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Efforts to improve urban bus transport systems' comfort and increase user satisfaction have been made for many years across the globe. Increasing bus users and reducing car users has an economic benefit. Whenever the urban bus share is larger than 25%, there are journey time savings due to lower congestion levels on the network. A driver's loss of alertness due to fatigue has been recognised to be one of the major factors responsible for road accidents/crashes for many decades. Comfort and fatigue are psychophysiological phenomena. Objective measures of human psychological and physiological factors must be defined, investigated, and evaluated in order to have an indepth understanding of the cause-effect mechanisms regulating psychophysiological factors. Electroencephalography (EEG) developed as bio-sensor equipment to interpret and collate bioelectrical signals was used to gather the time-series quantitative data of urban bus passengers and HGV drivers. This study's EEG data application was designed to link the brain activity dynamics to dynamic experimental design variables or tasks by correlating increased or decreased measured brain activity by using a baseline for comparisons. Two experiments were conducted in this study. The first sought to understand the influence of driving time and rest breaks on a driver's psychophysiological response. Therefore, the EEG data was collected, categorised and grouped based on two hours of driving before a 30 minute break, two hours of driving after a 30 minute break and four hours of driving with no break. The Samn-Perelli seven-point scale of fatigue assessment was used to evaluate the influence of the duration of driving time on a driver's performance decrements. The second experiment investigated bus passenger discomfort by examining experimental design stage-related changes in EEG measured by using a control experiment for comparison. Consequently, datasets in two stages were collected for each subject (passenger), including the stationary laboratory (control) and dynamic onboard bus environment experiments. A subjective evaluation of the average ride comfort on each stage of the experiments was conducted by using the recommended assessment scale of the International Standard ISO 2631-1. The ERP EEG oscillations were evaluated by decomposing the EEG signals into magnitudes and phase information, and then characterising their changes relative to the experimentally designed phases and variables. A two-way analysis of variance (ANOVA) was conducted to test the model's predictor under different experimental conditions for passenger discomfort and driving fatigue experiments. Efforts to improve urban bus transport systems' comfort and increase user satisfaction have been made for many years across the globe. Increasing bus users and reducing car users has an economic benefit. Whenever the urban bus share is larger than 25%, there are journey time savings due to lower congestion levels on the network. A driver's loss of alertness due to fatigue has been recognised to be one of the major factors responsible for road accidents/crashes for many decades. Comfort and fatigue are psychophysiological phenomena. Objective measures of human psychological and physiological factors must be defined, investigated, and evaluated in order to have an indepth understanding of the cause-effect mechanisms regulating psychophysiological factors. Electroencephalography (EEG) developed as bio-sensor equipment to interpret and collate bioelectrical signals was used to gather the time-series quantitative data of urban bus passengers and HGV drivers. This study's EEG data application was designed to link the brain activity dynamics to dynamic experimental design variables or tasks by correlating increased or decreased measured brain activity by using a baseline for comparisons. Two experiments were conducted in this study. The first sought to understand the influence of driving time and rest breaks on a driver's psychophysiological response. Therefore, the EEG data was collected, categorised and grouped based on two hours of driving before a 30 minute break, two hours of driving after a 30 minute break and four hours of driving with no break. The Samn-Perelli seven-point scale of fatigue assessment was used to evaluate the influence of the duration of driving time on a driver's performance decrements. The second experiment investigated bus passenger discomfort by examining experimental design stage-related changes in EEG measured by using a control experiment for comparison. Consequently, datasets in two stages were collected for each subject (passenger), including the stationary laboratory (control) and dynamic onboard bus environment experiments. A subjective evaluation of the average ride comfort on each stage of the experiments was conducted by using the recommended assessment scale of the International Standard ISO 2631-1. The ERP EEG oscillations were evaluated by decomposing the EEG signals into magnitudes and phase information, and then characterising their changes relative to the experimentally designed phases and variables. A two-way analysis of variance (ANOVA) was conducted to test the model's predictor under different experimental conditions for passenger discomfort and driving fatigue experiments.The variability in the driver's psychophysiological responses to the duration of driving occurs systematically. The effects appear to be progressive and aligned such that the driving performance was worst during the last 60 minutes of driving for four hours without a break, but better during the first 30 minutes. Data analysis also showed that a pronounced psychophysiological response exists relative to the influence of the road roughness characteristics, the passenger's postures, and the bus type. Further analysis of passenger discomfort showed that passengers are more strained while in a standing posture than in a seated posture, irrespective of the bus type and the degree of the road's roughness. The results indicated that passenger comfort deteriorates as the road roughness coefficient increases. Furthermore, the results demonstrated that female passengers express more discomfort/dissatisfaction than males under the same experimental conditions. Therefore, female passengers are more sensitive than males to a deviation from optimal comfort conditions.This study provides opportunities for future research applications of EEG in transport research studies. It also provides a platform for evaluating different Intelligent Transport System (ITS) technologies, particularly passenger's reactions in autonomous vehicles.

