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This paper presents a synthetic travel demand for the Greater Sao Paulo Metropolitan Region of Brazil, entirely based on open data and representative of the observed travel demand. The open-source and extendable pipeline creates a path from raw data to the synthetic travel demand and, further, to the downstream agent-based mobility simulation. An advantage of this approach is that it enables the reproduction of the synthetic travel demand and, therefore, provides the foundation of repeatability of downstream studies. Furthermore, as the methodology is based on open data, the study's outcomes are easily accessible to the broad research and practice-oriented community., Regional Studies, Regional Science, 8 (1), ISSN:2168-1376

Automated Mobility on Demand (AMoD) is a concept that has recently generated much discussion. In cases where large-scale adoption of an automated taxi service is anticipated, the service’s impacts may become relevant to key transport system metrics, and thus to transport planners and policy-makers as well. In light of this increasingly important question, this paper presents an agent-based transport simulation with (single passenger) AMoD. In contrast to earlier studies, all scenario data (including demand patterns, cost assumptions and customer behaviour) is obtained for one specific area, the city of Zurich, Switzerland. The simulation study fuses information from a detailed bottom-up cost analysis of mobility services in Switzerland, a specifically tailored Stated-Preferences survey about automated mobility services conducted in the canton of Zurich, and a detailed agent-based transport simulation for the city, based on MATSim. Methodologically, a comprehensive approach is presented that iteratively runs these components to derive states in which service cost, waiting times and demand are in equilibrium for a cost-covering AMoD operator with predefined fleet size. For Zurich, several cases are examined, with 4,000 AMoD vehicles leading to the maximum demand of around 150,000 requests per day that can be attracted by the system. Within these parameters, the simulation results show that customers are willing to accept average waiting times of around 4 min at a price of 0.75 CHF/km. Further cost-covering cases with lower demand are presented, where either smaller fleet sizes lead to higher waiting times, or larger fleet sizes lead to higher costs. While our simulations indicate that an AMoD system in Zurich can bring benefits to the users, they show that the system impact is largely negative. Caused by modal shifts, our simulations show an increase of driven distance of up to 100%. All examined fleet configurations of the unregulated, cost-covering, single-passenger, door-to-door AMoD service are found to be highly counter-productive on a path towards a more shared and active transport system. Accordingly, policy recommendations for regulation are discussed., Transportation Research Part C, 123

Hörl and Balac describe a data pipeline to generate a synthetic travel demand for Paris and Île-de-France. The data set consists of households, persons and their daily activity chains. It can be used in transport simulation, energy analysis and other research fields such as epidemiology. This data-in-brief article describes in detail the generated data set and how it can be regenerated based on publicly available and open data. The characteristics and pre-processing steps for the input data sets are covered in detail., Data in Brief, 39, ISSN:2352-3409

The work proposes a methodological approach to studying and assessing the environmental sustainability of the transport system of the city. The authors have selected parameters for assessing the environmental sustainability of the transport system and identified significant factors affecting environmental sustainability. A coefficient of environmental sustainability of the urban transport system and a formula for its calculation are proposed. A simulation was used to assess the amount of emissions of harmful substances from the car exhaust gases if the demand structure changes with respect to the means of transport and transportation methods. The paper presents the results of changing the parameters of the traffic flow and demand by means of transport and transportation methods when introducing a parking fee in the central part of the city, changing the cost of parking and expanding the paid parking area.

Simulation modeling is a well-known and recurrent approach to study the performance of urban systems. Taking into account the recent and continuous transformations within increasingly complex and multidimensional cities, the use of simulation tools is, in many cases, the only feasible and reliable approach to analyze such dynamic systems. However, simulation models can become very time consuming when detailed input-space exploration is needed. To tackle this problem, simulation metamodels are often used to approximate the simulators' results. In this paper, we propose an active learning algorithm based on the Gaussian process (GP) framework that gathers the most informative simulation data points in batches, according to both their predictive variances and to the relative distance between them. This allows us to explore the simulators' input space with fewer data points and in parallel, and thus in a more efficient way, while avoiding computationally expensive simulation runs in the process. We take advantage of the closeness notion encoded into the GP to select batches of points in such a way that they do not belong to the same high-variance neighborhoods. In addition, we also suggest two simple and practical user-defined stopping criteria so that the iterative learning procedure can be fully automated. We illustrate this methodology using three experimental settings. The results show that the proposed methodology is able to improve the exploration efficiency of the simulation input space in comparison with non-restricted batch-mode active learning procedures.

