Cost-benefit analysis of the congestion charge in Gothenburg

In 2013 a congestion charge was implemented in Gothenburg. The main goal of the charge is to co-finance the West Swedish package, a collection of infrastructural investments in the region. Implementing a congestion charge is a common policy instrument used in order to reduce different externalities associated with road transportation. By increasing the cost of driving, traffic volume decreases and different positive effects occur, such as reduced travel time as well as improved environmental and health benefits. By conducting a cost and benefit analysis these positive effects can be measured and compared with the associated costs of the charging system. In effect, a cost-benefit analysis can be used as a tool to measure the social benefits of a congestion charge. Studies conducted in Stockholm and London show positive net benefits resulting from the congestion charges implemented in respective city. This thesis uses a cost-benefit analysis to evaluate the welfare effects of the congestion charge in Gothenburg in a similar way. The results show a positive net benefit for Gothenburg with the current toll charge when public transportation is excluded from the analysis. The sensitivity analysis show that when the charge increases from 13 SEK to 15 SEK the net benefits also increases

Visual SLAM in an automotive context:

Simultaneous Localization and Mapping (SLAM) is a technique frequently used in the area of self-driving cars for mapping and odometry. SLAM has traditionally been performed using laser based range finders of the light detection and ranging (LIDAR) types. Due to the high cost of these sensors there is currently a trend of implementing visuallybased SLAM systems using cameras as sensory input. This thesis explores the possibility of integrating a visual-SLAM component into an automotive framework as well as how this visual-SLAM compares to LIDAR based SLAM techniques. Using a state of the art visual SLAM algorithm, ORB-SLAM2, we implement and evaluate a modern visual-SLAM solution within the OpenDLV framework by performing a Design Science Research (DSR) study with the goal of implementing a microservice containing the ORB-SLAM2 algorithm inside of OpenDLV. The software artifact resulting from the DSR study is then evaluated using the evaluation methodology included in the KITTI visual odometry benchmark. Based on the results from this evaluation we conclude that the ORB-SLAM2 algorithm can successfully be integrated in the OpenDLV framework and that it is a possible replacement for LIDAR-based SLAM