The last two decades have witnessed a rising research interest in integrated choice and latent variable (ICLV) modelling, in direct response to the inability of the traditional choice models to adequately explain the over half a century growing trend of vehicular traffic in cities around the world. With little variations, several researchers in transport choice behaviour have suggested that the theory behind the traditional choice models do not sufficiently account for the heterogeneity of human behaviour and observed choice preferences. Literature is replete with evidence suggesting that attitudes and perceptions significantly influence decision-making. The challenge for researchers is understanding the attitude with the most significant impact to include in the hybrid choice models. Interestingly, recent literature on consumer behaviour suggests that MINDSPACE have a significant impact on behaviour. MINDSPACE is the mnemonic for Messenger, Incentive, Norms, Default, Salience, Priming, Affect, Commitment, and Ego, these behavioural effects are believed to offer robust way of analysing and influencing behaviour. This study, therefore, exploits the potential benefits of these two new research areas to develop MINDSPACE enriched ICLV model to explain the underlying transport mode choice behaviour of the population of Edinburgh using five hundred responses collected in a mail-back revealed preference survey. The proposed model integrates variables from the MINDSPACE framework as latent variables in the ICLV model. The study found strong evidence aside the socio-demographic and mode specific variables that Norm, Salience, and Affect have a significant influence on transport mode choice, among others. Overall, the ICLV model demonstrates considerable improvement over a reference logit model. The study could prompt policy development toward urban transportation because the findings have broader policy implication for public transport and travel behaviour change.

Driver behaviour has become an important aspect of transport research and over the years a considerable number of car following models have been developed. However, many of these models do not accurately simulate actual driving behaviour due to a lack of suitable qualitative and quantitative data. Moreover, the inclusion of socioeconomic variables in the existing models to ascertain the effect on car following behaviour is lacking. This research underlines the need to further investigate driving behaviour and car following models and to develop techniques to provide a better understanding of driver-vehicle interactions during car following. It investigates data collection techniques and develop better techniques to enhance and improve the collection of microscopic driver behaviour and traffic flow data. This study developed a novel data collection technique which involved instrumenting a private vehicle with front and rear advanced radar sensors, both forward and rear facing video-audio recorders connected to GPS based time series speed and distance measurement devices, an in-vehicle computer logging vehicle speed and a CAN monitoring interface user program to provide real time monitoring and display of data. This system has been utilised to collect a more enhanced and reliable microscopic driver behaviour data in three consecutive vehicles movements which represents an improvement from previously used systems. Three different versions of the GHR car following model were produced for: car following car, truck following car and car following truck. Further analysis of the GHR model showed that in the case of car following car, car drivers responses to the lead car are more obviously stronger than in the case of truck following a car. A distance-based car following model and distance-based two-leader car following model that predict the safe following distance of following vehicles were developed to provide a better understanding of driver behaviour. An extension of these models to include gender, corridor (road) type and vehicle occupancy showed evidence of statistical significance of these variables on driver behaviour. A bus following model that predicts the “following distance” also has been calibrated to describe the interactions between a bus and a car within urban-rural driving conditions. In addition, data analysis showed that drivers were inconsistent with their driving behaviour and that there was variability in driving behaviour across the drivers observed in keeping a safe or desired following distance. This study provides a platform for a number of future research agendas including data collection techniques for collection of driver behaviour data; evaluation of different ITS technologies; impact assessment of ACC on driver safety and improvement of traffic microscopic simulation tools in order to strengthen their ability to simulate realistic transport problems for efficient and effective transportation systems.

