A model that can be used to analyze both current and future high-speed rail corridors is presented in this work. This model has been integrated into the Transportation Systems Analysis Model (TSAM). The TSAM is a model used to predict travel demand between any two locations in the United States, at the county level. The purpose of this work is to develop tools that will create the necessary input data for TSAM, and to update the model to incorporate passenger rail as a viable mode of transportation. This work develops a train dynamics model that can be used to calculate the travel time and energy consumption of multiple high-speed train types while traveling between stations. The work also explores multiple options to determine the best method of improving the calibration and implementation of the model in TSAM. For the mode choice model, a standard C logit model is used to calibrate the mode choice model. The utility equation for the logit model uses the decision variables of travel time and travel cost for each mode. A modified utility equation is explored; the travel time is broken into an in-vehicle and out-of-vehicle time in an attempt to improve the model, however the test determines that there is no benefit to the modification. In addition to the C-logit model, a Box-Cox transformation is applied to both variables in the utility equation. This transformation removes some of the linear assumptions of the logit model and thus improves the performance of the model. The calibration results are implemented in TSAM, where both existing and projected high-speed train corridors are modeled. The projected corridors use the planned alignment for modeling. The TSAM model is executed for the cases of existing train network and projected corridors. The model results show the sensitivity of travel demand by modeling the future corridors with varying travel speeds and travel costs. The TSAM model shows the mode shift that occurs because of the introduction of high-speed rail. / Master of Science

A tool to model both current rail and future high-speed rail (HSR) corridors has been presented in this work. The model is designed as an addition to the existing TSAM (Transportation System Analysis Model) capabilities of modeling commercial airline and automobile demand. TSAM is a nationwide county to county multimodal demand forecasting tool based on the classical four step process. A variation of the Box-Cox logit model is proposed to best capture the characteristic behavior of rail demand in US. The utility equation uses travel time and travel cost as the decision variables for each model. Additionally, a mode specific geographic constant is applied to the rail mode to model the North-East Corridor (NEC). NEC is of peculiar interest in modeling, as it accounts for most of the rail ridership. The coefficients are computed using Genetic Algorithms. A one county to one station assignment is employed for the station choice model. Modifications are made to the station choice model to replicate choices affected by the ease of access via driving and mass transit. The functions for time and cost inputs for the rail system were developed from the AMTRAK website. These changes and calibration coefficients are incorporated in TSAM. The TSAM model is executed for the present and future years and the predictions are discussed. Sensitivity analysis for cost and speed of the predicted HSR is shown. The model shows the market shift for different modes with the introduction of HSR. Limited data presents the most critical hindrance in improving the model further. The current validation process incorporates essential assumptions and approximations for transfer rates, short trip percentages, and access and egress distances. The challenges for the model posed by limited data are discussed in the model. / Master of Science

No description available.

Human behaviour produces massive greenhouse gas emissions, which trigger climate change and more unpredictable weather conditions. The fluctuation of daily weather corresponds to variations of everyday travel behaviour. This influence, although is less noticeable, can have a strong impact on the transport system. Specifically, the climate in Sweden is becoming warmer in the recent 10 years. However, it is largely unknown to what extent the change of travel behaviour would respond to the changing weather. Understanding these issues would help analysts and policy makers incorporate local weather and climate within our policy design and infrastructure management. The thesis contains eight papers exploring the weather and climate impacts on individual travel behaviour, each addressing a subset of this topic. Paper I explores the weather impact on individual’s mode choice decisions. In paper II and III, individual’s daily activity time, number of trips/trip chains, travel time and mode shares are jointly modelled. The results highlight the importance of modelling activity-travel variables for different trip purposes respectively. Paper IV develops a namely nested multivariate Tobit model to model activity time allocation trade-offs. In paper V, the roles of weather on trip chaining complexity is explored. A thermal index is introduced to better approximate the effects of the thermal environment. In paper VI, the role of subjective weather perception is investigated. Results confirm that individuals with different socio-demographics would have different subjective weather perception even given similar weather conditions. Paper VII derives the marginal effects of weather variables on transport CO2 emissions. The findings show more CO2 emissions due to the warmer climate in the future. Paper VIII summaries the existing findings in relations between weather variability and travel behaviour, and critically assesses the methodological issues in previous studies. / <p>QC 20160516</p> / Understanding the complexity of changes of travelers’ activity-travel choices and related transport CO2 emissions due to the variation of weather and climate in Sweden (Centre för Transport Studie, projekt kod: 446) / Understanding the impacts of weather and climate change on travel behavior (Centre för Transport Studie, projekt kod: 291)

