This thesis attempted to provide a detailed theoretical understanding of the effects of task-induced fatigue on simulated driving performance. Previous research has shown that duration of driving has only a weak effect on driving performance. A series of studies were conducted to examine how fatigue effects interact with task demands, and to explore the psychological changes associated with fatigue. The research also explored links between fatigue and stress in terms of their affective reactions and the coping mechanisms which are central to them. The first phase of the research consisted of a series of simulated studies of fatigue. The first study developed an experimental paradigm to examine both task-specific and aftereffects of fatigue on driving performance. The findings showed that fatigue effects interacted with task demands such that drivers' lateral control of the vehicle and trajectory were impaired during low demand rather than in high demand driving episodes. The study also showed that the fatigue state is a multidimensional state which is principally characterised by a reduction in motivation. The second and third studies attempted to explore the role of motivational mechanisms in fatigue-related impairments. This phase of the research showed that impairments in low demand driving conditions may be reduced by enhancing the driver's motivational state. The fourth study explored the development of subjective fatigue in two types of task-induced fatigue. The study showed that there is a dissociation between subjective and objective fatigue. The second phase of the research examined the links between stress and fatigue in simulated and real-life driving environments. The studies showed that stress and fatigue are similar states but there are particular features which make them distinct states. The results from simulated and real-life driving environments showed a high degree of consistency.

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Adverse weather conditions can increase travel risk. Understanding how drivers react to adverse weather, such as rainfall, can aid in the understanding of road safety patterns and traffic operations. This information can in turn be used to improve driver education as well as highway operation through improved signing or the introduction of intelligent highway systems. Hourly rainfall data collected from the Pearson International Airport weather station and City of Toronto traffic data collected at the study site on the Gardiner expressway were used to create event and control pairs. In total, 115 hours with rainfall were matched to control data one week before or after the rainfall event. The traffic sensor at the study site collected speed, volume, and occupancy data at 20-second intervals, which was aggregated to five minutes. In addition, speed deviation and headway data at the 5-minute interval were used for analysis purposes. Two methods were used to test the effects of rainfall on traffic variables and the relationships between them. Matched pair t-tests were used to determine the magnitude of change between event and control conditions for the volume, speed, speed deviation, and headway variables for congested and uncongested traffic conditions. In addition, stepwise multiple linear regression was used to test the effects of rainfall on speed-volume and volume-occupancy relationships. Results of the matched pair t-tests indicated that volumes, speeds, and speed deviations dropped in event conditions, while headways increased slightly. Changes tended to be greater for congested than uncongested conditions. Linear regression results indicated that changes in speed were sensitive to volume conditions, and changes in volume were sensitive to occupancy, although only to a limited extent. Overall, drivers respond to rainfall conditions by reducing both speed and speed deviations, and increasing headway. Reductions in speed are larger in congested conditions, while increases in headway are smaller. Taken in combination, drivers are taking positive steps in order to either maintain or improve safety levels.

Adverse weather conditions can increase travel risk. Understanding how drivers react to adverse weather, such as rainfall, can aid in the understanding of road safety patterns and traffic operations. This information can in turn be used to improve driver education as well as highway operation through improved signing or the introduction of intelligent highway systems. Hourly rainfall data collected from the Pearson International Airport weather station and City of Toronto traffic data collected at the study site on the Gardiner expressway were used to create event and control pairs. In total, 115 hours with rainfall were matched to control data one week before or after the rainfall event. The traffic sensor at the study site collected speed, volume, and occupancy data at 20-second intervals, which was aggregated to five minutes. In addition, speed deviation and headway data at the 5-minute interval were used for analysis purposes. Two methods were used to test the effects of rainfall on traffic variables and the relationships between them. Matched pair t-tests were used to determine the magnitude of change between event and control conditions for the volume, speed, speed deviation, and headway variables for congested and uncongested traffic conditions. In addition, stepwise multiple linear regression was used to test the effects of rainfall on speed-volume and volume-occupancy relationships. Results of the matched pair t-tests indicated that volumes, speeds, and speed deviations dropped in event conditions, while headways increased slightly. Changes tended to be greater for congested than uncongested conditions. Linear regression results indicated that changes in speed were sensitive to volume conditions, and changes in volume were sensitive to occupancy, although only to a limited extent. Overall, drivers respond to rainfall conditions by reducing both speed and speed deviations, and increasing headway. Reductions in speed are larger in congested conditions, while increases in headway are smaller. Taken in combination, drivers are taking positive steps in order to either maintain or improve safety levels.

