As Vehicle-to-Everything (V2X) communication technologies gain prominence, ensuring human safety from radiofrequency (RF) electromagnetic fields (EMF) becomes paramount. This study critically examines human RF exposure in the context of ITS-5.9 GHz V2X connectivity, employing a combination of numerical dosimetry simulations and targeted experimental measurements. The focus extends across Road-Side Units (RSUs), On-Board Units (OBUs), and, notably, the advanced vehicular technologies within a Tesla Model S, which includes Bluetooth, Long Term Evolution (LTE) modules, and millimeter-wave (mmWave) radar systems. Key findings indicate that RF exposure levels for RSUs and OBUs, as well as from Tesla’s integrated technologies, consistently remain below the International Commission on Non-Ionizing Radiation Protection (ICNIRP) exposure guidelines by a significant margin. Specifically, the maximum exposure level around RSUs was observed to be 10 times lower than ICNIRP reference level, and Tesla’s mmWave radar exposure did not exceed 0.29 W/m2, well below the threshold of 10 W/m2 set for the general public. This comprehensive analysis not only corroborates the effectiveness of numerical dosimetry in accurately predicting RF exposure but also underscores the compliance of current V2X communication technologies with exposure guidelines, thereby facilitating the protective advancement of intelligent transportation systems against potential health risks.
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The present invention refers to an autonomous road transport system based on autonomous vehicles operating similarly to trains on railways. In this system, a regular road vehicle, such as a car, bus or truck, can be properly equipped with sensors and computers to drive itself, guided by virtual tracks from one station to another. A virtual railroad is built from a set of stations connected by virtual rails. Virtual rails can be any type of technique or equipment capable of guiding the vehicle through the center of the road autonomously, such as advanced mapping and location techniques. The stations serve as a starting and stopping point for vehicles.
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This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users’ experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public.
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While modern construction vehicles often come equipped with proprietary telematic systems, a substantial portion of the global construction fleet consists of older machines that lack any form of digital monitoring. The exact share is unknown, but in many companies, legacy equipment still plays a critical role in daily operations. This gap limits the ability to track performance, optimize usage, or assess environmental impact. In response, this study presents a proof of concept for a low-cost, low-maintenance, plug-and-play solution designed to monitor the operational behaviour of such vehicles. The system combines a modular hardware unit with integrated Global Navigation Satellite System (GNSS) and accelerometers to capture data such as location, motion patterns, activity cycles, and engine RPM. All processing is performed locally on an edge device, eliminating the need for centralized computation or cloud connectivity. The goal is to provide a scalable and accessible tool for construction companies to better understand and manage their fleets, with future potential to link activity data to fuel consumption and emissions.
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Residential public charging points are shared by multiple electric vehicle drivers, often neighbours. Therefore, charging behaviour is embedded in a social context. Behaviours that affect, or are influenced by, other publiccharging point users have been sparsely studied and lack an overarching and comprehensive definition. Consequently, very few measures are applied in practice to influence charging behaviour. We aim to classify and define the social dimension of charging behaviour from a social-psychological perspective and, using a behaviour change framework, identify and analyse the measures to influence this behaviour. We interviewed 15 experts onresidential public charging infrastructure in the Netherlands. We identified 17 charging behaviours rooted in interpersonal interactions between individuals and interactions between individuals and technology. These behaviours can be categorised into prosocial and antisocial charging behaviours. Prosocial charging behaviour provides or enhances the opportunity for other users to charge their vehicle at the public charging point, for instance by charging only when necessary. Antisocial charging behaviour prevents or diminishes this opportunity, for instance by occupying the charging point after charging, intentionally or unintentionally. We thenidentified 23 measures to influence antisocial and prosocial charging behaviours. These measures can influence behaviour through human–technology interaction, such as providing charging etiquettes to new electric vehicle drivers or charging idle fees, and interpersonal interaction, such as social pressure from other charging point users or facilitating social interactions to exchange requests. Our approach advocates for more attention to the social dimension of charging behaviour.
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from the article: "Abstract The way in which construction logistics is organised has considerable impact on production flow, transportation efficiency, greenhouse gas emissions and congestion, particularly in urban areas such as city centres. In cities such as London and Amsterdam municipalities have issued new legislation and stricter conditions for vehicles to be able to access cities and city centres in particular. Considerate clients, public as well private, have started developing tender policies to encourage contractors to reduce the environmental impact of construction projects. This paper reports on an ongoing research project applying and assessing developments in the field of construction logistics in the Netherlands. The cases include contractors and third party logistics providers applying consolidation centres and dedicated software solutions to increase transportation efficiency. The case show various results of JIT logistics management applied to urban construction projects leading to higher transportation efficiencies, and reduced environmental impact and increased production efficiency on site. The data collections included to-site en on-site observations, measurement and interviews. The research has shown considerable reductions of vehicles to deliver goods and to transport workers to site. In addition the research has shown increased production flow and less waste such as inventory, waiting and unnecessary motion on site."
