Transportation System Performance Research Articles

Predictive Smart Mobility Systems for Sustainable and Efficient Urban Transportation

Abstract: The rapid urbanization and growth of cities have placed increasing pressure on transportation systems, leading to traffic congestion, environmental degradation, and inefficiencies in mobility. The Smart Mobility Prediction System (SMPS) is designed to address these challenges by leveraging advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and big data analytics to optimize transportation networks. This system gathers realtime data from sensors, traffic cameras, GPS devices, and social media feeds to predict traffic patterns, identify congestion hotspots, and suggest alternative routes to users. By utilizing predictive analytics, the SMPS can forecast traffic conditions, demand for public transportation, and the availability of shared mobility options such as ride-hailing and bike-sharing services. Furthermore, the system can support urban planners and policymakers by providing insights into the performance of transportation systems, enabling them to make informed decisions regarding infrastructure development and traffic management. The implementation of the Smart Mobility Prediction System aims to enhance the efficiency, sustainability, and safety of urban transportation networks, contributing to improved quality of life for city dwellers while reducing environmental impacts.

Intelligent Transportation System Performance Analysis of Indoor and Outdoor Internet of Vehicle (IoV) Applications Towards 5G

Intelligent Transportation System Performance Analysis of Indoor and Outdoor Internet of Vehicle (IoV) Applications Towards 5G

Evaluation of Travel Time Performance of Multimodal Transport System of Bhopal City

Evaluation of Travel Time Performance of Multimodal Transport System of Bhopal City

String stable control design for automated vehicles under cyberattacks

Emerging automated vehicle (AV) technologies open a door for cyberattacks, where a select number of AVs are compromised to drive in an adversarial manner, degrading the performance of transportation systems. Hence, designing stable controls for AVs that can mitigate the impact of attacks on traffic flow is important and necessary as AVs gradually become a reality. In this study, we first present a general framework for describing mixed-autonomy traffic involving AVs and human-driven vehicles (HVs) based on car-following dynamics. Under this framework, a class of malicious attacks on AV control commands (vehicle acceleration) is mathematically characterized. To deal with the lack of knowledge of the attacks, we model attacks as an unstructured process, allowing for the inclusion of both deterministic and stochastic attack behaviors, bounded by a known bound (to remain stealthy) without being subject to any specific statistical distribution. Moreover, we analytically derive a set of sufficient conditions for string stable control design of individual AVs which can help mitigate the disturbances to traffic flow caused by unknown attacks on AVs. Furthermore, for any given market penetration rate of AVs, a set of conditions is also derived for selecting appropriate feedback gains of AVs to ensure string stability of heterogeneous traffic, reducing the undesired impact of attacks on traffic flow. These sufficient conditions provide important criteria for string stable control design of AVs without requiring much knowledge of the attacks. A series of numerical results is presented to show effectiveness of the proposed approach on mitigating attack disruption.

Recent Advances in High-Performance Membrane Materials for Fuel Cells

Fuel cells have emerged as a key technology for clean energy production, with proton exchange membrane (PEM) fuel cells being one of the most promising types due to their high efficiency and low emissions. A critical component of PEM fuel cells is the membrane, which plays a crucial role in ion transport and overall system performance. Recent advances in membrane materials have focused on improving proton conductivity, chemical stability, and durability while reducing production costs. This review discusses recent developments in high-performance membrane materials, including polymer blends, hybrid membranes, and metal-organic frameworks (MOFs). These innovative materials have shown significant potential in overcoming the limitations of traditional membranes like Nafion®. Advances in acid-base membranes, such as polybenzimidazole (PBI)-based systems, have demonstrated improvements in high-temperature performance. Enhanced cross-linking techniques, the use of antioxidant additives, and nanofillers have further contributed to improved membrane durability. Despite these advancements, challenges remain in scaling up production and reducing costs. Future research must focus on addressing these issues to enable the widespread commercial use of fuel cells. The progress in membrane material technology is critical to realizing the potential of fuel cells as a viable solution for sustainable energy.

Evaluating low-emission-zone impacts on urban road transport system in large city

The purpose of the study was to assess the impact that a low emission zone (LEZ) would have on the road transport subsystem. Different scenarios were adopted regarding: the spatial extent of the zone itself; the stages of its implementation, and the vehicles on the network (by age, engine displacement, and fuel type). The study was based on a macroscopic traffic model of Łódź employed to analyse how any LEZ-related restrictions may affect the operation of the urban road transport system in the city. The conducted analyses showed that while the implementation of a low emission zone would positively affect the environment, it would have a negative impact on the performance of the urban transport system itself. The simulations for each spatial scenario of the LEZ revealed that it would increase the travel times and distances necessary within the city limits, and also decrease travel speeds.

