Advanced Driving Assistance Systems (ADAS) has the potential to decrease the number of fatal accidents in traffic. However, in some cases, drivers with the systems in their car are resistant against using them. Exploring the underlying reasons and factors of the low-usage of ADAS was the purpose of this thesis. The thesis consists of Study I, an exploratory interview study with ten drivers who had cars with ADAS. The goal of Study I was to highlight the possible reasons behind the low usage of ADAS. The results of Study I were used to design Study II, which consisted of a survey targeted to drivers who had access to the ADAS adaptive cruise control and lane keep assist (N = 49). The results indicate that the factors or circumstances that affect usage depend on the ADAS and the user groups. Some identified underlying factors for low usage behavior of ADAS are the need to monitor the vehicle more when ADAS is activated and lack of trust in own ability when using ADAS compared to the high usage group. / Advanced Driving Assistance Systems (ADAS) har potential att förhindra antalet dödsfall i trafiken. Det förekommer att förare som har systemen i sin bil, väljer bort att använda dem. Syftet med den här uppsatsen var att undersöka underliggande orsaker och faktorer till låg användningsgrad av ADAS. Uppsatsen består av två studier. Studie I är en explorativ intervjustudie med tio förare som hade bilar med ADAS. Målet med Studie I var att ringa in de möjliga bakomliggande faktorerna för låg användningsgrad av ADAS. Resultaten från Studie I användes för att utforma en enkätstudie till Studie II som var riktad till förare som hade bilar med förarstödsystemen adaptiv farthållare och körfältsassistans (N = 49). Resultaten pekar på att de underliggande orsakerna och faktorerna beror på vilken ADAS som avses samt vilket användargrupp föraren tillhör. Några underliggande faktorer för låg användingsgruppen tycks vara känsla av att behöva övervaka fordonet samt lägre grad av tilltro till den egna förmågan än vad höganvändingsgrupper rapporterade.

Vehicle platooning is an advanced vehicle maneuver that allows for the simultaneous control of several vehicles traveling on the roadway cite{al2010experimental}. Automated platoons, when activated in tractor trailer convoys, have a high potential of increasing the fuel efficiency and improving the utilization of roadways by allowing more vehicles to share the road at the same time. The increased fuel efficiency translates to lower cost on goods and motivates a more environmentally friendly and sustainable economy. In order to achieve the promised fuel savings from vehicle platooning, the vehicles need to follow each other at shorter headways than in typical driving scenarios. The reduced separation distance between the lead and follow vehicle reduces visibility and the reaction time available for the follow vehicle; this renders most modern Active Driver Assist Systems (ADAS) ineffective since they are not designed for operation in such short headway conditions. The focus of this work is related to understanding and improving the failures of Lane Keep Assist (LKA) systems in the follow vehicles of a platoon. In this work, the source of lane detection degradation when using a monocular forward facing camera in short headway platooning is identified. Furthermore, a novel lane augmentation algorithm is proposed to improve the lane detection capability of follow vehicles in a platoon. The lane augmentation process utilizes a longitudinal transformation of lane parameters from the lead to the follow vehicles. The transformation utilizes an accurate understanding of the relative spatial position and orientation of the two vehicles. The transformation also requires a reliable communication system between the two vehicles such as a Vehicle-to-Vehicle (V2V) module. The work presented in this thesis develops theory, simulation and verification using real world data of the proposed cooperative lane augmentation. The results of this work indicate that it is possible to improve vehicle platooning performance by distributing the required sensing across multiple agents of the platoon. / Master of Science / Vehicle platooning is an advanced vehicle maneuver that allows for the simultaneous control of several vehicles traveling on the roadway cite{al2010experimental}. Automated platoons, when activated in tractor trailer convoys, have a high potential of increasing the fuel efficiency and improving the utilization of our roadways by allowing more vehicles to share the road at the same time. The increased fuel efficiency translates to lower cost on goods and motivates a more environmentally friendly and sustainable economy. In order to achieve the promised fuel savings from vehicle platooning, the vehicles need to follow each other at closer distances (headway) than in typical driving scenarios. The reduced separation distance between the lead and follow vehicle reduces visibility and the reaction time available for the follow vehicle; this renders most modern Active Driver Assist Systems (ADAS) ineffective since they are not designed for operation in such short headway conditions. The focus of this work is related to understanding and improving the failures of Lane Keep Assist (LKA) systems - the automated system used to keep the vehicle in the center of the lane - in the follow vehicles of a platoon. In the proposed scenario, the LKA uses a single forward facing camera to detect the lane lines ahead of the vehicle. The detected lanes serve as inputs to the lateral position (steering) controller in order to keep the vehicle in the center of the lane. In this work, the source of lane detection degradation in a follow vehicle of a short headway platoon is identified. Furthermore, a novel cooperative lane detection algorithm is proposed to improve the lane detection capability of the follow vehicles. The proposed algorithm utilizes lane information transformed from the lead to follow vehicle frame. The transformation utilizes the relative spatial position and orientation of the two vehicles. Additionally, a reliable communication protocol between the vehicles is required to transport the lane information. The work presented in this thesis develops theory, simulation and verification using real world data of the proposed algorithm. The results of this work indicate that lane keeping performance in a platoon can be improved using cooperative lane detection.

Future heavy duty vehicles will be designed and manufactured with improved Advanced Driver Assistance Systems, ADAS. When developing ADAS, an accurate model of the vehicle dynamics greatly simplifies the development process. One element integral to the vehicle lateral dynamics and development of ADAS is the steering system. This thesis aims to develop an accurate model of a heavy duty vehicle steering system suitable for simulations. The input to the system is an input torque at the steering wheel and the output is the wheel angle. Physical models of the system components are developed using bond graphs and known relations. Some components are modelled with non-linear inefficiencies and friction of different complexity. Unknown parameters and functions are identified from measurement data using system identification tools such as, for example, linear regression and non-linear grid search. The different subsystems are identified separately to the extent deemed possible. Different model designs are considered, validated, and compared. The advantages and disadvantages of different model choices are discussed. Finally, a non-linear state space model is selected for its high accuracy and efficiency. As this final model can be used to simulate a heavy duty vehicle steering system on a desktop computer faster than real time, it fulfills its purpose.