Browse Topic: Public transportation systems

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A Mode Code Configuration Method for Remote Terminals in 1553B Bus Systems2026-99-18267/17/2026
Requirements of Interface for Aircraft/Store Electrical Interconnection System (GJB 1188A-99) is the current standard followed by all types of carrier aircraft and stores. This paper designed a 1553B bus remote terminal mode code configuration method that met the requirements of GJB1188A standard, completing the interrupt initialization and data initialization of compulsory mode codes. These comprehensive test results confirm that the proposed mode code configuration method is both reliable and effective, and provides strong portability, which can be used as a reference for the GJB1188A interface software design of other components
Han, Bin, Zhang, Kun, Liu, Xuhan, Ye, Jinhan, Li, Zhengmao
Research on Urban Bus Timetable Optimization Based on Deep Reinforcement Learning2026-99-05387/10/2026
Public transportation serves as a crucial component of urban mobility, contributing to the alleviation of urban congestion, reduction of travel expenses, and mitigation of air pollution. Nonetheless, the dynamic passenger demand and the complex traffic conditions render traditional bus timetables inadequate, leading to ineffective allocation of public transportation resources. Consequently, it is essential to create bus timetables that are responsive to actual traffic scenarios and fluctuating passenger demand. This study regards the bus timetable planning problem as a Markov decision-making process within a discrete time framework, proposing a deep reinforcement learning-based optimization model for bus timetables. In particular, the model is designed to account for both bus companies and passengers, incorporating a state space and reward calculation method that emphasizes passenger comfort. Then Deep Q-Network (DQN) methodology is employed to issue instructions on whether a bus departure at each time, and bus timetable is generated gradually over time. Experimental results indicate that the proposed approach significantly reduces bus travel costs and enhances the overall travel experience for passengers in comparison to traditional methods.
Xu, Jie, Xia, Dong, Yang, Jianxi, Wang, Bing
Research on the Operational Efficiency of Airlines Based on the Characteristics of Airport Clusters2026-99-05817/10/2026
The features of airport clusters have a big impact on regional air transport. But problems within these clusters also affect airline operations. This study uses the Data Envelopment Analysis (DEA) model. It selects 16 airlines of different sizes as samples. It also identifies relevant input and output indicators to measure operational efficiency. The results show that the efficiency of large and medium-sized airlines generally went up. Small airlines have shown a slow but steady improvement in efficiency, with significant volatility due to cost and slot constraints. So, the study analyzes pure technical efficiency, scale efficiency, and comprehensive efficiency. It finds out the changing patterns of operational efficiency among airlines of different sizes and the reasons behind them.
Hu, Kexin, Huang, Tao
Sustainable Airport Emissions Reduction through Optimized End-Around Taxiway Operations: A Simulation Approach2026-99-05827/10/2026
To mitigate the risks of runway incursions during aircraft transitions between closely spaced parallel runways, major hub airports globally have implemented End-Around Taxiway (EAT) as an effective safety solution. Operational data from leading international airports confirms that EAT installations have successfully enhanced surface safety while maintaining operational efficiency. However, the EAT involves a longer taxiing route, resulting in higher fuel consumption and pollutant emissions. This study takes the example of a set of closely spaced parallel runways at a domestic airport to analyze the ground taxiing process of arrival and departure flights, proposing a dynamic allocation strategy for EAT operations that can achieve energy conservation and emission reduction during the taxiing process. Through simulation, its effective operational performance is studied.
