Variable speed limits (VSL) are used more commonly around the globe lately. Although on a macroscopic level positive effects of VSLs have been reported, the caveat is that the impact of VSLs is very sensitive to the level of driver compliance. Thus far it is unknown whether all individual drivers are actually able to notice when a speed limit changes into another speed limit; a prerequisite for purposeful speed limit compliance in the first place. To simulate regular driving conditions, twenty-four participants were familiarised with a particular route by driving the same route in a driving simulator nineteen times on five separate days. Part of the route consisted of a motorway where VSL signs were regularly displayed above every driving lane. At drive nineteen, speed limits changed from 80 km/h to 100 km/h on four out of eight consecutive signs. After passing all signs, one expects 6.25% of the participants still to be unaware that the speed limit had increased (based on chance), while the results showed most participants had failed to notice the speed limit change (58.3%). Instead, they saw what they expected to see: a speed limit of 80 km/h. If the speed change had been vice versa, in other words from 100 km/h to 80 km/h, this would immediately result in speed offences, though not deliberately at all.

This thesis proposes an analysing tool that makes use of route set generation to perform road network analysis that can be used in both transport planning and traffic management analysis. The input to the tool is a routable road network and a geographical zoning system and the route set generation is performed on all Origin-Destination (OD) -pairs of the zoning system. The tool was implemented using a simplification of Stockholms road network and a zoning system defined by the Swedish Transport Administration. The result shows that a route set generation-based tool can provide support in both transport planning and traffic management, and that the procedure provides results within a reasonable amount of time. The tool provides both a general analysis of the road network, and a link capacity reduction analysis. In the latter, the proportion of affected destinations and mean travel time deterioration for each OD-zone work as metrics of how the zones are affected by the capacity reduction. Transport planners can use the tool to present the betweenness centrality, the proportion of affected destinations and the mean travel time deterioration, all of which are metrics that can be used to evaluate the potential need for new infrastructure. Traffic managers can use the proportion of affected destinations and the mean travel time deterioration as metrics that can be used to identify zones that are affected by a road capacity reduction. The betweenness centrality of the best alternative route can be used to support traffic diversion for a specific zone.

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The Federal Aviation Administration (FAA) is continuously assessing the operational performance of the National Airspace System (NAS), where they analyze trends in the aviation industry to help develop strategies for a more efficient air transportation system. To measure the performance of various elements of the aviation system, the FAA and the International Civil Aviation Organization (ICAO) developed nineteen key performance indicators (KPIs). This dissertation contains three research studies, each written in journal format, addressing select KPIs. These studies aim at answering questions that help understand and improve different aspects of airport operational efficiency. In the first study, we model the flight times within the terminal airspace and compare our results with the baseline methodology that the FAA uses for benchmarking. In the second study, we analyze the efficiency of deicing operations at Chicago O'Hare (ORD) by developing an algorithm that analyzes radar data. We also use a simulation model to calculate potential improvements in the deicing operations. Lastly, we present our results of a clustering analysis surrounding the response of airports to demand and capacity changes during the COVID-19 pandemic. The findings of these studies add to literature by providing a methodology that predicts travel times within the last 100 nautical miles with greater accuracy, by providing deicing times per aircraft type, and by providing insight into factors related to airport response to shock events. These findings will be useful for air traffic management decision makers in addition to other researchers in related future studies and airport simulations. / Doctor of Philosophy / The Federal Aviation Administration (FAA) is the transportation agency that regulates all aspects of civil aviation in the United States. The FAA is continuously analyzing trends in the aviation industry to help develop a more efficient air transportation system. They measure the performance of various elements of the aviation system. For example, there are indicators focused on the departure phase of flights measuring departure punctuality and additional time in taxi-out. On the arrivals side, there are indicators that measure the additional time spent in the last 100 nautical miles of flight. Additionally, there are indicators that measure the performance of the airport as a whole such as the peak capacity and the peak throughput. This dissertation contains three research studies, each one aims at answering questions that help understand and improve a different aspect of airport operational efficiency. The first study is focused on arrivals where we model the flight times within the last 100 nautical miles of flight. Our model incorporated factors such as wind and weather conditions to predict flight times within the last 100 nautical miles with greater accuracy than the baseline methodology that the FAA currently uses. The resulting more accurate benchmarks are important in helping decision makers, such as airport managers, understand the factors causing arrival delays. In the second study, we analyze the efficiency of deicing operations which can be a major source of departure delays during winter weather. We use radar data at Chicago O'Hare airport to analyze real life operations. We developed a simulation model that allowed us to recreate actual scenarios and run what-if scenarios to estimate potential improvements in the process. Our results showed potential savings of 25% in time spent in the deicing system if the airport changed their queueing style towards a first come first served rather than leaving it for the airlines to have their separate areas. Lastly, we present an analysis of the response of airports to demand and capacity changes during the COVID-19 pandemic. In this last study, we group airports by the changes in their throughput and capacity during two time periods. The first part of the study compares airports operations during 2019 to the pandemic during the "shock event" in 2020. The second part compares the changes in airports operations during 2020 with the "recovery" time period using data from 2021. This analysis showed which airports reacted similarly during the shock and recovery. It also showed the relationship between airport response and factors such as what kind of airlines use the airport, airport hub size, being located in a multi-airport city, percentage of cargo operations. The results of this study can help in understanding airport resilience based on known airport characteristics, this is particularly useful for predicting airport response to future disruptive events.

