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Implementation, validation and application of an activity-based transportation model for Flanders
No full textThis dissertation describes the development and application of two software
packages that can be used to assist transport researchers and practitioners.
The first software package, PARROTS, is an electronic survey tool that enables
traffic researchers to carry out surveys yielding activity-travel diary data of a
higher quality than traditional paper-and-pencil surveys. Furthermore, as this
electronic tool is a GPS-enabled PDA data collection tool, it also provides the
researcher with a rich GPS data set at the same time. To judge the effect of the
PARROTS tool on the quality of activity-travel diaries, a paper-and-pencil diary
was designed and deployed as well. Based on the analyses between the
PARROTS survey tool and the paper-and-pencil survey, it could be concluded
that PARROTS provides both high quality activity-travel diary data and GPSbased location information while keeping the burden for the respondents at an
acceptable level.
The second software package, FEATHERS, is a modeling framework specifically
designed for implementing activity-based transport models. As this framework
became operational after a substantial development period, an already existing
and proven activity-based model, namely ALBATROSS, was reverse engineered
and re-implemented from the bottom up into the FEATHERS framework in order
to prove this framework’s right to exist. As this process proved to be successful,
following on the implementation phase of this activity-based model, a validation
was performed on this model in order to demonstrate its capability to represent
an activity-based model for Flanders, which was the study area of interest.
The validation of the activity-based transport model inside FEATHERS was split
up according to different dimensions. In a first part, a validation on the level of
the model components, i.e. decision trees was performed. This validation
indicated that the decision trees of the activity-based model inside FEATHERS
were capable of capturing people’s travel behavior in a decent way. Moreover,
based on some data-mining criteria, it could also be concluded that the decision
trees were capable of predicting travel behavior of unseen test cases when
compared with the cases of the model’s training data set. In a second part, a
validation of the FEATHERS model according to the activity-time travel time
dimension was worked out. Here it was demonstrated that the model was able
to replicate the so called “camelback” curve when compared with the same kind
of curve stemming from the Onderzoek Verplaatsingsgedrag (OVG) survey. The third part of the validation comprehended a model validation according to the
activity-travel space dimension. For this purpose, a completely independent
census data set was chosen in order to see whether or not the prediction data
set within FEATHERS matched with this census data set. As it turned out, a very
high correlation was found between both data sets indicating that the model
inside FEATHERS was able to pick up the observed spatial travel patterns of the
OVG survey respondents nicely. The fourth and last part of the validation was
carried out in terms of comparing traffic counts and vehicle kilometers travelled
of all predicted diaries with official governmental reports on those same kind of
figures. To this end, within FEATHERS, activity-travel schedules were simulated
for all the individuals of the Flemish population. Next, the predicted trips for the
entire population were assigned to a road network and traffic flows were
determined so that traffic counts and vehicle kilometers could be calculated. Also
in this case, the model inside FEATHERS showed a very good correspondence
with what can be seen in reality.
Now that the model inside FEATHERS was accepted, based on the detailed
validation, two scenario’s were implemented so that FEATHERS could be brought
into service. The first scenario comprehended the calculation of the total vehicle
travel reduction in the case of telecommuting. To this end, also a more
conventional method for calculating the total vehicle travel reduction was
adopted. As became clear, both FEATHERS and the conventional method showed
exactly the same reduction of travel in the case of the same telecommuting
scenario. This similarity in figures therefore proved that FEATHERS can be used
for modeling scenario’s such as the telecommuting scenario. The second
scenario comprehended the assessment of the spatial and temporal electrical
vehicle power demand for Flanders under 4 different electrical vehicle charging
scenario scripts. To this end, FEATHERS was first used in order to predict
activity-travel schedules so that in a second step, those schedules could be used
in order to evaluate the charging power demand under 4 different scenario
scripts. The results of those 4 scenario scripts revealed that most predicted trips
can be performed by a battery-only electrical vehicle. Moreover, it could also be
concluded that replacing battery-only electrical vehicles by pluggable-hybrid
electrical vehicles might increase electric energy consumption as pluggablehybrid electrical vehicles can exploit their full electric range. Overall, this
electrical vehicle scenario proved that, next to the telecommuting scenario,
FEATHERS can also be used for more specific and detailed scenario’s, paving the
way for even more detailed future scenario’s. In summary, this dissertation demonstrated that both software packages,
namely PARROTS and FEATHERS, can be a true aid for traffic researchers and
practitioners. As demonstrated, PARROTS can be used as an electronic state-ofthe-art activity-travel survey tool, yielding data of high quality. FEATHERS, on
his turn, can easily be used for implementing activity-based models for a specific
study area and secondly, for working out scenario’s that can be employed for
predicting different kinds of changes in the travel behavior of the Flemish
citizen.Dit proefschrift beschrijft de ontwikkeling en de toepassing van twee software
pakketten die gebruikt kunnen worden door transport onderzoekers en technici.
