Integrating public transport into mobiTopp

Briem, Lars; Buck, H. Sebastian; Mallig, Nicolai; Vortisch, Peter; Strasser, Ben; Wagner, Dorothea; Zündorf, Tobias

doi:10.1016/j.procs.2017.05.401

Cited by 6 publications

(17 citation statements)

References 7 publications

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“…To distinguish between different times of the day, travel times can be modeled on an hourly basis. Route choice is currently only available for public transport (44). For other modes, external tools such as Visum and MATSim can be used (45).…”

Section: Approachmentioning

confidence: 99%

Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

Wilkes

Engelhardt

Briem

et al. 2021

Transportation Research Record: Journal of the Transportation R

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This paper presents the coupling of a state-of-the-art ride-pooling fleet simulation package with the mobiTopp travel demand modeling framework. The coupling of both models enables a detailed agent- and activity-based demand model, in which travelers have the option to use ride-pooling based on real-time offers of an optimized ride-pooling operation. On the one hand, this approach allows the application of detailed mode-choice models based on agent-level attributes coming from mobiTopp functionalities. On the other hand, existing state-of-the-art ride-pooling optimization can be applied to utilize the full potential of ride-pooling. The introduced interface allows mode choice based on real-time fleet information and thereby does not require multiple iterations per simulated day to achieve a balance of ride-pooling demand and supply. The introduced methodology is applied to a case study of an example model where in total approximately 70,000 trips are performed. Simulations with a simplified mode-choice model with varying fleet size (0–150 vehicles), fares, and further fleet operators’ settings show that (i) ride-pooling can be a very attractive alternative to existing modes and (ii) the fare model can affect the mode shifts to ride-pooling. Depending on the scenario, the mode share of ride-pooling is between 7.6% and 16.8% and the average distance-weighed occupancy of the ride-pooling fleet varies between 0.75 and 1.17.

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Section: Approachmentioning

confidence: 99%

Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

Wilkes

Engelhardt

Briem

et al. 2021

Transportation Research Record: Journal of the Transportation R

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“…A decision model is then used to decide whether a passenger would actually use the connection based on the PAT. Because of its efficiency, this approach has already been adapted for the travel demand simulation tool mobiTopp [6].…”

Section: Related Workmentioning

confidence: 99%

“…The departure buffer time models the time that is needed to walk to the platform where the vehicle departs and enter the vehicle, which may be considerable if the stop represents a large station. Many other works, including the CSA-based assignment algorithm we want to build upon, instead consider minimum change times [2,6,10,11]. The minimum change time must only be observed when transferring between trips at the same stop, but not when entering a trip after arriving via a footpath.…”

Section: Public Transit Routingmentioning

confidence: 99%

Efficient Computation of Multi-Modal Public Transit Traffic Assignments using ULTRA

Sauer

Wagner

Zündorf

2019

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

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We study the problem of computing public transit traffic assignments in a multi-modal setting: Given a public transit timetable, an additional unrestricted transfer mode (in our case walking), and a set of origin-destination pairs, we aim to compute the utilization of every vehicle in the network. While it has been shown that considering unrestricted transfers can significantly improve journeys, computing such journeys efficiently remains algorithmically challenging. Since traffic assignments require the computation of millions of shortest paths, using a multi-modal network has previously not been feasible. A recently proposed approach (ULTRA) enables efficient algorithms with UnLimited TRAnsfers at the cost of a short preprocessing phase. In this work we combine the ULTRA approach with a state-of-the-art assignment algorithm, making multi-modal assignments practical. Careful algorithm engineering results in a new public transit traffic assignment algorithm that even outperforms the algorithm it builds upon, while enabling unlimited walking which has not been considered previously. We conclude our work with an extensive evaluation of the algorithm, showing its versatility and efficiency. On our real world instance, the algorithm computes over 15 million unique journeys in less than 17 seconds.Figure 1: Utilization of public transit vehicles between 8:30 a.m. and 9:00 a.m. in the Stuttgart area (Germany), as computed by our assignment algorithm. Vehicles used by only a few passengers are depicted using thin, green lines. As vehicles are used by more passengers, their line is gradually drawn thicker and their color changes to red. The transfer graph is depicted in gray.

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“…New optimal approaches to solving the network approach are used in [10,11]. The authors in [12] integrated the side of the supply of public transport into the model of the traveler demand. The model also contains power limits for vehicles, which, when activated, lead to a significant increase in travel time.…”

Section: Research Of Existing Solutions Of the Problemmentioning

confidence: 99%

Investigation of approaches to modeling of intercity passenger transportation system

Dolya

Botsman

Kozhyna

2017

TAPR

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Integrating public transport into mobiTopp

Cited by 6 publications

References 7 publications

Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

Efficient Computation of Multi-Modal Public Transit Traffic Assignments using ULTRA

Investigation of approaches to modeling of intercity passenger transportation system

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