Wang, Zinan, Ye, Bojia
Aircraft Noise Event Identification Technology Based on Single Acoustic Vector Sensor2026-99-05917/10/2026
With the rapid development of China’s civil aviation industry, the problem of airport noise has attracted widespread social attention. The requirement for the real-time monitoring and evaluation of acoustic environment around airports is becoming more and more intense. The identification of aircraft noise events in the complex acoustic environment surrounding the airport is the most critical technical problem in airport noise monitoring. However, the traditional noise source identification technology is difficult to be widely used in real-time monitoring system due to its large errors and complex deployment conditions. This paper presented an aircraft noise source identification technique based on a single acoustic vector sensor. The azimuth parameters of the noise source were estimated by the three-dimensional spatial positioning algorithm of sound pressure and particle vibration velocity combined with information processing, and the three-dimensional footprint of the noise event in the complex acoustic environment was described. Finally, the event was judged as an aircraft noise event by matching the noise footprint with the aircraft flight path. By monitored and analyzed the actual noise events of aircraft departure, the results show that this method can only use a single acoustic vector sensor to locate the aircraft noise source and distinguish the aircraft noise event from the background noise event, which provide a new lightweight method for the real-time airport noise monitoring system to locate the noise source and identify the aircraft noise event
Hou, Jiayu, He, Tianlun, Zhu, Lin, Chen, Ying, Liu, Yinhui, Lv, Lei, Wang, Yuhao, Chen, Da
Design and Analysis of Orthogonal Excitation Eddy Current Brake for High-Speed Trains2026-99-05137/10/2026
As high-speed train technology advances, the demands on braking system performance have intensified. Known for their efficiency, reliability, and eco-friendliness, Linear Eddy Current Brakes (LECB) have become a focal point in the research and development of high-speed train braking systems. This paper presents an innovative Orthogonal Excitation Eddy Current Brake (OEECB), which enhances the braking force without modifying the overall dimensions of the conventional LECB. By adding a set of longitudinal excitation coils parallel to the rail surface, the OEECB creates an orthogonal excitation structure that augments the braking force. Initially, this paper outlines the design concept of the OEECB and then analyzes its working principle based on electromagnetic field theory. Subsequently, a finite element solver is employed to numerically model the electromagnetic characteristics of the OEECB. Finally, by comparing the performance differences between the conventional LECB and OEECB, the superiority of the OEECB in enhancing braking performance is demonstrated. The results indicate that under the same excitation current conditions, the OEECB increases the braking force by over 20 % while maintaining a controllable increase in attractive force.
Huang, Liuwen, Zuo, Jianyong, Zhang, Yu
Distributed Control Method and System of Formation Train Based on Multi-Objective Operation Curve Optimization2026-99-05557/10/2026
In order to improve the transportation efficiency of high-speed trains, reduce the operational energy consumption and ensure the on-time arrival of trains, the operation curve optimization is regarded as a key way to achieve the above objectives. In this paper, a distributed control method and system for grouped trains based on multi-objective running curve optimization is introduced. Firstly, the train dynamics equations are established by considering the combined forces during train operation and the train driving maneuvering strategy, combining with the line conditions, and dividing the train operating conditions; secondly, combining with the virtual grouping technology, the train units are kept in a high safety and smooth tracking operation with small intervals between the train units; and then the constraints, such as setting up safety protection distance and Then, the constraints of safety protection distance and space-time safety protection are set, and with energy-saving and comfort as the optimization goals, the multi-objective hiking optimization algorithm (MOHOA) is adopted to optimize the operation curve according to the train's working conditions; finally, the high-speed train tracking and operation system model is considered to have nonlinear and parameter-variable characteristics, and is susceptible to external factors. Finally, considering that the high-speed train tracking system model has nonlinear and time-varying characteristics and is easily affected by external disturbances, a distributed control law is designed for the optimized running curve, and a sliding mode control method is adopted for tracking operation. By optimizing the running curve of the train and realizing the precise protection strategy, the control method established based on the optimized curve can ensure the smooth running of the train while improving the efficiency of railroad transportation.
