Amidst the transformation of logistics dynamics due to the global pandemic, the attention directed toward the effects of the Arctic shipping route on Shanghai Port has intensified. This study thoroughly investigates the incorporation of the Arctic shipping route into Shanghai Port logistics, with a dedicated focus on sustainability implications in the post-pandemic era. Leveraging both gravity models and stochastic frontier gravity models, we meticulously analyze the multifaceted opportunities and challenges stemming from this integration, highlighting the pivotal roles of economic growth and geographical proximity. The empirical analysis, spanning the years 2010 to 2021, provides compelling evidence of the Arctic shipping route’s positive effects on the logistical operations of Shanghai Port. The analysis highlights its potential to substantially enhance trade volumes, streamline logistical efficiency, and broaden transit options. Additionally, our assessment of the post-pandemic challenges and opportunities faced by Shanghai Port underscores its adaptability and resilience in the constantly shifting trade milieu. Overall, this study makes significant contributions by offering a comprehensive perspective on the complex interplay between economic, geographical, and external factors. The insights provided here serve as invaluable guidance for policymakers, trade analysts, and businesses that are navigating the intricacies of the contemporary global trade environment. Our findings aim to foster sustainable and resilient trade relationships, facilitating the development of port logistics in the post-pandemic era.

Automated Vehicles (AVs) can drop off passengers at predetermined destinations and relocate to less expensive, remote parking facilities, which offers the potential to repurpose valuable urban land near activity centers for alternative uses beyond vehicle storage. While some researchers believe AVs are the core element to solving parking problems, relieving urban land use, and enabling low-emission travel, others contend that AVs could incentivize increased Vehicles Miles Traveled (VMT) and exacerbate congestion. To bridge these disparate perspectives, this study endeavors to elucidate the environmental ramifications of AVs on parking through a comprehensive literature review. Based on an initial sample of 299 retrieved papers, 52 studies were selected as the result of the selection criteria detailed in the paper. The selected papers were categorized into five gradual parts to answer the raised research questions. As a principal finding of this study, our research provides city planners, traffic operators, and scholars with full-picture insights and trustworthy guidance, emphasizing the pivotal role of AVs in deciphering the sustainable impact on the urban environment.

The study evaluates, in the context of freeway segments, the interaction between automated cars’ kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the ‘Assured Clear Distance Ahead’ criterion). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDA-compliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral ‘cut-ins’ by vehicles making lane changes. The paper concludes with a brief discussion of policy questions and research needs.