The growing fatality of road traffic accidents in most cities constitutes a public health challenge. Annually, about 1.24 million people are killed from road accidents, among which more than one fifth of these deaths occur among pedestrians. Pedestrian collisions are even more prevalent in cities that host mass gathering events such as the Hajj. Yet this phenomenon has been neglected within the existing literature. Correspondingly, this research examines the relationship between pilgrims' pedestrian casualties and the land use type in Madinah. The relationship between the land use and pedestrian casualty was determined from pilgrims pedestrian casualty data (N=2204) from 2001 to 2005 supplied by the Madinah Police Department. The accident data is characterized by the personal and socio-demographic attributes of the victims as well as the land use type of the accident. The significant findings from this study show that male pilgrims were over represented in pedestrian casualty in Madinah. This is consistent with other road accident studies in Arab-Muslim countries which also recorded higher male casualty compared to female. Again, more men embark on pilgrimage than their female counterpart. Young pilgrim (12-20's) pedestrians suffer the most casualties; while the least casualty was recorded for child pilgrim pedestrians (<12). In terms of day of the week, the high casualty occurs on Friday which is an important day for prayer that usually cause high incident of traffic and over-crowdedness. Though almost three-quarter of the pilgrim pedestrians sustained their casualties during high season months as most Moslem pilgrims embarks on pilgrimage during this period. However, most pilgrims' pedestrians suffer casualty during non-praying time because during prayer time, most of them would either be in the Mosque or residence fulfilling their obligation to pray, thereby, making them less exposed to pedestrian-vehicle collisions. In modelling the relationship between pilgrims' pedestrians and land use type, quasi-Poisson regression models fitted the accident data better than Negative Binomial regression models. Most of the models developed indicate strong association between pilgrims' pedestrian casualties and commercial and religious land use types. For the major land use types, fatalities were more prevalent in the commercial and religious land use types. In terms of road type, the highest iii casualties occurred on single carriageway-2 lanes and mostly on roads around the Holy site. Whilst the results indicate that there is a greater number of accidents occurring in proximity to junctions or close to T,Y or staggered junctions categories taken together, the large single category of accidents occurred ‘not at junction or within 20 metres of junction. Nevertheless, majority of coefficients for road type and junction details variables were insignificant. Main findings from this research are discussed and suitable recommendations are made to assist policy makers in proffering countermeasures to will help improve safety and reduce accidents. One of the main findings of this research is that the serious accident pattern indicates the need for improved pedestrian facilities for pilgrims. This is the major outcome of the modelling and the analysis in general.

Traffic congestion today is a major problem in almost all of the metropolitan areas of the world. An increasing level of congestion results in negative impacts on the urban environment. These include environmental pollution, energy problems and traffic accidents. The analysis of these problems and the predictions of the impacts of any transport policies that could be devised to deal with them are very critical to their success. Traffic problems are almost the same in most modern cities either in developed countries or less economically developed countries. The driving cycle for a vehicle is the representation of a speed–time sequenced profile, which is developed for a specific area or city. It is an important requirement in the evaluation of the driver's behaviour and the performance of vehicles for a number of applications, mainly in the area of environmental studies. For example, fuel consumption and emissions' predictions need information input on the characteristics of driving patterns of traffic. The applications of driving cycle analysis can be extended however, to many more other areas. The motivation for this research is to investigate the detailed impacts of travel demand management (TDM) measures, that are already in application. This is to improve the network performance, using driving cycle analysis. It is important to explicitly assess these measures using a micro-level detailed approach in order to comprehend overall results in terms of emissions and network performance. These understandings will benefit government agencies and policy makers in their planning and appraisals. It will also benefit public transport providers to improve their service in attracting and retaining their customers. The developments of the real world driving cycles in Edinburgh and Abu Dhabi have been presented in this research. The analysis of real world data, which has been obtained from monitoring traffic conditions in both cities using the GPS tracking of traffic, is presented. This data was collected from trips which have been carried out on a number of traffic corridors in both cities. The assessment of various parameters of traffic (i.e. speed, time percentage spent on acceleration, deceleration, idling, cruising and cycle duration) and their statistical validity, produced a real world driving cycle for the buses as well as the private cars. Two TDM measures have been considered; bus lanes and traffic calming measures. At each corridor, a handheld GPS device was used to record speed, acceleration, deceleration and distances driven. This data enabled the analysis of driving cycles for the buses and for the private cars. The driving cycle analysis and investigations have further been investigated using regression analysis techniques. The results suggest that the approach shows potential but further research is needed with more data available. The results suggest that the driving cycle analysis approach would be very useful to have a better understanding of driving behaviour and also the detailed impacts of the transport policies on traffic. In terms of bus lanes and traffic calming measures, the results show some positive impacts of these policies, while there are evidences of some negative impacts as well. These findings would be very valuable for the policy decision makers. It is recommended from this research that the driving cycle analysis could be utilised effectively in the assessment of TDM measures. Further investigations and analysis of driving cycle is urgently recommended in a number of research directions. Combined GIS and GPS data could also enhance the development in this research.