Jiang, Qiqi, Chen, Guangwu, Shi, Jianqiang, Wang, Dong, Si, Yongbo, Li, Peng, Zhang, Wentao, Yang, Yang
Improved Thermal Management for Operating a Battery Electric City Bus under Real Driving Conditions2026-01-07587/1/2026
The goal of reducing global CO2 emissions requires actions especially for the transportation sector. To achieve the goal, electric traction motors are frequently implemented in passenger vehicles, as well as in commercial vehicles like heavy-duty trucks or buses. Particularly electric city buses have the potential to reduce the local emissions in urban areas and provide local exhaust-emission-free mobility. While their number of registrations rises, research focusses on the improvement of the overall system in order to increase energy efficiency. High importance is gained by the thermal management of the whole system. This research investigates a simulative approach to improve the thermal management and therefore the energy efficiency of an electric city bus. The different thermal components of an electric city bus like drive system, battery system and heating, ventilation and air conditioning system (HVAC system) are modelled. Their thermal behavior has been validated in previous research. Based on the validated model, this study proposes an improved thermal management that, state-dependent, combines the thermal circuits of the single components to reduce the overall energy demand. Cooling or heating is provided by the HVAC system. Furthermore, the simulation utilizes real driving cycles of a city bus in the Hamburg area. Measurement data from an entire year are examined by a cluster analysis that results in typical application profiles for urban bus traffic. These profiles are used as basis for further research. An operating strategy for the thermal management of an electric city bus under real driving conditions is developed using the simulation model. Results are presented, which show that the overall energy demand decreases due to an improved, application profile-dependent thermal management system.
Schäfer, Henrik, Hellberg, Tobias, Meywerk, Martin
Data-Driven Air Traffic Management: Forecasting Demand, Modeling Delay Propagation, and Demand Capacity Balancing2026-26-07726/1/2026
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Senthilkumar, N., S, Gopalakrishnan, Gopinath, S
Autonomous Aircraft Docking: A Vision-Based Approach to Aircraft Parking Systems2026-26-07866/1/2026
Automated aircraft parking systems enhance airport ground operations by enabling precise and autonomous docking of aircraft at gates. These systems reduce turnaround time, minimize human error, and optimize apron space through real-time object detection, obstacle avoidance, and dynamic path planning. Unlike fixed guided-path methods, the proposed system adapts to congestion and environmental conditions such as low visibility, ensuring safety and efficient maneuvering. Validation through simulation demonstrates the system’s potential to improve operational resilience and support scalable automation in future airport infrastructure.
Penugonda, Navya Sunaina, Ediga, Venkatadiwakar Goud
SAE TOMORROW TODAY - Can Airports Become Innovation Labs?135685/21/2026
What if your airport was a living laboratory for innovation? Listen in as we sit down with Brian Cobb, Chief Innovation Officer at Cincinnati/Northern Kentucky International (CVG) Airport, to explore how CVG operates as a "city within a city," deploying emerging technologies to improve passenger experience, strengthen operational resilience, and reimagine the modern airport. Discover how CVG is advancing innovation through real-time TSA wait times, robotics testing, and the growing role of AI, autonomy, and cybersecurity. Get even more insight as Brian takes the stage as keynote speaker at the 25th anniversary of AeroTech(R) this June. He'll explore what's next for aviation innovation, from connected robotics and autonomous workflows to the standards and cross-industry collaboration needed to make it all work safely. To learn more and register, visit sae.org/events/aerotech. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
An Energy-Saving Coupling-Decoupling Optimization Strategy for Electric Modular Buses Considering Vehicle to Vehicle Charging2026-99-07305/15/2026
As an emerging innovative mode of public transportation, electric modular buses (EMBs) offer a novel solution to the problems of existing public transportation systems, due to the coupling-decoupling processes. In this paper, we study the energy consumption characteristics of EMBs by joining vehicle-to-vehicle (V2V) charging and reduction in aerodynamic drag due to coupling. For the pursuit of energy economy, ride comfort, and operational efficiency, we constructed an optimization scheme based on the simulated annealing (SA) algorithm to facilitate the coupling-decoupling process. The simulation results show that EMBs can meet 82.5 % of service requests compared with 61.8 % for the benchmark group, and V2V presents a significant contribution to energy efficiency, especially at low battery state of charge (SOC). Additionally, sensitivity analysis is conducted to study the impact of initial SOC, operation interval, and route type. The results provide insights for optimizing EMBs’ operations and emphasize the potential role of EMBs in supporting low-carbon and sustainable urban mobility systems.
