Dominik Grether

Effects of a Simple Mode Choice Model in a Large-Scale Agent-Based Transport Simulation

The traditional transportation planning forecasting process is the four-step process, consisting of the following four steps (for example, Ortuzar and Willumsen 1995):1. Trip generation, where sources and sinks of travel are computed 2. Destination choice, where sources and sinks are connected to trips. This results in the so-called origin–destination (OD) matrix 3. Mode choice, where the trips are differentiated by mode 4. Assignment, where routes are found for the trips, taking into account that much-used streets become slower (“congested assignment”).

Multi-Agent Transport Simulations and Economic Evaluation

Tolls are frequently discussed policies to reduce traffic in cities. However, road pricing measures are seldom implemented due to high investments and unpopularity. Transportation planning tools can support planning authorities by solving those problems if they take into account the following aspects:

Adding Mode Choice to Multiagent Transport Simulation

It had been shown previously that so-called agent-based traffic micro-simulations could be used for dynamic traffic assignment, that is, iterative route adjustment, until either a Nash equilibrium or some steady state distribution between alternatives had been found. It was also shown that the same approach could be extended to (departure) time adjustment; that is, time adjustment and route adjustment could exist in the same iterative approach. In this paper it is shown that the approach can be extended to mode choice by forcing every synthetic traveler to consider every available mode. The implementation is verified with a test case for which an approximate solution can be analytically derived and for which it is shown that simulation and theory are consistent. It is then applied to a large-scale real-world example, the metropolitan Zurich, Switzerland, area, with about 1 million inhabitants. For this example, it is shown that the adaptive scheme, albeit seemingly simple, can outperform a more traditional approach that first computes mode choice on the basis of aggregate data and then runs the assignment for car traffic only. Sensitivity tests show that the model reacts in meaningful ways, in particular concerning the interaction between the time structure of activities and mode choice.

Simulation of Urban Traffic Control: A Queue Model Approach

Abstract This paper aims at an agent-based simulation of the interplay between two types of agents within a transport system: travelers, and traffic signals. For the simulation of this interplay, a computationally efficient traffic model is needed. It is thus shown how queue models can be used to model traffic flow and spill-back at signalized intersections.

Extensible Software Design of a Multi-Agent Transport Simulation

Abstract This paper explains the chosen methodology for software design of the Multi-Agent Transport Simulation, MATSim. The design focusses on standard architectures and design patterns to ease usability and improve extensibility of the software. Potential for extension is discussed using an example implementation of a traffic signal control module. Both, MATSim and the extension are using the same concepts for software architecture.

Policy Evaluation in Multiagent Transport Simulations

In democratically organized societies, the implementation of measures with regressive effects on welfare distribution tends to be complicated because of low public acceptance. The microscopic multiagent simulation approach presented in this paper can help to design better solutions in such situations. Income can be included in utility calculations for a better understanding of problems linked to acceptability. This paper shows how the approach can be used in policy evaluation when income is included in user preferences. With the MATSim framework, the implementation is tested in a simple scenario. Furthermore the approach works in a large-scale, real-world example. On the basis of a hypothetical price and speed increase of public transit, effects on the welfare distribution of the population are discussed. This approach, in contrast with applied economic policy analysis, allows choice modeling and economic evaluation to be realized consistently.

Agent-based Modelling and Simulation of Air Transport Technology☆

Abstract Declining travel time differences of mid-distance transport modes motivate use of multi-agent simulation models to analyze and forecast behaviour of actors in the transport system. This paper focuses on air-transport technology. A simulation model is proposed, that represents details of air traffic microscopically but is fast enough to enable an iter- ative simulation-based passenger-trip assignment. Aircraft are modelled in detail in respect to departure time and seat availability. Modelling of airports and routes of aircraft focuses on the available capacity of runways. Several simulation runs illustrate how the model can be calibrated using available parameters. The model can be used for an agent-based traffic assignment. Overall, the approach appears to be suited to analyze and forecast mid-distance transport.