Het eerste software pakket, PARROTS, is een electronisch instrument dat
onderzoekers kan ondersteunen om transport enquetes uit te voeren waarbij de
activiteiten-verplaatsingen data van een hoger niveau is dan het geval is bij de
traditionele papier-en-potlood enquetes. Bovendien, aangezien het PDA data
collectie instrument ook een GPS bevat, levert dit instrument de onderzoeker
ook tegelijkertijd een rijke GPS data set. Om de kwaliteit van het PARROTS
instrument te beoordelen wat betreft de verzamelde activiteiten-verplaatsingen
dagboekjes, werd er ook een papier-en-potlood enquete samengesteld en
ingezet. Op basis van de daarop volgende analyses van beide data sets, kan
geconcludeerd worden dat PARROTS een hoog kwalitatieve activiteitenverplaatsingen data set verschaft samen met GPS-gebaseerde locatie informatie,
terwijl tegelijkertijd de belasting van de respondent op een acceptabel niveau
gehouden kon worden.
Het tweede software pakket, FEATHERS, levert een geraamte voor het
ontwikkelen van activiteiten-gebaseerde modellen. Nadat het raamwerk na een
substantiële ontwikkelingsperiode operationeel werd, werd een reeds bestaand
en beproefd activiteiten-gebaseerd model, namelijk ALBATROSS, zorgvuldig
doorzocht en opnieuw geïmplementeerd in het FEATHERS raamwerk. Na het
succesvol uitwerken van het activiteiten-gebaseerd model ALBATROSS, werd
een validatie uitgevoerd op dit model zodanig dat de capaciteit om een
volwaardig activiteiten-gebaseerd model voor Vlaanderen te kunnen zijn, kon
worden aangetoond.
De validatie van het activiteiten-gebaseerd transport model in FEATHERS werd
uitgesplitst volgens verschillende dimensies. In het eerste deel, werd er een
validatie uitgevoerd op de model componenten, namelijk de beslissingsbomen.
Dit deel van de validatie toonde aan dat de beslissingsbomen van het
activiteiten-gebaseerd model in FEATHERS in staat waren om het
verkeersgedrag van de burgers vast te leggen. Bovendien, was het op basis van
data-mining criteria ook mogelijk om vast te stellen dat de beslissingsbomen in
staat bleken te zijn om het verkeersgedrag te voorspellen van nieuwe test
records. In een tweede deel werd de validatie van het FEATHERS model volgens
de tijdsdimensie uitgewerkt. Hier werd aangetoond dat het model in staat is om de zogenaamde “kamelenrug curve” te voorspellen zoals ze voorkomt in de
Onderzoek Verplaatsingsgedrag (OVG) enquete. Het derde gedeelte van de
validatie behelsde aan model validatie volgens de ruimtelijke dimensie. Hiervoor
werd een volledig onafhankelijke census data set gebruikt om te zien of de
voorspelde data set in FEATHERS overeen zou komen met de census data set.
Uit deze analyse bleek dat er een heel hoge correlatie bestond tussen beide data
sets waaruit geconcludeerd kon worden dat het model in FEATHERS in staat was
om de geobserveerde ruimtelijke verkeerspatronen van de OVG enquete op een
ordentelijke wijze op te nemen. Het vierde en laatste gedeelte van de model
validatie betrof een vergelijking van verkeerstellingen en totaal aantal
voertuigkilometers tussen de voorspelde FEATHERS dagboekjes en officiële
reporten van de overheid. Hiervoor werd eerst op basis van FEATHERS
activiteiten-verplaatsingen patronen gesimuleerd voor al de Vlaamse burgers. In
een volgende stap werden al de verplaatsingen van de Vlamingen toegekend
aan een netwerk zodat verkeersstromen konden worden bepaald op basis
waarvan verkeerstellingen en totaal aantal voertuigkilometers konden berekend
worden. Op basis van deze analyse kon nogmaals worden aangetoond dat de
voorspellingen op basis van FEATHERS een heel goede overeenkomst tonen met
de werkelijkheid.
