Search Results (20)

Automatic passenger counting (APC) systems are an important asset for public transport operators, allowing them to optimise networks by monitoring lines’ utilisation. However, the cost of these systems is high and the development of alternative devices, cheaper than the most widely used optical systems, seems promising. This paper aims at understanding the influence of local factors on the accuracy of a Wi-Fi APC system by analysing error patterns in a real-world scenario. The APC system was installed on a bus operating regularly within the public transport network and, in the meantime, ground truth data were collected through manual counting. The collected data were then analysed to calculate accuracy and, finally, multilevel modelling was used to identify error patterns due to local factors. This study challenges traditional assumptions, revealing that factors like high pedestrian traffic or intense vehicular movement around the bus have minimal impact on accuracy, if effective received signal strength indicator filters are used. Instead, the number of passengers within the bus affects Wi-Fi systems significantly, especially when the bus is carrying more than 10 passengers, which leads to undercounting due to signal obstruction. This research lays the foundation for strategic error correction to improve accuracy in real-world scenarios. Full article

With the acceleration of urbanisation and the diversification of residents’ travel needs, rail transit plays a critical role in mitigating traffic congestion. However, existing studies predominantly rely on linear models, neglecting the nonlinear effects and spatial heterogeneity of built environment factors on ridership. To address this gap, this study integrates the Multiscale Geographically Weighted Regression (MGWR) model and the Gradient Boosting Decision Tree (GBDT) model to analyse the impact of built environment factors on total, inbound, and outbound ridership in Shenzhen. Utilising Automatic Fare Collection (AFC) data and multiple built environment variables, we identify six key factors (office type, accessibility, road network density, floor area ratio (FAR), public services, and residential type) through SHapley Additive exPlanations (SHAP) value and partial dependency plot (PDP) analysis. Notably, this study constructs a three-dimensional PDP to explore the linkage effects of building volume ratio and accessibility, revealing their joint influence on ridership. The results demonstrate that the GBDT model outperforms MGWR in handling high-dimensional nonlinear data. This paper provides policy recommendations for transport authorities, highlighting the synergies between optimising the planning of the built environment and the development of rail transport to improve the efficiency of short-distance commuting while supporting long-distance cross-city travel. Full article

Mobility-as-a-service (MaaS) apps provide a single platform for journey planning, booking, payment and ticketing, and are proposed as a medium for encouraging sustainable travel behaviour. Generating sustainable-vehicle-based journey alternatives can be formulated as a multi-modal multi-objective journey-planning problem, one that is known to have a prohibitively large solution space. Building on prior insights, we develop a scalable decomposition-based solution strategy. A Pareto set of journey profiles is generated based on inter-transfer-zone objective criteria contributions. Then, guided by neural-network predictions, extended versions of existing shortest-path algorithms for open and public transport networks are used to optimise the paths and transfers of journey profiles. A novel hybrid k-means and Dijkstra’s algorithm is introduced for generating transfer-zone samples while accounting for transport network connectivity. The resulting modularised algorithm knits together and extends the most effective existing shortest-path algorithms using neural networks as a look-ahead mechanism. In experiments based on a large-scale transport network, query response times are shown to be suitable for real-time applications and are found to be independent of transfer-zone sample size, despite smaller transfer-zone samples, leading to higher quality and more diverse Pareto sets of journeys: a win-win scenario. Full article

Wastewater surveillance is a powerful public health tool which gained global prominence during the COVID-19 pandemic. This article describes the development and implementation of the national wastewater surveillance network in France: SUM’EAU. Preliminary work included defining a sampling strategy, evaluating/optimising analytical methods, launching a call for tenders to select network laboratories and producing wastewater monitoring indicators. SUM’EAU was then deployed in three stages: (i) a pilot study, (ii) the transfer of analytical activities from the National Reference Laboratory to four selected network laboratories, and (iii) the extension of the system to additional sampling sites. Currently, SUM’EAU monitors SARS-CoV-2 across 54 wastewater treatment plants in mainland France. Once a week on business days, 24 h flow-proportional composite samples are collected at plant inlets and transported at 5 °C (±3 °C) to partner laboratories for analysis. The analytical process involves sample concentration, RNA extraction, and digital RT-PCR/q-RT-PCR to detect and quantify the presence of the SARS-CoV-2 genome in wastewater. Subsequently, data are transferred to Santé publique France, the French National Public Health Agency, for analysis and interpretation. While SUM’EAU has been instrumental in monitoring the COVID-19 pandemic and holds significant potential for broader application, securing sustainable funding for its operation remains a major challenge. Full article