The review of available literature related to pedestrian accidents indicates that the occurrence of pedestrian accidents is influenced by a diverse range of factors. However, few empirical studies have documented the effects of distance of pedestrian accidents from pedestrian crossing area or junction. The few studies which investigated the impact of the distance from the crossing line on pedestrian accidents, suggest that the longer the distance from road crossing facilities, the higher the likelihood of a pedestrian accident. With respect to the influence of the type of pedestrian crossing on the incidence of pedestrian accidents, a substantial body of literature has found that the types of pedestrian crossing indeed affect the frequency of pedestrian collisions. Additionally, all the available studies reviewed indicated the positive impact of signalised crossings on the reduction of pedestrian collision risk. Data from STATS19 show that pedestrian severity rates are higher over the pedestrian crossing points or within 50 meters of pedestrian crossing facilities than those away from it. This is contrary to the expectations that accidents should be least over these crossing facilities. This study investigates in more detail the factors that affect accident occurrence at signalised pedestrian junction and pelican or similar type of crossing facilities in the Scotland area. The main objective of this current research has been to investigate those factors most commonly associated with pedestrian injury severity at a pedestrian crossing or within 50m of one. Accident data of 14 years (from 1993 until 2006) in selected sites show that 942 pedestrian accidents occurred on or within 50m of a signalised pedestrian crossing area. Grid references of accident locations as well as locations of pedestrian crossings were obtained from the STATS 19 database and the local city council. The data was used to identify the locations of accidents relative to the location of pedestrian crossing facilities. In terms of severity of injuries models, results suggest that pedestrians from the older group received more severe injuries, compared with those from younger groups. Again, this finding underlines the importance of regulations and subsequent enforcement of traffic laws that protect and promote the safety of older pedestrians. The models also showed an association between the severity of injury and the type of pedestrian crossing. Since more KSI accidents have been associated with pelican crossings, there may be a need to undertake raising awareness and education for pedestrians to improve pedestrian safety. In terms of ROW models; it was shown that turning manoeuvres were more likely to violate pedestrian's ROW and result in accidents than other types of manoeuvres. Moreover, the model showed that heavy-goods vehicles and cars are associated with pedestrian's ROW, as compared to other types of vehicles. The various issues related to accidents resulting from pedestrian right-of-way can be effectively resolved by rationalisation of pedestrian crossing types; and provision of education with regards to the rules and responsibilities of both pedestrians and drivers at all available crossings. The models developed to profile pedestrian accidents in Edinburgh suggest that the highest number of pedestrian accidents occurred at pedestrian crossing lines; and that the number of pedestrian accidents decreased when moving away from pedestrian crossing lines or within 50 metres of pedestrian crossing lines. These have serious implications in terms of requiring improvements to pedestrian crossing facilities that can then ensure better pedestrian visibility and provide the public with more protection from moving vehicles. Moreover, another implication of this finding is that more regulatory instruments must be revalidated and further developed, since there are no laws to prevent pedestrians from crossing the road at certain points. The only laws being enforced in the UK are those relating to the prohibition of walking on motorways or slip roads but not regarding loitering on pedestrian crossings. Therefore, the guidelines specified in the Highway Code to deal with pedestrian behaviour while crossing the road have to be revisited and further developed. The results show that accidents rates decrease as distance increase from the pedestrian crossing facilities. The most risky locations are those at the pedestrian crossings or within 10 meters and the distance from 10 to 30 meters before the pedestrian crossing facilities. Analysis of pedestrian accidents rates and severities for each of pelican and signalised crossings were discussed. An investigation of right-of-way violations associated with pedestrian accidents at pedestrian crossing areas or within 50 metres of the same was carried out. Modelling accidents rates and severities at these pedestrian crossings is also presented in this thesis. Multinomial logit, ordinal and probit logit and binary logit modelling are used to analyse the results.