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Estimating preferred departure times of road users in a real-life network
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics. (CTR)ORCID iD: 0000-0002-3738-9318
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics. (CTR)ORCID iD: 0000-0002-4531-8659
2008 (English)In: Proceedings of the  European Transport Conference 2008, 2008Conference paper, Published paper (Refereed)
Abstract [en]

The demand for travel continues to increase in European cities of today, which results in long car travel times and highly congested road networks, especially during the morning and afternoon peak periods. The congested car system gives rise to high emissions of particles and greenhouse-gases, which is negative for both the local and global environment. Congestion also causes an uncertain travel time, something that in the latest years has been recognised as a major factor in car-users perception of trip disutility. Congestion is time-dependent in nature. Therefore, not only the spatial distribution of trips over the network is important in analysis and prediction, but also the temporal distribution of trips. A traditional congestion-relieving strategy such as a capacity expansion often has an impact on when people travel, since shorter travel times during the peak hour can attract traffic from the peak shoulders. The temporal effects are even more pronounced for the new policy measures gaining ground today, e.g. variable road pricing. Most variable road pricing systems aim at moving traffic from the peak hour to the peak shoulders, so called peak spreading. The means by which this is done is by charge differentiation: it is most expensive to travel at the most congested point in time. However, most large-scale transport planning models in use today are static and changes in the temporal distribution of trips are not considered. It is therefore likely that false conclusions are drawn when using these models to evaluate the ability of different pricing schemes or infrastructure investments to alleviate congestion.SILVESTER – A Dynamic Transport ModelTo better model the temporal distribution of traffic has been the basis in the development of SILVESTER (SImuLation of choice betWEen Sarting TimEs and Routes), which is a dynamic transport model for the Stockholm area. In SILVESTER road network conditions during the extended morning peak period (06:30-09:30) are modelled. The morning is divided into twelve 15-minute time intervals and a departure time choice model allocates trips to each interval depending on their attractiveness. The attractiveness of a time interval is determined by its corresponding travel time, travel time uncertainty, monetary cost and how close it is to the preferred time interval (PDT) of the traveller. The travellers can also choose to start before 06:30 or after 09:30. Mode choice is partially modelled by introducing the possibility for car-users to switch to public transport if it is perceived as a better option than any of the time intervals. It is distinguished between three trip purposes: business trips, trips with fixed schedule and school trips, and trips with flexible schedule and other trips. In SILVESTER iteration towards a general equilibrium between supply and demand is performed. The supply quantities (travel times, uncertainties etc.) are calculated with the mesoscopic dynamic traffic assignment model CONTRAM, whereas the demand for each time interval and public transport alternative is calculated with a mixed logit discrete choice model. A calibrated origin-destination-matrix (OD-matrix) for the Stockholm CONTRAM network exists and is based mainly on traffic counts but also on travel times for some selected OD-pairs. Calibration of Preferred Departure TimesEven though many trip-timing models use the concept of schedule delay, which is defined as the deviation from a preferred departure/arrival time, little work has been done on how to find the PDT-distribution when applying the model. For estimation the survey respondents can be asked to state their preferred time of travel, but for large-scale applications similar studies are expensive and time consuming. Previous work has often assumed a simplified distribution, such as all travellers in a market segment having the same PDT. Without calibration of PDT’s, e.g. using only a simplified exogenous assumption, the predictive capability of the transport model is questionable. Instead of making an exogenous assumption about the PDT-distribution this paper uses a reverse engineering approach to reveal PDT’s from the observed departure times of the reference situation. It is the combination of the estimated departure time choice model, the travel conditions and the observed departure times that can be used to get information about the PDT’s. Once the PDT’s have been calibrated for the reference situation they can be used in the evaluation of a congestion relieving strategy. This paper will present calibration methodology, obstacles overcome on the way and calibration results. It will also discuss future work in which the calibrated departure time choice model will be used to improve the design (charge levels and time periods) of a pricing scheme.

Place, publisher, year, edition, pages
2008.
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-10514OAI: oai:DiVA.org:kth-10514DiVA: diva2:218658
Conference
European Transport Conference 2008, 6-8 October 2008, Leeuwenhorst Conference Centre/ The Netherlands
Projects
silvester
Note
QC 20101015.Tidigare titel: "Deriving Preferred Departure Times of Road-Users in a Real-Life Network".Available from: 2009-05-20 Created: 2009-05-20 Last updated: 2011-10-19Bibliographically approved
In thesis
1. Incorporation of Departure Time Choice in a Mesoscopic Transportation Model for Stockholm
Open this publication in new window or tab >>Incorporation of Departure Time Choice in a Mesoscopic Transportation Model for Stockholm
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Travel demand management policies such as congestion charges encourage car-users to change among other things route, mode and departure time. Departure time may be especially affected by time-varying charges, since car-users can avoid high peak hour charges by travelling earlier or later, so called peak spreading effects. Conventional transport models do not include departure time choice as a response. For evaluation of time-varying congestion charges departure time choice is essential.

