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Smartphone sensors can collect data in many different contexts. They make it feasible to obtain large amounts of data at little or no cost because most people own mobile phones. In this work, we focus on collecting motion data in the car using a smartphone. Motion sensors, such as accelerometers and gyroscopes, can help obtain information about the vehicle’s dynamics. However, the different positioning of the smartphone in the car leads to difficulty interpreting the sensed data due to an unknown orientation, making the collection useless. Thus, we propose an approach to automatically re-orient smartphone data collected in the car to a standardized orientation (i.e., with zero yaw, roll, and pitch angles with respect to the vehicle). We use a combination of a least-square plane approximation and a Machine Learning model to infer the relative orientation angles. Then we populate rotation matrices and perform the data rotation. We trained the model by collecting data using a vehicle physics simulator.

This dissertation presents four empirical analyses on the urban economic effects of private vehicles. These analyses contribute to the current debate on urban and transport policy, covering topics ranging from the efficacy of hourly and residential parking prices, to the implications of in-vehicle distractions on road safety, and the long-term impact of cars on urban density. In each case, the empirical estimates are applied to improve our understanding of how automated vehicles (AVs) may impact our cities in the future. In cities, parking occupies a large share of land and is often provided to residents and visitors at prices below the market rate. According to economic theory, this causes excess car ownership and use; however, we lack well-defined quantitative estimates of these effects. Chapter 2 examines the effect of a large citywide increase in hourly on-street parking prices on parking and traffic demand in Amsterdam. Our findings indicate that the citywide increase in hourly on-street parking prices in 2019 of 66%, resulted in 9% fewer on-street parking arrivals and an overall reduction in traffic flow of around 2% - 3%. Chapter 3 focuses specifically on residents and examines how residential parking prices affect car ownership decisions. Our results indicate that for city centres, annual residential parking costs are around €1000, or roughly 17 percent of car ownership costs, and are more than double the costs in the periphery. Households facing one standard deviation (€503) higher annual parking costs own 0.085 fewer cars, corresponding to a price elasticity of car demand of about -0.7. This implies that the disparity in parking costs explains around 30% of the difference in average car ownership rates between the city centre and the periphery. These two chapters support the abundant theoretical literature, which indicates that parking prices are an integral part of urban transport policy. Chapter 4 studies how the rise in smartphone use over the past decade has impacted road safety in the Netherlands. Our results suggest that about 10% of vehicle accidents are caused by smartphone use and that these accidents mainly happen on urban roads. The findings imply that you are about 3.8 times more likely to cause an accident if using a mobile phone, which is larger than earlier field studies performed on data before the prevalence of widespread smartphone adoption. Chapter 5 studies the long-term effect of cars on urban density. Using a global sample of cities, we find that a one standard deviation increase in car ownership rates causes a reduction in population density of around 40%. This effect appears to be driven by expansions in the built-up area, suggesting that cars facilitate lower density development in the periphery. AVs are expected to result in improvements to accessibility and safety, increases in car demand, and a redistribution of people and jobs over space. Chapters 2 and 3 demonstrate how lower parking prices are expected to result in more traffic and vehicle demand within cities. Chapter 4 provides an indication for the potential safety benefits from AVs due to fewer smartphone distractions. Finally, Chapter 5 examines how increases in vehicle access and demand, due to cheaper and more comfortable car travel, are expected to impact urban population density in the long-run.

This dissertation presents four empirical analyses on the urban economic effects of private vehicles. These analyses contribute to the current debate on urban and transport policy, covering topics ranging from the efficacy of hourly and residential parking prices, to the implications of in-vehicle distractions on road safety, and the long-term impact of cars on urban density. In each case, the empirical estimates are applied to improve our understanding of how automated vehicles (AVs) may impact our cities in the future. In cities, parking occupies a large share of land and is often provided to residents and visitors at prices below the market rate. According to economic theory, this causes excess car ownership and use; however, we lack well-defined quantitative estimates of these effects. Chapter 2 examines the effect of a large citywide increase in hourly on-street parking prices on parking and traffic demand in Amsterdam. Our findings indicate that the citywide increase in hourly on-street parking prices in 2019 of 66%, resulted in 9% fewer on-street parking arrivals and an overall reduction in traffic flow of around 2% - 3%. Chapter 3 focuses specifically on residents and examines how residential parking prices affect car ownership decisions. Our results indicate that for city centres, annual residential parking costs are around €1000, or roughly 17 percent of car ownership costs, and are more than double the costs in the periphery. Households facing one standard deviation (€503) higher annual parking costs own 0.085 fewer cars, corresponding to a price elasticity of car demand of about -0.7. This implies that the disparity in parking costs explains around 30% of the difference in average car ownership rates between the city centre and the periphery. These two chapters support the abundant theoretical literature, which indicates that parking prices are an integral part of urban transport policy. Chapter 4 studies how the rise in smartphone use over the past decade has impacted road safety in the Netherlands. Our results suggest that about 10% of vehicle accidents are caused by smartphone use and that these accidents mainly happen on urban roads. The findings imply that you are about 3.8 times more likely to cause an accident if using a mobile phone, which is larger than earlier field studies performed on data before the prevalence of widespread smartphone adoption. Chapter 5 studies the long-term effect of cars on urban density. Using a global sample of cities, we find that a one standard deviation increase in car ownership rates causes a reduction in population density of around 40%. This effect appears to be driven by expansions in the built-up area, suggesting that cars facilitate lower density development in the periphery. AVs are expected to result in improvements to accessibility and safety, increases in car demand, and a redistribution of people and jobs over space. Chapters 2 and 3 demonstrate how lower parking prices are expected to result in more traffic and vehicle demand within cities. Chapter 4 provides an indication for the potential safety benefits from AVs due to fewer smartphone distractions. Finally, Chapter 5 examines how increases in vehicle access and demand, due to cheaper and more comfortable car travel, are expected to impact urban population density in the long-run.

