Дисертації з теми "Passenger modelling"

Un modèle structurel est fourni afin d'appréhender les phénomènes de capacité dans un modèle d'affectation de flux de voyageurs sur un réseau de transport collectifs. Cela a été fondé sur une représentation du réseau de transports collectifs en deux couches : sur la couche inférieure, le modèle traite séparément chaque sous système du réseau (ligne, station et rabattement) en fonction des effets de capacité spécifiques ; sur la couche supérieure, le choix d'itinéraire d'un voyageur individuel est adressée par une représentation du réseau en leg (ou segment de ligne) en utilisant le coût et les caractéristiques opérationnelles des sous-systèmes respectifs. On établit une cadre novateur pour modéliser les effets de capacité et on développe le modèle CapTA (pour Capacitated Transit Assignment). Il s'agit d'un modèle d'affectation de flux systémique et modulaire. Il adresse les phénomènes de capacité ci dessous : La qualité du service en véhicule est liée au confort de voyageurs à bord. L'occupation d'états de confort hétérogènes (places assises, strapontins et debout à de densités de voyageurs variables) influence la pénibilité perçu du voyage ; La capacité du véhicule à la montée impacte le temps d'attente de voyageurs et leur distribution aux missions disponibles ; La capacité de l'infrastructure de la ligne établit une relation entre le temps de stationnement des véhicules (and par extension les flux de voyageurs en montée et en descente) et la performance des missions et leur fréquence de service. Ces phénomènes sont traités par ligne d'exploitation sur la base d'un ensemble des modèles locaux qui rendent de flux et de coût spécifiques. Par conséquent, ils modifient les conditions locales d'un trajet en transports collectifs pour chaque voyageur individuel. Cependant, ils doivent être adressés dans le cadre d'un réseau de transports collectifs afin de recueillir leur effet sur les choix d'itinéraire sur le réseau ; essentiellement sur les arbitrages économiques qui impactent le choix entre itinéraires alternatifs. Leur traitement sur la couche réseau garantir la cohérence du choix d'itinéraire. Le modèle de station traite de contraintes de capacité spécifiques et évalue les conditions locales de marche, qui est sensible aux interactions des voyageurs à l'intérieur de la station : le goulot instantané à l'entrée d'un élément de circulation retard l'évacuation de la plateforme ; la densité de voyageurs et l'hétérogénéité des leur flux ralenti les voyageurs qui circulent dans une station ; la présence de l'information en temps réel influence le processus de décision des voyageurs. Ces effets n'ont pas seulement un impact sur le choix d'itinéraire à l'intérieure de la station, mais notamment ils modifient les choix de service sur le niveau du réseau. La Région Ile-de-France fournit un champ d'application idéal pour un modèle d'affectation de flux de voyageurs en transport collectifs sous contraintes de congestion. Plus précisément, il est utilisé dans le cadre du modèle CapTA pour illustrer les capacités de simulation et la finesse de l'approche de modélisation adoptée. Le réseau de transports collectifs contient 1 500 missions de cars et autocars, tout comme 260 missions ferroviaires et inclut 14 lignes de métro et 4 lignes de tramway. L'affectation de trafic à l'heure de pointe du matin est caractérisée d'une charge importante en voyageurs sur les sections centrales de lignes ferroviaires qui traversent la ville. Un temps de stationnement élevé, en raison de flux de montée et descente, et la réduction de la fréquence de service impactent la capacité des missions et des lignes. Le temps généralisé d'un trajet est impacté notamment de sa composante de confort à bord. De résultats détaillés sont présentés sur le RER A, la ligne la plus chargée du réseau ferroviaire régional
A structural model is provided to capture capacity phenomena in passenger traffic assignment to a transit network. That has been founded on a bi-layer representation of the transit network : on the lower layer the model addresses each network sub-system (line, station and access-egress) separately, on the basis of specific capacity effects ; on the upper layer a leg-based representation is used with respect to the sub-systems' costs and operating characteristics to address the trip maker's path choices. We establish a novel framework for modelling capacity effects and develop the CapTA network model (for Capacitated Transit Assignment). It is systemic and modular and addresses in particular the following capacity phenomena, the in-vehicle quality of service is linked to the comfort of the passengers on-board. The occupation of heterogeneous comfort states (seats, folding seats and standing at different passenger densities) influences the perceived arduousness of the travel ; the vehicle capacity at boarding influences the waiting time of the passengers and their distribution to the transit services ; the track infrastructure capacity relates the dwelling time of the vehicles (and by extent the alighting and boarding flows) with the performance of the transit services and their service frequency. These phenomena are dealt with by line of operations on the basis of a set of local models yielding specific flows and costs. Accordingly, they modify the local conditions of a transit trip for each individual passenger. However, these should be addressed within the transit network in order to capture their effect on the network path choices; essentially the economic trade-offs that influence the choice between different network itineraries. Their treatment in a network level assures the coherence of the path choice. Equivalently, a station sub-model addresses specific capacity constraints and yields the local walking conditions, sensible to the interaction of the passengers in the interior of a station : the instant bottleneck created at the entry of the circulation elements delays the evacuation of the station platforms; the passenger density and presence of heterogeneous passenger flows slows down the passengers who circulate in the station; and the presence of real-time information influences the decision making process of the transit users exposed to. These effects do not only impact locally the in-station path choice, but most notably they modify the choices of transit routes and itineraries on a network level. The Paris Metropolitan Region provides an ideal application field of the capacity constrained transit assignment model. It is mainly used as a showcase of the simulation capabilities and of the finesse of the modelling approach. The transit network involves 1 500 bus routes together with 260 trains routes that include 14 metro lines and 4 light rail lines. Traffic assignment at the morning peak hour is characterized by heavy passenger loads along the central parts of the railway lines. Increased train dwelling, due to boarding and alighting flows, and reduction in the service frequency impact the route and the line capacity. The generalized time of a transit trip is impacted mainly though its in-vehicle comfort component. Detailed results have been provided for the RER A, the busiest commuter rail line in the transit network

Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations.
QC 20111201

This thesis describes the development of a computer simulation model for the investigation of airliner fire accident safety. The aim of the work has been to create a computer-based analysis tool that generates representative aircraft accident scenarios and then simulates their outcome in terms of passenger injuries and fatalities. The details of the accident scenarios are formulated to closely match the type of events that are known to have occurred in aircraft accidents over the last 40 years. This information has been obtained by compiling a database and undertaking detailed analysis of approximately 200 airliner fire accidents. In addition to utilising historical data, the modelling work has incorporated many of the key findings obtained from experimental research undertaken by the world's air safety community. An unusual feature of the simulation process is that all critical aspects of the accident scenario have been analysed and catered for in the formative stages of the programme development. This has enabled complex effects, such as cabin crash disruption, impact trauma injuries, fire spread, smoke incapacitation and passenger evacuation to be simulated in a balanced and integrated manner. The study is intended to further the general appreciation and understanding of the complex events that lead to fatalities in aircraft fire accidents. This is achieved by analysing all contributory factors that are likely to arise in real fire accident scenarios and undertaking quantitative risk assessment through the use of novel simulation methods. Future development of the research could potentially enable the undertaking of a systematic exploration and appraisal of the effectiveness of both current and future aircraft fire safety policies.