Comparative analyses of European horizontal-landing reusable first stage concepts

AbstractPartially reusable two-stage-to-orbit (TSTO) launch configurations have been investigated on system level by DLR in the ENTRAIN study which encompasses an examination of both vertical takeoff horizontal landing (VTHL) and vertical takeoff vertical landing (VTVL) reusable first stages. A target payload performance of 7.5 Mg into GTO is selected as the common mission requirement of all concepts. In this paper, the preliminary designs of TSTO configurations consisting of a winged reusable first stage and an expendable upper stage are presented and discussed. The considered propellant combinations include LOX/LH2, LOX/LCH4 and LOX/RP-1. Configurations based on staged combustion and gas generator cycle engines are analyzed. The focus of the presented preliminary analyses is on the overall performance of the space transportation system, the design and architecture of the winged reusable first stage and the comparison and evaluation of different VTHL configurations.

The optimization algorithm of intelligent transportation systems based on reinforcement learning

With the acceleration of urbanization and the increase in traffic load, traditional traffic management methods struggle to cope with the complexity of modern traffic conditions. Intelligent Transportation Systems (ITS), utilizing modern information technology and artificial intelligence, have improved the efficiency and safety of transportation systems. Reinforcement Learning (RL), as an adaptive optimization method, can dynamically adjust traffic signals and flow control strategies through trial and error and reward mechanisms, optimizing traffic flow management and signal control. This paper investigates the optimization algorithms of intelligent transportation systems based on reinforcement learning, including their design, application, and performance evaluation. Research indicates that RL optimization algorithms can significantly enhance the organizational performance of transportation systems, increasing the efficiency and flexibility of traffic management. Empirical analysis verifies the effectiveness of the algorithm, and future improvement directions are proposed.

Simulation Techniques in Sugarcane Transportation Model Using R Programming Language

The R programming language is generally known for its strength in Monte Carlo simulations, and numerical computing. This study will try to utilize R for discrete event simulations, namely in transportation systems, especially sugarcane transportation. The purpose of this paper is to study the performance of the sugarcane transportation system from the plantation to the factory, by utilizing the R programming language. The things that will be studied are to obtain changes in the system parameters so that more optimal performance is obtained. These parameters include the time required for the sugarcane to be in the transportation system, the length of the sugarcane pile in the plantation before being transported, the amount of resources needed for all transportation activities (loading, transporting and unloading), the number of transport equipment, loading equipment and unloading equipment needed, so that the harvest target is met and the waiting time for the sugarcane to be milled is as minimal as possible. As well as the level of utility of all resources provided in the system. The stages in this study include 1) literature review, 2) describing the sugarcane transportation system, 3) building assumptions and system constraints, 4) designing the transportation system conceptually, 5) developing programming code, 6) model testing/verification, 7) model validation, and 8) conducting experiments on the model. The results of the analysis of the model output indicate that the “open source R” programming language can be effectively applied to model the sugarcane transportation system.

Assessing travel time performance of multimodal transportation systems using fuzzy-analytic hierarchy process: A case study of Bhopal City

Insufficient multimodal transportation infrastructure in Indian cities increases travel time, waiting time, traffic congestion, traffic accidents, travel costs, fast-growing energy consumption, and walking distance. The multimodal transportation system's journey time performance must be analysed to tackle these transportation concerns. Thus, this research provides a fundamental method for assessing multimodal transportation system trip time performance. This study proposes three steps for assessing travel time performance: identifying factors, generating individual indices, and evaluating the Multimodal Transport System Travel-Time Performance Index. The travel-time performance index of Bhopal city was 0.79 after evaluating the results of the individual indices (Access 0.49, In-vehicle 0.39, and Egress 0.38). Consequently, this study will help identify areas for improvement in Bhopal's multimodal transportation system and provide insights for enhancing its efficiency and user satisfaction. The proposed methodology can be applied to other cities facing similar challenges, aiding in the development of more sustainable and user-friendly transportation systems.

Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems

ABSTRACT Big mobility data (BMD) have shown many advantages in studying human mobility and evaluating the performance of transportation systems. However, the quality of BMD remains poorly understood. This study evaluates biases in BMD and develops mitigation methods. Using Google and Apple mobility data as examples, this study compares them with benchmark data from governmental agencies. Spatio-temporal discrepancies between BMD and benchmark are observed and their impacts on transportation applications are investigated, emphasizing the urgent need to address these biases to prevent misguided policymaking. This study further proposes and tests a bias mitigation method. It is shown that the mitigated BMD could generate valuable insights into large-scale public transit systems across 100+ US counties, revealing regional disparities of the recovery of transit systems from the COVID-19. This study underscores the importance of caution when using BMD in transportation research and presents effective mitigation strategies that would benefit practitioners.