Nudat het model in FEATHERS op basis van de validatie geaccepteerd kon
worden, werden er twee scenario’s geselecteerd om uitgewerkt te worden wat
de uiteindelijke doelstelling van FEATHERS is. Het eerste scenario betrof een
berekening van de totale voertuigkilometer reductie in het geval een deel van de
bevolking zou telewerken. Om in te kunnen schatten of FEATHERS juiste
resultaten zou opleveren werd er ook een conventionele berekeningswijze
uitgevoerd en vergeleken met de berekeningen op basis van FEATHERS. Uit de
vergelijking tussen beide berekeningen kon worden geconcludeerd dat
FEATHERS exact dezelfde reductie in totaal aantal voertuigkilometers berekende
als het geval is met de conventionele berekeningswijze. De sterke overeenkomst
tussen beide resultaten toonde aan dat FEATHERS in staat is om scenario’s uit te
werken vergelijkbaar met dit telewerken scenario. Het tweede scenario betrof
een inschatting van de ruimtelijke en temporale component van de electrische
voertuig energie vraag voor Vlaanderen gegeven 4 verschillende electrische
voertuig oplading scenario scripts. Hiervoor werd FEATHERS eerst toegepast om
activiteit-trip dagboekjes te voorspellen om dan vervolgens, in een tweede stap,
deze dagboekjes te gebruiken om de energie oplading vraag te evalueren,
gegeven de 4 verschillende scenario scripts. De resultaten van deze 4 scenario scripts onthulden dat de meeste trips uitgevoerd kunnen worden door een
‘battery-only’ electrisch voertuig. Verder kon er ook afgeleid worden dat het
vervangen van ‘battery-only’ electrische voertuigen door ‘pluggable-hybrid’
electrische voertuigen het electrische ernergieverbruik zou kunnen verhogen
aangezien ‘pluggable-hybrid’ electrische voertuigen hun volledige capaciteit
kunnen benutten. Alles samen beschouwd, heeft het electrische voertuig
scenario kunnen aantonen dat, naast het telewerken scenario, FEATHERS ook
gebruikt kan worden voor meer specifieke en gedetailleerde scenario’s,
waardoor de weg gebaand kon worden voor nog meer gedetailleerde toekomst
scenario’s.
Kort samengevat kan worden gesteld dat dit proefschrift heeft kunnen aantonen
dat de beide software pakketten, namelijk PARROTS en FEATHERS, een ware
hulp kunnen betekenen voor verkeerskundige onderzoekers en technici. Zoals
aangetoond kon worden, kan PARROTS gebruikt worden als een electronische
state-of-the-art activiteiten-verplaatsingen enquete instrument waarmee data
van een hoge kwaliteit mee verzameld kan worden. FEATHERS, op zijn beurt,
kan gebruikt worden om activiteiten-gebaseerde transport modellen te
implementeren voor een specifiek studie gebied en bijkomend, voor het
uitwerken van scenario’s die kunnen worden ingezet voor het voorspellen van
allerhande veranderingen in het verplaatsingspatroon van de Vlaamse burger
A Generic Data-driven Sequential Clustering Algorithm Determining Activity Skeletons
No full textAbstractMany activity-based models start by scheduling inflexible or mandatory activities (if present), before more flexible activities. Often work and educational activities are assumed as most stringent and recognized as the only mandatory activities. According to this definition, only 45% of all schedules contains a mandatory activity (OVG single-day travel survey in Flanders, Belgium). This means 55% of schedules does not have a traditional mandatory-flexible activity structure. This research proposes a completely data-driven approach to reveal the real basic structure of individuals’ schedules, i.e. the skeleton schedule sequence. To this end, a sequential clustering algorithm was developed. Furthermore, an in-depth analysis of the parameter settings was performed. The proposed method reveals a set of skeleton activity schedules and confirms the importance of work and education
Investigating micro-simulation error in activity-based travel demand forecasting: a case study of the FEATHERS framework
No full textActivity-based models of travel demand have received considerable attention in transportation planning and forecasting over the last decades. However, they use in most cases micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a consequence, running a transport microsimulation model several times with the same input will generate different outputs, which to a great extent baffles practitioners in applying such a model and in interpreting the results. In order to take the variation of outputs in each model run into account, a common approach is to run the model multiple times and to use the average value of the results. The question then becomes: what is the minimum number of model runs required to reach a stable result (i.e., with a certain level of confidence that the obtained average value can only vary within an acceptable interval). In this study, systematic experiments are carried out by using the FEATHERS, an activity-based micro-simulation modeling framework currently implemented for the Flanders region of Belgium. Six levels of geographic detail are taken into account, which are Building block level, Subzone level, Zone level, Superzone level, Province level, and the whole Flanders. Three travel indices,
i.e., the average daily number of activities per person, the average daily number of trips per person, and the average daily distance travelled per person, as well as their corresponding
segmentations are calculated by running the model 100 times. The results show that the more disaggregated level is considered (the degree of the aggregation not only refers to the size of the
geographical scale, but also to the detailed extent of the index), the larger the number of model runs is needed to ensure confidence of a certain percentile of zones at this level to be stable. Furthermore, based on the time-dependent origin- destination table derived from the model output, traffic assignment is performed by loading it onto the Flemish road network, and the total vehicle kilometres travelled in the whole Flanders are computed subsequently. The stable results at the