In this thesis a transport model called SILVESTER is implemented for Stockholm. It includes departure time, mode and route choice. Morning trips, commuting as well as other trips, are modelled and time is discretized into fifteen-minute time periods. This way peak spreading effects can be analysed. The implementation is made around an existing route choice model called CONTRAM, for which a Stockholm network already exists. The CONTRAM network has been in use for a long time in Stockholm and an origin-destination matrix calibrated against local traffic counts and travel times guarantee local credibility. On the demand side, an earlier developed departure time and mode choice model of mixed logit type is used. It was estimated on CONTRAM travel times to be consistent with the route choice model. The behavioural response under time-varying congestion charges was estimated from a hypothetical study conducted in Stockholm.

Paper I describes the implementation of SILVESTER. The paper shows model structure, how model run time was reduced and tests of convergence. As regards run time, a 75% cut down was achieved by reducing the number of origin-destination pairs while not changing travel time and distance distributions too much.

In Paper II car-users underlying preferred departure times are derived using a method called reverse engineering. This method derives preferred departure times that reproduce as well as possible the observed travel pattern of the base year. Reverse engineering has previously only been used on small example road networks. Paper II shows that application of reverse engineering to a real-life road network is possible and gives reasonable results.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2009. 25 p.
Series
TRITA-TEC-LIC, ISSN 1653-445X ; 09-001
Keyword
Transport Modelling, Departure Time Choice, Dynamic Traffic Simulation, Time-Varying Congestion Charges, Peak Spreading, Reverse Engineering
National Category
Civil Engineering
Identifiers
urn:nbn:se:kth:diva-10516 (URN)978-91-85539-39-0 (ISBN)
Presentation
2009-06-04, V3, KTH, Teknikringen 72, Stockholm, 10:00 (English)
Opponent
Supervisors
Projects
Silvester
Note

QC 20170222

Available from: 2009-05-26 Created: 2009-05-20 Last updated: 2017-02-22Bibliographically approved
2. Congestion Charging in Urban Networks: Modelling Issues and Simulated Effects
Open this publication in new window or tab >>Congestion Charging in Urban Networks: Modelling Issues and Simulated Effects
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

One of the major challenges cities face today, in their development towards sustainable urban areas, is the need for an efficient and environmentally friendly transport system. This transport system should manage to tie together the city without strong adverse impact on urban environment, air-quality and climate change. The specialized labour (and leisure) market, typical of a large urban area, exaggerates the need for efficient travel, as it is increasingly difficult to live and work within short distances.   

The use of demand management tools has become more frequent in transport planning with this development towards more sustainable cities. Whereas investing in new capacity was previously the main response to increased demand for travel, there is a much broader range of policies in use today. One of these demand management tools is congestion charging. Singapore was first to implement congestion charging and during the last decade it was followed by London and Stockholm, with increasing support from the citizens as a consequence. Many other cities have performed feasibility studies for introduction of congestion charging. 

The development of transport models for prediction of demand management tools, such as congestion charging, has however not been able to keep up with this change in kind of policy. Transport models that were developed for prediction and evaluation of infrastructure investments, such as new motorways, are often used to forecast effects of policies aimed at managing demand, which too often results in poor prediction.

This thesis focuses on the needs for modelling of congestion charging. The state-of-practice models used before implementation in Singapore, London and Stockholm are reviewed, as well as more advanced dynamic models developed for prediction of congestion charging and other demand management tools. A number of gaps in the modelling of congestion charging are described and a new model called SILVESTER is developed, which closes some of these gaps. In particular, SILVESTER involves dynamic mesoscopic modelling of traffic flows, flexible departure times and users with heterogeneous preferences.

The thesis describes the implementation of SILVESTER and considers and compares different methods of demand aggregation in order to reduce run-time of the large-scale dynamic model (Paper I). It also describes how preferred departure times of road users can be determined in calibration such that consistency exists between the departure time choice model and dynamic traffic flows which are input to assignment (Paper II). The unique implementation of congestion charging in Stockholm gives the possibility to validate SILVESTER on real-world measurement of reductions in traffic flow and behavioural adjustments to the charges (Paper III). SILVESTER is then used to analyse several modified versions of the Stockholm congestion charging scheme and to compare welfare and equity effects of the different schemes. It is shown that the welfare of the current scheme could be improved if charges were allowed to differ by location and driving direction (Paper IV). It is shown that the benefits of congestion charges calculated using SILVESTER are greater than the benefits calculated with a static model. Finally, the reasons for the greater benefits are investigated (Paper V).

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. x, 59 p.
Series
Trita-TEC-PHD, ISSN 1653-4468 ; 11:003
Keyword
Transport Modelling, Congestion Charging, Departure Time Choice, Dynamic Traffic Simulation, Welfare Effects, Equity
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-43732 (URN)978-91-85539-79-6 (ISBN)
Public defence
2011-11-09, F3, Lindstedsvägen 26, KTH, Stockholm, 10:30 (English)
Opponent
Supervisors
Funder
TrenOp, Transport Research Environment with Novel Perspectives
Note
QC 20111019Available from: 2011-10-19 Created: 2011-10-18 Last updated: 2012-06-12Bibliographically approved

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