Bus bunching indicated the situation when two originally equally spaced bus services running close to each other as the earlier service runs increasingly late or the later service runs ahead. This phenomenon corresponds to bus services unreliability due to the extra passenger boarding, improper dispatching or travelling irregularity resulting in traffic congestions, for example. Bunched buses deteriorate passengers travel experience on public transport services that share the infrastructure with other travel modes. This has become a growing concern in big cities where traffic problems are common. It is challenging to improve the bus service reliability as a variety of chaotic sources, such as traffic congestion or unpredictable travel demand, can affect it. In order to understand the main influence factors of bus bunching in Sydney, this thesis first investigates in detail the bus service operations in Sydney and develops three passenger-oriented bus bunching mitigation approaches to improve the bus service reliability. The real picture of bus bunching in Sydney is scrutinised based on the Sydney bus system automatic vehicle location (AVL) field data. By developing the bus bunching distributions based on different criteria, such as stop location, the bus running direction, month, weekday, time and route number, bus bunching is observed to have a higher possibility in occurring during afternoon peak hours on weekdays in March and July. Additionally, buses with an outbound direction are more likely to be bunched. The ten most heavily-used bus routes with the highest number of bus bunching have also been identified using Sydney AVL data. It is observed that the overlapping routes and shared stops result in more bunches due to the interaction between buses. All the above findings have been used as the input for the simulation modelling. Second, we develop a discrete-event micro-simulation model of a bus service system with overlapping routes. The model tracks the number of passenger waiting at each bus stop as well as the amount of rider inside the vehicle of each running bus. The arrival of riders to stops are modelled as a random process while origin and destination of riders are then stored. With the input, as mentioned above, including the bus service schedule, bus stop locations, and the arrival information of riders, we have modelled Sydney's top 10 routes that have the highest number of bunches, assuming that the bus running speed follows the lognormal distribution. The lognormal distribution is determined by a historical bus running speed data fitting and each link's lognormal distribution parameter for running speed generating can be designated by a MATLAB program based on historical field data for each link. The proposed model offers waiting and in-vehicle time of each rider and can replicate the bus bunching situation in Sydney. To mitigate the number of bus bunching and reduce the unreliability of passengers travel time, we propose three control approaches in this study: (i) bus running speed management (ii) pre-planned limited-stop services (stop-skipping) and (iii) real-time boarding restrict approach. The first two approaches are associated with the planning-level control while the third is related to the operation-level bunching control. Bus running speed management method aims at identifying the links with a large number of bunching and equipping the links with the dedicated bus lane to increase the mean bus running speed and to reduce the variability of the bus running speed. This leads to a reduced likelihood of delays, and hence, mitigate the number of bus bunching. This control has considered minimizing the influence of other traffic modes on speed by selecting the least number of critical links in the network. Pre-planned limited-stop (stop-skipping) service applies as an express service in order to reduce the bus total travel time. The limited-stop pattern is rationalized by skipping the low-demand bus stops determined by historical data. This reduces total dwell time and total travel time, and then, the number of bus bunching. As a pre-planned control, passengers are assumed to be informed with all limited-stop services information, thus, none of the passengers would board on the limited-stop service at the low demand stops. Real-time boarding restrict control is a real-time control level method to reduce bus total dwell time by controlling the number of boarding. This approach is triggered when the headway between two buses is less than a pre-defined scheduled headway, in which the delayed bus will subsequently restrict passenger boarding while allow alighting only. Without passenger boarding, a decreasing number of in-vehicle passengers will alight at the following stop, which reduces the bus total running time and corrects the bus trajectory. Extensive numerical experiments have been carried out to analyse the control strategies using the developed model. The analysis results indicate that all of the control approaches achieve a high performance in reducing the number of bunching; bus running speed management and pre-planned stop-skipping methods also perform superior in reducing passenger travelling time; while real-time boarding restrict control, as a remedy method, have a better potential in steadying the passenger mean waiting time.

The ratification of the Paris agreement has motivated nations to investigate howsubstantial greenhouse gas emission reductions can be accomplished for limiting globalwarming under two degrees Celsius. In Sweden, the magnitude of CO2 emissionsfrom domestic transportation is approximately one third of all other emission sectorscombined. It is therefore crucial for Sweden to stimulate substantial reductions in thissector. Local actors' possibilities to contribute to climate change mitigation arecentral to succeed albeit constrained in the transportation sector due to data andresource limitations. With the intention to benefit local climate change mitigationwork, a model capable of estimating the tailpipe CO2 emissions from passenger carswas created. The modelling exploited traffic work data from mandatory vehiclechecks conducted in Sweden for calculating CO2 emissions per car and year for theperiod of 1999-2017, to thereafter be aggregated for a municipality, i.e. a bottom-upapproach. The model and model results have been validated with official data andemission factors from HBEFA, whereas model configurations have also beencontrolled with sensitivity analyses. The model was applied for a case-study, Järfälla, amunicipality who recently had a carbon budget developed. Model results illustrated anincreasing trend in CO2 emissions for the period of 1999-2017 and were alsopresented over fuel technology, mass and car age. Moreover, the model was appliedto produce CO2 estimates per postal codes in the municipality for 2017 and toquantify the effect of explorative scenarios, i.e. policy goals, on CO2 emissions.

This thesis investigates the influence of passenger group dynamics on passengers' behaviour in an international airport. A simulation model is built to analyse passengers' behaviour during airport departure processes and during an emergency event. Results from the model showed that passengers' group dynamics have significant influences on the performance and utilisation of airport services. The agent-based model also provides a convenient way to investigate the effectiveness of space design and service allocations, which may contribute to the enhancement of passenger airport experiences.