To improve the safety and comfort of intelligent vehicles, advanced driver models offer promising solutions. However, several shortcomings of these models prevent them from being widely applied in reality. To address these shortcomings, advanced artificial intelligence algorithms in conjunction with the sufficient driving environmental factors are proposed based on real-life driving data. More specifically, three typical problems will be addressed in this thesis: Mandatory Lane Changing (MLC) suggestion at the highway entrance; Discretionary Lane Changing (DLC) intention prediction; Car-Following gap model considering the effect of cuts-in from the adjacent lanes. For the MLC suggestion system, in which the main challenges are efficient decision making and high prediction accuracy of both non-merge and merge events, an additional gated branch neural network (GBNN) is proposed. The proposed GBNN algorithm not only achieves the highest accuracy among conventional binary classifiers in terms of great performance on the non-merge accuracy, the merge accuracy, and receiver operating characteristic score but also takes less time. For the DLC, we propose a recurrent neural network (RNN)-based time series classifier with a gated recurrent units (GRU) architecture to predict the surrounding vehicles’ intention. It can predict the surrounding vehicles’ lane changing maneuver 0.8 s in advance at a recall and precision of 99.5% and 98.7%, respectively, which outperforms conventional algorithms such as the Hidden Markov Model (HMM). Finally, drivers are typically faced with two competing challenges when following a preceding vehicle. A method is proposed to address the problem through an overall objective function of car-following gap and velocity. Based on this, seeking the strategic car-following gap translates to finding the optimal solution that minimizes the overall objective function. With the support of field data, the method along with concrete models are instantiated and the application of the method is elaborated. / Thesis / Doctor of Philosophy (PhD) / Lane changing and car following are the two most frequently encountered driving behaviours for intelligent vehicles. Substantial research has been carried out and several prototypes have been developed by universities as well as companies. However, the low accuracy and high computational cost prevent the existing lane changing models from providing safer and more reliable decisions for intelligent vehicles. In the existing car-following models, there are also few models that consider the effects of cut-ins from adjacent lanes which may result in their poor accuracy and efficiency. To address these obstacles, advanced artificial intelligence algorithms combined with sufficient driving environmental factors are proposed due to their promise of providing accurate, efficient, and robust lane changing and car-following models. The main part of this thesis is composed of three journal papers. Paper 1 proposed a gated branch neural network for a mandatory lane changing suggestion system at the on-ramps of highways; paper 2 developed a recurrent neural network time-series algorithm to predict the surrounding vehicles’ discretionary lane changing intention in advance; paper 3 researched the strategic car-following gap model considering the effect of cut-ins from adjacent lanes.

