VACANCY INTERNSHIP PROJECT We are looking for students interested in carrying out their internship or master thesis project at DAT.Mobility
Extending STAQ to a semi dynamic assignment model Problem description Static Traffic Assignment with Queuing (STAQ) is an assignment model for road traffic that was developed as an alternative to traditional static traffic assignment (STA) models, providing more accuracy on congested networks without reducing robustness, applicability and accountability and without increasing input requirements, whilst keeping computational requirements to acceptable levels (Brederode et al., 2019). Like STA models, STAQ assumes stationary travel demand during a single study period (typically the AM or PM peak) and instantaneous flow propagation, but contrary to traditional STA models it adheres to strict road capacity constraints. Because of this latter difference, in STA models, all traffic reaches its destination, whereas In STAQ it is possible that part of the traffic is held up in queues. This is illustrated below (right) where the blue pie charts in the STAQ results represent queue locations. This traffic still needs to travel from the queue location to its destination, but this happens only after the study period and is therefore not handled by the STAQ instance of the study period. Omitting this traffic yields too little traffic on the network in the subsequent time period, which causes it to become too attractive causing the time of day choice model to shift too much traffic from the peak to the off-peak period.
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Figure 1: Assignment results of an STA model (left) and STAQ (right). Bandwidth colours: modelled speed as ratio of freeflowspeed; bandwidth widths:`modelled flow; blue circles in STAQ results (right): vertical queues (radius indicates queue size).
Master thesis assignment To properly handle traffic that is held up in queues and apply a time of day choice model, it would be required to run an additional STAQ instance describing the subsequent time period. This additional STAQ instance should handle both the traffic that was held up in queues in the study period and the additional traffic departing in the subsequent period. This concept could be extended to more time periods (e.g. 24 subsequent instances describing each hour of the day), effectively yielding a semi-dynamic version of STAQ (using the definition described in (Bliemer et al., 2017)). In this master thesis assignment, the merits and benefits of such a version in combination with a time of day choice model should be researched and demonstrated. Roughly, the assignment will consist of the following steps: 1. Create a prototypical implementation in Omni TRANS / Ruby that adds traffic from vertical queues (stored in a postgresql database) to the OD matrix of a subsequent period. 2. Test the now semi-dynamic version of STAQ for a 24h period, as this allows for better demand matrix calibration results (the latter is outside of scope of this research) 3. Test the semi dynamic version in combination with the time of day choice model described in (Zantema et al., 2016) which is also available in Omni TRANS / Ruby. 4. Compare the semi dynamic version of STAQ in combination with the departure time choice model with the regular STAQ version to demonstrate the benefits of the new approach.
Research group DAT.Mobility Deventer Daily supervisors: Luuk Brederode, Bastiaan Possel When interested in this Masters thesis assignment, please contact Ir. Luuk Brederode (lbrederode@DAT.nl, +31 (0) 627369830)
Literature Bliemer, M.C.J., Raadsen, M.P.H., Brederode, L.J.N., Bell, M.G.H., Wismans, L.J.J., Smith, M.J., 2017. Genetics of traffic assignment models for strategic transport planning. Transp. Rev. 37, 56–78. https://doi.org/10.1080/01441647.2016.1207211 Brederode, L., Pel, A., Wismans, L., de Romph, E., Hoogendoorn, S., 2019. Static Traffic Assignment with Queuing: model properties and applications. Transp. Transp. Sci. 15, 179–214. https://doi.org/10.1080/23249935.2018.1453561 Zantema, K., Heynickx, M., Brederode, L., Koopal, R., 2016. Time of Day and Demand Equilibrium in Large Scale Models, in: European Transport Conference 2016Association for European Transport (AET).