Redland Shire Council (RSC) has recently completed the preparation of Integrated Local Transport Plan (ILTP) and started its implementation and monitoring program. One of the major thrusts of the ILTP is to reduce the car dependency in the Shire and increase the shares of sustainable environmental-friendly travelling modes, such as walking, cycling and public transport. To achieve these objectives, a mathematical model is needed that is capable of modelling and forecasting the travelling mode choice behaviour in the multi modal environment of Redland Shire. Further, the model can be employed in testing the elasticity of various level-of-service attributes, under a virtual travel environment, as proposed in the ILTP, and estimating the demand for the new travelling alternatives to private car, namely the bus on busway, walking on walkway and cycling on cycleway. The research estimated various nested logit models for different trip lengths and trip purposes, using the data from a stated preference (SP) survey conducted in the Shire. A unique computer assisted personal interviewing (CAPI) instrument was designed, using both the motorised (bus on busway) and non-motorised travelling modes (walking on walkway and cycling on cycleway) in the SP choice set. Additionally, a unique set of access modes for bus on busway was also generated, containing hypothetical modes, such as secure park and ride facilities and kiss and ride drop-off zones at the busway stations, walkway and cycleway facilities to access the busway stations and a frequent and integrated feeder bus network within the Shire. Hence, this study created a totally new virtual travel environment for the population of Redland Shire, in order to record their perceived observations under these scenarios and develop the mode choice models. From the final model estimation results, it was found that the travel behaviour forecasted for regional trip-makers is considerably different from that of local trip-makers. The regional travellers for work, for instance, were found not to perceive the non-motorised modes as valid alternatives to car, possibly due to longer trip lengths. The value of time (VoT) determined for local work trip-makers (16.50 A$/hr) was also found to be higher than that of regional work trip-makers (11.70 A$/hr). From the survey analysis, a big part of the targeted population was found to be car captives, who are not likely to switch from cars to public transport; even if a more efficient transit infrastructure is implemented. In the past, the models have been generally calibrated using the mode choice survey data only, while that of the captive users were ignored. This yields a knowledge gap in capturing the complete travel behaviour of a region, since the question of what particular biases can be involved with each model estimation parameter by the captives remain unresolved. In this research, various statistical analyses were performed on the car captive users' data by categorising them into various trip characteristics and household parameters, in order to infer the relative influence of the car captive population on the travel behaviour of the study area. The outcomes of the research can assist the policy makers in solving the strategic issues of transit planning, including the future development of a busway corridor, with an efficient transit access mode network. The research findings can also be utilised in evaluating the feasibility of developing walkways and cycleways in the Shire, along with appraising the relative influence of car captive users on the travel behaviour forecasts for the study area.

Redland Shire Council (RSC) has recently completed the preparation of Integrated Local Transport Plan (ILTP) and started its implementation and monitoring program. One of the major thrusts of the ILTP is to reduce the car dependency in the Shire and increase the shares of sustainable environmental-friendly travelling modes, such as walking, cycling and public transport. To achieve these objectives, a mathematical model is needed that is capable of modelling and forecasting the travelling mode choice behaviour in the multi modal environment of Redland Shire. Further, the model can be employed in testing the elasticity of various level-of-service attributes, under a virtual travel environment, as proposed in the ILTP, and estimating the demand for the new travelling alternatives to private car, namely the bus on busway, walking on walkway and cycling on cycleway. The research estimated various nested logit models for different trip lengths and trip purposes, using the data from a stated preference (SP) survey conducted in the Shire. A unique computer assisted personal interviewing (CAPI) instrument was designed, using both the motorised (bus on busway) and non-motorised travelling modes (walking on walkway and cycling on cycleway) in the SP choice set. Additionally, a unique set of access modes for bus on busway was also generated, containing hypothetical modes, such as secure park and ride facilities and kiss and ride drop-off zones at the busway stations, walkway and cycleway facilities to access the busway stations and a frequent and integrated feeder bus network within the Shire. Hence, this study created a totally new virtual travel environment for the population of Redland Shire, in order to record their perceived observations under these scenarios and develop the mode choice models. From the final model estimation results, it was found that the travel behaviour forecasted for regional trip-makers is considerably different from that of local trip-makers. The regional travellers for work, for instance, were found not to perceive the non-motorised modes as valid alternatives to car, possibly due to longer trip lengths. The value of time (VoT) determined for local work trip-makers (16.50 A$/hr) was also found to be higher than that of regional work trip-makers (11.70 A$/hr). From the survey analysis, a big part of the targeted population was found to be car captives, who are not likely to switch from cars to public transport; even if a more efficient transit infrastructure is implemented. In the past, the models have been generally calibrated using the mode choice survey data only, while that of the captive users were ignored. This yields a knowledge gap in capturing the complete travel behaviour of a region, since the question of what particular biases can be involved with each model estimation parameter by the captives remain unresolved. In this research, various statistical analyses were performed on the car captive users' data by categorising them into various trip characteristics and household parameters, in order to infer the relative influence of the car captive population on the travel behaviour of the study area. The outcomes of the research can assist the policy makers in solving the strategic issues of transit planning, including the future development of a busway corridor, with an efficient transit access mode network. The research findings can also be utilised in evaluating the feasibility of developing walkways and cycleways in the Shire, along with appraising the relative influence of car captive users on the travel behaviour forecasts for the study area.

In this thesis a novel approach to modelling passenger response to disruption on metro rail networks is developed, consisting of a two step process using smart-card data to produce disaggregate models expressed in terms of individual response behaviours. The work is carried out in the context of the London Underground, using a full snapshot of the Oyster smart-card travel histories of all passengers in conjunction with records of all incidents to occur on the network during the study time period. The combination of two key factors differentiates this work from existing studies in this area: the model is built on a large, passively collected dataset (smart-card data), but is expressed in a disaggregate form in terms of the actual actions taken by passengers, rather than the aggregate overall changes to the origin-destination flows. The conceptual framework underlying this work considers a three step process. First, incidents occur on the metro rail network causing disruption to train services, which consequently affects passengers using those services. Second, on experiencing disruption to their journeys, passengers may continue with them as planned, or may take a number of actions in an attempt to mitigate the effects of the disruption that they experience, such as changing to a different mode of transport or abandoning their journey altogether. Finally, using fare-collection smart-card data, it is possible to observe these responses in the individual travel histories of passengers. This thesis first presents a qualitative investigation into passenger response to disruption, with the dual objectives of confirming the assumptions of the conceptual framework and identifying the set of actions passengers take when their journeys are disrupted. The subsequent quantitative investigation is expressed in terms of this set of behaviours. The next stage consists of the development of a heuristic process to identify instances of those behaviours in a smart-card travel history dataset, in conjunction with the transport operator’s logs of the incidents which occurred during the same time period. Finally, a series of models of individual passenger response to disruption are developed from the data produced by the heuristic process. These models serve two purposes. The first is to understand the impact of a range of explanatory variables related to the passengers and the incidents on the response behaviours exhibited, for which the logistic regression family of models is used due to its easily interpretable coefficients. The second is to provide predictive modelling of the response behaviours, which imposes no requirement of model interpretability, allowing the logistic regression models to be compared with a range of black box machine learning classifiers. The initial qualitative investigation identified six behaviours exhibited by passengers in response to disruption: “carry on regardless”, “abandon journey”, “change time of travel”, “change origin or destination”, “change mode of transport” and “change route”. The first five of these can be identified from the available data sources through the heuristic behaviour extraction process. The logistic regression models identified a number of patterns, the most distinctive of which include an increase in the relative probabilities of the “change” behaviours over “carry on” as the incident length increases, an increase in the relative probabilities of “change origin/destination” and “abandon journey” as passenger average household income increases, and a corresponding substantial decrease in the relative probability of “change to bus” also as passenger household income increases. Significant evidence of individual heterogeneity in response behaviours was also identified. Overall model predictive performance was similar between the logistic regression models and a number of the investigated machine learning classifiers.