Travel demand analysis has traditionally focused on exploring and modeling travel behavior on weekdays. This emphasis on weekday travel behavior analysis was largely motivated by the presence of well-defined peak periods, primarily associated with the journey to and from work. Most travel demand models are based on weekday travel characteristics and purport to estimate traffic volumes for daily or peak weekday conditions. Much of the planning and policy making that occurs in transportation arena in response to weekday travel behavior and forecasts. More recently, there had been a growing interest in exploring, understanding, and quantifying weekend travel characteristics. The ability to do this has been limited due to the non-availability of travel survey data that includes weekend trip information. Most travel surveys collect information about weekday travel behavior and ignore weekend days. However, the 2001 National Household Travel Survey includes a substantial sample that provided detailed trip information for weekend days and therefore this dataset offers a key opportunity to explore in-depth weekend travel characteristics. Weekend travel behavior is expected to be substantially different from the weekday travel behavior for difference in several spatial and temporal constraints. The difference in constraints can also lead to a change in trip chaining patterns on weekdays and weekends. Differences in constraints coupled with socio-economic changes characterized by greater disposable income, time-constrained lives, and greater discretionary activity opportunities point towards the growing role that weekend travel behavior is going to play in transportation planning and policy-making. This thesis provides a comprehensive analysis of weekend travel behavior using the 2001 NHTS. Differences and similarities between weekday and weekend travel behavior are identified and presented for different urban areas sizes varying according to Metropolitan Statistical Area (MSA) size. Models of weekend and weekday travel behavior are developed to capture the structural relationship of socio-demographics, activity durations, and travel duration are developed using structural equations modeling approaches to better understand the relationships among these aspects of travel behavior on weekdays and weekends. This report is supposed to act as an updated data guide to the National Cooperative Highway Research Program's (NCHRP) Report 365 titled "Travel Estimation Techniques for Urban Planning" aims at studying the changes in behavioral characteristics between two categories of the day of week - a weekday and a weekend based on personal, household and trip characteristics.

Recent developments in microsimulation modeling of activity and travel demand have called for the explicit recognition of time-space constraints under which individuals perform their activity and travel patterns. The estimation of time-space prism vertex locations, i.e., the perceived time constraints, is an important development in this context. Stochastic frontier modeling methodology offers a suitable framework for modeling and identifying the expected vertex locations of time space prisms within which people execute activity-travel patterns. In this work, stochastic frontier models of time space prism vertex locations are estimated for samples drawn from a household travel survey conducted in 2001 in the city of Thane on the west coast of India and National Household Travel Survey 2001, United States. This offers an opportunity to study time constraints governing activity travel patterns of individuals in a developing as well as developed country context. The work also includes comparisons between males and females, workers and non-workers, and developed and developing country contexts to better understand how socio-economic and socio-cultural norms and characteristics affect time space prism constraints. It is found that time space prism constraints in developing country data set can be modeled using the stochastic frontier modeling methodology. It is also found that significant differences exist between workers and non-workers and between males and females,possibly due to the more traditional gender and working status roles in the Indian context. Finally, both differences and similarities were noticed when comparisons were made between results obtained from the data set of India and United States. Many of these differences can be explained by the presence of other constraints including institutional, household, income, and transportation accessibility constraints that are generally significantly greater in the developing country context.

Literature on transportation planning and modeling is replete with the concept of a travel time budget. According to this concept, average daily travel times tend to be relatively constant. However, evidence from the 1983 Nationwide Personal Transportation Survey and the 2001 National Household Travel Survey suggest that the average daily travel time has increased by 1.9 minutes per year. Understanding travel time expenditures is important for forecasting travel demand, especially future vehicle miles of travel. Historically, travel demand models considered vehicle availability and income as limiting factors for travel, but going forward time may be the constraint. As individuals spend more time devoted to travel, less time will be available for other activities. Therefore, future travel demand is dependent on people's willingness to spend time traveling. Growth of travel demand has been per capita based not just population based. This has been enabled by several cultural trends, including fewer children to care for; specialization of activities; multitasking during travel, for example, cell phone use can add value to travel time; seeking socialization away from home; and increases in real income enabling more activity participation. This study will report the increase in average daily travel time expenditures and analyze the increase by various demographic segments of the population. Travel time expenditures are also related to activity participation, the characteristics of the area, and many other interrelated factors at the person level. Aggregate values will be used to investigate the general relationships between daily travel time expenditures and socio-demographic characteristics. Careful consideration of the implications of the increase in travel time, as well as the changes in society that have contributed to these changes will be explored. The increase in travel time expenditures is likely to play a significant role in future travel demand growth in the United States and will impact the performance of the transportation system going forward. If travel time expenditures continue to grow, the hope for slowing VMT growth may not materialize. Understanding the mechanics of why people are traveling more will aid planners and modelers in estimating future travel demand.

