This diploma thesis is concerned with the use of the choice experiment method for modelling travel behaviour. The main scope of this diploma thesis is to find the main attributes for the individual's decision making about the student's choice of mean of transport. The models have been applied to long intercity trips between Prague and Brno. The model specification combines trip-based characteristics with socioeconomic characteristics. There are numerous European and US studies which have been conducted in a national context. In recent years, studies have been implemented also in the Czech Republic, but none of them focus on the specific segment of students. The principles of the choice experiment come out from the Lancaster' characteristics theory of value and random utility theory. The multinominal logit is used to the choice experiment analysis.

The equity effect of congestion pricing has been advocated to be given enough concern for its acceptability. This thesis aimed to explore the mixed effects in travel behaviour changing caused by congestion charging in demography factors (social economic status) and context factors (location, flexibility, access to car and possession of long-term public transport card). In order to understand by what mechanisms congestion pricing affects the equity, structural equation modelling was applied to model the causal networks in the case study of Stockholm congestion charge. Results revealed a more complicated influence from different combination of factors. The location relative to charging cordon mattered for the trip-making both directly and indirectly through the transport mode preference. The work schedule flexibility should be also taken into consideration when considering the time-based scheme. The mixed effects between two groups of factors suggested that more factors should be considered when justifying the privileged group and disadvantaged group to implement the policy. The method used in this thesis could be very constructive for equity effect evaluation in other cities with different conditions.

Ethnicity and culture are increasingly considered in the study of travel behaviour given the global movement of people. Historically during apartheid in South Africa, there was not much leisure travel amongst the Black, Coloured and Indian population groups. This discrepancy became a focus of the National Department of Tourism’s (NDT) domestic policy after 1994 to encourage all South Africans to travel, explore and experience all facets of our beautiful rainbow country in real time. This study focuses on South African Indians (SAI) as there is limited knowledge of the drivers of travel behaviour amongst such minority populations. Pragmatic mixed methods are used to collect qualitative (focus groups) and quantitative (survey) data amongst SAI living in KwaZulu-Natal and Gauteng provinces. Findings suggest that there is already established domestic travel amongst the population. SAI have strong ethnic and cultural (Indian) identities that form a significant part of their decision-making; though not specifically having bearing on inter-provincial travel decisions. Of note is strong familial bonds extending beyond the nuclear family to their extended family members, influencing their travel behaviour. Other aspects include value for money, cuisine, safety and service. The study provides layered information presenting opportunities for future research. It also presents a profile of the market’s travel behaviour that can be useful for destination marketing authorities and travel trade in efforts to attract the SAI market. / Dissertation (MCom)--University of Pretoria, 2020. / Tourism Management / MSc / Unrestricted

What causes people to change their primary transportation mode and sustain the change in the absence of an incentive? Shifting towards sustainable modes is a vision shared by many municipal, regional, national and international bodies around the world, but it is difficult to change individuals’ behaviour, especially when there is no incentive to do so. Through understanding how individuals make decisions about their planned behaviour and determining what are opportune moments to re- learn travel habits, it may serve as a key opportunity to influence sustainable mode share. This study focuses on residential relocation to understand if the act of relocating serves as a catalyst to change transport behaviour. It further studies if car-lite developments under the Stockholm Green Parking Guidelines have impacted changes in travel behaviour towards more sustainable modes. By using surveys and interviews based on behavioural theory, it is possible to understand how individuals change their transport mode. The data collected also show how individuals may have a bias towards a particular transport mode and how policies can work to persuade them to choose another. The findings recommend measures to target programs for mode shift to the right people, at the right time to maximise effectiveness. They further recommend that proactive notification from information available in official databases can be used to implement this within the capabilities that currently exist in many jurisdictions. / Vad är det som får människor att ändra sitt primära transportsätt och upprätthålla förändringen trots avsaknad av incitament? Att övergå till mer hållbara transportsätt är en vision som delas av många kommunala, regionala, nationella och internationella organ runt om i världen men det är svårt att ändra individers beteende, särskilt när det inte finns något incitament till en förändring. Genom att förstå hur individer fattar beslut om sitt planerade beteende och att fastställa vilka tillfällen man som individ är mer öppen för att ta till sig nya resvanor, öppnas möjligheter för att påverka resvanor i en mer hållbar riktning. Denna studie fokuserar på individer som har bytt bostad, i syfte att förstå om flytten fungerar som en katalysator för ett förändrat transportbeteende. Den studerar vidare om utvecklingen mot ett minskat bilanvändande enligt riktlinjerna för Stockholms Gröna parkeringstal har skapat en förändring mot mer hållbara transportsätt. Genom att använda undersökningar och intervjuer baserade på beteendeteori är det möjligt att förstå hur individer ändrar sitt transportsätt. Uppgifterna som samlas in visar också hur individer kan ha en preferens för ett visst transportsätt och hur policyer kan arbeta för att övertyga dem att välja ett annat. Resultaten rekommenderar att man identifierar åtgärder för ett mer hållbart transportsätt och riktar in dessa till rätt personer vid rätt tidpunkt, i syfte att maximera effekten. De rekommenderar vidare att information tillgänglig i officiella databaser, och som är tillåten att användas inom dagens regelverk, kan användas för att implementera detta.