Transportation infrastructure has long been recognized as the sine qua non of rapid economic development. As a predominantly agrarian economy with a vast and growing population spread over an extensive mass of land, India presents a veritable case of this truism, sadly by the lack of it. Notwithstanding the vagaries of development in other sectors, the transport sector in India, ironically, has received scant attention over five decades of the planning era, which has lent itself to lop-sided development in favour of the railways. Though deregulation and attendant economic reforms have augmented transport services by air and road in the last decade, the inadequacy of transport infrastructure and the acute paucity of resources to fulfil the provision of the same have been the bane of problems confronting the government. Privatization as a solution to circumvent resource constraints has raised new issues of social and environmental equity, which transcends the immediate concerns of infrastructure development. As is evident, though the solutions to the problems of the transport sector are multifarious, they emphasize the imperative need for rational and integrated transport planning and policy. A cursory look at the problems plaguing this sector also reveals that the issues and concerns cannot be dealt with in its entirety. Against this background, we confine ourselves to the study of the passenger transport sector and attempt to address an interesting and increasingly apparent phenomenon of travel behaviour, namely intermodal choice and modal substitution. The genesis of this study was an earlier work done by a research team at the Centre for Mathematical Modelling and Computer Simulation (C-MMACS), NAL, where in, a general methodology to describe the growth of the transport sector in India was developed in terms of appropriate mathematical models. Significantly most of the variables describing demand, supply and performance were found to trend exponentially. However, the models failed to reflect the trends in intermodal substitution and its significance in evaluating future transport demand. For example, the development or availability of alternative means like rail or personalized vehicles may influence the demand for bus transport. Similarly demand for air transport may be a function of comparative advantages presented by alternatives like upper class rail travel. This phenomenon is observed to be pronounced on short-haul routes characterizing inter-city travel, where such modes are extremely competitive. We consider a regional network of high-density routes in southern India, as a representation of several such transport networks across the country, to study this phenomenon and its implications for future policy. The primary objective of this study is to develop and evaluate a set of econometric models that would adequately measure the extent of intermodal substitution in passenger transport on short-haul routes (inter-city travel) and, critically evaluate the factors that affect travel choice in a multimodal environment. Toward this, the study is divided into three parts. Part one focuses on understanding broad trends in air, rail and road travel, for the routes in consideration. Suitable regressions are estimated to measure the effect of critical transport variables on route-wise travel demand. The coefficients are estimated separately for two categories of travel - First Class and Second Class. Part two of the study is based on data collected from individual travel surveys on the route network. A simplified questionnaire was used for this purpose. We use the traditional logit framework to estimate choice probabilities based on user perceptions about factors affecting their choices. As in the previous case, we estimate the logits for both classes of travel, viz. First Class and Second Class, under the equal substitutability assumption. We also estimate the logits for the general case for the sake of comparison, though not practicable. Part three involves a case-study of an alternative high-speed rail link for one of the routes in the network having the highest traffic density, to illustrate its effect on travel choice in a multimodal transport network. We also demonstrate the feasibility of the project using a benefit-cost approach. From the results, it is observed that substitution is predominantly from air to rail for "first-class" travel, and from rail to road for "second-class" travel. Besides, it is also observed that travel choice is largely influenced by non-price (fare) considerations. The value of travel time is estimated for both categories of travel, using the trade-off method and is found to be significantly different. All regressions show a high and the coefficients are significant at the 5% level. The logit analysis validates the earlier conclusion that non-price (fare) factors influence the demand for different modes. It is found that users attach considerable importance to comfort and convenience, including time of travel, while making travel choices. It is also observed that the logits vary significantly when factors are grouped, and further, between categories of travel In the case of the high-speed link, we estimate that there will be a significant shift in travel demand from air to rail and also from road to rail, given substantial travel time savings. The estimates of passenger revenue and decongestion benefits also provide a strong rationale for the implementation of the project. Sources of data include published and unpublished records of Indian Airlines, Indian Railways and State Road Transport Undertakings (SRTUs) on air, rail and road travel respectively. Data on population and other macroeconomic variables were obtained from census records and similar statistical publications. An important feature of this study is its attempt to bridge the macro and micro policy environments. It is one of the first attempts to study the dynamics of travel demand and choice behaviour in a multimodal regional transport network in India. Unlike previous studies, it transcends the realm of urban transport economics and extends its scope to the study of regional transport characteristics, where inter-city passenger travel has undergone significant changes both in environment and behaviour in the last decade. The entire study has been conceptualized in a system dynamics framework to describe its relevance to overall transport planning. It is believed that such an exercise would be a precursor for the development of a full-fledged macroeconomic model of the transport sector in India.

In traditional aircraft wing structural design, the emphasis has been on pursuing the minimum weight or improved performance. The manufacturing complexity or cost assessments are rarely considered because it is usually assumed that the minimum weight design is also the minimum cost design. However, experience from industry has shown that this is not necessarily the case. It has been realised that in the cases where no manufacturing constraints are imposed, the extra machining cost can erode the advantages of the reduced weight. As manufacturing cost includes material cost and machining cost, whilst reducing weight can reduce the material cost, if the manufacturing complexity increases greatly as a result the overall cost may not go down. Indeed, if the manufacturing complexity is not checked, the machining cost could increase by more than the amount by which the material cost reduces. To enable the structural manufacturing complexity to be controlled, manufacturing constraints are established in this thesis and integrated into the optimisation of the aircraft wing structural design. As far as the manufacturing complexity is concerned, attention has been paid to both 3-axis and 5-axis machining. The final designs of optimisations with manufacturing constraints prove the efficiency of these constraints in guiding the design in the manufacturing-feasible direction.

This research identifies highly congested areas in Bus Rapid Transit (BRT) platforms and apply measures to improve Quality of Service and capacity. It developed a novel model that partitioned BRT platforms into cells and examined passenger activities to evaluate variation in area available per passenger across the platform. It was identified that areas available for stationary and circulating passengers in a platform cell differed significantly. BRT platform operation during the COVID-19 pandemic was evaluated. Significant variations exist in waiting passenger distributions between the Before COVID-19 and During COVID-19 cases.