This dissertation presents four empirical analyses on the urban economic effects of private vehicles. These analyses contribute to the current debate on urban and transport policy, covering topics ranging from the efficacy of hourly and residential parking prices, to the implications of in-vehicle distractions on road safety, and the long-term impact of cars on urban density. In each case, the empirical estimates are applied to improve our understanding of how automated vehicles (AVs) may impact our cities in the future. In cities, parking occupies a large share of land and is often provided to residents and visitors at prices below the market rate. According to economic theory, this causes excess car ownership and use; however, we lack well-defined quantitative estimates of these effects. Chapter 2 examines the effect of a large citywide increase in hourly on-street parking prices on parking and traffic demand in Amsterdam. Our findings indicate that the citywide increase in hourly on-street parking prices in 2019 of 66%, resulted in 9% fewer on-street parking arrivals and an overall reduction in traffic flow of around 2% - 3%. Chapter 3 focuses specifically on residents and examines how residential parking prices affect car ownership decisions. Our results indicate that for city centres, annual residential parking costs are around €1000, or roughly 17 percent of car ownership costs, and are more than double the costs in the periphery. Households facing one standard deviation (€503) higher annual parking costs own 0.085 fewer cars, corresponding to a price elasticity of car demand of about -0.7. This implies that the disparity in parking costs explains around 30% of the difference in average car ownership rates between the city centre and the periphery. These two chapters support the abundant theoretical literature, which indicates that parking prices are an integral part of urban transport policy. Chapter 4 studies how the rise in smartphone use over the past decade has impacted road safety in the Netherlands. Our results suggest that about 10% of vehicle accidents are caused by smartphone use and that these accidents mainly happen on urban roads. The findings imply that you are about 3.8 times more likely to cause an accident if using a mobile phone, which is larger than earlier field studies performed on data before the prevalence of widespread smartphone adoption. Chapter 5 studies the long-term effect of cars on urban density. Using a global sample of cities, we find that a one standard deviation increase in car ownership rates causes a reduction in population density of around 40%. This effect appears to be driven by expansions in the built-up area, suggesting that cars facilitate lower density development in the periphery. AVs are expected to result in improvements to accessibility and safety, increases in car demand, and a redistribution of people and jobs over space. Chapters 2 and 3 demonstrate how lower parking prices are expected to result in more traffic and vehicle demand within cities. Chapter 4 provides an indication for the potential safety benefits from AVs due to fewer smartphone distractions. Finally, Chapter 5 examines how increases in vehicle access and demand, due to cheaper and more comfortable car travel, are expected to impact urban population density in the long-run.