Bus is the main mode of urban transport in most cities in developing countries. Despite a high mode share, bus service quality is often poor and para-transit services are regarded as a problem in urban transport systems rather than a solution. Using Dhaka as a case study, this thesis investigates bus service quality through identification and valuation of thirteen important attributes using discrete choice models. The attributes examined are travel time, travel cost, waiting time, headway, priority seats for women, crowding inside the bus, boarding and alighting, picking up and dropping off passengers, bus stop facilities, driving quality, driver and crew behaviour, cleanliness inside the bus, and air conditioning. Five focus groups were conducted to identify key qualitative bus attributes and their levels in order to design choice experiments for valuation. A survey of 431 respondents in Dhaka was then undertaken. Two choice experiments were designed and implemented within the survey, each with seven attributes (set A and set B) with travel cost as the common attribute. Multinomial Logit (MNL) models and Mixed Logit (MXL) models were developed using the Dhaka choice data. Twelve of the thirteen attributes were statistically significant at the 99% level. The values of in-vehicle time (IVT), waiting time and headway were BDT 34.80, 47.40 and 64.20 per hour respectively for low income groups in the segmented model. Waiting time has a premium valuation, 1.36 times higher than IVT, which endorses existing evidence. The highest valuation is for the dummy variable seating all the way which is BDT 42.20 for high income females. The next largest was bus stops properly, picks and drops passengers nicely , followed by wide door and mild steps for boarding and alighting , smooth and safe journey , bus stop with shed, but no seating arrangements , and air conditioning . The lowest value was BDT 4.61 for deck and seats are clean and tidy , for the low income group. The WTP for the qualitative attributes is high, but given the poor level of the existing service and low fare levels this seems reasonable. Income has a significant impact on travel cost, as well as gender on priority seats for women and crowding inside the bus. However, household car ownership does not have a significant impact on any of the bus attributes examined. The high income group has 75% higher WTP for A set attributes and 79% higher WTP for B set attributes than low income group. Females have 76% higher WTP for standing comfortably all the way , but 38% higher WTP for seating all the way compared to the male. However, females have a WTP of BDT 0.44 for per percent of priority seats for women in contrast with males who have a WTP of BDT -0.11. There is significant taste heterogeneity for both quantitative and qualitative attributes. The qualitative attributes for picking up and dropping off passengers, boarding and alighting facilities and driving facilities have higher valuation and this attributes came from the existing within the market competition structure in a highly fragmented bus market. Therefore, it is recommended to introduce competition for the market and incentives for bus industry consolidation.

The basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This passive way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, system optimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.