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Two key air pollutants that affect asthma are ozone and particle pollution. Studies show a direct relationship between the number of deaths and hospitalizations for asthma and increases of particulate matter in the air, including dust, soot, fly ash, diesel exhaust particles, smoke, and sulfate aerosols. Cars are found to be a primary contributor to this problem. However, patient awareness of the link is limited. This chapter begins with a general discussion of vehicular dependency or ‘car culture’, and then focuses on the discussion of the effects of air pollution on asthma in the Netherlands. I argue that international organizations and patient organizations have not tended to put pressure on air-control, pollution-control or environmental standards agencies, or the actual polluters. While changes in air quality and the release of greenhouse gases are tied to practices like the massive corporate support for the ongoing use of motor vehicles and the increased prominence of ‘car culture’ globally, patient organizations seem more focused on treating the symptoms rather than addressing the ultimate causes of the disease. Consequently, I argue that to fully address the issue of asthma the international health organizations as well as national health ministries, patient organizations, and the general public must recognize the direct link between vehicular dependency and asthma. The chapter concludes with a recommendation for raising environmental health awareness by explicitly linking the vehicular dependency to the state of poor respiratory health. Strategic policy in the Netherlands then should explicitly link the present pattern of auto mobility to public health. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118786949 LinkedIn: https://www.linkedin.com/in/helenkopnina/
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Densely populated areas are major sources of air, soil and water pollution. Agriculture, manufacturing, consumer households and road traffic all have their share. This is particularly true for the country featured in this paper: the Netherlands. Continuous pollution of the air and soil manifests itself as acification, decalcification and eutrofication. Biodiversity becomes lower and lower in nature areas. Biological farms are also under threat. In case of mobility, local air pollution may have a huge health impact. Effective policy is called for, after high courts blocked construction projects, because of foreseen building- and transport-related NOx emissions. EU law makers are after Dutch governments, because these favoured economics and politics over environmental and liveability concerns. But, people in the Netherlands are strongly divided. The latest provincial elections were dominated by environmental concerns, next to many socio-economic issues. NOx and CO2 emissions by passenger cars are in focus. Technical means and increasing fuel economy norms strongly reduced NOx emissions to a still too high level. A larger number of cars neutralized a technological reduction of CO2 emissions. The question is: What would be the impact of a drastic mandatory reduction in CO2, NOx, and PM10 emissions on car ownership and use in the Netherlands? The authors used literature, scenario analysis and simulation modelling to answer this question. Electric mobility could remove these emissions. Its full impact will only be achieved if the grid-mix, which is still dominated by fossil fuels, becomes green(er), which is a gradual, long-term, process. EVs compete with other consumers of electricity, as many other activities, such as heating, are also electrifying. With the current grid-mix, it is inevitable that the number of km per vehicle per year is reduced to reach the scenario targets (−25% resp. −50% CO2 emissions by cars). This calls for an individual mobility budget per car user.
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With a growing number of electric vehicles (EVs) on the road and charging infrastructure investments lagging, occupation of installed charging stations is growing and available charging points for EV drivers are becoming scarce. Installing more charging infrastructure is problematic from both a public(tax payers money, parking availability) and private (business case) perspective. Increasing the utilization of available charging stations is one of the solutions to satisfy the growing charging need of EV drivers and managing other stakeholders interests. Currently, in the Netherlands only 15-25% of the time connected to a public charging station is actually used for charging. The longest 4% of all sessions account for over 20% of all time connected while barely using this time for actually charging. The behaviour in which EV users stay connected to a charging station longer than necessary to charge their car is called “charging station hogging”. Using a large dataset (1.3 million sessions) on publiccharging infrastructure usage, this paper analyses the inefficient use of charging stations along three axes: where the hogging takes place (spatial), by whom (the characteristics of the user) and during which time frames (day, week and year). Using the results potential solutions are evaluated and assessed including their potential and pitfalls.
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The ever-increasing electrification of society has been a cause of utility grid issues in many regions around the world. With the increased adoption of electric vehicles (EVs) in the Netherlands, many new charge points (CPs) are required. A common installation practice of CPs is to group multiple CPs together on a single grid connection, the so-called charging hub. To further ensure EVs are adequately charged, various control strategies can be employed, or a stationary battery can be connected to this network. A pilot project in Amsterdam was used as a case study to validate the Python model developed in this study using the measured data. This paper presents an optimisation of the battery energy storage capacity and the grid connection capacity for such a P&R-based charging hub with various load profiles and various battery system costs. A variety of battery control strategies were simulated using both the optimal system sizing and the case study sizing. A recommendation for a control strategy is proposed.
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