Hasil untuk "Transportation and communications"

Yifan Zhuang, Pei Liu, Hao Yang et al.

Chris HC. Nguyen, James M. Shihua, Rhea P. Liem

Xiaohui Zhang, Jie Sun, Jian Sun

Shubham Parashar, Zuduo Zheng, Andry Rakotonirainy et al.

Yonghui Liu, Qian Li, Inhi Kim

Zhixiao Zhang, Keyu Wen, Hao Gong et al.

Dan Zhu, ChiSin Ng, Litian Xie et al.

Rodrigo Mora, Cristhian Figueroa-Martínez, Natan Waintrub

The surge in cycling in Chilean cities is increasing the number of conflicts between bus drivers and cyclists. However, these conflicts have traditionally been ignored by the literature, especially those labelled as minor conflicts, which are not recorded by official statistics. Through three focus groups, we sought to explore the perception that drivers have about the cyclists of Santiago (Chile). The results suggest that drivers consider that cyclists do not perceive their own vulnerability and consider that many cyclists do not respect or know the Traffic Law. In their interactions, bus drivers often generate and abide to stereotypes of cyclists. Bus drivers perceive that the quality of road infrastructure is making their job harder, which potentially creates more conflicts with cyclists. Finally, the main strategy employed by bus drivers to deal with these conflicts is to maintain as much distance as possible from cyclists.

Luay Jum’a, Ahmed Adnan Zaid, Mohammed Othman

<i>Background</i>: This study conceptualizes supply chain ambidexterity through two capabilities, supply chain adaptability and agility. Accordingly, it investigates the impact of supply chain adaptability and agility on green product innovation (GPI) and supply chain sustainability in Jordanian manufacturing firms. It also examines the mediating role of GPI in these relationships. The study is based on dynamic capabilities theory (DCT) as the theoretical foundation. <i>Methods</i>: A quantitative research approach was employed, with data collected from 346 supply chain managers using a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for analysis. <i>Results</i>: The findings reveal that supply chain adaptability does not directly influence sustainability but significantly enhances GPI, which positively impacts sustainability. Supply chain agility, however, directly and significantly improves both GPI and sustainability, highlighting its importance in achieving sustainable supply chain performance. Additionally, GPI mediates the relationship between supply chain ambidexterity and sustainability, reinforcing its role as a key enabler of eco-friendly supply chain management. These findings provide theoretical and managerial implications. <i>Conclusions</i>: The study extends DCT by confirming the role of GPI in linking supply chain ambidexterity to sustainability. Managers should prioritize agility, invest in sustainable products, and adopt green practices to enhance competitiveness.

Parisa Kanani, Mohammad Javad Omidi, Mahmoud Modarres-Hashemi et al.

This paper introduces a novel high altitude platform station (HAPS)-based integrated sensing and communication (ISAC) system, referred to as HAPS-ISAC, designed to enhance the capabilities of future 6G networks by simultaneously optimizing communication and sensing functions. HAPS operates as a super-macro base station in the stratosphere, utilizing advanced beamforming techniques within a multiple-input multiple-output (MIMO) architecture, supplemented by multiple-input single-output (MISO) configurations, effectively enabling the system to serve ground communication users (CUs) while conducting high-resolution sensing of potential targets. A Rician channel model is employed to capture both line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. The performance of the system is optimized through a non-convex optimization problem that maximizes the minimum beampattern gain towards desired sensing angles while ensuring that the signal-to-interference-plus-noise ratio (SINR) requirements for CUs are satisfied, all under the power constraints of the HAPS. Compared to the traditional terrestrial and UAV-based ISAC systems, HAPS-ISAC delivers sustained and reliable service over extensive areas, leading to significantly improved overall performance. Simulation results show that HAPS-ISAC significantly improves SINR, resource allocation, sensing accuracy, and fairness, outperforming existing technologies. This establishes HAPS-ISAC as a key enabler for 6G networks and advances intelligent infrastructures like IoT and smart cities.

Roni Zakaria Raung, Wahyudi Sutopo, Muhammad Hisjam et al.

With over 130 million motorcycles, Indonesia faces a critical challenge in transitioning to electric mobility to meet its carbon emission reduction commitments under the Paris Agreement. Despite the existing government incentives and subsidies, the adoption of electric motorcycles (EM) remains critically low, only 0.18% of the 13 million units targeted by 2030. This study aims to evaluate the effectiveness of current EM subsidy and incentive policies and to determine the suitable strategies for achieving the 2030 target. It adapts PTTMAM model, a system dynamics (SD) model that captures the complex interactions among four market agents: users, manufacturers, infrastructure providers, and government, to the context of EM in Indonesia. It also enriches the willingness to consider (WTC) framework within the model by incorporating behavioral variables such as lifestyle and awareness of future trends. The model is calibrated and validated using historical data (2013–2023) through sensitivity and extreme case analysis. A total of 72 subsidy and incentive policy scenarios involving the market agents were constructed to assess the achievement of current policies and identify optimal strategies to reach government’s target. Simulation results of the scenarios reveal that current policies are insufficient, projecting only 15.9% achievement of the 2030 target. More aggressive interventions, including extended subsidies, carbon taxes, and electricity incentives, could enable reaching the target by 2033. Hence, the existing 2030 goal appears overly ambitious without strategic adjustments. This study underscores the need for policy redesign and offers a robust, behaviorally informed SD framework to guide Indonesia’s electric mobility transition.

Anjelyn Norlintya Ringa Reo, Reinald Juanli Kota, Indriyati Indriyati et al.

