Cooperative driving holds the potential to considerably improve the level of safety and efficiency on our roads. Recent advances in in-vehicle sensing and wireless communication technology have paved the way for the development of cooperative traffic safety applications based on the exchange of data between vehicles (or between vehicles and road side units) over a wireless link. The access to up-to-date status information from surrounding vehicles is vital to most cooperative driving applications. Other applications rely on the fast dissemination of warning messages in case a hazardous event or certain situation is detected. Both message types put high requirements on timeliness and reliability of the underlying communication protocols. The recently adopted European profile of IEEE 802.11p defines two message types,periodic beacons for basic status exchange and event-triggered hazard warnings, both operating at pre-defined send rates and sharing a common control channel. The IEEE 802.11p Medium Access Control (MAC) scheme is a random access protocol that doesnot offer deterministic real-time support, i.e. no guarantee that a packet is granted access to the channel before its deadline can be given. It has been shown that a high number of channel access requests, either due to a high number of communicating vehicles or highdata volumes produced by these vehicles, cannot be supported by the IEEE 802.11p MAC protocol, as it may result in dropped packets and unbounded delays. The goal of the work presented in this thesis has therefore been to enhance IEEE 802.11p without altering the standard such that it better supports the timing and reliability requirements of traffic safety applications and provides context-aware andefficient use of the available communication resources in a vehicular network. The proposed solutions are mapped to the specific demands of a set of cooperative driving scenarios (featuring infrastructure-based and infrastructure-free use cases, densely and sparsely trafficked roads, very high and more relaxed timing requirements) and evaluated either analytically, by computer simulation or by measurements and compared to the results produced by the unaltered IEEE 802.11p standard. As an alternative to the random MAC method of IEEE 802.11p, a centralized solution isproposed for application scenarios where either a road side unit or a suitable dedicated vehicle is present long enough to take the coordinating role. A random access phase forevent-driven data traffic is interleaved with a collision-free phase where timely channel access of periodic delay-sensitive data is scheduled. The ratio of the two phases isdynamically adapted to the current data traffic load and specific application requirements. This centralized MAC solution is mapped on two cooperative driving applications: merge assistance at highway entrances and platooning of trucks. Further,the effect of a context-aware choice of parameters like send rate or priority settings based on a vehicle’s position or role in the safety application is studied with the goal to reduce the overall number of packets in the network or, alternatively, use the available resources more efficiently. Examples include position-based priorities for the merge assistance use case, context-aware send rate adaptation of status updates in anovertaking warning application targeting sparsely-trafficked rural roads and an efficient dissemination strategy for warning messages within a platoon. It can be concluded that IEEE 802.11p as is does not provide sufficient support for the specific timing and reliability requirements imposed by the exchange of safety-criticalreal-time data for cooperative driving applications. While the proper, context-awarechoice of parameters, concerning send rate or priority level, within the limits of the standard, can lead to improved packet inter-arrival rates and reduced end-to-end delays,the added benefits from integrating MAC solutions with real-time support into the standard are obvious and needs to be investigated further.

With limited road infrastructure and increasing number of vehicles on the road, an intelligent transport system is needed to increase the throughput in traffic and minimize traffic jams in highly populated areas. The purpose of this project is to design and implement a control system that is capable of driving and following the preceding vehicle autonomously in the longitude direction only. The vehicle is also equipped with a vehicle to vehicle communication unit. With this information, all vehicles on the road can communicate with each other and are able to achieve shorter distances between vehicles and damp any disturbance caused by upstream traffic. A general structure on Cooperative Adaptive Cruise Control (CACC) is created by studying the research from The Netherlands Organization for Applied Scientific Research (TNO). A string stability criterion is used to determine if the system is suitable of driving in a platoon, where a string of vehicles are following a lead vehicle. This system is then implemented in a Volvo S60 and has participated in the 2011 Grand Cooperative Driving Challenge hosted in The Netherlands. The results show that the system has ability to increase throughput and damp disturbance on the upstream traffic by communicating with the other vehicles ahead. The system is also robust and simple enough to earn the 2nd place in the competition. / Grand Cooperative Driving Challenge

Cooperative driving in a connected vehicle (CV) environment has received increasing attention over the years due to its ability to enhance driving safety and efficiency. Despite many efforts that have been made in this field, the role of human drivers and pedestrians is frequently omitted. It is important to consider them to develop cooperative driving algorithms that are intelligent and robust to incorporate any uncertainty brought by humans. In this dissertation, a framework of a multi-driver in-the-loop driving simulator and a pedestrian in-the-loop digital twin system is introduced. Three important topics in cooperative driving were investigated using the developed framework: the effects of human-machine interface (HMI) design for cooperative driving, vehicle-pedestrian interaction under occlusion scenarios, and multi-vehicle decision-making at weaving segments. In the first topic, three HMIs were designed for collaborative speed adaptation following the skills, rules, and knowledge (SRK) taxonomy. The HMI designs were tested using a multi-driver simulator, and the results showed that the graphic-based HMI improved cooperative driving performance and was preferred by the participants. In the second task, a Digital Twin framework for CV and pedestrian in-the-loop simulation was proposed based on Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). The effects of Vehicle-Pedestrian (V2P) warning systems under occlusion scenarios were investigated for different connectivity and vehicle automation levels. In the third task, an edge-enhanced graph attention deep reinforcement learning algorithm was developed to aid autonomous vehicles in diverging at weaving segments. The results showed that the proposed algorithms outperformed existing models and performed well in real-world driving scenarios. The dissertation provides insights into developing safe and efficient cooperative driving algorithms and applying advanced simulation technologies to human-in-the-loop cooperative driving testing.

