För att skapa en så bra livsmiljö som möjligt spelar medborgardeltagandet en stor roll i den urbana planeringen. För att gemene man ska kunna se framtida konsekvenser av nya planförslag måste de också förstå planens innehåll. Det finns olika slags verktyg för att presentera dessa planförslag. Syftet med denna studie var att genom ett experiment jämföra hur deltagarna förstod detaljplanematerial som presenterades på två olika sätt. Målet var att komma fram till hur olika presentationsverktyg kunde underlätta förmedlingen av nya planförslag vid medborgardialoger. Experimentets upplägg omfattade två moment: 2D-metoden och 4D- metoden. I 2D-metoden fanns detaljplanehandlingar som använts under Södertäljes samråd om Kvarteret Orion. I 4D-metoden tillämpades en 4D-modell över Södertälje som har använts vid medborgardialog. För att samla rådata tillämpades enkäter som insamlingsmetod. Enkätfrågorna utformades för att undersöka deltagarnas förmåga att förstå spatial och instruktiv information. Deltagarna delades slumpmässigt in i två grupper där respektive grupp fick prova en behandling: behandling A eller behandling B. Resultatet analyserades med hjälp av ett Wilcoxon signed rank test och en kvalitativ stapeldiagramsanalys. Slutsatsen visade att 4D- metoden förmedlade informationen tydligast, men att 2D- och 4D-metoderna har olika egenskaper. Dessa metoder behöver därför kompletteras med varandra för att förmedla detaljplaneinformationen till medborgaren på bästa möjliga sätt. / To create a good living environment the civic participation plays a major role in urban planning. In order for the common man to be able to see the future implications of the new planning proposal they must also understand the plan’s content. There are various tools to present these planning proposals. The purpose of this study was to through an experiment compare how the participants understood the zoning plan presented to them in two different ways. The aim was to come up with how various presentation tools could facilitate the communication of planning proposals for citizen dialogues. The experiment set-up comprised two parts: the 2D method and 4D method. In the 2D method, information and planning documents from the Södertälje consultation of Kvarteret Orion were used. In the 4D method, a 4D model of Kvarteret Orion previously used for citizen dialogue was employed. To collect raw data, questionnaires were applied as a collection method. The survey questions were designed to examine the participants’ ability to understand spatial and instructional information. The participants in the experiment were divided randomly into two groups, with each group assigned to try one of two treatments: treatment A or treatment B. The results were analyzed by a Wilcoxon Signed Rank Test and a bar graph qualitative analysis. The conclusion was that the 4D method was the most efficient in communicating the information, but that both methods have their different strengths. To fully convey zoning planning information to the citizen, both methods need to be used since only when complementing each other do they present a full picture of the plan at hand.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.