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On-Demand Automotive Fleet Electrification Can Catalyze Global Transportation Decarbonization and Smart Urban Mobility
journal contribution
posted on 2020-05-29, 23:03 authored by Gordon Bauer, Cheng Zheng, Jeffery B. Greenblatt, Susan Shaheen, Daniel M. KammenMobility
on-demand vehicle (MODV) services have grown explosively
in recent years, threatening targets for local air pollution and global
carbon emissions. Despite evidence that on-demand automotive fleets
are ripe for electrification, adoption of battery electric vehicles
(BEVs) in fleet applications has been hindered by lack of charging
infrastructure and long charging times. Recent research on electrification
programs in Chinese megacities suggests that top-down policy targets
can spur investment in charging infrastructure, while intelligent
charging coordination can greatly reduce requirements for battery
range and infrastructure, as well as revenue losses due to time spent
charging. Such capability may require labor policy reform to allow
fleet operators to manage their drivers’ charging behavior,
along with collection and integration of several key data sets including
(1) vehicle trajectories and energy consumption, (2) charging infrastructure
installation costs, and (3) real-time charging station availability.
In turn, digitization enabled by fleet electrification holds the potential
to enable a host of smart urban mobility strategies, including integration
of public transit with innovative transportation systems and emission-based
pricing policies.
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energy consumptiontransportation systemsdata setsChinese megacitiesOn-Demand Automotive Fleet Electrificationlabor policy reformmobility strategiescarbon emissionsBEVintegrationinfrastructure installation costsrevenue lossesemission-based pricing policiesbattery rangeSuch capabilityRecent researchelectrification programsfleet applicationsSmart Urban Mobility Mobility on-demand vehiclefleet operatorsstation availabilityMODVCatalyze Global Transportation Decarbonizationair pollutionfleet electrificationtop-down policy targets
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