Vehicle-to-Vehicle communication is the key technology for achieving increased perception for automated vehicles where the communication allows virtual sensing with the use of sensors placed in other vehicles. In addition, this technology also allows recognising objects that are out-of-sight. This thesis presents a Trust System that allows a vehicle to make more reliable and robust decisions. The system evaluates the current situation and generates a Trust Index indicating the level of trust in the environment, the ego vehicle, and the other vehicles. Current research focuses on securing the communication between the vehicles themselves, but does not verify the content of the received data on a system level. The proposed Trust System evaluates the received data according to sensor accuracy, behaviour of other vehicles, and the perception of the local environment. The results show that the proposed method is capable of correctly identifying various situations and discusses how the Trust Index can be used to make more robust decisions.

Traffic signals typically produce vehicle stops and thus increase vehicle fuel consumption levels. Vehicle stops produced by traffic signals, decrease vehicle fuel economy on arterial roads making it significantly lower than that on freeways. Eco-Cooperative Adaptive Cruise Control (Eco-CACC) systems can improve vehicle fuel efficiency by receiving Signal Phasing and Timing (SPaT) data form downstream signalized intersections via vehicle-to-infrastructure communication. The algorithm that was developed in an earlier study provides advisory speed recommendations to drivers to reduce vehicle fuel consumption levels in the vicinity of traffic signalized intersections. The research presented in this thesis enhances the algorithm by adding a queue length estimation component and incorporates the algorithm in the INTEGRATION microscopic traffic simulation software to test the system under varying conditions. The enhanced Eco-CACC algorithm is then tested in a simulation environment considering different levels of connected vehicle (CV) market penetration levels. The simulation analysis demonstrates that the algorithm is able to reduce the vehicle fuel consumption level by as high as 40%. Moreover, the overall benefits of the proposed algorithm is evaluated for different intersection configurations and CV market penetration rates (MPRs). The results demonstrate that for single lane approaches, the algorithm can reduce the overall fuel consumption levels and that higher MPRs result in larger savings. While for multilane approaches, lower MPRs produce negative impacts on fuel efficiency; only when MPRs are greater than 30%, can the algorithm work effectively in reducing fuel consumption levels. Subsequently a sensitivity analysis is conducted. The sensitivity analysis demonstrates that higher market penetration rates of Eco-CACC enabled vehicles can improve the environmental benefits of the algorithm, and the overall savings in fuel consumption are as high as 19% when all vehicles are equipped with the system. While, on multi-lane approaches, the algorithm has negative impacts on fuel consumption levels when the market penetration rate is lower than 30 percent. The analysis also indicates that the length of control segments, the SPaT plan, and the traffic demand levels affect the algorithm performance significantly. The study further demonstrates that the algorithm has negative impacts on fuel consumption levels when the network is over-saturated. / Master of Science

Autonomous vehicles, commonly known as “self-driving cars”, are increasingly becoming of interest for researchers due to their potential to mitigate traffic accidents and congestion. Using reinforcement learning, previous research has demonstrated that a DQN agent can be trained to effectively navigate a simulated two-lane environment via cooperative driving, in which a model of V2X technology allows an AV to receive information from surrounding vehicles (termed Primary Perceived Vehicles) to make driving decisions. Results have demonstrated that the DQN agent can learn to navigate longitudinally and laterally, but with a prohibitively high collision rate of 1.5% - 4.8% and an average speed of 13.4 m/s. In this research, the impact of including information from traffic vehicles that are outside of those that immediately surround the AV (termed Secondary Perceived Vehicles) as inputs to a DQN agent is investigated. Results indicate that while including velocity and distance information from SPVs does not improve the collision rate and average speed of the driving algorithm, it does yield a lower standard deviation of speed during episodes, indicating lower acceleration. This effect, however, is lost when the agent is tested under constant traffic flow scenarios (as opposed to fluctuating driving conditions). Taken together, it is concluded that while the SPV inclusion does not have an impact on collision rate and average speed, its ability to achieve the same performance with lower acceleration can significantly improve fuel economy and drive quality. These findings give a better understanding of how additional vehicle information during cooperative driving affects automated driving. / Thesis / Master of Applied Science (MASc)

