This study aims to quantify the impact on the traffic flow performance of different regulation strategies for a centralised route guidance system where road authorities and service providers work together in a coordinated approach. Previous research concentrates on the effect of a centralised route guidance system when every vehicle participates and all vehicles have perfect knowledge of the traffic state. This is not the real case with human drivers and multiple service providers and the impact of cooperation may be limited. This study combines habitual driving behaviour, the effect of the quality of information and a congestion avoiding user optimum algorithm to quantify the impact of a centralised route guidance system. The congestion avoiding user optimum algorithm will add a perceived time penalty to all routes with links above a certain intensity/capacity ratio to avoid choosing the congested route. The cooperation is described by the coordinated approach model of the SOCRATES²·⁰ project. In this model, the cooperation is organised by an intermediary who takes on the management tasks. Because a lack of commitment could be a problem for the success of the system, the services of the intermediary can be regulated with four regulation strategies starting with no regulation to regulation for both service providers and road users. The impact is determined with the dynamic macroscopic traffic model MARPLE. The result shows that without commitment the system does not improve the traffic state. For the maximum potential of the system, it must be fully regulated for both service providers and road users. Although with only the commitment of service providers, there is already a positive impact on the traffic flow and in less complex networks it can already solve all congestion.

This thesis provides an insight into the role of dockless shared-bikes (Mobike) in Delft. The objective of is to fill the knowledge gap about the users of shared-bicycles and their motivations to use shared-bikes in Delft. A survey is and finally gained 91 useful results. 76% of respondents are students, and in general, people are highly educated. 46% of respondents are commuters who work/study in Delft, 5% are tourists, and the other half are living in Delft. Most of the Delft’s inhabitants also own a bike; they are classified as ‘casual’, occasional Mobike users with the main reason to use Mobike as a temporary replacement for their own bike. Most of the commuters, who live outside of Delft, do not own a bike in and use Mobike every (week)day. Their main motivator to use Mobike is out of convenience. All this information finally leads to the main conclusion about the role of dockless shared-bike in sustainable mobility in Delft. From this research, it turned out that 98% of Mobike trips is replacing trips made with other sustainable transport modes such as walking, other forms of cycling and public transport.

With the increasing use of big data in varied applications to improve decision making and provide new insights, the research explores the potential of the Uber Movement data set released by Uber comprising of travel times from one zone to the other. A better understanding of the potential of the dataset could lead to the addition of the existing tool kit of Transport planners and city officials at the municipality of Amsterdam. Moreover, it would be the first of a kind data set enabling an understanding of taxi movement in the city. The Uber Movement Travel Time comprises of the average travel time between two wijken, where the ‘sourceid’ and ‘dstid’ do not correspond to the origin and destination of a trip but simply represent the directionality of the travel time measured. The data is aggregated across different levels of temporal detail and the number of data points directly corresponds to the level of temporal aggregation. For instance, if the quarterly aggregated data for the different days of the week is downloaded, the number of data points between a ‘sourceid’ and ‘dstid’ cannot exceed seven. Three aspects of the data set were explored: 1) ability to capture the demand for Ubers 2) ability to capture recurrent congestion and 3) ability to capture non-recurrent congestion. While the data according to the Uber Movement and previously used instances, the data is suited for performance (recurrent congestion and non-recurrent congestion) and impact-related studies of the network. The absence of route related information limits the applications of the data. The potential of the data is also limited by the data sparsity. The potential of the data was best revealed through demand studies which indicated a skewed user group of tourists, airport users (to and fro), work-related trips and users using Ubers late at night. In addition, with respect to the goals of the municipality in managing traffic activity across different zones and time periods, by implementing and extending an existing model in the form of adding ‘occupancy related measures’ and ‘shortest path’. Thus, based on the data penetration levels and travel time data, the model developed offers insights at a strategic level to the city in the form of Spatio-temporal concentration of Uber vehicles, occupancy levels through the day. The potential of the data lies in its ability to offer strategic insights to the city of Amsterdam and the greater Amsterdam region in the form of the unique Spatio-temporal spread of Uber vehicles across different hours of the day.

