City authorities want to know how to match the charging infrastructures for electric vehicles with the demand. Using camera recognition algorithms from artificial intelligence we investigated the behavior of taxis at a charging stations and a taxi stand.
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Recent studies show that charging stations are operated in an inefficient way. Due to the fact that electric vehicle (EV) drivers charge while they park, they tend to keep the charging station occupied while not charging. This prevents others from having access. This study is the first to investigate the effect of a pricing strategy to increase the efficient use of electric vehicle charging stations. We used a stated preference survey among EV drivers to investigate the effect of a time-based fee to reduce idle time at a charging station. We tested the effect of such a fee under different scenarios and we modelled the heterogeneity among respondents using a latent class discrete choice model. We find that a fee can be very effective in increasing the efficiency at a charging station but the response to the fee varies among EV drivers depending on their current behaviour and the level of parking pressure they experience near their home. From these findings we draw implications for policy makers and charging point operators who aim to optimize the use of electric vehicle charging stations.
This paper analyses the effect of two new developments: electrification and ‘free floating’ car sharing and their impact on public space. Contrary to station based shared cars, free floating cars do not have dedicated parking or charging stations. They therefore park at public parking spots and utilize public charging stations. A proper network of public charging stations is therefore required in order to keep the free floating fleet up and running. As more municipalities are considering the introduction of an electric free floating car sharing system, the outline of such a public charging network becomes a critical piece of information. The objective of this paper is to create insights that can optimize charging infrastructure for free floating shared cars, by presenting three analyses. First, a business area analysis shows an insight into which business areas are of interest to such a system. Secondly, the parking and charging behaviour of the vehicles is further examined. The third option looks deeper into the locations and their success factors. Finally, the results of the analysis of the city of Amsterdam are used to model the city of The Hague and the impact that a free floating electric car sharing system might have on the city and which areas are the white spots that need to be filled in.
