Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Our cities have been continually growing at an uncontrolled rate leading to the problem of trafficcongestion, which has discernable effects on all the aspects of sustainability, be it social,environmental or economical. This continual shift of increasing size of centre and decreasingsize of periphery poses huge sustainability challenge of meeting the consumption demands. Wepresently face the most unprecedented times in terms of the pace at which our natural resourcesare getting consumed. It is clear that replenishing some of these resources is totally out ofquestion. On the other side of the coin, the advances of human technology have provided itsgreatest gift of information & communication technology (ICT). Today we have access to datafrom any point of the world to anywhere. There is a growing need to use this data andinformation with a holistic view to build more Intelligent Transport Systems. In our paper wediscuss how the advent of ICT can have an impact on bringing a sustainable transportationsystem. The work is divided in two folds, by first understanding the direct role of ICT intransport sustainability and then observing the direct correlation between usage of ICT andtravel demand. The problems of traffic congestion and its solutions like congestion pricing haveexisted in practice since ages; the perspective which we add to it is the role of ICT in making itbetter. The greater perspective that is being researched here is at an absolute fundamental leveland takes us to the question if and how ICT can work on root level challenges, like findingmethods to have a better traceability without compromising on privacy, changing driverbehaviour patterns and stopping the expansion of centre & contraction of periphery.

This master’s thesis is focused on elderly drivers‘ behavior in various traffic situations and its comparison with a group of drivers in their productive years. The first part of the thesis compiles the current state of knowledge of the matter with a focus on age-related changes in driver performance. The analytical part is dedicated to the evaluation of the data collected from test drive video recordings. The data is evaluated to determine time spent on risk area assessments and habits of the groups. The added value and possible limitations given by the methodology are evaluated in the final part of the thesis.

Inductive charging, a form of wireless charging, uses an electromagnetic field to transfer energy between two objects. This emerging technology offers an alternative solution to users having to physically plug in their electric vehicle (EV) to charge. Whilst manufacturers claim inductive charging technology is market ready, the efficiency of transfer of electrical energy is highly reliant on the accurate alignment of the coils involved. Therefore understanding the issue of parking misalignment and driver behaviour is an important human factors question, and the focus of this paper. Two studies were conducted, one a retrospective analysis of 100 pre-parked vehicles, the second a dynamic study where 10 participants parked an EV aiming to align with a charging pad with no bay markings as guidance. Results from both studies suggest that drivers are more accurate at parking laterally than in the longitudinal direction, with a mean lateral distance from the centre of the bay being 12.12 and 9.57 cm (retrospective and dynamic studies respectively) compared to longitudinally 23.73 and 73.48 cm. With current inductive charging systems having typical tolerances of approximately ±10 cm from their centre point, this study has shown that only 5% of vehicles in both studies would be aligned sufficiently accurately to allow efficient transfer of electrical energy through induction.

This document is intended to give an overview of the validation of the human subject study, conducted in the driving simulator of the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD), as well of the validation of the stochastic traffic simulation developed in the AutoDrive project by the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD. Furthermore, the evaluation process of a C-AEB (Cooperative-Automatic Emergency Brake) system is demonstrated. The main purpose was to compare the driving behaviour of the study participants and the driving behaviour of the agents in the traffic simulation with real world data. Based on relevant literature, a validation concept was designed and real world data was collected using drones and stationary cameras. By means of qualitative and quantitative analysis it could be shown, that the driving simulator study shows realistic driving behaviour in terms of mean speed. Moreover, the stochastic traffic simulation already reflects reality in terms of mean and maximum speed of the agents. Finally, the performed evaluation proofed the suitability of the developed stochastic simulation for the assessment process. Furthermore, it could be shown, that a C-AEB system improves the traffic safety for the chosen test-scenarios.

Within the AutoDrive project, openPASS is used to develop a cognitive stochastic traffic flow simulation for urban intersections and highway scenarios, which are described in deliverable D1.14. The deliverable D2.16 includes the customizations of the framework openPASS that are required to provide a basis for the development and implementation of the driver behavior model and the evaluated safety function. The trial design for the evaluation of the safety functions is described. Furthermore, the design of the driver behavior study is introduced to parameterize and validate the underlying driver behavior model.

As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).

As part of the AutoDrive project, the OpenPASS framework is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. This framework was adapted and further developed. The deliverable D5.13 deals with the construction of the stochastic traffic simulation. At this point of the process, the theoretical design aspects of D4.20 are implemented. D5.13 explains the operating principles of the different modules. This includes the foundations, boundary conditions, and mathematical theory of the traffic simulation.

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

La conduite automobile est l’une des rares tâches nécessitant un apprentissage et le passage d’un examen initial, qui ne prévoit pas de mise en situation critique ni l’obligation de recyclages réguliers. En conséquence, les conducteurs ne connaissent pas les nouveaux systèmes d’aide et de sécurité proposés par les constructeurs automobiles et risquent de ne pas ou de mal s’en servir en conduite nominale. L’objectif de ce travail a été de vérifier, auprès de conducteurs novices et expérimentés, leur réelle capacité à utiliser les systèmes d’aide et de sécurité impliqués dans la régulation longitudinale du véhicule, en situation nominale et en situation d’urgence. Des essais ont été menés sur route, piste et simulateur de conduite. L’originalité de l’étude a porté sur la mesure du comportement du conducteur et de ses performances, pour approcher au mieux leur état fonctionnel (éveil physiologique, attention) induit par la charge mentale lorsqu’ils étaient confrontés à ces situations. On a privilégié l’utilisation de mesures physiologiques en continu et, en particulier, celles de l’activité électrodermale. Les résultats obtenus ont permis de conclure que les conducteurs -soumis à une situation critique, et en conséquence à une charge mentale élevée - utilisaient ces systèmes d’aide de manière inappropriée. Découlent de ces conclusions, deux offres de formations pour pallier la méconnaissance et la mauvaise utilisation des systèmes d’aide et de sécurité / Driving is one of the few activities which require both training and initial examination, but for which there are neither critical situation testing nor regular refresher courses. This creates two key problems: Through a lack of knowledge of the driving aids and safety systems offered by car manufacturers, drivers may fail to use or may misuse them in normal driving situations; secondly, an emergency situation may become critical if the driver has not previously experienced it in controlled conditions. The aim of this study was to check novice and experienced drivers’ ability to use the driving aids and safety systems proposed for vehicle longitudinal control in both nominal and critical situations. Trials were carried out in the field, on tracks and on driving simulators. The uniqueness of the study comes from combining driver behaviour and performance measurements to best correspond to the attention and workload observed when drivers were subjected to these situations. We therefore favoured the use of continuous physiological measures, and in particular electrodermal activity. The results enabled us to conclude that the use of these systems in critical situations was often inappropriate and necessitated a high workload. These conclusions led to the development and deployment of two training programmes in order to compensate for the lack of knowledge and misuse of the driving aids and safety systems