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This dissertation deals with issues concerning driver education and driver training courses. It first deals with driver education in Czech schools and its representation in RVP.A comparison of driver education in the Czech Republic with driver education in foreign countries is presented in accordance with the results of research project Q F 44L/058/050. It also deals with the preparation of teachers for driver education in terms of a university study. The text attempts to highlight the importance of driver education throughout the entire lifetime of drivers. It covers driver education in the family, preschool, grammar school and high school education as well as preventive driving campaigns and training courses, and also in driving schools. The work also deals with differences between various ways of driving, and more specifically, those between defensive and cooperative driving. It attempts to find a delineation between these concepts in a non-uniform community of specialists. A significant part of the work deals with investigative research, which is primarily centered in interviews with transportation specialists, observation of participants in defensive driving courses and the analysis of documents. Keywords: traffic education, traffic prevention, defensive driving, cooperative driving, course of...

With the advent of autonomous driving, concepts like road trains or platoons are becoming more popular. In these arrangements, vehicles travel at separations of only 5 to 10m between them. These short inter-vehicle distances allow compacting vehicle flows resulting in increased throughput on highways. In addition, there are also fuel/energy savings as the magnitude of aerodynamic resistance acting on vehicles is reduced. These benefits increase when reducing inter-vehicle separations to below 5m. However, it becomes extremely difficult to guarantee safety, especially, when braking in an emergency. The longitudinal and lateral control systems developed so far aim to achieve string stability in the cruise scenario, i.e., to prevent that small variations at the lead magnify towards the trail. Unfortunately, this has no relevance during emergency braking, since control systems incur saturation, i.e., the condition where computed output brake forces exceed those that can be applied by actuators. This is because all vehicles have to apply their maximum brake forces in order to minimize the stopping distance of the platoon and reach a complete standstill. As a result, emergency braking requires special attention and needs to be designed and verified independent of the cruise scenario. Braking in an emergency is mainly characterized by the problem of heterogeneous deceleration capabilities of vehicles, e.g., due to their type and/or loading conditions. As a result, a deceleration rate possible by one vehicle may not be achievable by its immediately leading or following vehicles. Not addressing this heterogeneity leads to inter-vehicle collisions. Moreover, transitions in the road profile increase the complexity of such brake maneuvers. Particularly, when there is a transition from a flat road to a steep downhill, an already saturated brake controller cannot counteract the effect of the downhill slope. Hence, its deceleration magnitude will be reduced, potentially leading to intra-platoon crashes that would otherwise not occur on a flat road. In this work, we first analyze the problem of emergency braking in platoons operating at inter-vehicle separations below 5m and under idealized conditions (i.e., flat road, instantaneous deceleration, etc.). For this case, we propose a cyber-physical approach based on exploiting space buffers that are present in the separations between vehicles, and compare it with straightforward schemes (such as Least Platoon Length and Least Stopping Distance) in terms of achieved aerodynamic benefits, overall platoon length, and stopping distance. We then consider realistic conditions (in particular, changing road profiles as mentioned before) and investigate how to design a brake-by-wire controller present at each vehicle that accounts for this. We further extend our proposed cyber-physical approach by adding cooperative behavior. In particular, if an individual vehicle is unable to track its assigned deceleration, it coordinates with all others to avoid inter-vehicle collisions, for which we propose a vehicle-to-vehicle (V2V) communication strategy. Finally, we present a detailed evaluation of the proposed cyber-physical approach based on high-fidelity vehicle models in Matlab/Simulink. Even though more work is needed towards a real-life implementation, our simulation results demonstrate benefits by the proposed approach and, especially, its feasibility.

Vehicular ad hoc networks (VANETs) are a hot topic in the intelligent transport system (ITS) area. The introduction of wireless communications between vehicles will enable many useful applications to enhance road traffic safety as well to increase efficiency. The standardization of IEEE 802.11p, being an amendment to IEEE 802.11 intended for VANETS, faces many challenges. In Europe a 30 MHz spectrum at 5.9 GHz have been dedicated for ITS and this spectrum has to be used to its full potential. For this reason this thesis compares a 20 MHz wide frequency channel with a 10 MHz wide through measurements using 802.11p hardware. The measurements were conducted on a highway with relative speeds of up to 240 km/h. The results from these initial measurements show that a 20 MHz channel does not perform worse than a 10 MHz channel despite the high relative speeds and large metal signs scattering the signals. What enabled this thesis to do the measurements was Halmstad University‟s participation in the Grand Cooperative Driving Challenge (GCDC) 2011. In GCDC nine teams mostly from Europe competed in having the vehicle that had the best behaviour in a platoon of vehicles using cooperative adaptive cruise control (CACC), the CACC algorithm controlled the vehicles‟ acceleration and breaking autonomously based on in-vehicle sensors and communicated messages between the vehicles in the platoon using 802.11p. This thesis implemented the communication part of Halmstad University‟s vehicle. The challenge was held in Helmond, Holland, May 14-15, 2011. Halmstad University‟s team finished in second place. / CoAct