This replication package accompanies the revised JICV manuscript, "Vehicle Platooning and Signal Coordination for Intelligent Connected Intersections Toward Autonomous Transportation Systems." It contains original and supplementary SUMO code, 1,000/760-m networks, processed DLR traffic-demand inputs, routes, signal plans, MA10/LSTM prediction assets, and scripts. It covers Fixed-time, Platoon-only, Adaptive-only, Joint, and bounded MaxPressure controllers at demand scales 1.0, 1.2, and 1.5; prediction sensitivity, LSTM substitution, shorter approaches, and multi-seed robustness. New evidence includes seven feedback-matched Signal-only runs, 30 controlled platoon-release trials, 92 archived completed-platoon events, and a 782-check design-speed audit. The README documents dependencies, setup, commands, and reproduction of delay, queues, throughput, clearance, safety metrics, tables, and figures. DLR-derived inputs retain CC BY-NC-SA 4.0; other files retain their respective licenses.

This replication package accompanies the manuscript "DS-MPC: An integrated decision-making and control framework for autonomous driving in urban environments", submitted to the Journal of Intelligent and Connected Vehicles (Manuscript ID: JICV-2026-0084.R1). It contains the DS-MPC source code, CARLA scenario initialization files, the GPR prediction model, experimental configurations, archived results, and a Replication Explanatory File. The materials cover four urban driving scenarios and support the evaluation of safety, task completion, computational performance, component ablations, and horizon sensitivity. The explanatory file describes the package structure, software requirements, execution procedures, result mappings, and known limitations.

Describe the public's psychological perceptions and willingness to pay for CV applications. For psychological perceptions toward CV applications, we measured participants' perceived usefulness, trust, attitudes, perceived risk, and behavioral intentions toward CV applications.

AdaFusionNet replication package for the article (DOI: 10.26599/JICV.2026.9210102). The package contains STTransformer, RSFM, and GRU fusion code, together with utilities for interaction-scene extraction, recording-level data preparation, sample-window construction, auditing, and prediction alignment. The data directory contains 110 cleaned car and two-wheeler trajectory CSVs. The study uses 45 recording pairs from Tianjin, Changchun, and Xi’an. The additional ChongqingNR files are retained in the source collection but are not used in the study. Install requirements.txt and run ./scripts/run_pipeline.ps1 from the package root. See README.md and REPLICATION_EXPLANATORY_FILE.md for data formats, processing steps, and outputs. Software and documentation are licensed under MIT; trajectory-data rights remain with the data provider.

The replication package associated with this study is publicly available at ETS-Data. The package contains the input data, source codes, parameter files, and computational results. The data used in this study describe the daily operation of a real-world multi-route electric bus system. The data were provided in JSON format in the replication package and named as dataConfig.