Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, due to financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP prior to implementation in order to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated using microscopic simulation models. However, the application of these models is resource intensive and requires specialized expertise that is often not available in-house to transit agencies. In this thesis, an analytical model was proposed for estimating the delay impacts of green extension and early green (red truncation) TSP strategies. The proposed model is validated with analytical model reported in the literature and microscopic simulation model. This is followed by model sensitivity analysis. A software module is developed using the proposed model. The usefulness of the model is illustrated through its application to estimate the TSP performance. Finally, a prioritization is conducted on sixteen intersections with different geometric and operational traffic strategies. The overall results indicate that the proposed model is suitable for both estimating the pre-deployment and post-deployment TSP performance. The proposed model is suitable for implementation within a spreadsheet and requires considerably less effort, and less technical expertise, to apply than a typical micro-simulation model and therefore is a more suitable tool for transit agencies to use for prioritising TSP deployment.

Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, due to financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP prior to implementation in order to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated using microscopic simulation models. However, the application of these models is resource intensive and requires specialized expertise that is often not available in-house to transit agencies. In this thesis, an analytical model was proposed for estimating the delay impacts of green extension and early green (red truncation) TSP strategies. The proposed model is validated with analytical model reported in the literature and microscopic simulation model. This is followed by model sensitivity analysis. A software module is developed using the proposed model. The usefulness of the model is illustrated through its application to estimate the TSP performance. Finally, a prioritization is conducted on sixteen intersections with different geometric and operational traffic strategies. The overall results indicate that the proposed model is suitable for both estimating the pre-deployment and post-deployment TSP performance. The proposed model is suitable for implementation within a spreadsheet and requires considerably less effort, and less technical expertise, to apply than a typical micro-simulation model and therefore is a more suitable tool for transit agencies to use for prioritising TSP deployment.

En viktig del av passagerartillfredsställelsen utgörs av hur smidiga köpprocesserna är. I denna studie analyseras delprocesser hos KING SEAWAYS med mål om att skapa ett optimerat förbättringsförslag till de studerade processerna. Den nuvarande processen gällande fartygets tid i hamn innefattar delprocesser som körs beroende och oberoende av varandra. Fokus i studien är på de sista delprocesserna innan fartygets avgång från det att passageraren ankommer till check-in fram till dem står parkerade på bildäcket. Kundundersökningen visar ett missnöje bland passagerarna gällande väntetid på kajen. Efter att ha analyserat passagerarbeteendet och genom att göra några resonabla antaganden för att förenkla uträkningarna gällande köer, är det uppenbart att det finns betydande flaskhalsar i processen som kan åtgärdas. Att applicera köteori i varje steg, skapar en klar bild av att förändringar kan skapa förutsättningar för reducerade kostnader samt en förhöjd kundnöjdhet.   Förbättringsförslaget som framkom efter analys av den nuvarande processen och kundernas upplevelse var att nyttja tiden på kajen till att förbereda inför ombordkörning och placera bilar efter layout ombord på fartyget. Med detta kan bilarna på kajen hanteras som en homogen grupp, snarare än enskilda enheter och då öka effektiviteten i processen. Förslaget bör även ge ett positivt utfall på kundtillfredsställelsen.   Denna rapport berör endast ett fartyg i DFDS totala flotta om cirka 50 fartyg, men tankarna som lett fram till resultat och slutsats bör även vara applicerbart på flertalet andra fartyg i flottan. Bara för fartyget KING SEAWAYS skulle en förändring om en minskad tid i hamn, om 15 minuter dagligen, innebära en bränslebesparing årligen om 1,7 miljoner danska kronor. Med en snabb beräkning gällande besparingar av resurser visar förbättringsförslaget att det kan komma att handla om flertalet miljoner. Med nöjdare kunder skaps även konkurrenskraft och det är en förutsättning för att DFDS även i framtiden behålla sin marknadsposition. / An important factor in passenger satisfaction is queue management. In this study processes at KING SEAWAYS are analyzed with the aim of creating a proposal for improvement and optimization. The current process of the vessels turnaround includes sub-processes that run dependent and independent of each other. The focus in this study deals with the final sub-processes before departure, from the time that the passenger arrives at the check-in until they are parked on the car deck. The customer survey shows dissatisfaction among passengers regarding waiting time on the dock. After analyzing the behavior of passengers and by taking a couple of reasonable assumptions, it becomes obvious that bottlenecks could be reduced. Applying queuing theory in each step creates a clear picture that changes can create conditions for reduced costs as well as increased condition for customer satisfaction.   The improvement proposal that emerged after analyzing the current process and customer experience was to utilize time on the quay to prepare for boarding and place cars according to the ship layout. With this, the cars on the dock can be handled as a homogeneous group, rather than individual units, and then increase the efficiency of the process. The proposal should also give a positive outcome to customer satisfaction.   This report deals with one vessel in DFDS' total fleet of about 50 vessels, but the thoughts that led to the results and conclusion could be applicable to most of the other fleet vessels. For KING SEAWAYS only, a reduced turnaround time of 15 minutes corresponds to fuel saving of 1.7 million Danish kroner per year. With a quick estimation on resource savings the proposal for improvement shows that improvements could have a considerable impact on DFDS bottom line. Satisfied customers are also a prerequisite for DFDS to maintain its market position in the future.