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Autonomous vehicles are expected to offer a higher comfort of traveling at lower prices and at the same time to increase road capacity -a pattern recalling the rise of the private car and later of motorway construction. Using the Swiss national transport model, this research simulates the impact of autonomous vehicles on accessibility of the Swiss municipalities. The results show that autonomous vehicles could cause another quantum leap in accessibility. Moreover, the spatial distribution of the accessibility impacts implies that autonomous vehicles favor urban sprawl and may render public transport superfluous except for dense urban areas.

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For the simulation of public transport, next to a schedule, knowledge of the public transport routes is required. While the schedules are becoming available, the precise network routes often remain unknown and must be reconstructed. For large-scale networks, however, a manual reconstruction becomes unfeasible. This paper presents a route reconstruction algorithm, which requires only the sequence and positions of the public transport stops and the street network. It uses an abstract graph to calculate the least-cost path from a route's first to its last stop, with the constraint that the path must contain a so-called link candidate for every stop of the route's stop sequence. The proposed algorithm is implemented explicitly for large-scale, real life networks. The algorithm is able to handle multiple lines and modes, to combine them at the same stop location (e.g., train and bus lines coming together at a train station), to automatically reconstruct missing links in the network, and to provide intelligent and efficient feedback if apparent errors occur. GPS or OSM tracks of the lines can be used to improve results, if available. The open-source algorithm has been tested for Zurich for mapping accuracy. In summary, the new algorithm and its MATSim-based implementation is a powerful, tested tool to reconstruct public transport network routes for large-scale systems.

Autonomous vehicles (AVs), here self-driving and driverless vehicles, SAE levels 4 and 5 are becoming more clearly a reality. Potential services based on AVs and their consequences for the transport system are of increasing importance. This paper investigates policy combinations for a world with such services. The policy measures investigated are pricing of public transport (through subsidies), pricing of private motorized transport (through taxation or mobility pricing), and the organization of AV services (monopoly vs. oligopoly, with or without ride-sharing). Further, the perception of travel times for autonomous private cars is considered. All combinations of policies (respectively two to four levels each) were implemented in a simulation to determine their synergies. The applied model was the agent-based transportation simulation MATSim. The scenario employed for the tests was the agglomeration of Zug, Switzerland. The results suggest that, given the current spatial distribution of the demand and the current transport system, AV systems are only able to reduce travel times at the cost of substantial mode shifts and additional vehicle kilometers driven. Of the tested policy measures, although all showed the expected causality, only the organizational form of the AV service had a statistically significant effect. Therefore, this paper suggests that policy makers should be cautious when confronted with the promises of future transport services. To invest the benefits of automation into an improvement of the existing transport system (e.g., automation of public mass transit or complementing public mass transit with ride-sharing AVs in low-demand areas) might be a good alternative.

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The MATSim team frequently uses the Zürich scenario, based on the Switzerland scenario described above. The Zürich scenario, however, is more detailed; it was enhanced by data available only for the smaller region; e.g., tra c light data or freight demand data was only included for Zürich city and the canton. It is under continuous development, calibration and validation and has been applied in numerous projects, serving as a real-world research example. Horni et al. (2011b) provide a technical overview of the rst scenario branch; Balmer et al. (2009a) describe its generation for the "Westumfahrung" project. The study area was delineated by a circle, with a 30 kilometer radius around Bellevue, a central and prominent Zürich location. This delineation led to two versions, the Zürich diluted scenario and the Zürich cut scenario. For the rst, all agents crossing the study area during the simulated day were considered (Figure 56.1), resulting in almost two million agents. For the second, only agents remaining in this area the whole day were modeled. The Zürich cut scenario was employed as an experiment in Hackney (2009), but using the Zürich diluted scenario for production runs is preferable. Demand was taken directly from the Swiss model; freight tra c was added to the Zürich scenario, as follows. Canton Zürich raw freight tra c data was taken from the KVMZH (Kantonales Verkehrsmodell Zürich), provided by Amt für Verkehr, Volkswirtscha sdirektion Kanton Zürich (2011) and documented by Gottardi and Bürgler (1999). Zonal level matrices were disaggregated to single MATSim plans (Shah, 2010). Matrices for small delivery and heavy trucks were combined into one activity called freight. An additional 180 000 agents were generated for the Zürich region. For the diluted Zürich scenario, all Swiss facilities, as described above, were used as activity locations and the networks were not thinned out. For public transport simulation, network and transport schedules were derived from the KVMZH. Walk and bike modes were "teleported". Calibration was mainly done for modal split and distance distributions and utility function values set accordingly.

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