In recent years, various researches are under progress to enhance the quality of the travel survey. These researches were mainly performed with the aid of GPS technology. Initially the researches were mainly focused on the vehicle travel mode due to the availability of GPS technology in vehicle. But, nowadays due to the accessible of GPS devices for personal uses, researchers have diverted their focus on personal mobility in all travel modes. This master’s thesis aimed at developing a mechanism to extract one type of travel survey information particularly travel mode from collected GPS dataset. The available GPS dataset is collected for travel modes of walk, bike, car, and public transport travel modes such as bus, train and subway. The developed procedure consists of two stages where the first is the dividing the track trips into trips and further the trips into segments by means of a segmentation process. The segmentation process is based on an assumption that a traveler switches from one transportation mode to the other. Thus, the trips are divided into walking and non walking segments. The second phase comprises a procedure to develop a classification model to infer the separated segments with travel modes of walk, bike, bus, car, train and subway. In order to develop the classification model, a supervised classification method has been used where decision tree algorithm is adopted. The highest obtained prediction accuracy of the classification system is walk travel mode with 75.86%. In addition, the travel modes of bike and bus have shown the lowest prediction accuracy. Moreover, the developed system has showed remarkable results that could be used as baseline for further similar researches.

<p>The Stockholm Congestion Tax Trial is one of the few projects where an automatic system was implemented to tax road vehicles in order to reduce congestion. The taxation period lasted from January until July 2006 and vehicles going in or out of the inner city during daytime were taxed with 10 to 20 SEK (1.07 to 2.14 Euro). The project included improved public transportation and more park & ride sites. The trial was limited to a half year and the public was able to vote on the congestion tax afterwards. A large research package was set up in order to inform everybody about the effects of the tax. The referendum was positive and the congestion tax is permanent today, but the data collected for research purposes is not fully analyzed yet. This thesis focuses on travel behavior of the population in Stockholm County and uses a household panel survey with 24,000 individuals. The waves took place in September 2004 and March 2006.The main idea is to use the advantages of the panel survey and keep track of how the individuals behaved during the two waves. The analysis is done separately for each trip purpose and examines the change of mode choice during the second wave in comparison to the individual’s choice before the congestion tax. This can be even specified for different socio-demographic groups.The cross-sectional comparison shows that avoiding trips to and from the inner city is not an option. The number of trips of the individuals passing through the congestion tax cordon is reduced to a lower extend by seasonal influences than the trips in all other parts of the county. Therefore the inner city has become more attractive as a origin or destination or the trips passing through the cordon can not be substituted by trips free of tax.Public transportation is the mode which benefits most from the congestion tax in terms of modal split. The importance of it increases in the whole county, but the gain is a lot higher for trips through the cordon. The modes foot and bike are not a relevant alternative for trips through the cordon because of long distances in general and cold weather during the survey. The panel analysis shows that many more people doing cordon passages to work, home and shopping change from car to public transportation in comparison to the rest of the county. Changes from public transport to car occur less often for cordon passages than for trips not being taxed.Certain socio-demographic groups adapt differently to the congestion tax. Compared to men, up to 30 percent point fewer women continue to use the car depending on the trip purpose. This may be related to personal income, but the variables household income has proofed to have a smaller impact. Only really poor households use the car a lot less often and the highest income group tends to continue to drive by car.The main limiting factor of the analysis is the seasonal and weather influence because of unusual cold weather during the second wave. It is not possible to take this completely into account because the control group of the cordon passages has different trip characteristics.The thesis provides better knowledge how a congestion tax affects the behavior of the people. It allows checking the reasonability of transportation modeling results and shows that certain socio-demographic variables should be used if modeling is done for areas with a different composition of the population than Stockholm.