Urban transportation efficiency is critical in densely populated cities, such as Seoul, South Korea, where subway transfer stations are vital. This study investigates the spatial efficiency and passenger flow dynamics of multilayered transfer stations, using triangular Fourier transform as the primary analytical method. The research incorporates principal component analysis (PCA) and K-means clustering to classify stations based on structural characteristics and congestion patterns. Data derived from transportation card usage during peak hours and architectural layouts were analysed to identify critical bottlenecks. The results highlighted notable inefficiencies in transfer times and congestion. For example, the analysis revealed that optimising transfer corridors at Seoul Station could reduce average transfer times by over 10 min. Dongdaemun History & Culture Park Station would benefit from ground-level pathways to address inefficiencies caused by its extensive underground network. Sindorim Station’s reorganisation of above-ground and underground connectivity was found to enhance passenger flow. By introducing the concept of the ‘entry baseline for passenger flow in public buildings’, this study offers a novel framework for evaluating and improving urban transit infrastructure. The findings provide actionable insights into transfer station design, supporting strategies for addressing the challenges of urban mobility in megacities while contributing to transit-oriented development. Full article

This study investigates the use of biometric technology in public transit to improve trip safety and effectiveness. The incorporation of biometric technology into transit networks improves efficiency and security but also poses substantial challenges of privacy, standardisation, and public acceptability. Conducted via a poll of 25 specialists in Lithuania, the objective was to assess the level of acceptability and practicality of using biometric identification for both drivers and passengers. The results suggest a divided view about the specific demographic that biometric applications should target. However, there is agreement on the considerable potential of these technologies to enhance transportation safety. Face recognition has been the favoured approach due to its non-intrusive nature and simplicity of integration. The statistical research demonstrated significant positive correlations between different biometric approaches, indicating that a multimodal strategy is effective for providing full security coverage. The research highlights the significance of resolving privacy issues, emphasising that public acceptability depends on the open management and strong safeguarding of biometric data. The findings support the deliberate use of biometric technologies in sustainable public transportation, emphasising their ability to improve safety, optimise operations, and even revolutionise the passenger experience. This emphasises the equitable examination of technology, security, and privacy in the progress of sustainable public transportation systems. Biometric technology in public transport, especially for monitoring driver health and ensuring passenger safety, is supported by experts as a means to enhance service quality, reduce accidents, and optimize route planning. Full article

Mobility as a service, and its associated variants, has been proposed as a method to improve the sustainability of transport systems; however, most of the approaches that have been proposed so far have been unsuccessful or have worsened the situation. The work presented in this paper investigates an intermodal system that combines a ride-pooling service with a public transport network. The system is composed of a dedicated simulator that evaluates the transport scenario and an intermodal dispatcher that optimises the service according to requests, accounting for their time windows. This intermodal approach considers trips with multiple legs, for which either ride-pooling or public transport are used. This study investigates how the batch size and the early dispatching of the last leg, supported by a vehicle reservation strategy, impact diverse demand profiles that range from single-passenger to multiple-passenger requests, while also addressing the critical aspect of fleet size. The experimental setting used in this work is the metropolitan area of Barcelona; the experimentation results yield valuable insights into the functionality of the proposed intermodal system. Full article

Public transport (PT) networks face significant challenges in achieving optimal outcomes due to the presence of risk and uncertainty. Despite the importance of optimising PT networks’ performance, limited research has applied risk management tools to tackle this issue. In response, this study presents a three-stage framework to optimise PT networks’ performance in uncertain conditions. First, we establish a PT criteria matrix using an analytic hierarchy process to develop a criteria model and calculate the criteria weightings. Second, we propose a multi-aspiration-level goal programming approach to optimise a PT network’s performance based on the weighted results. To manage uncertainty, we use Monte Carlo simulation to analyse the probability of the optimal solution. Finally, to validate our approach, we apply the three-stage framework to three case study areas in Australia. The results of this research offer significant insights into identifying the likelihood of criteria optimisation scenarios, thereby assisting decision makers in allocating resources for optimising the delivery of PT network performance solutions in accordance with government requirements. Full article