Unified closure relationship for slug liquid holdup

AbstractSlug flow is a common flow pattern in pipes operating with gas–liquid mixtures. The slug flow's periodic behaviour affects the performance of multiphase transportation systems, which is generally predicted using mechanistic models. Mechanistic models are based on one‐dimensional mass and momentum conservation equations and require additional relationships to define a complete system of equations. These additional equations are usually called closure relationships. The slug liquid holdup () is one of the required closure relationships. In this paper a unified closure model for is proposed considering the energy balance and the interaction between inertial, gravitational, viscous, and surface tension forces. The model parameters' behaviour is described as a function of a new dimensionless number. The experimental data analysis shows that this number can quantitatively define two flow categories: ‘low viscosity flow’ and ‘medium/high viscosity flow’. Slug liquid holdup changes its behaviour in these regions due to the predominance of inertial–surface tension forces or gravitational–viscous forces, respectively. The proposed closure performs better than the existing mechanistic and empirical models.

Good practices on transit operation design: bus drivers’ perspective

Understanding which aspects can have the greatest influence on the performance, comfort and safety of a public transport system can be of great help in improving its operation and promoting more sustainable mobility. To find out more about these aspects, a survey was carried out among more than 180 drivers of urban bus transport systems in seven medium-sized cities in Spain. The drivers' perspective has been insufficiently taken into account in previous research, despite the fact that these workers have a high and direct knowledge of the operation and problems directly affecting the service. The data collected through this survey have been analysed using descriptive statistics and an Ordered Probit model. The results have allowed us to detect specific aspects to improve the performance and comfort of users and drivers such as the correct location and length of bus stops and enforcing regulation to ensure that buses have priority in traffic and that illegal parking does not interfere with their operations. In addition, bus lanes were seen as important by drivers to improve the comfort and safety of the service. Other factors related to safety were generally highly rated and there was little dispersion in the responses about their importance, although aspects such as proper visibility, avoiding illegal parking, and campaigns to encourage bus users to be aware of their surroundings stood out in the answers. Finally, the payment system was highlighted as very relevant to ensure the performance and comfort of users and drivers during the operation at bus stops. Improving this system was identified as the measure that could have the greatest impact on the performance of the service as a whole.

Mechanisms that Alter Capacity for Adenosine Triphosphate Production and Oxidative Phosphorylation: Insights from Avian Migration.

Avian migration is among the most energetically demanding feats observed in animals. Studies evaluating the physiological underpinnings of migration have repeatedly shown that migratory birds display numerous adaptations that ultimately supply the flight muscle mitochondria with abundant fuel and oxygen during long-distance flights. To make use of this high input, the organs and mitochondria of migrants are predicted to display several traits that maximize their capacity to produce adenosine triphosphate (ATP). This review aims to introduce readers to several mechanisms by which organs and mitochondria can alter their capacity for oxidative phosphorylation and ATP production. The role of organ size, mitochondrial volume, substrate, and oxygen delivery to the electron transport system are discussed. A central theme of this review is the role of changes in electron chain complex activity, mitochondrial morphology and dynamics, and supercomplexes in allowing avian migrants and other taxa to alter the performance of the electron transport system with predictable shifts in demand. It is my hope that this review will serve as a springboard for future studies exploring the mechanisms that alter bioenergetic capacity across animal species.

Managing Urban Environment: Assessing the Role of Planning and Governance in Controlling Urbanization in the City of Amman, Jordan

The aim of this paper is to explore gaps in the spatial planning and governance systems that affect the ability of local authorities to manage urbanization in Amman, the capital of Jordan. A qualitative method using in-depth interviews with top managers was adopted to understand urbanization challenges and their relationship with spatial planning and governance systems. Findings reveal that spatial planning and governance systems are unable to manage urbanization effectively. Several planning gaps, such as the inability of the spatial planning system to align with the socio-economic context, the lack of policy instruments that provide practical solutions to urbanization challenges, the mismatch between planning and natural resources, the inefficiency of the land subdivision system, the ineffectiveness of urban growth boundary policy, and the poor performance of the public transportation system, have contributed to this lack of inability. The findings reveal a number of governance gaps, such as lack of coordination and overlapping roles between public authorities, centralization, lack of public participation, and insufficient information, have hindered the ability of public authorities to manage urbanization efficiently. To enhance the urban environment, this study provides important insights for policymakers to improve the overall performance of spatial planning and governance.