This dissertation presents four empirical analyses on the urban economic effects of private vehicles. These analyses contribute to the current debate on urban and transport policy, covering topics ranging from the efficacy of hourly and residential parking prices, to the implications of in-vehicle distractions on road safety, and the long-term impact of cars on urban density. In each case, the empirical estimates are applied to improve our understanding of how automated vehicles (AVs) may impact our cities in the future. In cities, parking occupies a large share of land and is often provided to residents and visitors at prices below the market rate. According to economic theory, this causes excess car ownership and use; however, we lack well-defined quantitative estimates of these effects. Chapter 2 examines the effect of a large citywide increase in hourly on-street parking prices on parking and traffic demand in Amsterdam. Our findings indicate that the citywide increase in hourly on-street parking prices in 2019 of 66%, resulted in 9% fewer on-street parking arrivals and an overall reduction in traffic flow of around 2% - 3%. Chapter 3 focuses specifically on residents and examines how residential parking prices affect car ownership decisions. Our results indicate that for city centres, annual residential parking costs are around €1000, or roughly 17 percent of car ownership costs, and are more than double the costs in the periphery. Households facing one standard deviation (€503) higher annual parking costs own 0.085 fewer cars, corresponding to a price elasticity of car demand of about -0.7. This implies that the disparity in parking costs explains around 30% of the difference in average car ownership rates between the city centre and the periphery. These two chapters support the abundant theoretical literature, which indicates that parking prices are an integral part of urban transport policy. Chapter 4 studies how the rise in smartphone use over the past decade has impacted road safety in the Netherlands. Our results suggest that about 10% of vehicle accidents are caused by smartphone use and that these accidents mainly happen on urban roads. The findings imply that you are about 3.8 times more likely to cause an accident if using a mobile phone, which is larger than earlier field studies performed on data before the prevalence of widespread smartphone adoption. Chapter 5 studies the long-term effect of cars on urban density. Using a global sample of cities, we find that a one standard deviation increase in car ownership rates causes a reduction in population density of around 40%. This effect appears to be driven by expansions in the built-up area, suggesting that cars facilitate lower density development in the periphery. AVs are expected to result in improvements to accessibility and safety, increases in car demand, and a redistribution of people and jobs over space. Chapters 2 and 3 demonstrate how lower parking prices are expected to result in more traffic and vehicle demand within cities. Chapter 4 provides an indication for the potential safety benefits from AVs due to fewer smartphone distractions. Finally, Chapter 5 examines how increases in vehicle access and demand, due to cheaper and more comfortable car travel, are expected to impact urban population density in the long-run.

This article is concerned with the interaction of regulated efficiency and World Trade Organization (WTO) accession and its impact on China's motor vehicle sector. The analysis is conducted using a 23 sector-25 region computable general equilibrium model. Regulatory reform and internal restructuring are found to be critical. Restructuring is represented by a cost reduction following from consolidation and rationalization that moves costs toward global norms. Without restructuring, WTO accession means a surge of final imports, though imports of parts could well fall as production moves offshore. However, with restructuring, the final assembly industry can be made competitive by world standards, with a strengthened position for the industry.

The objective of this project is to determine the trajectory of the vehicle in situations where the GPS signal is not sufficient to obtain the localization correctly, that is to say, when there is no signal or it is too low, e.g., parking lots or tunnels. This way we can know the position where the vehicle has parked on the case of a car park, or in general terms, act as an indoor localization system. The system will combine information from the vehicle with data from the sensors of a smartphone to be able to know the path of it, from the point where the GPS localization is lost until the vehicle parks. Moreover, the system will correct the path in case of deviation due to sensor errors. We conclude that the system is capable of printing the trajectory thanks to the diverse sensors and that it can make little corrections in known environments such as a parking lot. El objetivo de este proyecto es determinar la trayectoria del vehículo en situaciones donde la señal del GPS no es adecuada para obtener la localización correctamente, es decir, cuando no hay señal o esta es muy baja, por ejemplo, en parkings o túneles. De esta manera podremos conocer el lugar donde ha aparcado el conductor en el caso de un parking, o de manera más general, funcionar como sistema de localización en interiores. El sistema combinará la información procedente del vehículo junto con información de los sensores de un smartphone para poder conocer el recorrido de este, desde el punto en el que se pierde la localización GPS hasta que el vehículo aparca. Además, el sistema corregirá la trayectoria en caso de desviación debido a los errores que introducen los sensores. Concluimos que el sistema es capaz de recuperar la trayectoria gracias a los diversos sensores y que puede efectuar pequeñas correcciones en entornos conocidos como puede ser un parking. L'objectiu d'aquest projecte és determinar la trajectòria del vehicle en situacions on la senyal del GPS no és adequada per obtenir la localització correctament, és a dir, quan no hi ha senyal o aquesta és molt baixa, per exemple, en pàrquings o túnels. D'aquesta manera podrem conèixer el lloc on ha aparcat el conductor en el cas d'un pàrquing, o de manera més general, funcionar com a sistema de localització en interiors. El sistema combinarà la informació procedent del vehicle junt amb informació dels sensors d'un smartphone per poder conèixer el recorregut d'aquest, des del punt en que es perd la localització GPS fins que el vehicle aparca. Addicionalment, el sistema corregirà la trajectòria en cas de desviació degut als errors que introdueixen els sensors. Concloem que el sistema és capaç de recuperar la trajectòria gràcies als diversos sensors i que pot efectuar petites correccions en entorns coneguts com pot ser un pàrquing.