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Assessing travel time savings and user benefits of automated driving – A case study for a commuting relation

Eckhard Szimba and Martin Hartmann

Transport Policy, 2020, vol. 98, issue C, 229-237

Abstract: Combining cooperative vehicle driving behavior of Connected and Automated Vehicles with supporting information infrastructure, is expected to increase the capacity of roadway infrastructure, which in turn results in travel time savings and user benefits. Automated driving also relieves the driver from steering the car, allowing to conduct other activities during the trip, which is likely to generate further user benefits. In order to assess the magnitude of automated driving on travel time-related user benefits, a typical commuting relation is analyzed, considering three route options as well as level 4 and 5 vehicle automation. The impacts on travel times are estimated by microscopic traffic flow simulations. The simulations reveal that around 27% of the travel time can be saved on a commuting relation due to road automation according to level 5. For level 4 vehicles the travel time savings amount to up to 20%. User benefits that accrue from time savings and the passenger's option of using travelling time for activities other than conducting the car, are expected at a relevant magnitude. Even under consideration of higher operating costs of an automated car, significant user benefits accrue: 1,310–2,240 € p.a. for level 4 and 2,770–3,440 € p.a. for level 5 vehicles during a passenger car's typical depreciation period. Thus, automated driving will decrease the commuters' generalized user costs for individual motorized mobility, which is likely to enhance the urban hinterland's attractiveness as residential area. This pattern and inherent second-order effects pose challenges for transport, land use and urban planners. Furthermore, it represents a challenge for transport research: to elaborate appropriate concepts that allow for exploiting the benefits of use of automated vehicles while countervailing undesirable socio-economic effects, as well as strains on the transport system and land use.

Keywords: Automated driving; Infrastructure capacity; Assessment; Travel time savings; User benefits; Generalized user costs; Case study (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.tranpol.2020.03.007

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