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We are excited to present the inaugural issue of the ACM Journal on Autonomous Transportation Systems (JATS).This journal is timely given the significant disruptions we are witnessing in the transportation and mobility landscape.Autonomous transportation systems represent the frontier of modern mobility, promising safer, more efficient, and environmentally friendly modes of travel.By harnessing advanced technologies such as artificial intelligence, machine learning, and sensor fusion, these systems aim to navigate vehicles without human intervention.The future importance of autonomous transportation systems cannot be overstated.They can potentially revolutionize various industries, including personal commuting, logistics, public transit, parking, and city design.With the ability to reduce accidents caused by human error, optimize traffic flow, and lower carbon emissions through improved route planning and vehicle efficiency, autonomous transportation will contribute to sustainable development.Moreover, as populations grow and urbanization intensifies, the demand for efficient transportation solutions will only escalate.Autonomous systems offer a promising solution to address these challenges by providing on-demand mobility services, enhancing accessibility, and reducing congestion in densely populated areas.The JATS will address a wide array of topics encompassing the design, analysis, and control of autonomous transportation systems.At this juncture, the field is confronting critical challenges related to data, models, computation, and scalability, which are increasingly integral to its advancement.There are many unique challenges in the Autonomous Vehicle (AV) space related to improving traffic operations, road safety, sustainability, and the efficient management of passenger and goods delivery on roads.Effective decision-making for the control and management of transportation systems necessitates interdisciplinary research, particularly transportation engineering, computer science and policy, spanning control systems, machine learning, traffic engineering, safety, asset management, and logistics engineering.Such a collaborative approach is essential for crafting innovative solutions to the multifaceted challenges confronting autonomous transportation systems.The journal will focus on articles that contribute to the algorithms, computational solutions, and frameworks that will advance the AV research domain.This inaugural issue exemplifies the wide range of topics covered, spanning from the proposal of an asymmetric linear bilateral control model assessed on automated truck platoon to the classification of drivers based on their car-following behavior to a research note aimed at addressing concerns regarding the impact of autonomous vehicles on societal digital disparities and, finally, an approach for selecting safe lane-changing trajectories.
Aggarwal et al. (Tue,) studied this question.