Luka DEDIĆ, Miroslav VUJIĆ

In urban networks, periodic peak traffic congestion often occurs during the day, namely in the morning and afternoon hours. Due to spatial constraints and the inability to increase capacity through physical road expansion, modern traffic management increasingly relies on Intelligent Transport Systems (ITS) solutions. One such solution is the integration of automatic licence plate recognition, an expert system and microsimulation tools aimed at optimising the network performance of signalised intersections within a network. Based on real-time and historical data on individual vehicle trajectories, the system predicts the route of each vehicle through the observed segment of the traffic network, determines the network load and proposes optimal signal plans. This paper provides an overview of conducted research related to the optimisation of signal plans utilising expert systems. Mathematical models for capacity and load determination, as well as computational intelligence-based systems used for signalised intersection management strategies, are described. Finally, the paper proposes a basic framework and guidelines related to the suggested system, highlighting open questions and potential challenges in its development.

2024 (Vol 36), Issue 5

Wei LI, Tian’ai LI, Yongying MENG, Xuecai XU, Zhifeng MA

This study intended to explore college students’ cognition and attitudes towards connected and autonomous vehicles (CAVs) in China. A comprehensive questionnaire was designed and distributed in Mainland China, and after collecting and processing the data, Bayesian multivariate analysis was presented to evaluate the six dimensions of cognition, consciousness, safety, privacy, liability, education and acceptance. By analysing each dimension, the results show that gender and status are significant for consciousness, safety, privacy and education, but location plays a significant role in safety and liability. It is found that each dimension reveals a specific thought of college students, and the potential users’ cognition and attitude should be paid more attention to. Some empirical suggestions are presented to enhance the systematic improvement of CAVs and possible ethics issues.

2024 (Vol 36), Issue 5

Yubin ZHENG, Cheng CHENG, Yong ZHANG, Lingyi WANG, Qixuan LI, Hailin ZHANG

Vehicle turn-in rate is a critical and widely adopted input for expressway rest area design and operation. With the implementation of expressway ETC gantries, the ERA turn-in rate can be further estimated by measuring the travel speed distribution via ETC gantry data. This paper proposed an adaptive density peak clustering Gaussian mixture model (ADPC-GMM) for ERA turn-in rate estimation. The ADPC algorithm is applied to generate the GMM’s inputs accommodating to the traffic characteristic of ERA expressway segments and GMM would further provide the turn-in rate estimation results. To validate the model precision, the turn-in rate data of four selected ERAs in Sichuan, China, as well as the ETC gantry data of their corresponding expressway sections are obtained. According to the estimation results, the MAE and RMSE are 0.0228 and 0.0267 for the passenger car scenario and 0.0264 and 0.0356 for the commercial truck scenario, respectively. These results are also at the lowest level compared with the results acquired from ordinary GMM, K-Means and DBSCAN algorithms. The proposed method has good applicability for vehicle turn-in rate estimation and can be deployed at different ERAs, especially those ERAs without traffic monitoring.

2024 (Vol 36), Issue 5

Yong CUI, Qing YU, Ullrich MARTIN

This study introduces an advanced software platform and process for the quantitative national economic evaluation of high-speed maglev systems, overcoming limitations of traditional methods through parameter variation experiments and automated solution search. Utilising the adapted German standardised evaluation, this research demonstrates how integrated modelling, evaluation and optimisation software can deeply analyse the impact of various variables and parameters on economic outcomes. By employing an optimisation algorithm, the software not only determines critical evaluation parameters to ensure benefits exceed costs but also deduces optimised model variables. The macroeconomic benefit-cost ratio guides the optimal design concept, with the research finding a critical value for ensuring economic feasibility. The proposed solution achieves a 22% improvement in this ratio (1.106 vs. 0.909) compared to the existing Hefei-Wuhu route, highlighting its potential for large-scale maglev implementation. Future development directions include integration with micro-simulation systems, support for random behaviour, sensitivity analysis, data-driven machine learning and enhanced user interface design for broader applicability. The findings underscore the software’s capability to provide robust, data-driven insights for economic feasibility studies of high-speed maglev systems, presenting a significant step forward in infrastructure project evaluation.

2024 (Vol 36), Issue 5

Milivoje ILIĆ, Đorđe MAKSIMOVIĆ, Norbert PAVLOVIĆ, Ivan BELOŠEVIĆ

The concept of risk analysis is especially important because it examines and analyses in a detailed manner the factors that affect the normal functioning of a system. In this paper, the level crossing is considered as one system, composed of several elements. The failures of those elements were analysed with the aim of showing which are the most frequent and most critical failures. A multi-methodological approach was used in the analysis. The failure modes and effects analysis (FMEA) method was used to determine risk factors, after that a multi-criteria model was created in a fuzzy environment, and as output, it gave a ranking list of critical failures in the system. Through the discussion of the results, a comparison of the basic model with two other similar ones was made, and the comparative results were analysed. The main aim of this paper is to present one of the possible ways to analyse the risk of the system of level crossings with the aim of improving traffic safety at the crossing.

2024 (Vol 36), Issue 5

Qing LIU, Qiwei QIAN

Airport clusters are of great significance to the sustainable development of the civil aviation transportation industry. The study utilises common frontier and super-efficiency DEA methods to assess the efficiency of China’s six major airport groups. It then employs the Malmquist index method to analyse changes in airport productivity. The results highlight regional disparities in airport efficiency. The East China Airport Group and the Southwest Airport Group consistently demonstrate excellent efficiency values, while the North China Airport Group and the Northeast Airport Group have significant room for improvement. Most airports within the groups operate at low and ineffective levels, with efficiency initially increasing and then decreasing. Moreover, the technology gap ratio (TGR) for each airport group somewhat shows a downward trend. The Malmquist index indicates that the overall factor productivity of each airport has generally remained stable, with efficiency growth primarily dependent on scale efficiency. On average, technical efficiency has increased by 1.5%. However, in terms of technological changes, most airports have experienced technological regression, indicating insufficient focus on technological improvement. Therefore, it is crucial to prioritise technological innovation and enhance management efficiency to achieve efficiency improvements in airport clusters. It is necessary to formulate strategies accurately based on the specific conditions of different regions, promote coordinated development, foster regional exchanges and cooperation, address regional disparities, ensure sustainable development of China’s airport clusters, and establish a world-class airport cluster.

2024 (Vol 36), Issue 5