “number of lanes” and “flow capacity”.

A MATSim model of the Seattle region — more precisely the PSRC (Puget Sound Regional Council) area — was developed during K. Nagel’s sabbatical stay with the UrbanSim team in Seattle in 2008. The model resulted from a prototypical integration of the UrbanSim software (e.g.,Waddell et al., 2003) with MATSim.

In this chapter you will learn about possibilities to extend and customize MATSim (Multi-Agent Transport Simulation) through provided functionality.

Cadyts (Calibration of Dynamic Traffic Simulations) — licensed under GPLv3 (GNU General Public License version 3.0) — calibrates disaggregate travel demand models of DTA (Dynamic Traffic Assignment) simulators from traffic counts and vehicle re-identification data. Cadyts is broadly compatible with DTA microsimulators, into which it can be hooked through parsimonious interfaces.

This chapter describes how new functionality enters MATSim. It describes the MATSim team and community, the different roles existing in the MATSim project, the development drivers and processes, and the tools used for integration. The goal is to provide an overview of the development process so that one quickly finds access to the MATSim community and is able to efficiently contribute to MATSim, based on one role or another.