Increasing disasters in recent years have necessitated the development of emergency logistics plans. Evacuation planning plays an important role in emergency logistics management, particularly when it comes to addressing transit-dependent populations that are often neglected in previous studies. This systematic literature review explores the current state of transit-based evacuation planning and examines the current gaps. We focused on transit-based evacuation planning problems that used optimisation and modelling approaches. This review conducts an extensive analysis of relevant studies to provide a comprehensive overview, identify research gaps, and outline future directions in the evacuation planning body of knowledge. Using an integrated systematic review methodology, a thorough search of the Scopus and Web of Science databases was conducted, resulting in a total of 538 articles. These articles were screened and evaluated based on predetermined inclusion and exclusion criteria, ultimately yielding 82 studies for final analysis. The findings highlight the growing importance of optimisation and modelling approaches within transit-based evacuation planning. Studies emphasize the integration of public transportation networks into evacuation strategies to enhance operational efficiency, optimize resource allocation, and ensure evacuee safety. Transit-based evacuation planning is vital for both those without personal vehicles, making evacuation more equitable, and vehicle owners, particularly in earthquakes where vehicles might be inaccessible or trapped, demonstrating its wide usefulness in all emergency scenarios. Various optimisation and modelling approaches have been employed in transit-based evacuation planning studies to simulate and analyse the flow of evacuees and vehicles during emergencies. Transit-based evacuation planning exhibits unique characteristics within disaster management, including the consideration of spatial and temporal dynamics of transit systems, integration of social and demographic factors, and involvement of multiple stakeholders. Spatial and temporal dynamics encompass transportation schedules, capacities, and routes, while social and demographic factors involve variables such as income, age, and mobility status. Stakeholder engagement facilitates collaborative decision-making and effective plan development. However, transit-based evacuation planning faces challenges that require further research and development. Data availability and accuracy, model validation, stakeholder coordination, and the integration of uncertainty and dynamic factors pose significant hurdles. Addressing these challenges necessitates advances in data collection, robust modelling frameworks, and improved communication and coordination mechanisms among stakeholders. Addressing these gaps requires interdisciplinary collaborations and advances in data analytics and modelling techniques. Full article

Arrow signs found on roadway pavement are an important component of modern transportation systems. Given the rise in autonomous vehicles, public agencies are increasingly interested in accurately identifying and analysing detailed road pavement information to generate comprehensive road maps and decision support systems that can optimise traffic flow, enhance road safety, and provide complete official road cartographic support (that can be used in autonomous driving tasks). As arrow signs are a fundamental component of traffic guidance, this paper aims to present a novel deep learning-based approach to identify the orientation and direction of arrow signs on marked roadway pavements using high-resolution aerial orthoimages. The approach is based on convolutional neural network architectures (VGGNet, ResNet, Xception, and DenseNet) that are modified and adapted for regression tasks with a proposed learning structure, together with an ad hoc model, specially introduced for this task. Although the best-performing artificial neural network was based on VGGNet (VGG-19 variant), it only slightly surpassed the proposed ad hoc model in the average values of the R² score, mean squared error, and angular error by 0.005, 0.001, and 0.036, respectively, using the training set (the ad hoc model delivered an average R² score, mean squared error, and angular error of 0.9874, 0.001, and 2.516, respectively). Furthermore, the ad hoc model’s predictions using the test set were the most consistent (a standard deviation of the R² score of 0.033 compared with the score of 0.042 achieved using VGG19), while being almost eight times more computationally efficient when compared with the VGG19 model (2,673,729 parameters vs VGG19′s 20,321,985 parameters). Full article

This paper provides a simulation and optimisation-based system to combine public transport (PT) with ride-pooling services (RP). According to the International Transport Forum (ITF), the RP could be established as a feeder of PT and included as the first or last leg of the journey with the option of transferring to/from PT in between. The system contains a dispatching core that uses an optimisation model with heuristic parameters to quickly analyse the potential permutations for each request. This topic is frequently based on simplistic modelling in the literature, and it has not been extensively tested in major urban regions. The whole metropolitan region of Barcelona is employed in this study, with a large realistic simulation model encompassing a 20 × 15 km area with a PT network of about 3000 stations and 300 route lines and nearly 114,000 traffic links. This enables for a more accurate evaluation of system performance and trip quality computation. Full article

