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This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.

The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations. The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs, respectively, as well as accommodating the heterogeneity issue simultaneously.

The findings show that day, location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.

The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.

The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied.

This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies.

The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed.

This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

Individuals’ driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems. The incoming data can be sampled at rates ranging from one Hertz (or even lower) to hundreds of Hertz. Failing to capture substantial changes in vehicle movements over time by “undersampling” can cause loss of information and misinterpretations of the data, but “oversampling” can waste storage and processing resources. The purpose of this study is to empirically explore how micro-driving decisions to maintain speed, accelerate or decelerate, can be best captured, without substantial loss of information.

This study creates a set of indicators to quantify the magnitude of information loss (MIL). Each indicator is calculated as a percentage to index the extent of information loss (EIL) in different situations. An overall information loss index named EIL is created to combine the MIL indicators. Data from a driving simulator study collected at 20 Hertz are analyzed (N = 718,481 data points from 35,924 s of driving tests). The study quantifies the relationship between information loss indicators and sampling rates.

The results show that marginally more information is lost as data are sampled down from 20 to 0.5 Hz, but the relationship is not linear. With four indicators of MILs, the overall EIL is 3.85 per cent for 1-Hz sampling rate driving behavior data. If sampling rates are higher than 2 Hz, all MILs are under 5 per cent for importation loss.

This study contributes by developing a framework for quantifying the relationship between sampling rates, and information loss and depending on the objective of their study, researchers can choose the appropriate sampling rate necessary to get the right amount of accuracy.

The purpose of this paper is to explore and test the motivation behind the evolution of China’s vast network of partnerships around the globe since the end of the Cold War.

After combing through 24 types of partnerships with 78 countries, the authors empirically tested four hypotheses using data from Correlates of War and World Bank.

The analysis indicates that China’s choice to build such an elaborate network is not random. On the contrary, it is largely determined by three factors: the need to counter the US pressure; the necessity of maintaining peace and stability along its borders and achieving the long-term goal of modernization.

The research is among the first attempts to comprehensively test the possible motivations behind China’s partnership building efforts and provides a stepping stone for analyzing this important aspect of China’s foreign policy.

Incorporating conservation of resources theory into the sustainable career framework, this study empirically examines how social support at work, harmonious passion and strengths use interact to bolster work–home enrichment.

This study tested hypotheses through a two-wave research design with a final sample of 357 academic respondents from public universities in Vietnam.

We found positive relationships between social support, harmonious passion and work–home enrichment. Strengths use significantly moderated these relationships.

Organizations should cultivate a supportive environment and opportunities to help individuals utilize social support and exert their strengths to be more passionate and enrich their work–home activities.

This study addresses the knowledge gap regarding the crucial interdependence and interactions between contextual and personal resources in promoting work–home enrichment, an underexplored aspect in sustainable career literature. It highlights how social support and harmonious passion enhance work–home enrichment. Using strengths is a fundamental boundary condition for these associations. The findings offer invaluable implications for leveraging work-related resources and personal qualities to enrich work and home domains for a sustainable career.