<p dir="ltr">Traffic Incident Management (TIM) is an important tool for agencies to reduce secondary crashes, improve travel reliability, and ensure safety of first responders. Having “eyes” on the scene from roadside traffic cameras can assist operators to dispatch appropriate personnel, provide situational awareness, and allow for quick response when incident conditions change. Many intelligent traffic systems (ITS) centers deploy pan-tilt-zoom (PTZ) cameras that provide broad coverage but require operators to position. When incidents occur or a public safety vehicle stops for roadside assistance, Traffic Management Center (TMC) operators need to reposition cameras to monitor the event. The camera positioning time depends on operator experience, accuracy of 911 call, location, public safety radio reports, and in some cases, GPS positions. This research outlines the methodology to use GPS data sources to automate camera position to a scene for event nature verification. In general, this GPS information can come from either connected vehicles or public safety vehicles, such as Indiana Department of Transportation (INDOT) Hoosier Helpers. Implementing this research into INDOT daily operations has increased the number of events that cameras verify, while decreasing the time from event occurrence to camera verification from a median of 5 minutes to a median of approximately 90 seconds. The time is driven by the accuracy and frequency of GPS data from devices. With increased telematics polling rates and availability of enhanced vehicle data such as door open/close and seatbelt latch events, this latency is expected to further decline. </p>

Traditional crash frequency prediction models cannot capture the temporal effects of traffic characteristics due to the high level of data aggregation. Also, this approach is less suitable to address the crash risk for active traffic management strategies that typically operate for short-time intervals. Hence, this research proposes short-term crash prediction models for traffic management strategies such as Variable Speed Limit (VSL)/Variable Advisory Speed (VAS), and Part-time Shoulder Use (PTSU). By using high-resolution traffic detectors and VSL/VAS operational data, short-term Safety Performance Functions (SPFs) are estimated at weekday hourly and peak period aggregation levels. The results indicate that the short-term SPFs could capture various crash contributing factors and safety aspects of VSL/VAS more effectively than the traditional highly aggregated Average Annual Daily Traffic (AADT)-based approach. The study also investigates the safety effectiveness of VSL/VAS for different types and severity levels of traffic crashes. The results specify that the VSL/VAS system is effective in reducing rear-end crashes in the Multivariate Poisson Lognormal (MVPLN) crash type model as well as Property Damage Only (PDO) and C (non-incapacitating) crashes in the MVPLN crash severity model. Recommendations include deploying the VSL/VAS system combined with other traffic management strategies, strong enforcement policies, and drivers' compliance to increase the effectiveness of this strategy. Further, this research estimates the Random Parameters Negative Binomial-Lindley (RPNB-L) model for PTSU sections and provides valuable insights on potential crash contributing factors related to PTSU operation, design elements, and high-risk areas. Last, the study proposes a novel integrated crash prediction approach for freeway sections with combined traffic management strategies. By incorporating historical safety conditions from SPFs, real-time crash prediction performance could be improved as a part of proactive traffic management systems. The findings could assist transportation agencies, policymakers, and practitioners in taking appropriate countermeasures for preventing and reducing crash occurrence by incorporating safety aspects while implementing traffic management strategies on freeways.

