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Impact of vehicle automation and electric propulsion on production costs for mobility services worldwide
Becker H., Becker F., Abe R., Bekhor S., Belgiawan P.F., Compostella J., Frazzoli E., Fulton L.M., Guggisberg Bicudo D., Murthy Gurumurthy K., Hensher D.A., Joubert J.W., Kockelman K.M., Kroger L., Le Vine S., Malik J., Marczuk K., Ashari Nasution R., Rich J., Papu Carrone A., Shen D., Shiftan Y., Tirachini A., Wong Y.Z., Zhang M., Bosch P.M., Axhausen K.W.
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 The AuthorsAutomated driving technology along with electric propulsion are widely expected to fundamentally change our transport systems. They may not only allow a more productive use of travel time, but will likely trigger completely new business models in the mobility market. A key determinant of the future prospects of both existing and new mobility services will be their production costs. Hence, in this research the production costs of various transport modes both today and in an automated-electric future are analyzed. To account for different local contexts, the study is conducted for 17 cities across the globe. The results indicate that high-income countries will benefit the most from vehicle automation, while only smaller changes can be expected in lower-income countries. This is due to the different relative contribution of labor cost to the total cost of current taxi and bus operations. In a likely final state, transportation costs will be largely decoupled from a country’s income level, which will favor productivity in higher-income locations. While this research provides valuable first insights into potential future developments, the underlying assumptions will need to be updated as better information becomes available.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Automated driving,Key determinants,Mobility service,New business models,Relative contribution,Transport systems,Transportation cost,Vehicle automations[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Automated vehicles,Cost structures,Driverless vehicles,International comparison,Market segments,Taxi[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][{‘$’: “This research has been carried out in the context of the project Induced Demand by Autonomous Vehicles (SVI project 2016/001). Support from CONICYT Chile (Grant PIA/BASAL AFB180003) is also acknowledged. Furthermore, this paper contributes to the research program of the Volvo Research and Educational Foundation’s Bus Rapid Transit (BRT+) Centre of Excellence. We acknowledge the Foundation for funding support. We further acknowledge Tobias Kuhnimhof for his assistance with the Berlin case as well as Meygantara Faozal Holieff for his help on the Jakarta data. Special thanks go to Xiao Sun for her assistance in compiling the supplementary material for this paper.”}, {‘$’: ‘This research has been carried out in the context of the project Induced Demand by Autonomous Vehicles (SVI project 2016/001). Support from CONICYT Chile (Grant PIA/BASAL AFB180003) is also acknowledged. Furthermore, this paper contributes to the research program of the Volvo Research and Educational Foundation’s Bus Rapid Transit (BRT+) Centre of Excellence. We acknowledge the Foundation for funding support.’}][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.tra.2020.04.021[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]