Flanders level provides model users with confidence that application of the FEATHERS at an aggregated level only requires limited model runs
In the field evaluation of the impact of a GPS-enabled personal digital assistant on activity-travel diary data quality
No full textAbstract. A custom tool, PARROTS (PDA system for Activity Registration and Recording of Travel Scheduling) was developed to collect both activity data and GPS data. This tool is currently deployed in a survey that is carried out on 2,500 households in Flanders (Belgium). This paper discusses the findings on the effects of a GPS-enabled PDA data collection tool featuring default answers, pre-defined drop-down lists and many other graphical design elements on data quality. Two types of data are collected using PARROTS: activity-travel diaries inputted by the respondents and location data logged by a GPS receiver. To judge the effect of the PARROTS tool on the quality of activity-travel diaries, a paper-and-pencil diary was designed and deployed as well and various analyses were performed on both the paperandpencil and PDA data. For the collected GPS data the data quality was investigated in terms of availability of location information in the logs. In addition to investigating data quality, the impact of using PDA-technology on user response rates is examined and compared to response rates for the paper-and-pencil format. Based on the above analyses, the performance of PARROTS as an activity-based survey data collection tool is assessed
Activity-based model for medium-sized cities considering external activity–travel: Enhancing FEATHERS framework
No full textTravel demand modeling has evolved from the traditional four-step models to tour-based models which eventually became the basis of the advanced Activity-Based Models (ABM). The added value of the ABM over others is its ability to test various policy scenarios by considering the complete activity–travel pattern of individuals living in the region. However, the majority of the ABM restricts residents’ activities within the study area which results in distorted travel patterns. The external travel is modeled separately via external models which are insensitive to policy tests that an ABM is capable of analyzing. Consequently, to minimize external travel, transport planners tend to define a larger study area. This approach, however, requires huge resources which significantly deterred the worldwide penetration of ABM. To overcome these limitations, this study presents a framework to model residents’ travel and activities outside the study area as part of the complete activity–travel schedule. This is realized by including the Catchment Area (CA), a region outside the study area, in the destination choice models. Within the destination choice models, a top-level model is introduced that specifies for each activity its destination inside or outside the study area. For activities to be performed inside the study area, the detailed land use information is utilized to determine the exact location. However, for activities in the CA, another series of models are presented that use land use information obtained from open-source platforms in order to minimize the data collection efforts. These modifications are implemented in FEATHERS, an ABM operational for Flanders, Belgium and the methodology is tested on three medium-sized regions within Flanders. The results indicate improvements in the model outputs by defining medium-sized regions as study areas as compared to defining a large study area. Furthermore, the Points of Interests (POI) density is also found to be significant in many cases. Lastly, a comprehensive validation framework is presented to compare the results of the ABM for the medium-sized regions against the ABM for Flanders. The validation includes the (dis)aggregate distribution of activities, trips, and tours in time, space and structure (e.g. transport modes used and types of activities performed) through eleven measures. The results demonstrate similar distributions between the two ABM (i.e. ABM for medium-sized regions and for Flanders) and thus confirms the validity of the proposed methodology. This study, therefore, shall lead to the development of ABM for medium-sized regions.Part of this research was funded by Higher Education Commission (HEC) of Pakistan
Linking activity-travel diaries and GPS-based route choice information: A Flemish case study
No full textLinking activity-travel diaries and GPS-based route choice information: A Flemish case study
No full text
Geographical Extension of the Activity-based Modeling Framework FEATHERS
No full textAbstractFEATHERS is an activity-based micro-simulation modeling framework used for transport demand forecasting. Currently, this framework is implemented for the Flanders region of Belgium and the most detailed travel demand data can be obtained at the Subzone level, which consists of 2,386 virtual units with an average area of 5.8 km2. In this study, we investigated the transferability of applying the FEATHERS framework from the Subzone zoning system to a more disaggregated zoning system, i.e., Building block (BB), which is the most detailed geographical level currently applicable in Belgium consisting of 10,521 units with an average area of 1.3 km2. In this paper, we elaborated the data processing procedure in order to implement the FEATHERS framework under the BB zoning system. The observed as well as the predicted travel demand in Flanders based on the two zoning systems were compared. The results indicated the validity and also the necessity of this extension
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