Persistent condensation trails are clouds, induced by the exhaust of an aircraft engine in a cold and ice-supersaturated environment. These artificial ice clouds can both cool and heat the atmosphere by scattering solar radiation and absorbing terrestrial radiation, respectively. The influence of condensation trails on the Earth-atmosphere energy balance and therewith the answer to the question of the dominating process had been mostly approximated on a global scale by treating the condensation trail as plane parallel layer with constant optical properties. Individual condensation trails and the influence of the solar angle had been analyzed, always using a course spatial grid and never under consideration of the aircraft performance, generating the condensation trail. For a trajectory optimization, highly precise results of the impact of condensation trails on the radiation budget and the influence of the aircraft performance on this impact is needed, so that future air traffic may consider the main factors of flight performance on the environmental impact of condensation trails. That’s why, a model is developed in this thesis to continuously estimate the scattering and absorption properties and their dependence on the aircraft performance. / Langlebige Kondensstreifen sind Eiswolken, welche durch Kondensation von Wasserdampf an Rußpartikeln in einer eisübersättigten Atmosphäre entstehen. Der Wasserdampf entstammt einerseits aus dem Triebwerkabgas und andererseits aus der Atmosphäre. Kondensstreifen können die Atmosphäre durch Rückstreuung solarer Strahlung kühlen und durch Rückstreuung und Absorption terrestrischer Strahlung erwärmen. Der Einfluss von Kondensstreifen auf den Wärmehaushalt der Atmosphäre und damit die Antwort auf die Frage nach dem dominierenden Effekt wurde bisher zumeist auf globaler Ebene ermittelt, wobei der Kondensstreifen als planparallele Schicht mit konstanten optischen Eigenschaften angenähert wurde. Individuelle Kondensstreifen und der Einfluss des Sonnenstandes wurden bisher nur mithilfe eines groben Rasters betrachtet und niemals unter Berücksichtigung der Flugleistung des Luftfahrzeuges, welches den Kondensstreifen generiert hat. Für eine Trajektorienoptimierung sind jedoch präzise Berechnungen des Strahlungseinflusses und eine gewissenhafte Berücksichtigung der Flugleistung notwendig. Nur so kann der zukünftige Luftverkehr die Haupteinflussfaktoren der Flugeigenschaften auf den Strahlungseinfluss der Kondensstreifen berücksichtigen. Aus diesem Grund wurde in dieser Arbeit ein Modell entwickelt, welches die Eigenschaften des Strahlungstransfers durch den Kondensstreifen kontinuierlich bestimmt und die aus der Flugleistung resultierenden Parameter berücksichtigt.

Von Fahrzeugen des Öffentlichen Verkehrs sind deren Positionen bekannt, wenn sie informationstechnisch in ein Betriebsleitsystem eingebunden sind. Über die auf dem Streckenband zwischen Meldepunkten zurückgelegte Wegstecke und die jeweils dafür benötigte Zeit kann auf die mittlere Geschwindigkeit geschlossen werden. Aus dieser wiederum kann eine Verkehrslageaussage abgeleitet werden. In wie weit diese für den Gesamtverkehrsstrom gültig, belastbar und richtlinienkonform ist, welche Randbedingungen für eine Auswertung einzuhalten sind, welche Verfahren sich zur Aufbereitung anbieten und welche Nutzungsszenarien unterstützt werden, wird aufgezeigt.