The ‘hydrogen economy’ represents an energy system in which hydrogen and electricity are the dominant energy carriers for use in transportation applications. The ‘hydrogen economy’ minimizes the use of fossil fuels in order to lower the environmental impact of energy use associated with urban air pollution and climate change. An integrated energy system is required to deal with diverse and distributed energy generation technologies such a wind and solar which require energy storage to level energy availability and demand. A distributed ‘energy hub’ is considered a viable concept in envisioning the structure of an integrated energy system. An energy hub is a system which consists of energy input/output, conversion and storage technologies for multiple energy carriers, and would provide an interface between energy producers, consumers, and the transportation infrastructure. Considered in a decentralized network, these hubs would form the nodes of an integrated energy system or network. In this work, a model of a clean energy hub comprising of wind turbines, electrolyzers, hydrogen storage, a commercial building, and a fleet of plug-in fuel cell vehicles (PFCVs) was developed in MATLAB, with electricity and hydrogen used as the energy carriers. This model represents a hypothetical commercial facility which is powered by a renewable energy source and utilizes a zero-emissions fleet of light duty vehicles. The models developed herein capture the energy and cost interactions between the various energy components, and also calculate the CO2 emissions avoided through the implementation of hydrogen economy principles. Wherever possible, similar models were used to inform the development of the clean energy hub model. The purpose of the modelling was to investigate the interactions between a single energy hub and novel components such as a plug-in fuel cell vehicle fleet (PFCV). The final model reports four key results: price of hub electricity, price of hub hydrogen, total annual costs and CO2 emissions avoided. Three scenarios were analysed: minimizing price of hub electricity, minimizing total annual costs, and maximizing the CO2 emissions avoided. Since the clean energy hub could feasibly represent both a facility located within an urban area as well as a remote facility, two separate analyses were also conducted: an on-grid analysis (if the energy hub is close to transmission lines), and an off-grid analysis (representing the remote scenarios). The connection of the energy hub to the broader electricity grid was the most significant factor affecting the results collected. Grid electricity was found to be generally cheaper than electricity produced by wind turbines, and scenarios for minimizing costs heavily favoured the use grid electricity. However, wind turbines were found to avoid CO2 emissions over the use of grid electricity, and scenarios for maximizing emissions avoided heavily favoured wind turbine electricity. In one case, removing the grid connection resulted in the price of electricity from the energy hub increasing from $82/MWh to $300/MWh. The mean travel distance of the fleet was another important factor affecting the cost modelling of the energy hub. The hub’s performance was simulated over a range of mean travel distances (20km to 100km), and the results varied greatly within the range. This is because the mean travel distance directly affects the quantities of electricity and hydrogen consumed by the fleet, a large consumer of energy within the hub. Other factors, such as the output of the wind turbines, or the consumption of the commercial building, are largely fixed. A key sensitivity was discovered within this range; the results were ‘better’ (lower costs and higher emissions avoided) when the mean travel distance exceeded the electric travel range of the fleet. This effect was more noticeable in the on-grid analysis. This sensitivity is due to the underutilization of the hydrogen systems within the hub at lower mean travel distances. It was found that the greater the mean travel distance, the greater the utilization of the electrolyzers and storage tanks lowering the associated per km capital cost of these components. At lower mean travel distances the utilization of the electrolyzers ranged from 25% to 30%, whereas at higher mean travel distances it ranged from 97% to 99%. At higher utilization factors the price of hydrogen is reduced, since the cost recovery is spread over a larger quantity of hydrogen.

Recent research suggests that, besides traditional socio-demographic and built environment attributes, the attitudes and perceptions of parents toward walking and bicycling play a crucial role in deciding their children’s mode choice to school. However, very little is known about the factors that shape these parental attitudes toward their children actively commuting to school. The current study aims to investigate this unexplored avenue of research and identify the influences on parental attitudes toward their children walking and bicycling to school, as part of a larger nationwide effort to make children more physically active and combat rising trends of childhood obesity in the US. Through the use of a multivariate ordered response model (a model structure that allows different attitudes to be correlated), the current study analyses five different parental attitudes toward their children walking and bicycling to school, based on data drawn from the California add-on sample of the 2009 National Household Travel Survey. In particular, the subsample from the Los Angeles – Riverside – Orange County area is used in this study to take advantage of a rich set of micro-accessibility measures that is available for this region. It is found that school accessibility, work patterns, current mode use in the household, and socio-demographic characteristics shape parental attitudes toward children walking and bicycling to school. The study findings provide insights on policies, strategies, and campaigns that may help shift parental attitudes to be more favourable toward their children walking and bicycling to school. / text

This thesis jointly models the 24 hour work trip timing and mode choice decisions of commuters in the Greater Toronto Area. A discrete-continuous specification, with a multinomial logit model for mode choice and an accelerated time hazard model for trip timing, is used to allow for unrestricted correlation between these two fundamental decisions. Statistically significant correlations are found between mode choice and trip timing for work journeys with expected differences between modes. Furthermore, the joint models have a wide range of policy sensitive statistically significant parameters of intuitive sign and magnitude, revealing expected differences between workers of different occupation groups. Furthermore, the estimated models have a high degree of fit to observed cumulative departure and arrival time distribution functions and to observed mode choices. Finally, sensitivity tests have demonstrated that the model is capable of capturing peak spreading in response to increasing auto congestion.

This thesis jointly models the 24 hour work trip timing and mode choice decisions of commuters in the Greater Toronto Area. A discrete-continuous specification, with a multinomial logit model for mode choice and an accelerated time hazard model for trip timing, is used to allow for unrestricted correlation between these two fundamental decisions. Statistically significant correlations are found between mode choice and trip timing for work journeys with expected differences between modes. Furthermore, the joint models have a wide range of policy sensitive statistically significant parameters of intuitive sign and magnitude, revealing expected differences between workers of different occupation groups. Furthermore, the estimated models have a high degree of fit to observed cumulative departure and arrival time distribution functions and to observed mode choices. Finally, sensitivity tests have demonstrated that the model is capable of capturing peak spreading in response to increasing auto congestion.