During the 1990s, governments, managements and unions have been focused upon improving the cost efficiency of firms. This focus has been strongest for firms in the public sector where improved outcomes can be expected to significantly improve the Gross Domestic Products of whole economies. This case study looks at the cost efficiency of NSW rail passenger services over a 41 year period to 1991/92, long suspected (but hitherto only tentatively demonstrated) as a paradigm of cost inefficiency. The case study focuses upon the use of the total factor productivity (TFP) index, as a datum point for measuring change in productivity in four markets: suburban, internrban, country and interstate passenger services since 1951/52. From this datum, changes over the years in management, technology and other external factors can be identified and assessed. The thesis identifies management quality (the organising element in the firm) as the preeminent factor in determining productivity change, and the role that new technology plays in its impact on failures in management. We establish the linkages between management and innovation, with TFP, pricing efficiency and economic resource use efficiency, to present a rich paradigm for assessing the economic performance of any business firm. Borrowing from systems theory and other management practices such as total quality management, we disaggregated the case firm into its component systems, sub-systems and processes, for separate study in relation to impact on TFP. The database for 41 years of rail behaviour is the richest ever compiled for any railway in Australia, and with enhanced modelling, enables a systematic treatment of the performance through time of State Rail's passenger services.

Doctor of Philosophy
During the 1990s, governments, managements and unions have been focused upon improving the cost efficiency of firms. This focus has been strongest for firms in the public sector where improved outcomes can be expected to significantly improve the Gross Domestic Products of whole economies. This case study looks at the cost efficiency of NSW rail passenger services over a 41 year period to 1991/92, long suspected (but hitherto only tentatively demonstrated) as a paradigm of cost inefficiency. The case study focuses upon the use of the total factor productivity (TFP) index, as a datum point for measuring change in productivity in four markets: suburban, internrban, country and interstate passenger services since 1951/52. From this datum, changes over the years in management, technology and other external factors can be identified and assessed. The thesis identifies management quality (the organising element in the firm) as the preeminent factor in determining productivity change, and the role that new technology plays in its impact on failures in management. We establish the linkages between management and innovation, with TFP, pricing efficiency and economic resource use efficiency, to present a rich paradigm for assessing the economic performance of any business firm. Borrowing from systems theory and other management practices such as total quality management, we disaggregated the case firm into its component systems, sub-systems and processes, for separate study in relation to impact on TFP. The database for 41 years of rail behaviour is the richest ever compiled for any railway in Australia, and with enhanced modelling, enables a systematic treatment of the performance through time of State Rail's passenger services.

This master thesis investigates and analyzes the energy use for traction and auxiliary equipment in passenger rail vehicles. It covers both the train service with passengers and when the trains are going through other stages in the everyday operation. The operational cycle and associated operational situations are introduced as a way of describing the varying use of a train over time. The descriptions focus on the most common activities and situations, such as stabling and parking, regular cleaning, inspections and maintenance. Also how these situations affect energy use by their need for different auxiliary systems to be active. An energy model is developed based on the operational cycle as a primary input, together with relevant vehicle parameters and climate conditions. The latter proving to be a major influence on the energy used by the auxiliary equipment. The model is applied in two case studies, on SJ's X55 and Västtrafik's X61 trains. Both are modern electric multiple units equipped with energy meters. Model input is gathered from available technical documentation, previous studies and by measurements and parameter estimations. Operational cycle input is collected through different planning systems and rolling stock rosters. Climate input is finally compiled from open meteorological data banks. The results of the case studies show that the method and models are useful for studying the energy used by the trains in their operational cycles. With the possibility to distinguish the energy used by the auxiliary equipment, both during and outside the time the trains are in service with passengers. With this it's also possible to further investigate and study potential energy saving measures for the auxiliary equipment. Simulations of new ventilation control functions and improved use of existing operating modes on the trains show that considerable energy savings could be achieved with potentially very small investments or changes to the trains. The results generally show the importance of a continued investigation of the auxiliary equipment's energy use, as well as how the different operational situations other than the train service affect the total energy use.
Detta examensarbete utreder och analyserar energianvändningen för passagerarjärnvägsfordons traktion- och hjälpkraftssystem, både under tågdriften med passagerare och andra delmoment som tågen genomgår under den normala dagliga driften. För detta introduceras driftcykeln och tillhörande driftsituationer som ett sätt att beskriva användningen av ett tåg över tiden. Syftet är att beskriva de vanligast förekommande aktiviteterna och situationerna, såsom uppställning och parkering, regelbundna inspektioner, klargörningar och underhåll. Även hur dessa situationer påverkar energianvändningen genom ett varierande behov av hjälpkraft och aktiva funktioner i tågen. En energimodell baserad på driftcykeln som huvudsaklig indata, tillsammans med tågets egenskaper samt det omgivande klimatet, tas fram. Klimatet visar sig vara en avgörande faktor i hjälpkraftens energianvändning. Modellen utvärderas i typstudier på SJs X55 och Västtrafiks X61. Båda är elektriska motorvagnståg utrustade med energimätare. Indata till modellen samlas in genom tillgänglig teknisk dokumentation, tidigare studier och genom mätningar samt parameterestimering. Driftcyklerna för tågtyperna sammanställs med hjälp av olika planeringssystem och omloppsplaner. Väder- och klimatdata samlas slutligen in från öppna databaser för metrologiska data. Resultaten från typstudierna visar att metoden och modellerna är användbara verktyg för att kunna beskriva tågens energianvändning i deras driftcykler. Med möjligheten att särskilja hjälpkraftssystemens energianvändning vid tågdriften med passagerare men även i de övriga situationerna. Med detta blir det också möjligt att undersöka potentiella energibesparingsåtgärder för hjälpkraftssystemen. Simulering av förbättrade styrfunktioner för ventilationen och förbättrat utnyttjade av redan inbygga energibesparande driftlägen på tågen visar att betydande energibesparingar kan fås med relativt små medel och få förändringar på fordonen. De sammantagna resultaten av arbetet visar på vikten av att fortsätta undersöka och utreda hjälpkraftens energianvändning samt hur driftsituationerna utanför tågdriften med passagerare påverkar den totala energianvändningen.

The subject of this thesis is the investigation of multibody system modelling and control analysis techniques for the development of advanced suspension systems in passenger cars. A review of the application of automatic control to all areas of automotive vehicles illustrated the important factors in such developments, including motivating influences, constraints and methodologies used. A further review of specific applications for advanced suspension systems highlighted a major discrepancy between the significant claims of theoretical performance benefits and the scarcity of successful practical implementations. This discrepancy was the result of idealistic analytical studies producing unrealistic solutions with little regard for practical constraints. The predominant application of prototype testing methods in implementation studies also resulted in reduced potential performance improvements. This work addressed this gap by the application of realistic modelling and control design techniques to practical realistic suspension systems. Multibody system modelling techniques were used to develop vehicle models incorporating realistic representations of the suspension system itself, with the ability to include models of the controllers, and facilitate control analysis tasks. These models were first used to address ride control for fully active suspension systems. Both state space techniques, including linear quadratic regulator and pole placement and frequency domain design methods were applied. For the multivariable frequency domain study, dyadic expansion techniques were used to decouple the system into single input single output systems representing each of the sprung mass modes. Both discretely and continuously variable damping systems were then addressed with a range of control strategies, including analytical solutions based on the active results and heuristic rule-based approaches. The controllers based on active solutions were reduced to satisfy realistic practical limitations of the achievable damping force. The heuristic techniques included standard rule-based controllers using Boolean logic for the discretely variable case, and fuzzy logic controllers for the continuously variable case.