Toward better equity: Analyzing travel patterns through a neural network approach in mobility-as-a-service

The quantitative implications of Mobility-as-a-Service (MaaS) for travel equity and transportation system performance are underexplored, a gap primarily attributed to the complexities of forecasting travel pattern shifts in response to a broad spectrum of MaaS bundles via conventional methodologies. In this study, we utilize Neural Network models to identify the primary characteristics that influence the use of various travel modes, drawing upon data from a stated preference (SP) survey administered in Hong Kong. We evaluate the repercussions of enforcing various equity metric constraints on system efficiency and undertake a thorough analysis of the ensuing variations in system emissions and profitability. Our findings highlight the profound influence of established pre-MaaS travel patterns on subsequent behaviors following MaaS introduction. Moreover, our findings reveal that socio-demographic characteristics exert a greater impact on travel mode usage than the attributes of MaaS bundles, highlighting the entrenched lifestyle preferences and economic conditions that shape travel behavior. Furthermore, our research reveals that while the enforcement of equity constraints typically reduces system efficiency, specific ranges exist where such enforcement may be advantageous in terms of emission reductions and increased profitability for MaaS platforms.

Optimizing platoon safety through key node selection in pinning control strategy

The advent of Connected and Automated Vehicles (CAVs) and vehicular platooning has ignited high expectations for improving the safety performance of future transportation systems. Present control strategies for CAV platoons primarily concentrate on regulating each vehicle within the platoon. Although theoretically equipped to optimize a variety of performance metrics, this method is heavily dependent on communication and computational resources, which may lead to exorbitant costs. This study proposes a pinning control strategy that focuses on the selection of pivotal nodes, thereby facilitating the optimization of safety indexes for the entire platoon through the control of a select group of vehicles. The strategy encompasses two critical aspects: the identification of key control nodes and the application of node-based control. Initially, a feature matrix that includes both the intrinsic dynamics of the vehicles and the dynamics relative to other vehicles is developed. Spectral clustering is then utilized to identify these pivotal nodes. Subsequently, specialized control mechanisms for these nodes are devised, based on Proportional-Integral-Derivative (PID) controllers, with the objective of improving platoon safety. The efficacy of this strategy is corroborated through numerical simulations. To assess the safety performance, four categories of Surrogate Safety Measures (SSMs), which consider distance and acceleration, are applied. The findings confirm that the pinning control strategy significantly enhances performance across various SSMs, considerably reducing the risk of collisions during platoon operations. Moreover, it improves operational efficiency and platoon stability, establishing its value as an effective method for safety enhancement.

A decentralized production approach to measure fuel performance of bus transportation systems

AbstractThis paper presents a comprehensive measure of fuel performance, considering economic and environmental factors using Data Envelopment Analysis (DEA). The study uses decentralized production approach, modeling two technology specifications, one with abatement and one without. The study focuses on the Indian public bus transport industry, treating carbon emissions as bad outputs with joint disposability alongside fossil fuels. Additionally, it examines fuel performance drivers through bootstrapped truncated regression. The findings reveal that maintenance practices and vehicle age negatively affect fuel performance, with the latter showing a non‐linear influence. As fuel prices rise, bus company managers increasingly adopt fuel‐saving practices.

An explicit approach for modeling the performance of transportation networks immediately after an earthquake

Surface transportation systems play a vital role in supporting a region’s functionalities. They are expected to remain operational before and even after a hazardous event (e.g. an earthquake). The importance is evident to estimate the post-disaster performance of traffic systems under a probability-based framework, considering the uncertainties arising from both the hazards and the transportation infrastructure fragilities. This paper proposes an explicit approach for evaluating the performance of transportation systems immediately after an earthquake event. The method estimates the spatial distribution of vehicles in the traffic network in a closed form and thus is relatively efficient compared with traditional methods (e.g. an agent-based method). The applicability of the proposed approach is demonstrated through an application to the post-earthquake performance assessment of the traffic network in Tangshan City, China, a city that suffered catastrophically from the 1976 Tangshan Earthquake. Analytical results show that the proposed method can well reflect both the temporal and the spatial variations of the traffic flow, and thus offers rational support for predicting the post-earthquake traffic scenarios and for optimizing strategies to improve the transportation capability under emergent conditions.

Analysis of multi-modal public transportation system performance under metro disruptions: A dynamic resilience assessment framework

The well-functioning multi-modal public transportation systems play crucial roles in reducing traffic congestion, alleviating environmental pollution, and improving mobility. There are variants of disruptions that may impede the smooth functioning of public transportation systems and challenge their normal operations. It is essential to develop resilient multi-modal public transportation systems, and a reasonable resilience assessment framework serves as the foundation for developing such systems. In this paper, we propose a resilience assessment framework based on performance-based measurement metrics. We develop a dynamic simulation procedure that considers the impacts of disruptions on passenger choices of path and departure time. By incorporating these features into the simulation procedure, we can effectively model the variations of passenger flow under disruptions. Finally, to demonstrate the proposed resilience assessment framework and dynamic simulation procedure, the multi-modal public transportation system in Beijing is considered as a case study. The results reveal that the system exhibits good resistance and recovery capabilities, but it lacks robustness. Additionally, we discuss the effects of downtime, bus frequency, bus bridging services, and proportions of commuters on resilience, which lead to several valuable policy implications.