This paper describes the design of SimPark, an agent-based micro-simulator with state-of-the-art parking components. The goal is to allow the simulation of parking policies and strategies while capturing their effects on traffic flow and personal schedules. Though individuals’ parking strategies are an important part of the simulator, they are out of scope in the presented research. All other components of the simulator are discussed in depth and compared with existing parking simulators.

International audience; Synthetic populations of travelers and their detailed mobility behavior are an important basis for agent-based transport simulations, which are increasingly used in transport planning and research today. To date, research based on such simulations is rarely replicable as it is based on proprietary data and tools. To foster the discussion and steer research towards reproducible transport simulations, this paper introduces a process for generating a synthetic travel demand with individual households, persons, and their daily activity chains for Paris and its surrounding region Île-de-France — entirely based on open data and open software and replicable by any researcher. The resulting travel demand is published for others to use as a comprehensive data basis for agent-based transport simulations and as a test bed for population and demand synthesis algorithms. Furthermore, it is discussed how implicit correlation structures impact the potential use cases of the synthetic travel demand for simulation and analysis purposes and how the common practice of using population samples for downstream simulations affects the results.

The modifiable areal unit problem is of great importance in geographic science. The use of a specific zoning impacts the social and economic imbalances that can be generated in the deployment of services, facilities, and infrastructure. In this article, GIS is used together with simulation and optimization tools to analyse the effects of bus frequency changes in the levels of service and horizontal equity derived from different types of territorial zoning. The city of Palma (Balearic Islands, Spain) was chosen as a case study for the method, for which different geographical areas are used: neighbourhoods, census sections, cadastral blocks, and a 400 × 400 m mesh. The results show significant variations of the optimal frequencies obtained, depending on the type of zoning used. In general, smaller zonings show much higher sensitivity for the detection of imbalances between the population and bus service level. Likewise, orthogonal zonings also prove useful for identifying service and population concentration over other zonings. The use of large spatial units could lead to the misdiagnosis of needs and the implementation of actions that do not actually improve the level of service or the equity of the transport service. It is recommended to consider combining zonings of different sizes simultaneously, in order to accurately highlight imbalances and to argue for transport service improvements.

This paper reports on initial steps of an integration of the microscopic land-use simulation system SILO (Simple Integrated Land- Use Orchestrator) and the agent-based transport simulation system MATSim (Multi-Agent Transport Simulation). It is shown how information can be transferred from the land-use model to the transport model in an agent-oriented fashion and how MATSim can be used as a transport model within the SILO framework in lieu of an aggregate transport model, which SILO has been coupled with up to now. It is shown that results of the previous model structure can be reproduced by the new fully microscopic modeling system based on SILO and MATSim. It is discussed how an agent-based transfer of information can also be established in the reverse direction, i.e. from the transport model to the land-use model based on the implementation of a query architecture. Finally, it is discussed how an integration of SILO and MATSim can help addressing additional current demands for research.

Explicit parking search is not widely integrated into transport simulation and transport models. In this paper, the integration of a parking search simulation into MATSim (Multi-Agent Transport Simulation) is demonstrated. This includes the integration into the agent's simulation logic using within-day re-planning methodology, a separation up of car trips into several segments for each stage of the trip, a parking search behavior and a data structure for parking infrastructure. The parking search model is applied in a case study for an area in Berlin, Germany. Compared to a standard simulation without parking search, results suggests that parking search traffic sums up to 20 per cent of the overall traffic in a residential area and has a significant impact on the overall travel times of agents traveling by car.