</p> / <p>Der Versuch der Stockholmer Innenstadtmaut ist eines der wenigen Projekte, bei dem ein automatisches Mauterhebungssystem für Fahrzeuge zur Stauminderung eingeführt wurde. Der Versuchszeitraum mit Mauterhebung reichte von Januar bis Juli 2006. Alle Fahrzeuge, die in und aus der Innenstadt fuhren, mussten tagsüber 10 bis 20 SEK (1,07 bis 2,14 Euro) bezahlen. Das Projekt beinhaltete einen verbesserten öffentlichen Personennahverkehr und mehr Park&Ride-Stellplätze.Der Versuch war auf ein halbes Jahr begrenzt und im Anschluss wurde eine Volksabstimmung durchgeführt. Zur Information der Bevölkerung über die Auswirkungen der Maut wurde ein großes Forschungspaket aufgelegt. Die Volkabstimmung verlief positiv und die Maut ist heute dauerhaft eingeführt, aber die gesammelten Daten aus dem Forschungsprojekt sind noch nicht vollständig ausgewertet. Diese Arbeit konzentriert sich auf das Mobilitätsverhalten der Bevölkerung im Bezirk Stockholm und verwendet eine Panelbefragung in Haushalten mit 24.000 Teilnehmern. Die Befragungswellen fanden im September 2004 und März 2006 statt.Die Untersuchung verfolgt das Verhalten einzelner Individuen während der beiden Wellen und nutzt somit die Vorteile, die die Panelbefragung bietet. Die Analyse wird separat für jeden Wegezweck durchgeführt und betrachtet die Änderung der Verkehrmittelwahl während der zweiten Welle im Vergleich zur ursprünglichen Wahl vor der Maut. Dies wird durch die Auswertung einzelner soziodemographischer Gruppen ergänzt.Die Querschnittsuntersuchung zeigt, dass die Maut nicht zu einer Vermeidung von Wegen in oder aus der Innenstadt führt. Die Anzahl an Wegen durch den Mautgürtel nimmt leichter durch saisonale Einflüsse ab als in anderen Teilen des Bezirkes. Somit ist die Stadt entweder als Quell- oder Zielgebiet attraktiver geworden oder die Wege durch den Mautgürtel können nicht durch kostenfreie Fahrten ersetzt werden.Der öffentliche Personennahverkehr profitiert im Sinne vom Modal Split am meisten von der Maut. Die Bedeutung steigt im gesamten Bezirk, aber das Wachstum ist deutlich stärker für Wege durch den Mautgürtel. Die Verkehrsmittel Fuß und Fahrrad sind keine Alternative für die kostenpflichtigen Wege, da die Reiseweiten zu hoch sind und das Wetter zu kalt war. Die Panelanalyse zeigt, dass deutlich mehr Personen mit Wegen durch den Mautgürtel zur Arbeit, nach Hause und zum Einkaufen vom Auto zum öffentlichen Verkehr umsteigen als im Rest des Bezirks. Wechsel vom öffentlichen Verkehr zum Auto treten seltener bei Wegen in oder aus der Innenstadt auf als bei kostenfreien Fahrten.Einzelne soziodemographische Gruppen passen sich besonders an die Maut an. Frauen ersetzen je nach Wegezweck im Vergleich zu Männern bis zu 30 % häufiger das Auto durch alternative Verkehrsmittel. Dies kann mit geringerem persönlichen Einkommen zusammenhängen, aber die Variable Haushaltseinkommen hat in der Untersuchung einen eher geringen Einfluss bewiesen. Nur sehr arme Haushalte nutzen das Auto deutlich weniger und die Haushalte in der höchsten Einkommensgruppe behalten die Autonutzung bei.Die gesamte Analyse wird durch saisonale Einflüsse und das Wetter eingeschränkt, das während der zweiten Welle ungewöhnlich kalt war. Dieser Einfluss kann nicht vollständig berücksichtigt werden, da die Kontrollgruppe für die Wege durch den Mautgürtel Unterschiede bei der Wegecharakteristik aufweist.Die Studienarbeit verbessert das Wissen über Verhaltensänderungen der Menschen durch eine Maut. Sie ermöglicht die Überprüfung von Ergebnissen der Verkehrsmodellierung und zeigt, dass einzelne soziodemographische Merkmale für die Modellierung in anderen Regionen genutzt werden sollten, wenn die Zusammensetzung der Bevölkerung von Stockholm abweicht.</p> / <p>Stockholmsförsöket är ett av de få projekten som brukar ett automatik systemet för beskatta fordon med trängselskatt. Syftet är att minska trängseln på gatorna. Försöksperioden låg mellan januari och juli 2006. Fordon som åkte in eller ut i innerstaden måste betala 10 till 20 SEK under dagtid. Försöket omfattade förbättrad kollektivtrafik samt fler infartsparkeringar.Försöket var begränsat till ett halvt år och allmänhet hade folkomröstning om skatten senare. En stort  paket med många forskningsprojekt startas för att informera alla om effekter av skatt. Folkomröstning gav ett jakande svar och trängselskatt är idag permanent. Men all samlad data är ännu inte analyserad. Det här examensarbetet koncentrerar på resvanor av alla invånare i Stockholms Län och använder kohortstudier med 24 000 personer. Vågor uppstod i september 2004 och mars 2006.Huvudideen var att  använda sig av kohortstudier och studera beteendet i båda vågorna. Alla ärenden analyserades separat och skillnaderna på färdmedelna undersötes mellan förre och efter trängselskatt. Det kan även bli specificerad för flera olika sociala bakgrundsgrupper.Tvärsnittstudiens analys visar att förhindra resor till och från innerstaden inte är ett alternativ. Antal av resenärer som passerat avgiftssnittet har inte minskat så mycket av väder än alla andra resor i länet. Innerstaden är mer attraktiv som utgångspungt eller destination. De kan inte ersättnas med resor som kostar ingen skatt.Färdmedelfördelning har förbättrats för kollektivtrafiken på grund av trängselskatt. Kollektivtrafiken ökar i hela länet, men vinsten är störst för resor som passerat avgiftnittet. Färdmedeln fot och cykel är inget alternativ på grund av långt avstånd och dåligt väder under andra vågor. Kohortstudier visar att många resenärer byter från bil till kollektivtrafiken när man resan till jobbet, hemmet och inför shoping om man jämför med hela länet. Växling från kollektivtrafiken till bil är mindre för resorna som måste betala skatt.Några sociala grupper anpassar sig annorlunda till trängselskatten. Kvinnor åker bil ner till 30 procent mindre än men. Orsak är kanske lägre personlig inkomst, men variabel hushållinkomst har mindre effekt. Fattiga hushåll andvänder  bil mycket mindre än rika hushåll, som åker bil mycket mer.Huvudbegränsningen av analysen är årstiderna och vädret,, som tillexempel ovanlig kallt väder under andra vågoen. Man kan inte förklara hela effekten därför att kontrollgruppen av har olika egenskaper.Examensarbetet  bättre kunskap hur trängselskatten påverkar beteendet av människor. Det möjliggör att kontrollera transportmodellerings resultat och visar att några variabler skulle användas om modellering skulle göras i annan region med en annan typ av  sammansättning av befolkning  än i Stockholm.</p>

