The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, Picnik); and same-day courier services (e.g., Amazon Same-Day Delivery) has significantly enhanced both convenience and safety for customers, particularly during the COVID-19 pandemic.

Despite their rapid growth, on-demand transportation services bear several challenges for key stakeholders. The private sector, which includes online platforms, strives to optimize system efficiency and revenue through advanced artificial intelligence techniques and optimization methods. Meanwhile, the public sector aims to strike a balance between the interests of various stakeholders to create more sustainable, equitable, and eco-friendly mobility systems. As such, new mobility paradigms arise in which public authorities require decision support tools that offer realistic cost and benefit estimations for all parties involved. As these services continue to expand, researchers, operators, and policymakers can leverage the vast amount of data generated to better understand, model, analyze, and effectively coordinate both the supply and demand dynamics within these systems.@en

The thermal stability of the microstructure, in particular that of the precipitates, has been known to be a critical factor for the creep strength of 9–12Cr martensitic heat-resistant steels. In the present study, four martensitic heat-resistant steels were designed to have different precipitate types and morphologies. Steel NS1 (nitride strengthened, NS) has a low density of fine nitrides and Steel NS2 is strengthened by a high density of fine nitrides. Steel CNS (carbide and nitride strengthened, CNS) contains large size carbides and fine carbonitrides and Steel CS (carbide strengthened, CS) mainly possesses large size carbides. Both aging and creep tests at 650 °C were employed to evaluate the stability of the microstructure and properties of the steels during high-temperature exposure as a function of the precipitate morphology. It was found that Steel NS1 and Steel NS2 displayed a good creep performance, but they already recrystallized after a relatively short-term aging treatment. On the other hand, Steel CNS and Steel CS gave poor creep strength, but they could still maintain the tempered martensitic microstructure during long-term aging. The relation between microstructural stability and precipitate morphology/density was linked to the dislocation-precipitate interaction.

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