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Supporting user interaction with the range of electric buses in local public transport

Authors:
Implications + Next Steps
Range-Interaction in Electric Buses
Authors The “NuR.E” Project
External Factors Appraisal Optimization
barriers
Driving
behavior
E-Bus
configuration
Consequences
Dispatchers-
Info
Dispatchers-
Decision
Range
Assessment
Range
Optimization
Situation
E-Bus state
information
Dispatchers-
Appraisal
Dispatchers-
Tips
Factors for Range Utilization
General Range Utilization
Comfortable Range
71% 29%
Subjective Range Competence
Scale
Comfortable Range
Eco-Driving Motivation
“…difficulties in estimating the
range…?”
“…communication with the
dispatchers…?”
“…which information do
you wish to have… ?”
“…strategies/barriers of
extending the range?”
Method
Conference Paper
Energy-related behavior in resource dependent systems (e.g. electric vehicles, houses, ships) is an important factor for the actual energy efficiency such systems can achieve. Energy feedback human-machine-interfaces (HMIs) can support the awareness of energy dynamics in order to comprehend the situation and the influences on energy consumption and to control the system to enhance energy efficiency. To evaluate these HMIs, a scale to assess the energy dynamics awareness (EDA) is needed. Therefore, we developed the EDA scale with 7 items and tested the scale in a study with N = 40 battery electric bus (BEB) drivers on two different HMIs. First results indicated an excellent reliability (Cronbach's ą = .92 and .93) and principal factor analyses revealed a solid single factor structure (61.8% and 67.8% explained variance) with high factor loadings (> .61 for all items). Future studies should further explore the construct and criterion validity of the scale.
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