Long waiting delays for users and significant imbalances in vehicle distribution are bothering traditional station-based one-way electric car-sharing system operators.To address the problems above,a“demand forecast-s...Long waiting delays for users and significant imbalances in vehicle distribution are bothering traditional station-based one-way electric car-sharing system operators.To address the problems above,a“demand forecast-station status judgement-vehicle relocation”multistage dynamic relocation algorithm based on the automatic formation cruising technology was proposed in this study.In stage one,a novel trip demand forecast model based on the long short-term memory network was established to predict users'car-pickup and car-return order volumes at each station.In stage two,a dynamic threshold interval was determined by combining the forecast results with the actual vehicle distribution among stations to evaluate the status of each station.Then vehicle-surplus,vehicleinsufficient,vehicle-normal stations,and the number of surplus or insufficient vehicles for each station were counted.In stage three,setting driving mileage and carbon emission as the optimization objectives,an integer linear programming mathematical model was constructed and the optimal vehicle relocation scheme was obtained by the commercial solver Gurobi.Setting 43 stations and 187 vehicles in Jiading District,Shanghai,China,as a case study,results showed that rapid vehicle rebalancing among stations with minimum carbon emissions could be realized within 15 min and the users’car-pickup and car-return demands could be fully satisfied without any refusal.展开更多
Social media applications are essential for next-generation connectivity.Today,social media are centralized platforms with a single proprietary organization controlling the network and posing critical trust and govern...Social media applications are essential for next-generation connectivity.Today,social media are centralized platforms with a single proprietary organization controlling the network and posing critical trust and governance issues over the created and propagated content.The ARTICONF project funded by the European Union's Horizon 2020 program researches a decentralized social media platform based on a novel set of trustworthy,resilient and globally sustainable tools that address privacy,robustness and autonomy-related promises that proprietary social media platforms have failed to deliver so far.This paper presents the ARTICONF approach to a car-sharing decentralized application(DApp)use case,as a new collaborative peer-to-peer model providing an alternative solution to private car ownership.We describe a prototype implementation of the car-sharing social media DApp and illustrate through real snapshots how the different ARTICONF tools support it in a simulated scenario.展开更多
Fostering co-modality and consequently reducing carbon emissions is a leading objective of the Scottish and UK governments and the wider EU and worldwide community.The achievement of such goals can be facilitated by t...Fostering co-modality and consequently reducing carbon emissions is a leading objective of the Scottish and UK governments and the wider EU and worldwide community.The achievement of such goals can be facilitated by the adoption of ICT measures within the transport systems.Over recent years,many online and mobile applications have emerged which improve the usability and attractiveness of more sustainable transport modes(such as public transport,taxis,and cycling)and can help to utilise private cars more effectively by promoting and enabling car-sharing and car-pooling.The recently completed FP7 funded EU project COMPASS has investigated the impact of a range of Information and Communication Technology(ICT)tools which have the potential to improve co-modality.This paper discusses the results of Scotland specific modelling which demonstrates and quantifies the relative carbon/congestion reductions feasible from ICT measures to improve bus journey times and ICT measures to improve car-sharing.It may be seen that measures which act to decrease overall car usage have more impact on reduction of carbon emissions than measures to improve public transport travel-times.展开更多
基金supported by the Science and Technology Project of State Grid Corporation of China“Research on urban power grid dispatching technology for large-scale electric vehicles integration”(grant number 5108202119040A-0-0-00)。
文摘Long waiting delays for users and significant imbalances in vehicle distribution are bothering traditional station-based one-way electric car-sharing system operators.To address the problems above,a“demand forecast-station status judgement-vehicle relocation”multistage dynamic relocation algorithm based on the automatic formation cruising technology was proposed in this study.In stage one,a novel trip demand forecast model based on the long short-term memory network was established to predict users'car-pickup and car-return order volumes at each station.In stage two,a dynamic threshold interval was determined by combining the forecast results with the actual vehicle distribution among stations to evaluate the status of each station.Then vehicle-surplus,vehicleinsufficient,vehicle-normal stations,and the number of surplus or insufficient vehicles for each station were counted.In stage three,setting driving mileage and carbon emission as the optimization objectives,an integer linear programming mathematical model was constructed and the optimal vehicle relocation scheme was obtained by the commercial solver Gurobi.Setting 43 stations and 187 vehicles in Jiading District,Shanghai,China,as a case study,results showed that rapid vehicle rebalancing among stations with minimum carbon emissions could be realized within 15 min and the users’car-pickup and car-return demands could be fully satisfied without any refusal.
基金funding from the European Union's Horizon 2020 research and innovation program under grant agreement number 825134funded the deployemnt and integration of the blockchain platform at the University of Klagenfurt under the grant agreement 881703(ADAPT project).
文摘Social media applications are essential for next-generation connectivity.Today,social media are centralized platforms with a single proprietary organization controlling the network and posing critical trust and governance issues over the created and propagated content.The ARTICONF project funded by the European Union's Horizon 2020 program researches a decentralized social media platform based on a novel set of trustworthy,resilient and globally sustainable tools that address privacy,robustness and autonomy-related promises that proprietary social media platforms have failed to deliver so far.This paper presents the ARTICONF approach to a car-sharing decentralized application(DApp)use case,as a new collaborative peer-to-peer model providing an alternative solution to private car ownership.We describe a prototype implementation of the car-sharing social media DApp and illustrate through real snapshots how the different ARTICONF tools support it in a simulated scenario.
文摘Fostering co-modality and consequently reducing carbon emissions is a leading objective of the Scottish and UK governments and the wider EU and worldwide community.The achievement of such goals can be facilitated by the adoption of ICT measures within the transport systems.Over recent years,many online and mobile applications have emerged which improve the usability and attractiveness of more sustainable transport modes(such as public transport,taxis,and cycling)and can help to utilise private cars more effectively by promoting and enabling car-sharing and car-pooling.The recently completed FP7 funded EU project COMPASS has investigated the impact of a range of Information and Communication Technology(ICT)tools which have the potential to improve co-modality.This paper discusses the results of Scotland specific modelling which demonstrates and quantifies the relative carbon/congestion reductions feasible from ICT measures to improve bus journey times and ICT measures to improve car-sharing.It may be seen that measures which act to decrease overall car usage have more impact on reduction of carbon emissions than measures to improve public transport travel-times.