The article discusses the issue of modelling traffic flows and the transport network. Faced with an increase in the number of vehicles in road networks, the problem of congestion and the need to optimise traffic and adapt the transport infrastructure to changing demand are growing, especially in large cities. With this in mind, the authors of this publication developed a model of the road network in the north-eastern part of the Warsaw agglomeration based on the proposed algorithm. Two methods were used to optimise the distribution of traffic flows: the Nash equilibrium and the Stackelberg approach. The Nash equilibrium assumes the aim of achieving equal average times on all roads for each origin–destination (O-D) pair. This describes the state pursued by a decentralised system guided by the individual benefits of the traffic users. On the contrary, the Stackelberg approach aims to achieve optimal travel times for the entire system. The study was carried out for three scenarios that differed in the assumed traffic demand on the road network. The basic scenario assumed the average hourly traffic demand during the morning peak hour based on traffic measurements. On the other hand, the two alternative scenarios were developed as a 10% variation in traffic volumes from the baseline scenario. On the basis of the results, it was concluded that an increase in traffic volumes for all O-D pairs could result in a decrease in traffic volumes on some links of the road network. This means that the transport network is a complex system and any change in parameters can cause significant and difficult to predict changes. Therefore, the proposed approach is useful in terms of traffic forecasting for road networks under conditions of changing traffic flow volumes. Additionally, the total travel time for the entire system differed for each scenario by a percentage difference of 0.67–1.07% between the optimal solution according to the Nash equilibrium and the Stackelberg approach. Full article

The supply logistics of energy biomasses generally involves a complex system of supply chains, which aim to achieve timely and cost-efficient feedstock deliveries to biomass demand points. The performance of supply chains is often examined in case studies where spatial data about biomass sources and transportation networks are deployed in varying resolutions and to different geographical extents. In this paper, we have reviewed 94 publications, in which spatial data were used in case studies that focused on analysing and optimising energy biomass supply chains. The reviewed publications were classified into 16 categories, according to the publication year, study methods and objectives, biomass types, supply system complexity and the spatial features of each study area. This review found that the use of geographical information systems in this context has increased in popularity in recent years, and that and the multiformity of the applied methods, study objectives and data sources have increased simultaneously. Another finding was that most of the studies that we reviewed focused on countries in which spatial biomass and transport network data of high quality were unrestrictedly available. Nevertheless, case studies, including spatial data from multiple countries, were represented marginally in the papers that we reviewed. In this paper we also argue that a standard way of reporting geographical contents in biomass case studies should be developed to improve the comprehension and reproducibility of the publications in this field of research. Full article

The present study aimed to provide an in-depth assessment of the commuting patterns of scholar communities of southwestern European countries and to identify measures to improve their sustainable performance regarding mobility. The adopted methodology characterised the mobility pattern of students as a sustainability indicator and the availability of related infrastructures and local public transport network. Data were gathered by qualitative (behavioural questionnaires) and quantitative (technical audits) approaches, based on measurable indicators (key performance indicators and scores (ranging between 0–5)). Overall, French schools showed the best sustainable performance regarding mobility (2.0) and Gibraltar had the lowest (1.2). The existence of bike parking and electric car charging points were the main weaknesses founds (with their related mean scores being 0.6 and 0.2, respectively). The score associated with annual CO₂ emissions due to students’ mobility had the best performance, where all countries managed to obtain an average of 3.1. The global score, which assessed the sustainable performance of scholar communities regarding mobility, had a mean value of 1.5 for all studied countries, which highlights the potential for improvement of the studied schools, mainly targeting the public transport network optimisation and the enhancement of scholar infrastructures concerning bicycle parking and electric cars. Full article

This study proposes an optimisation approach to improve multiple-criteria aspiration-level public transportation performance by combining public transport criteria matrix analytic hierarchy process (PTCM-AHP) models and multi-aspiration-level goal programming. The approach uses the PTCM-AHP to calculate the system weights. Based on the weight values, the approach combines the multi-aspiration goal-level selection process in three different ways. The proposed approach was used to optimise public transportation networks in Bayswater, Cockburn, and Stonnington, Australia, to demonstrate the public transportation network performance optimisation process. By controlling the criteria goal value interval, this new approach combines decision-making plans and strategies to optimise various scenarios. The optimisation outcomes can be applied to provide guidelines for improving the performance of public transportation networks. Full article