The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles’ operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state.

The increasing shift towards battery electric vehicles (BEVs) in urban environments raises the question of how real-world traffic conditions affect their energy consumption. While BEVs are expected to reduce local emissions, their total energy demand, particularly in city traffic with with low average speeds, and therefore a higher impact of secondary consumption, remains insufficiently understood. To address this, a simulative framework to analyze the average energy consumption of an all-electric vehicle fleet in a mid-sized city, using Darmstadt, Germany, as a case study, is presented. A validated microscopic traffic simulation is built based on 2024 data and enriched with representative powertrain models for various vehicle classes, including passenger cars, trucks, and buses. The simulation allows the assessment of consumption under different traffic densities and speeds, revealing the substantial influence of secondary consumers and traffic flow on total energy demand. Furthermore, the study compares the $C{O}_2$ emissions of an all-BEV fleet with those of a fully combustion-based fleet. The findings aim to highlight the role of secondary consumers in urban traffic and to identify the potential for energy-saving.

Connected, automated, shared, and electric (CASE) vehicle concepts are considered a promising approach for improving the sustainability of urban mobility by increasing vehicle utilization and reducing fleet size. While the energy consumption of conventional battery electric vehicles has been investigated extensively, the influence of fleet size, speed limits, and ambient temperature on the energy demand of CASE vehicle fleets has received little attention. This study presents a simulative consumption analysis of an all-electric CASE vehicle fleet based on the EDAG CityBot concept. A validated microscopic traffic simulation of the city center of Darmstadt, Germany, is coupled with a backward-facing powertrain model and detailed secondary consumer models to determine the total fleet energy consumption under varying operating conditions. The analysis considers fleet sizes between 20% and 100% of a reference fleet, together with a 17% fleet size scenario, which allows for the fulfillment of the urban mobility demand according to the vehicle system provider. Besides fleet size, three urban speed limit scenarios and five ambient temperature scenarios are evaluated. Among the investigated fleet size scenarios, the lowest mean fleet energy demand is observed at a fleet size of 20%, resulting from the opposing effects of increasing driving energy consumption and decreasing secondary consumer energy consumption. However, the difference between the 20% and 17% scenarios is not statistically significant. Furthermore, the study demonstrates that secondary consumers, particularly automated driving hardware and heating, ventilation and air conditioning systems, represent a major contribution to the total energy consumption of CASE vehicles and must therefore be considered in fleet-level energy analyses. Although an individual CASE vehicle exhibits higher average energy consumption than a conventional battery-electric vehicle, primarily due to its greater average weight and rolling resistance, an increase in utilization of more than 16% would be sufficient to offset this disadvantage.