This thesis investigates the possible future pathways for the road transportation sector of Cyprus, in a time horizon from the year 2013 to 2040. The road transportation sector of Cyprus is the most energy consuming sector in the country, completely dependent on the use of diesel and gasoline. In order to comply with the renewable energy target for the transportation sector set by the European Union, Cyprus needs to transform its road transportation sector. The software MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impact) is used to model the road transport sector, consisting of passenger and freight transportation. The results of the modelling provides insights into the most cost-effective pathways for Cyprus in the future. In addition to the reference scenario, four different scenarios are examined. These scenarios are focusing on different relevant aspects for Cyprus which are renewable energy, natural gas, public transport and hydrogen. The results of the study indicate that the total numbers of petroleum fueled vehicles will increase in the future, and the freight transport will be particularly difficult to transform. For the passenger transport, there will be a fuel switch from gasoline to diesel, since diesel is less expensive than gasoline. There are possibilities for increasing the numbers of alternative low-carbon emitting vehicle technologies in Cyprus. For the passenger transport, the most cost-effective low-carbon vehicle technologies are hybrid diesel electric cars, plug-in hybrid diesel electric cars and hybrid electric diesel buses. For the freight transport, the most cost-effective low-carbon vehicle technologies are natural gas heavy trycks and electric light trucks. Lastly, the results of the study indicate that it will not be possible for Cyprus to reach the renewable energy target for the transportation sector. The country has to investigate in taxation schemes for increasing the numbers of alternative vehicles as well as increasing the blends of biofuels into gasoline and diesel.

Evacuation modelling technology offers designers and regulators of aircraft new opportunities to rigorously test designs and theories. However, before evacuation models can be used effectively they need to be understood by the regulatory and aviation industry, validated and developed further. This thesis tackles each of these aspects. This thesis provides a detailed review of evacuation modelling with special emphasis on aviation evacuation models and the available data upon which models and understanding can be based. Of these the airEXODUS model is selected for this thesis and it is described in detail and critically evaluated. The evaluation revealed three main issues that needed to be addressed in order for aircraft evacuation modelling to advance. These issues relate to, (1) the limited quantity of model verification, (2) the inability of models to represent crew procedures, and (3) the limited behavioural capabilities of these models with regard to simulating real accidents as opposed to certification scenarios. The fundamental accuracy and predictive capability of airEXODUS is evaluated. This is followed by a comprehensive investigation of cabin crew and passenger behaviour in 90-second certification trials and real emergency evacuations. The conclusions from this investigation serve as the basis for the development of new algorithms to addresses issues (2) and (3). Behavioural algorithms are developed to simulate cabin crew bypass in conjunction with algorithms for passengers exit choice and methods for simulated passengers to optimise their chosen route to an exit. Finally, this thesis concludes by demonstrating the value of evacuation modelling in the design of future aircraft, the regulation of current aircraft and in understanding some of the contributing factors involved in past evacuation related disasters.

This thesis contributes to the area of integrated management of outbound and inbound passenger flows at an international airport terminal for optimal utilisation of resources with maximum comfort to the passengers. The main goal of this research is to develop a holistic model based on the combination of simulation, airport resource management algorithms and analytical optimisation approaches. This model provides an important step forward in the development of a fully-fledged holistic decision support tool. The model can be used for strategic and operational requirements for multi-terminal International/Domestic.

One of the benefits of electric vehicles (EVs) and hybrid vehicles (HVs) is their potential to recuperate braking energy. Regenerative braking (RB) will minimize duty levels on the brakes, giving advantages including extended brake rotor and friction material life and, more significantly, reduced brake mass and minimised brake pad wear. In this thesis, a mathematical analysis (MATLAB) has been used to analyse the accessibility of regenerative braking energy during a single-stop braking event. The results have indicated that a friction brake could be downsized while maintaining the same functional requirements of the vehicle braking in the standard brakes, including thermomechanical performance (heat transfer coefficient estimation, temperature distribution, cooling and stress deformation). This would allow lighter brakes to be designed and fitted with confidence in a normal passenger car alongside a hybrid electric drive. An approach has been established and a lightweight brake disc design analysed FEA and experimentally verified is presented in this research. Thermal performance was a key factor which was studied using the 3D model in FEA simulations. Ultimately, a design approach for lightweight brake discs suitable for use in any car-sized hybrid vehicle has been developed and tested. The results from experiments on a prototype lightweight brake disc were shown to illustrate the effects of RBS/friction combination in terms of weight reduction. The design requirement, including reducing the thickness, would affect the temperature distribution and increase stress at the critical area. Based on the relationship obtained between rotor weight, thickness and each performance requirement, criteria have been established for designing lightweight brake discs in a vehicle with regenerative braking.

This thesis presents an investigation of braking system characteristics, brake system performance and brake system component design parameters that influence brake pedal force / displacement characteristics as ‘felt’ by the driver in a passenger car. It includes detailed studies of individual brake system component design parameters, operation, and the linear and nonlinear characteristics of internal components through experimental study and simulation modelling. The prediction of brake pedal ‘feel’ in brake system simulation has been achieved using the simulation modelling package AMESim. Each individual brake system component was modelled individually before combining them into the whole brake system in order to identify the parameters and the internal components characteristics that influence the brake pedal ‘feel’. The simulation predictions were validated by experimentally measured data and demonstrated the accuracy of simulation modelling. Axisymmetric Finite Element Analysis (using the ABAQUS software) was used to predict the behaviour of nonlinear elastomeric internal components such as the piston seal and the booster reaction disc which was then included in the AMESim simulation model. The seal model FEA highlighted the effects of master cylinder and caliper seal deformation on the brake pedal ‘feel’. The characteristics of the brake booster reaction disc were predicted by the FEA and AMESim simulation modelling and these results highlighted the importance of the nonlinear material characteristics, and their potential contribution to brake pedal ‘feel’ improvement. A full brake system simulation model was designed, prepared, and used to predict brake system performance and to design a system with better brake pedal ‘feel’. Each of the brake system component design parameters was validated to ensure that the braking system performance was accurately predicted. The critical parameter of brake booster air valve spring stiffness was identified to improve the brake ‘pedal ‘feel’. This research has contributed to the advancement of automotive engineering by providing a method for brake system engineers to design a braking system with improved pedal ‘feel’. The simulation model can be used in the future to provide an accurate prediction of brake system performance at the design stage thereby saving time and cost.