Food security is a crucial issue, especially in areas with challenging geographical and climatic conditions such as Retraen Village, Amarasi Selatan Subdistrict, Kupang Regency. To address this issue, the Demonstration Garden Program was designed as an educational effort to increase community awareness and understanding of the importance of local food security. This program aims to provide practical knowledge to villagers on appropriate, sustainable crop cultivation techniques that suit the local environment. The implementation of the program consists of three main stages: preparation, implementation, and evaluation. Activities were carried out using a participatory approach to ensure community involvement in every process. The results showed an increase in community participation, improved understanding of cultivation techniques, and the emergence of local initiatives to develop gardens independently. This program is expected to serve as a learning model that can be replicated in other areas and to promote local food self-sufficiency in a sustainable manner.

Daniel Štraub, Daniel Baldwin Hess

Attila Aba, Domokos Esztergár-Kiss

Linning Liu, Xinglong Wang, Min He et al.

To ensure the safety of operations in the airfield area, it is crucial to address the increased conflict risks resulting from the growing number of vehicles and aircraft. Based on the complex network theory, this study takes aircraft and vehicles in the airfield area as nodes and selects five different indicators (average degree, average node weight, average weighted clustering coefficient, network density, and network efficiency) to characterize the operation state of the airfield area, so as to identify conflict risks. Building on this framework, an ATT-Bi-LSTM innovation prediction model based on LSTM network architecture is established to forecast the evolution of network indicators over time. By leveraging the algorithm to predict the temporal evolution of indicators, valuable insights into the future evolution of conflict risk can be gleaned from the prediction results. Real operational data from Xi’an Xianyang Airport are utilized as a demonstrative example in this study. The results of the experiments illustrate that the analytical approach proposed in this study achieves a precise identification of the indicators. The experimental results are then compared with data from other predictive models that operate on the same data set. Compared to alternative prediction models, the accuracy is increased by nearly 10%, reaching 89.78%. The results of the study help to accurately identify conflict risks in the airfield area in advance and provide strategic conflict avoidance strategies for relevant staff. This is essential to ensure the security of airfield area.

Bing Liu, Xiaoyue Liu, Yang Yang et al.

Zhifeng Tang, Zhuo Sun, Nan Yang et al.

In this paper, we analyze the average age of information (AoI) and the average peak AoI (PAoI) of a multiuser mobile edge computing (MEC) system where a base station (BS) generates and transmits computation-intensive packets to user equipments (UEs). In this MEC system, we focus on three computing schemes: (i) The local computing scheme where all computational tasks are computed by the local server at the UE, (ii) The edge computing scheme where all computational tasks are computed by the edge server at the BS, and (iii) The partial computing scheme where computational tasks are partially allocated at the edge server and the rest are computed by the local server. Considering exponentially distributed transmission time and computation time and adopting the first come first serve (FCFS) queuing policy, we derive closed-form expressions for the average AoI and average PAoI. To address the complexity of the average AoI expression, we derive simple upper and lower bounds on the average AoI, which allow us to explicitly examine the dependence of the optimal offloading decision on the MEC system parameters. Aided by simulation results, we verify our analysis and illustrate the impact of system parameters on the AoI performance.

Tomoya Kawasaki, Wataru Nakanishi, Satoshi Hyodo et al.

Ravina N. Jain, Srinivas S. Pulugurtha

The differences in travel times of passenger cars, traffic stream, and trucks depend on the area type, temporal factors, reference speed, and traffic condition. These explanatory variables account for the effect of geometric conditions and variations in the traffic flow. The focus of this research is to examine the correlations and estimate truck travel time to passenger car or traffic stream travel time ratio of a road link (dependent variable) as a function of these explanatory variables. Travel time data for Mecklenburg County and Iredell County in North Carolina, USA were gathered for the year 2017 to examine correlations, develop generalized estimating equations (GEE) models, and identify explanatory variables influencing the ratios. Gamma log-link distribution-based models are the best-fitted models to estimate the average travel time (ATT) of trucks to the ATT of passenger cars or traffic stream ratios. Notable differences in the coefficients were observed when the ATT of trucks was compared with the ATT of passenger cars or traffic stream. The area type (urban or rural) was observed to influence the ratios differently. The influence of traffic condition, reference speed (or free-flow speed), day-of-the-week (DOW) and time-of-the-day (TOD) on the ratios also varied with the area type.

Wenbo Huang, Yanyan Chen, Shushan Chai et al.

Large-scale activities such as the Winter Olympics are usually held in areas with low temperature or other harsh environments, which greatly affects the spectating experience of pedestrians. In order to improve the travel efficiency and reduce the safety risk of pedestrians, an adaptive information-distribution strategy of VMS (variable message sign) for road networks is proposed to guide the pedestrians. In the proposed strategy, the dynamic feedback mechanism between the VMS information distribution and the state of crowded pedestrians is established, and the dynamic optimization model of the VMS information release layout is formulated. To evaluate the effectiveness of the strategy, a multiagent-based simulation method is proposed. Through numerical simulation, it is found that the guidance strategy can improve the movement efficiency by adjusting releasing duration of VMS information or improving the information obedience rate of pedestrians. In this paper, a large-scale competition area in the Xiaohaituo Mountain in Beijing was taken as an example to simulate the scenarios of ingress and egress with and without the strategy. The results show that the average walking time and the road congestion can be significantly reduced in the road network with the strategy, and the proportion of pedestrians with shorter travel time can be increased. Therefore, the research can provide theoretical foundation and data support for managers to guide passenger flows and improve the spectating experience.