Intriguingly Simple and Fast Transit Routing

Dibbelt, Julian; Pajor, Thomas; Strasser, Ben; Wagner, Dorothea

doi:10.1007/978-3-642-38527-8_6

Cited by 77 publications

(86 citation statements)

References 13 publications

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“…In the past several routing algorithms have been developed to solve this problem. 10,11,12 Instead of developing a new algorithm, we decided to choose one that fits our needs. As the routing algorithm will be used heavily during simulation, the speed of a single route search requests is quite important.…”

Section: Public Transport In Mobitoppmentioning

confidence: 99%

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Integrating public transport into mobiTopp

Briem

Buck

Mallig

et al. 2020

Future Generation Computer Systems

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Demand and supply are both relevant for travel time in public transport. While it is obvious that the supply side in form of the timetable corresponds directly to the travel time, the demand side influences the travel time only partially, but in critical moments. During peak hours, when the demand reaches the capacity of the vehicles, the interaction between demand and supply becomes important. Overcrowded vehicles, hindering passengers to catch their chosen route, lead to longer travel times. Therefore, it is important to integrate the supply side of public transport into a travel demand model.The supply side of public transport has been integrated into the agent-based travel demand model mobiTopp. A timetable has been implemented, which is used for two purposes. First, it serves as input for the Connection Scan Algorithm, which is used by the agents to find the routes with earliest arrival time at their destinations. Second, it is used for the movement of the public transport vehicles. The model also contains capacity constraints for vehicles, which, when activated, result in a noticeable increase in travel time.

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Section: Public Transport In Mobitoppmentioning

confidence: 99%

“…Transfer times are only relevant, if the vehicle (trip) of the connection has not already been used. If the arrival time is updated, all footpaths of this stop are used to update the arrival time at the other stop of each footpath 12,14 . The algorithm is described in pseudocode in Listing 1.…”

Section: Connection Scan Algorithmmentioning

confidence: 99%

Integrating public transport into mobiTopp

Briem

Buck

Mallig

et al. 2020

Future Generation Computer Systems

Self Cite

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“…The Ðˆ parameter is usually calculated using General Transit Feed Specification (GTFS) data -if available for the city, and computed using the Connection Scan Algorithm (Dibbelt et al, 2013) or the RAPTOR algorithm (Delling et al, 2012). The limitation of these methods is the huge computational time required.…”

Section: Modal Splitmentioning

confidence: 99%

OLYMPUS v1.0: Development of an integrated air pollutant and GHG urban emissions model – Methodology and calibration over the greater Paris

Etuman¹,

Coll²

2018

Preprint

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Abstract. Air pollutants and greenhouse gases have many effects on health, the economy, urban climate and atmospheric environment. At the city level, the transport and heating sectors contribute significantly to air pollution. In order to quantify the impact of urban policies on anthropogenic air pollutants, the main processes 15 leading to emissions need to be understood: they principally include mobility for work and leisure as well as household behavior, themselves impacted by a variety of social parameters. In this context, the Olympus modeling platform has been designed for environmental decision support. It generates a synthetic population of individuals and defines the mobility of each individual in the city through an activitybased approach of travel demand. The model then spatializes road traffic by taking into account congestion on the 20 road network. It also includes a module that estimates the energy demand of the territory by calculating the unit energy consumption of households and the tertiary sector. Finally, the emissions associated with all the modeled activities are calculated using the COPERT emission factors for the traffic, and the European Environmental Agency (EEA) methodology for heating-related combustions. The comparison of emissions with AIRPARIF's regional inventory shows discrepancies that are consistent with differences in assumptions and input data, mainly 25 in the sense of underestimation. The methodological choices, as well as the potential ways of improvement, including the refinement of traffic congestion modeling and of the transport of goods, are discussed.

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“…We have chosen this approach to get a broad view on how the newly-introduced connections can massively affect a large network. We have used the connection scan algorithm (CSA) [48] as an EAT implementation, since it matches with our notion of connection. In short, CSA works by receiving a stream of connections ordered by departure time and chooses the fastest way to reach one stop from another.…”

Section: Calculating Routes Using Discovered Connectionsmentioning

confidence: 99%

An Automatic Matcher and Linker for Transportation Datasets

Masri

Zeitouni

Kedad

et al. 2017

Preprint

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Multimodality requires the integration of heterogeneous transportation data to construct a broad view of the transportation network. Many new transportation services are emerging while being isolated from previously-existing networks. This leads them to publish their data sources to the web, according to linked data principles, in order to gain visibility. Our interest is to use these data to construct an extended transportation network that links these new services to existing ones. The main problems we tackle in this article fall in the categories of automatic schema matching and data interlinking. We propose an approach that uses web services as mediators to help in automatically detecting geospatial properties and mapping them between two different schemas. On the other hand, we propose a new interlinking approach that enables the user to define rich semantic links between datasets in a flexible and customizable way.

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Intriguingly Simple and Fast Transit Routing

Cited by 77 publications

References 13 publications

Integrating public transport into mobiTopp

Integrating public transport into mobiTopp

OLYMPUS v1.0: Development of an integrated air pollutant and GHG urban emissions model – Methodology and calibration over the greater Paris

An Automatic Matcher and Linker for Transportation Datasets

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