Doctor of Philosophy / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / Centerline rumble strips (CLRS) are effective in preventing cross-over crashes and are promoted in the United States (U.S.) as a low-cost safety measure. However, there may be negative issues and/or concerns that question their use under certain road conditions. This dissertation is the result of studying these issues and concerns to provide guidance to policy makers on future installations of CLRS, based on current good practices and on the results of specific investigations of exterior noise, safety effectiveness, economics, and drivers’ behavior, including their interaction with shoulders and shoulder rumble strips (SRS). From a survey conducted, good practices in the U.S. were summarized. From a before-and-after study of CLRS safety effectiveness, results showed that total correctable crashes were reduced by 29.21%. Crashes involving fatalities and injuries were reduced by 34.05%. Cross-over crashes were reduced by 67.19%, and run-off-the-road crashes were reduced by 19.19%. Both Naïve and Empirical Bayes methods were applied and showed statistically similar results. There was no statistical difference between football shaped and rectangular shaped CLRS. From the external noise study performed, it was found that external noise depends on vehicle speed, type of vehicle, and distance. Both football and rectangular CLRS substantially increased the levels of external noise at distances up to 45 m (150 ft). Therefore, before installing CLRS, the distance from houses or businesses should be considered. A distance of 60 m (200 ft) was recommended as the limit of the potential exterior noise problem area. From a study of drivers’ behavior, the analyzed configurations of rumble strips and shoulder width levels affected vehicular lateral position and speed levels, although speed deviations were not practically significant. The study of safety performance function models provided technical and economical recommendations for installation of CLRS. Overall, this study recommends the installation of CLRS on rural, two-lane, undivided rural roads in Kansas. Both patterns, rectangular and football, currently installed in Kansas have provided crash reductions, which have been reflected in economic benefits for society. Shoulder width and traffic volume should be considered as crash predictors for enhancement of the benefits. Guidelines were recommended for future better applications of CLRS.

Os acidentes de trânsito são uma das principais causas de morte e invalidez no mundo inteiro, e projeções indicam que sua participação entre essas causas tende a aumentar no futuro. Estima-se que o fator humano contribua para a ocorrência de mais de 90% dos acidentes, e grande parte desta contribuição advém do comportamento. Nesta dissertação de mestrado, buscou-se identificar e caracterizar medidas de segurança de trânsito conforme sua influência em inibir o cometimento de infrações à legislação de trânsito por parte dos motoristas. Para tanto, foram conduzidas uma pesquisa qualitativa e uma pesquisa quantitativa. A pesquisa qualitativa, realizada através da técnica de Grupos Focados, foi utilizada para identificar as principais infrações de trânsito que contribuem para a ocorrência de acidentes, além de coletar subsídios para a elaboração da pesquisa quantitativa. Esta, por sua vez, consistiu na aplicação de um questionário auto-relatado a motoristas de automóvel da cidade de Porto Alegre. Como resultado, a pesquisa qualitativa indicou que as infrações que mais contribuem para os acidentes são a embriaguez, o excesso de velocidade e o avanço de sinal vermelho de semáforo. A pesquisa quantitativa permitiu concluir que as medidas de segurança de trânsito que mais influenciam os motoristas a não cometerem infrações de trânsito são aquelas relacionadas à restrição de direitos, como apreensão do veículo ou suspensão da habilitação, e à possibilidade de ser flagrado pelas autoridades. Por outro lado, as campanhas de conscientização na mídia demonstraram ser o tipo de medida com menor potencial para influenciar o comportamento dos motoristas. / Road traffic crashes are one of the main causes of death and disability worldwide, and it is believed that their share among these causes will grow in the future. The human factor contributes to over 90% of traffic crashes, and a great part of this contribution originates from human behaviour. This master’s thesis aimed to identify and characterize road safety measures according to their influence on driver behaviour, regarding the commitment of traffic offences. In order to do that, a qualitative and a quantitative survey were carried on. The qualitative survey was made with the Focus Group technique and was used to identify the traffic offences that contribute the most to road crashes, as well as to collect information to help preparing the quantitative survey. The last consisted in applying a self-reported questionnaire to automobile drivers from Porto Alegre, Brazil. As a result, the qualitative survey indicated that speeding, drunk driving and red light crossing are the traffic offences that contribute the most to road crashes. The quantitative survey allowed to conclude that the road safety measures with more influence on drivers, so they do not commit traffic offences, are those related to their rights restriction, like vehicle seizure or driver’s licence suspension, and to the possibility of being caught by authorities. On the other hand, road safety campaings on the media seemed to be the kind of measure with the smallest potential to influence driver behaviour.

