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The characterizations of Kean mirrored the deprivation which he suffered as a child, as well as his wild and volcanic nature. It is difficult in a study of Kean to divorce the actor from the man, and the man from the actor. This thesis concludes that each of these two aspects of this genius of the English stage exerted a profound influence upon the other.

Driving Assistance Systems such as lane departure and front collision warning has caught great attention for its promising usage on road driving. This, this research focus on implementing lane departure and front collision warning at same time. In order to make the system really useful for real situation, it is critical that the whole process could be near real-time. Thus we chose Hough Transform as the main algorithm for detecting lane on the road. Hough Transform is used for that it is a very fast and robust algorithm, which makes it possible to execute as many frames as possible per frames. Hough Transform is used to get boundary information, so that we could decide if the car is doing lane departure based on the car's position in lane. Later, we move on to use front car's symmetry character to do front car detection, and combine it with Camshift tracking algorithm to fill the gap for failure of detection. Later we introduce camera calibration, stereo calibration, and how to calculate real distance from depth map.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1967. / Typescript. Vita. Description based on print version record. Includes bibliographical references (leaves 167-178).

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Värmdö is a commuter municipality to Stockholm. Road 222 between Värmdö and Stockholm is the main commuter route for both bus and car traffic. Road 222 is a bottleneck at Farstabron in the direction towards Värmdö, where the motorway will go from two to one lane and become a non-meeting motorway. Towards Stockholm, the bridge has two lanes, which is why capacity is not affected as strongly in that direction. The accessibility problems arise mainly in the direction of Värmdö during maximum hours in the afternoon and during weekends and summer time as the municipality also has many holiday homes. Measures to improve accessibility have been raised by both the municipality and the Swedish Transport Administration. Building a new bridge is not relevant as the remaining expected technical life of the bridge is long. The Swedish Transport Administration has an idea for a reversible lane solution on the bridge, which is the proposal studied in this thesis. Data collection and traffic analysis has been performed to study how the travel time effect would be if Farstabron was rebuilt into a reversible 2 + 1 road, with or without a reversible bus lane. The tool used is the microsimulation program PTV VISSIM. The results show that a reversible solution without a bus lane is the alternative that provides by far the largest travel time gains for both car and bus in 2040. The degree project contains a chapter that deals with traffic engineering theory and traffic simulation theory as well as a literature study chapter that summarizes the knowledge about reversible lanes. The information about reversible lanes, even international studies, is poor.Experiences of reversible lanes is good and is mainly to be recommended as the flow in one direction is significantly greater than in the other. The traffic safety risk is primarily linked to unprotected road users. The most common internationally according to what has been identified is to implement reversible lanes on motorways with protective barriers. However, no reversible lane without a barrier have been identified holding 80km/h. Studies have shown that reversible lanes could have a cost-benefit ratio of around 7, which means that the benefit outweighed the costs 7 times in money measured. The weaving dynamics of VISSIM from two to one lane were challenging to calibrate against the reality. Preparatory behavior during lane changes is mainly affected by car-following and lane-changing models in VISSIM. In the simulation the correlation with collected data was slightly more accurate with the car following model for W99 (freeway) rather than W74 (weaving urban rd).

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this thesis, a human-centric approach is adopted in order to provide an enriching driving experience. The thesis investigates the natural behavior of drivers when changing lanes in terms of preferences of vehicle kinematics parameters using a real-world driving dataset collected as part of the Second Strategic Highway Research Program (SHRP2). The SHRP2 Naturalistic Driving Study (NDS) set is mined for lane change events. This work develops a way to detect reliable lane changing instances from a huge NDS dataset with more than 5,400,000 data files. The lane changing instances are distinguished from noisy and erroneous data by using machine vision lane tracking system variables such as left lane marker probability and right lane marker probability. We have shown that detected lane changing instances can be validated using only vehicle kinematics data. Kinematic vehicle parameters such as vehicle speed, lateral displacement, lateral acceleration, steering wheel angle, and lane change duration are then extracted and examined from time series data to characterize these lane-changing instances for a given driver. We have shown how these vehicle kinematic parameters change and exhibit patterns during lane change maneuvers for a specific driver. The thesis shows the limitations of analyzing vehicle kinematic parameters separately and develops a novel metric, Lane Change Dynamic Score(LCDS) that shows the collective effect of these vehicle kinematic parameters. LCDS is used to classify each lane change and thereby different driving styles. / Master of Science / The current tendency of car manufacturers is to create vehicles that will offer the user the most comfortable ride possible. The user experience is given a lot of attention to ensure it is up to par. With technological advancements, we are moving closer to an era in which automobiles perform many functions autonomously. However, different drivers may react differently to highly automated driving technologies. Therefore, adapting to different driving styles is critical to increasing the acceptance of autonomous vehicle features. In this work, we examine one of the stressful maneuvers of lane changes. The analysis of various drivers' lane-changing behaviors and the value of personalization are the main subjects of this study based on actual driving scenarios. To achieve this, we have provided an algorithm to identify occurrences of lane-changing from real driving trip data files. Following that, we investigated parameters such as lane change duration, vehicle speed, displacement, acceleration, and steering wheel angle when changing lanes. We have demonstrated the patterns and changes in these vehicle kinematic characteristics that occur when a particular driver performs lane change operations. The thesis shows the limitations of analyzing vehicle kinematic parameters separately and develops a novel metric, Lane Change Dynamic Score(LCDS) that shows the collective effect of these vehicle kinematic parameters. LCDS is used to classify each lane change and thereby different driving styles.

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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.