https://so05.tci-thaijo.org/index.php/PSAKUIJIR <p><em>PSAKU International Journal of Interdisciplinary Research</em> (<a href="https://portal.issn.org/resource/ISSN/2730-3632">e-ISSN: 2730-3632</a>) is an international open peer reviewed journal published half yearly by the Political Science Association of Kasetsart University, Thailand in cooperation with Management and Science University, Malaysia &amp; Sekolah Tinggi Ilmu Administrasi Abdul Haris, Indonesia. The aim of <em>PSAKUIJIR</em> is to promote new discoveries in the various disciplines of knowledge, within and across sciences and technologies and humanities and social sciences, which are contributed by researchers and experts from all over the world. Therefore, the editors dedicated to providing a venue for both academics and practitioners to publish their original research articles and reviews in English.</p> White Tiger Legal Business and Research Consultants Co., Ltd. en-US Asian Interdisciplinary and Sustainability Review 2730-3632 https://so05.tci-thaijo.org/index.php/PSAKUIJIR/article/view/279880 <p>This research explores a novel method for integrating Internet of Things (IoT) with adaptive Q-learning (AQL) to enhance urban autonomous vehicle (AV) navigation for improved sustainability. The core of this method is an AQL algorithm that dynamically modifies learning settings in response to real-time traffic conditions, which optimizes decision-making. The effectiveness of the model was evaluated in a detailed simulation environment designed to reflect the complexity of urban settings. This infrastructure included sensors, communication protocols, and cloud-based systems. The simulation results show substantial advances in route optimization, hazard avoidance, and overall vehicle safety. The results show that integrating AQL with IoT improves the performance of self-driving cars and promotes more ecological and smart urban transportation strategies.</p> Pannee SUANPANG Pitchaya JAMJUNTR Chanchai TECHAWATCHARAPAIKUL Chutiwan BOONARCHATONG Wattanapon CHUMPHET Nawanun SRISUKSAI Copyright (c) 2025 Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ 2025-06-03 2025-06-03 14 2 1 1 10.14456/aisr.2025.12 https://so05.tci-thaijo.org/index.php/PSAKUIJIR/article/view/279882 <p>This study explores the integration of adaptive Q-learning into Electric Vehicle (EV) Adaptive Cruise Control (ACC) systems, with a focus on enhancing sustainability in Thailand's smart tourism destinations. It presents an adaptive Q-learning approach to improve efficiency, safety, and environmental performance in dynamic environments by learning optimal speed and distance policies through continuous interaction. The simulations demonstrated that adaptive Q-learning significantly improved ACC's fuel efficiency, reduces traffic congestion and improves air quality. These improvements are crucial for developing sustainable transportation solutions in environmentally sensitive tourist destinations. The study stresses how adaptive Q-learning transforms EV safety, efficiency, and environmental management, setting a sustainable benchmark for ADAS systems in Thailand and elsewhere.</p> Pannee SUANPANG Pitchaya JAMJUNTR Chanchai TECHAWATCHARAPAIKUL Chutiwan BOONARCHATONG Wattanapon CHUMPHET Nawanun SRISUKSAI Copyright (c) 2025 Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ 2025-06-03 2025-06-03 14 2 2 2 10.14456/aisr.2025.13