Les réseaux de transport multimodaux modernes sont essentiels pour la durabilité écologique et l’aisance économique des agglomérations urbaines, par conséquent aussi pour la qualité de vie de leurs habitants. D’ailleurs, le bon fonctionnement sur le plan de la compatibilité entre les différents services et lignes est essentiel pour leur acceptation, étant donné que (i) la plupart des trajets nécessitent des changements entre les lignes et que (ii) des investissements coûteux, dans le but de créer des liens plus directs avec la construction de nouvelles lignes ou l’extension de lignes existantes, ne sont pas à débattre. Une meilleure compréhension des interactions entre les modes et les lignes dans le contexte des transferts de passagers est ainsi d’une importance cruciale. Toutefois, comprendre ces transferts est singulièrement difficile dans le cas de situations inhabituelles comme des incidents de passagers et/ou si la demande dévie des plans statistiques à long terme. Ici le développement et l’intégration de modèles mathématiques sophistiqués peuvent remédier à ces inconvénients. À ce propos, la supervision via des modèles prévoyants représente un champ d’application très prometteur, analysée ici. La supervision selon des modèles prévoyants peut prendre différentes formes. Dans le présent travail, nous nous intéressons à l’analyse de l’impact basé sur des modèles de différentes actions, comme des départs en retard de certains véhicules après un arrêt, appliqué sur le fonctionnement du réseau de transport et sa gestion de situations de stress qui ne font pas partie des données statistiques. C’est pourquoi nous introduisons un nouveau modèle, un automate hybride avec une dynamique probabiliste, et nous montrons comment ce modèle profondément mathématique peut prédire le nombre de passagers dans et l’état de fonctionnement du véhicule en question du réseau de transport, d’abord par de simples estimations du nombre de tous les passagers et la connaissance exacte de l’état du véhicule au moment de l’incident. Ce nouvel automate réunit sous un même regard les passagers demandeurs de services de transport à parcours fixes ainsi que les véhicules capables de les assurer. Il prend en compte la capacité maximale et le fait que les passagers n’empruntent pas nécessairement des chemins efficaces, dont la représentation sous la forme d’une fonction de coût facilement compréhensible devient nécessaire. Chaque passager possède son propre profil de voyage qui définit un chemin fixe dans l’infrastructure du réseau de transport, et une préférence pour les différents services de transport sur son chemin. Les mouvements de véhicules sont inclus dans la dynamique du modèle, ce qui est essentiel pour l’analyse de l’impact de chaque action liée aux mouvements de véhicule. De surcroît, notre modèle prend en compte l’incertitude qui résulte du nombre inconnu de passagers au début et de passagers arrivant au fur et à mesure. Comparé aux modèles classiques d’automates hybrides, notre approche inspirée du style des réseaux de Pétri ne requiert pas le calcul de ces équations différentielles à la main. Ces systèmes peuvent être dérivés de la représentation essentiellement graphique d’une manière automatique pour le calcul en temps discret d’une prévision. Cette propriété de notre modèle réduit le risque de précisions faites par des humains et les erreurs qui en résulteraient. Après avoir introduit notre nouveau modèle, nous développons dans ce rapport également quelques éléments constitutifs sous la forme d'algorithmes qui visent les deux types d'impasses qui sont probables d'occurir pendant la simulation faisant un pronostic, c-à-d l'intégration numérique des systèmes de haute dimension d'équations différentielles et l'explosion combinatoire de son état discret. En plus, nous prouvons la faisabilité des calculs et nous montrons les bénéfices prospectifs de notre approche dans la forme de quelques tests simplistes et quelques cas plus réalistes
Without any doubt, modern multimodal transportation systems are vital to the ecological sustainability and the economic prosperity of urban agglomerations, and in doing so to the quality of life of their many inhabitants. Moreover it is known that a well-functioning interoperability of the different modes and lines in such networked systems is key to their acceptance given the fact that (i) many if not most trips between different origin/destination pairs require transfers, and (ii) costly infrastructure investments targeting the creation of more direct links through the construction of new or the extension of existing lines are not open to debate. Thus, a better understanding of how the different modes and lines in these systems interact through passenger transfers is of utmost importance. However, acquiring this understanding is particularly tricky in degraded situations where some or all transportation services cannot be provided as planned due to e.g. some passenger incident, and/or where the demand for these scheduled services deviates from any statistical long term-plannings. Here, the development for and integration of sophisticated mathematical models into the operation of such systems may provide remedy, where model-predictive supervision seems to be one very promising area of application which we consider here. Model-predictive supervision can take several forms. In this work, we focus on the model-based impact analysis of different actions, such as the delayed departure of some vehicle from a stop, applied to the operation of the considered transportation system upon some downgrading situation occurs which lacks statistical data. For this purpose, we introduce a new stochastic hybrid automaton model, and show how this mathematically profound model can be used to forecast the passenger numbers in and the vehicle operational state of this transportation system starting from estimations of all passenger numbers and an exact knowledge of the vehicle operational state at the time of the incident occurrence. Our new automaton model brings under the same roof, all passengers who demand fixed-route transportation services, and all vehicles which provide them. It explicitly accounts for all capacity-limits and the fact that passengers do not necessarily follow efficient paths which must be mapped to some simple to understand cost function. Instead, every passenger has a trip profile which defines a fixed route in the infrastructure of the transportation system, and a preference for the different transportation services along this route. Moreover, our model does not abstract away from all vehicle movements but explicitly includes them in its dynamics, which latter property is crucial to the impact analysis of any vehicle movement-related action. In addition our model accounts for uncertainty; resulting from unknown initial passenger numbers and unknown passenger arrival flows. Compared to classical modelling approaches for hybrid automata, our Petri net-styled approach does not require the end user to specify our model's many differential equations systems by hand. Instead, all these systems can be derived from the model's predominantly graphical specification in a fully automated manner for the discrete time computation of any forecast. This latter property of our model in turn reduces the risk of man-made specification and thus forecasting errors. Besides introducing our new model, we also develop in this report some algorithmic bricks which target two major bottlenecks which are likely to occur during its forecast-producing simulation, namely the numerical integration of the many high-dimensional systems of stochastic differential equations and the combinatorial explosion of its discrete state. Moreover, we proof the computational feasibility and show the prospective benefits of our approach in form of some simplistic test- and some more realistic use case

The purpose of this this report was to find the sources that led to the deviation between the simulation and measurement on the ride comfort evaluation of a high-speed train. This report consists of a literature study, introduction of the train where the measurement was taken on, result analysis and sensitivity test of the secondary suspension. The literature study focused on the modelling of secondary suspensions and the simulation of rail vehicles. The predicted results were compared with the measured results. Furthermore, comparison was carried out among three different secondary suspension concepts. The secondary suspensions went through a sensitivity test to see how the parameters influence the ride comfort evaluation of the rail vehicle.It was figured out that the main deviation between the simulation and the measurement was focused on a carbody where a hydraulic damper was introduced. The difference was mainly at 1.3Hz and between 7.5Hz and 9Hz.With the main deviations figured out, the sources that might influence the ride comfort evaluation was tested. It showed that the detail of track measurement had influence on the ride comfort evaluation. More detailed measurement should be carried out if higher agreement is wanted. The secondary suspensions went through a sensitivity test. The key parameters and their influence on ride comfort evaluation was pointed out. This report can be a guidance if further tuning on the parameters of the secondary suspensions are needed.