Automated vehicles are conventional vehicles equipped with advanced sensors, controller and actuators. They achieve intelligent information exchange with the environment through the onboard sensing and cooperative system. vehicles are possible to have situation awareness and automatically analyze the safety and dangerous state of journeys. Finally vehicles can reach destinations following drivers' willing. The ongoing research on intelligent vehicles is mainly about improving the safety, comfort, efficiency and provide an excellent human-car interface. As a self-organizing system, the traffic system is quite complicated. There are many disturbance factors to lead to various traffic problems. One of the daily occurring problems is congestion on the motorway. In order to reduce congestion, Rijkswaterstaat applies various dynamic traffic management (DTM) measures to guide the traffic. It works well nowadays in conventional traffic. However, automated vehicles entered the market recently and will start to play an essential role in future traffic. The automated vehicles' reaction to DTM measures may be different from conventional vehicles while the traffic problems still exist. Therefore, it is necessary to research the effectiveness of current Dutch traffic management in automated vehicles. This thesis aims to investigate the effectiveness of current Dutch DTM measures with driver assistant and partially automated vehicles. Due to the time limitation, only the ramp metering measure will be researched through a simulation study. Therefore the main research question is 'How partial automated driving influences the performance of current Dutch dynamic traffic management system and how can this be evaluated via simulation?'. Three methods are applied, including literature review, simulation and statistical analysis. The literature part reviews levels of automation, various longitudinal and lateral vehicle motion models, which are chosen and modified in the simulation. Many ramp metering algorithms are also introduced in the literature review. The ramp metering controller in the simulation follows RWS algorithm. Besides, the motorway demand and the penetration rate of level 1 and 2 vehicles are two input of the simulation. From the simulation results, it is concluded that the level 2 automation consisting of Adaptive Cruise Control (ACC) and Lane Change Assistance (LCA) system brings a negative impact on the motorway capacity. The ramp metering measure remains efficient if the penetration rate of level 2 vehicles is low. However, when the capacity reduces to the critical flow set up in the ramp metering controller, Ramp metering loses its efficiency. The parameters in the ramp metering controller therefore, require an update. For further research, it is recommended to simulate the same scenarios with different ramp metering algorithms. Since the functions of the algorithms are different, there might be other robust control algorithms for automated vehicles. Besides, another limitation of this thesis is that the automation system in level 2 vehicles is defined as Adaptive Cruise Control (ACC) plus Lane Change Assistance (LCA) system. Other partial automation systems may have a different effect on the performance of ramp metering. This thesis can be expanded by research the ramp metering performance under various types of partial automation systems.

Dynamic traffic management (DTM) plays an important role from Dutch policy perspective to prevent road congestion and has been developed from control strategies to services. Five traffic control centers, 22 different DTM systems with 35 functions and over 50,000 DTM components make up the national traffic management network in the Netherlands. The malfunctioning of the DTM systems is expected to create negative impacts to the traffic, proper maintenance planning is necessary to ensure their availabilities. However, there is less knowledge about the DTM malfunctions, which makes it difficult to monetize the malfunction effects and therefore to optimally deploy the maintenance budget. In this research, a macroscopic dynamic traffic assignment model “MARPLE” is used to evaluate the social costs of the DTM malfunctions according to the failure function, failure duration, and failure location. The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified. This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts.

Approximately 200,000 individuals travel to & from Schiphol Airport daily through various means such as cars, taxis, buses, shuttles, trains, motorcycles, scooters, and bicycles. With this perspective, Schiphol Airport is the largest mobility hub in the whole Netherlands, making accessibility a critical aspect. The Schiphol Group is responsible for providing/ensuring accessibility. Their main goal is to alleviate accessibility for Schiphol's customers, including passengers, personnel/commuters, business partners, and cargo, by focusing on different transportation modalities. To achieve the goal of “the best airport for accessibility and sustainable aviation as well as land-side transport in Europe,” Schiphol Group works toward a car-free, emission-free vision and plans to apply on-site. This thesis conjugates Schiphol’s and European Union’s (EU) goals (EGD, TULIPS) set for the aviation sector and further investigates the possibility of reaching the “Car-free Schiphol Centrum”. The objectives designated the reach this primary goal. - A combined method to design and evaluate the car-free Schiphol Airport efficiency - A system that uses the methods to display the efficiency of the car-free Schiphol Airport. By exploring these objectives, the thesis aims to contribute to the overall goal of making Schiphol Airport a sustainable, accessible, and car-free hub for all commuters and users. The problem statement and main research question gather around this unifying goal: “How can Schiphol Airport become car-free in its land-side areas?” To address this question, the thesis proposes a combined method to design and evaluate the efficiency of a car-free Schiphol Airport. This method considers the goals set by the Schiphol Group and the European Union. The methodology constitutes the combination of the literature-based frameworks to create anew the thesis as well as finding the best measurement tools to seek the results of a successful car-free Schiphol Centrum. Car-free Development and Transit-oriented development allow for discussing and creating the framework for a car-free Schiphol Airport. The evaluation of this framework will be done by implementing new modalities to the Schiphol to ensure a possible/potential modal shift of the users and assess the walkability of the land-side areas. Along with the theoretical work, a case study for the thesis is conducted to apply the proposed methodology and evaluate its effectiveness. The case study focuses on the land-side areas of Schiphol Airport and aims to assess the feasibility of implementing car-free measures in these areas. The case study's findings show that a car-free Schiphol Centrum is feasible and should be implemented in real life. The proposed measures depict such as improving public transportation, promoting cycling and walking, and providing efficient and sustainable alternatives to private cars (micro mobility options), can contribute to reducing car dependency and creating a more sustainable and accessible airport. Overall, this thesis provides valuable insights and recommendations for achieving a car-free Schiphol Airport. By combining theoretical frameworks, measurement tools, and a practical case study.