The application of Connected and Automated Vehicles (CAVs) is steadily increasing, bringing forward expectations of substantial improvements in road safety, traffic efficiency, and environmental sustainability. A fully integrated vehicle–human–infrastructure ecosystem promises reduced crash rates, smoother traffic flow, enhanced mobility, and more efficient use of road network capacity. However, before such a fully automated paradigm can be realized, transportation systems must navigate a prolonged transitional phase characterized by the coexistence of human-driven vehicles, semi-automated systems, and fully autonomous vehicles.
This mixed vehicle technologies environment introduces complex operational and safety challenges that directly affect vehicle safe motion. Heterogeneity in driving behavior, perception capabilities, communication reliability, and control strategies can amplify traffic disturbances, increase conflict likelihood, and undermine expected safety gains, particularly in demanding conditions such as work zones, lane closures, and dense urban networks. Addressing these challenges requires a holistic understanding of how vehicles interact with both one another and infrastructure under partial automation and connectivity. The present Special Issue aims to advance knowledge on vehicle safe motion during this critical transition period by bringing together recent research on mixed traffic flow dynamics, safety assessment, and intelligent control strategies. The included contributions examine these issues through complementary methodological lenses, including microscopic traffic simulation, surrogate safety analysis, vehicle-to-infrastructure communication frameworks, and advanced computer vision-based detection and monitoring techniques. Collectively, the papers in this Special Issue provide scientific insights and practical tools that support safer, more efficient, and more resilient vehicle motion in increasingly complex mixed-technology traffic environments.
| ID | pj285 |
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