The Dutch government decided to implement a road pricing system called, 'paying differently for mobility'. The main idea is that road users have to pay for using the road infrastructure instead of for owning a car. In the future, the price per kilometre will also depend on the time of the day and the location of the travel. Crowded locations and peak hours will be charged at a higher price per kilometre. In this study we examine the expected effect of the proposed road pricing scheme on logistics decisions to supply stores in urban areas based on in-depth interviews with carriers. Based on the revealed logistics reaction to current developments, such as the German LKW Maut, increasing congestion and the high fuel prices in 2008 and the stated reaction to the proposed road pricing scheme, we derive the expected impact of the scheme for urban goods transport in the Netherlands. The expected reactions differ between for-hire carries, shippers and private carriers. In the short term, carriers try to limit logistics changes by passing on extra costs or absorbing the extra costs in their margins. In the longer term, logistics changes are to be expected.
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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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Currently EVs constitute only 1% of all vehicles on the road. We are at the eve of the large scale introduction of EVs. Large scale introduction requires a significant growth in charging infrastructure. In an urban context, in which many rely on on-street charging facilities, policy makers deal with a large number of concerns. Policy makers are uncertain about which charging deployment strategy to follow. This paper presents results from simulating different strategies for charging infrastructure roll to facilitate a large scale introduction of EVs using agent based simulation. In contrast to other models, the model uses observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. The simulation incorporates different user types (Inhabitants, visitors, taxis and sharing) to model the complexity of charging in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging), the intensity of rollout (EV to Charging point ratio) and adoption rates. The simulation measures both the success rate and the additional miles cruising for a charging station. Results shows that scaling effects in charging infrastructure exist allowing for more efficient use of the infrastructure at a larger size.
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