<p>This master thesis deals with experimental data that were collected through a crash avoidance experiment (which was lead by Professor Lennart Strandberg) in February and March 1990. Fifty-two ordinary drivers were instructed to perform two different kinds of manoeuvres on ice to determine the effectiveness of antilock brakes and of four tyre configurations. Results were reported at the 1991 ESV Conference.</p><p>The first aim of this master thesis is to check and revise the measured data (used by Prof. Strandberg in courses at Linköping University). Checking out many hours of video recordings from onboard cameras reveals various protocol inconsistencies and errors, which in some cases it is not possible to correct. This work might increase the reliability of any further analysis of these data.</p><p>The second aim is to elaborate on the revised data and to test the hypothesis that quick steering is a key factor to not lose control of the car during a crash avoidance manoeuvre. Different variables are introduced and used to estimate the steering wheel velocity and lateral friction use.</p><p>The results show linear (positive) correlations between lateral friction use and steering wheel velocity. The greatest steering wheel velocities appear in the tests with loss-of-control and reach values up to 1180 degrees per second. However, the 1990 experimental layout was not intended for this type of research questions and it seems difficult to determine the causal relationship between quick steering and control of the car. Some cases of excessive steering input might have occurred. The results indicate that quick steering by itself is not enough to guarantee the total control of the car. An early reaction to the skid might be necessary too. Evidently, further research is needed.</p>

<p>Every year many people all over the world are killed and severely injured in road traffic accidents. Even though driving too fast is a behaviour well known to contribute to both the number and the outcome of these accidents, drivers are still speeding. The general aim of this thesis, and its five empirical studies, is therefore to further the knowledge about drivers speeding behaviour by using the theory of planned behaviour and the model underpinning the driver behaviour questionnaire as frames of reference. The behavioural data used is obtained from field trials with intelligent speed adaptation and the speed reducing potential of this system is also examined. The results show that attitude towards exceeding the speed limits, subjective norm, perceived behavioural control and moral norm from the theory of planned behaviour, but also violations and inattention errors from the model underpinning the driver behaviour questionnaire, can be used to predict drivers’ everyday speeding behaviour. These two models can also be combined in order to gain further knowledge about the causes of speeding. Identification of drivers’ beliefs about exceeding the speed limits gives further insight into the underlying cognitive foundation of their attitude, subjective norm and perceived behavioural control. This provides valuable information for future design of speed reducing measures. Regarding intelligent speed adaptation, the results show that the ISA speed-warning device greatly reduces the amount of time drivers spend above the speed limits, and to some extent also reduces their mean speeds, but that this effect decreases with time. Although the drivers are not totally satisfied with the experience of the ISA speed-warning device, they like the idea and can see its usefulness. As the device tested is a first generation ISA speed-warning device, further research has the potential to greatly improve the system.</p>

Every year many people all over the world are killed and severely injured in road traffic accidents. Even though driving too fast is a behaviour well known to contribute to both the number and the outcome of these accidents, drivers are still speeding. The general aim of this thesis, and its five empirical studies, is therefore to further the knowledge about drivers speeding behaviour by using the theory of planned behaviour and the model underpinning the driver behaviour questionnaire as frames of reference. The behavioural data used is obtained from field trials with intelligent speed adaptation and the speed reducing potential of this system is also examined. The results show that attitude towards exceeding the speed limits, subjective norm, perceived behavioural control and moral norm from the theory of planned behaviour, but also violations and inattention errors from the model underpinning the driver behaviour questionnaire, can be used to predict drivers’ everyday speeding behaviour. These two models can also be combined in order to gain further knowledge about the causes of speeding. Identification of drivers’ beliefs about exceeding the speed limits gives further insight into the underlying cognitive foundation of their attitude, subjective norm and perceived behavioural control. This provides valuable information for future design of speed reducing measures. Regarding intelligent speed adaptation, the results show that the ISA speed-warning device greatly reduces the amount of time drivers spend above the speed limits, and to some extent also reduces their mean speeds, but that this effect decreases with time. Although the drivers are not totally satisfied with the experience of the ISA speed-warning device, they like the idea and can see its usefulness. As the device tested is a first generation ISA speed-warning device, further research has the potential to greatly improve the system.