abstract: Institutions of higher education, particularly those with large student enrollments, constitute special generators that contribute in a variety of ways to the travel demand in a region. Despite the importance of university population travel characteristics in understanding and modeling activity-travel patterns and mode choice behavior in a region, such populations remain under-studied. As metropolitan planning organizations continue to improve their regional travel models by incorporating processes and parameters specific to major regional special generators, university population travel characteristics need to be measured and special submodels that capture their behavior need to be developed. The research presented herein begins by documenting the design and administration of a comprehensive university student online travel and mode use survey that was administered at Arizona State University (ASU) in the Greater Phoenix region of Arizona. The dissertation research offers a detailed statistical analysis of student travel behavior for different student market segments. A framework is then presented for incorporating university student travel into a regional travel demand model. The application of the framework to the ASU student population is documented in detail. A comprehensive university student submodel was estimated and calibrated for integration with the full regional travel model system. Finally, student attitudes toward travel are analyzed and used as explanatory factors in multinomial logit models of mode choice. This analysis presents an examination of the extent to which attitudes play a role in explaining mode choice behavior of university students in an urban setting. The research provides evidence that student travel patterns vary substantially from those of the rest of the population, and should therefore be considered separately when forecasting travel demand and formulating transport policy in areas where universities are major contributors to regional travel. / Dissertation/Thesis / Doctoral Dissertation Civil Engineering 2014