As with many other nations, the passenger motor vehicle industry has long been central to the economic health of Australia. In addition, the purchase of a motor vehicle is a commitment of considerable magnitude to most consumers. As a result, the passenger motor vehicle industry has attracted the attention an interest of a wide and diverse range of groups who have brought to bear a multitude of often-conflicting concerns and interests. Nowhere has this been more apparent that in the development and execution of industry policy. This thesis examines the development and application of Australian passenger motor vehicle industry policy from the turn of the twentieth century until the mid-1990s.

D. Phil. (Energy Studies)
Quantifying energy consumed and emissions produced by transport is essential for effective policy formulation and urban environmental management. Current first-world methods for determining vehicle emissions factors are technology and resource intensive, and results cannot be applied directly to cities in other parts of the world. There is a need for alternative cost-effective and accurate methods for determining real-world fuel consumption and emissions from vehicles in cities of the developing world. In this thesis, a new emissions simulation and inventory model is developed and implemented as a software tool. A novel application of low cost on-board diagnostics equipment and Global Positioning System sensors is devised to survey engine-operating parameters, driving conditions and vehicle usage profiles needed by the model. An emissions inventory is produced for the City of Johannesburg using the software tool and surveying method to demonstrate the overall process. The core contribution of this thesis is the logical development of data structures and software tools which link base engine-operating patterns (of engine speed and engine load), derived from the literature, to measured engine-operating patterns and vehicle activity from real-world driving. A range of real-world driving cycles and emission factors published by the Swiss Institute of Materials Science and Technology are transformed to produce the base engine-operating patterns and their corresponding emissions factors. The calculation of emission factors for real-world driving involves matching measured engineoperating patterns to combinations of the base engine-operating patterns using numerical methods. The method is validated using a cross validation technique. The emissions inventory application integrates measured engine-operating patterns, vehicle activity, fleet structure, fuel sales and the emissions simulation procedure to calculate total emissions. Fuel consumption and emissions of interest are CO2, CO, HC, NOx. Measurements of engine operating parameters and vehicle usage patterns were recorded for 30 privately owned passenger vehicles from the Johannesburg fleet. The selection included Euro-0 (a mixture of pre Euro-1 vehicles), Euro-2 and Euro-3 petrol vehicles, and Euro-2 diesel private passenger vehicles. Fifteen billion vehicle kilometres were driven in Johannesburg by private passenger vehicles per year consuming 325 million litres of diesel and 1 524 billion litres of petrol. iv Total emissions were estimated to be 4.13 Mt CO2, 82.77 kt CO, 9.15 kt HC, and 24.49 kt NOx. Between 88 and 93% of the total emissions were from vehicles which fall into the Euro-0 petrol category. Diesel vehicles did not make a significant contribution to CO and HC emissions but contributed 14% of the NOx and 19% of the CO2 emissions. During weekdays, 28 to 31% and 25 to 27% of the total fuel consumption and emissions were due to the morning commute and the evening commute periods respectively. Although minibus taxis, buses, freight and vehicle age significantly impact on total fuel consumption and emissions in cities they were not considered within the scope of this study. Vehicle usage patterns are analysed to produce spatial maps and diurnal charts of congestion on suburban roads, streets and highways within the Johannesburg municipal area. Times and locations of congestion are presented in terms of a standard congestion index, and suggestion given on how and where congestion problems could be addressed. This study shows that vehicle emissions inventories can be cost effectively produced by surveying engine-operating parameters and vehicle usage profiles using on-board diagnostics and Global Positioning System sensors and simulating emissions factors using a new emissions simulation and emissions inventory model.

Motion Sickness (MS) is an issue of most transportation systems. Several countermeasures to this problem in cars are proposed in the literature, but most of them are qualitative, behavioural or involving complex chassis systems. Autonomous Driving (AD) can exacerbate the problem of MS due to the change from driver to passenger with the consequent loss of control over the vehicle. With the growing interest in self-driven vehicles, the issue of MS may be so important as to undermine their benefits in terms of increased productivity; not addressing this issue may limit the users’ acceptance reducing the safety and the environmental impact of autonomous vehicles. In this thesis, the issue of carsickness is discussed, analysing the potential technologies to monitor MS in cars and discussing their feasibility. After the analysis of the monitoring technologies, in the final part of the manuscript, the issue of reducing MS in cars is analysed, proposing optimal methods for carsickness reduction. To optimise the vehicle behaviour, two Model Predictive Control (MPC) problems are formulated to analyse the potential impact in different applications of optimal MS reduction techniques. The first task is to find the optimal speed profile to travel on a given path while trading-off between minimal travel time and minimal Motion Sickness Incidence (MSI); in this part, several strategies are proposed and analysed comparing their performance. This novel methodology may be used in autonomous cars to create a reference velocity profile for lower control layers or, in human-driven ones, to advise the driver. The second task applies only to autonomous vehicles, implementing the MS optimisation in the motion planning layer; a trajectory optimisation problem is solved using the best performing strategies of the optimal speed profile task. The results show that optimising vehicle behaviour may significantly reduce the MSI, improving the user experience in cars; furthermore, the wider possibilities offered by autonomous cars allow for further reduction of MSI. The optimal methodologies proposed and the strategies used are the main contribution of this doctoral thesis; the coherency of the results in the different cases analysed suggests that these strategies have a general validity for MS reduction. In the conclusions chapter, the impact of these methods is discussed; possible ways of integrating MS monitoring technology into the proposed reduction techniques are analysed.

Yes
The paper presents a text analytics framework that analyses online reviews to explore how consumer-perceived negativity corresponding to the supply chain propagates over time and how it affects car sales. In particular, the framework integrates aspect-level sentiment analysis using SentiWordNet, time-series decomposition, and bias-corrected least square dummy variable (LSDVc) – a panel data estimator. The framework facilitates the business community by providing a list of consumers’ contemporary interests in the form of frequently discussed product attributes; quantifying consumer-perceived performance of supply chain (SC) partners and comparing the competitors; and a model assessing various firms’ sales performance. The proposed framework demonstrated to the automobile supply chain using a review dataset received from a renowned car-portal in India. Our findings suggest that consumer-voiced negativity is maximum for dealers and minimum for manufacturing and assembly related features. Firm age, GDP, and review volume significantly influence car sales whereas the sentiments corresponding to SC partners do not. The proposed research framework can help the manufacturers in inspecting their SC partners; realising consumer-cited critical car sales influencers; and accurately predicting the sales, which in turn can help them in better production planning, supply chain management, marketing, and consumer relationships.
The full-text of this article will be released for public view at the end of the publisher embargo on 21 Oct 2022.