Liao, Peng, Guo, Jiahe, Ning, Donghong, Li, Sijia, Wang, Tao
SAE TOMORROW TODAY - How Kansas is Reshaping Multimodal Transportation135624/7/2026
What does it take to build a multimodal transportation network that actually works for rural communities, growing regions, and everyone in between? In Kansas, that question is critical as the Kansas City Chiefs plan their stadium move and the 2026 FIFA World Cup comes to town. Listen in as we sit down with Matt Messina, Chief of Multimodal Transportation at the Kansas Department of Transportation (KDOT), to explore how Kansas is prioritizing transit solutions for upcoming projects and how community input shapes decisions. It's an insightful journey into the challenges and opportunities of public transit, pedestrian infrastructure, and the future of mobility. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
From Propane to Pi: Affordable AI-Driven Solutions for Sustainable Bus Heating2026-01-01644/7/2026
This paper proposes an intelligent, artificial intelligence (AI) enabled seat heating system for school buses that saves energy by only activating heating elements when a passenger is identified. A custom-trained YOLOv8 deep learning model identifies passengers in real time and opens/closes real-time control of the individual electric seat heaters via a Raspberry Pi 5. The detector achieves around 10 frames-per-second (FPS) of inference on the Raspberry Pi 5 and 80–90 FPS on a laptop with over 92% detection confidence across various illumination conditions. Energy modeling shows the anticipated demand for a 10-kW propane-based heater is approximately 75% lower by implementing a 2.52 kW electric seat-heating system. In a typical operation schedule of 540 hours a year, this results in 4,000–5,000 kWh of annual savings, $465–$579 of annual cost savings and mitigates 0.9–1.3 t CO₂ per bus, annually. When implemented at the fleet level, the energy and cost saving will be in proportion. This approach offers a cost-effective, modular, and safe electrified public transportation solution that integrates comfort optimization with environmental accountability.
Chikkala, Daney Bhargav, Zadeh, Mehrdad, Tan, Teik-Khoon, Ponnam, Jitin, Batte, Jai Rathan
Operational Feasibility of Battery Swapping in U.S. Transit: A Case Study of King County Metro2026-01-04024/7/2026
Battery swapping technology has emerged as a promising alternative to conventional charging for electric bus fleets, offering rapid turnaround times and improved vehicle availability. This paper utilizes existing bus routing information to perform an initial site evaluation for battery swapping stations. A Seattle-based public transit agency—King County Metro, a partner on this project—is used as a case study. Using General Transit Feed Specification (GTFS) data from King County Metro, a MATLAB model was built to reconstruct blocks and layovers, extracts dwell-time opportunities, and performs block-distance and block-time analyses to understand operational rhythms. based bus model was developed that maps route mileage, efficiency, and layover availability for battery swap decisions, using a look-ahead rule that defers battery exchanges whenever the next feasible layover can still be reached while respecting a minimum state-of-charge. The workflow estimates how many swaps each block requires over a service day, the effective driving range a pack can deliver between swaps, and the spatial clustering of recurring layovers. This clustering, combined with assumed battery swapping time provides initial identification of suitable battery swapping station placement. Results indicate that swap windows naturally emerge from scheduled layovers, enabling a swapping system to be layered onto current service patterns, providing estimates for station sizing by corridor demand, and planned within existing operational constraints. The approach offers a practical template for transit agencies to assess technical and operational feasibility and to start planning right-sized battery swapping infrastructure.
Vadlapatla, Taraka Rishi, Jankord, Gregory, D'Arpino, Matilde
Optimized Design and Economic Evaluation of a Renewable Hydrogen Refueling Station for Public Transport on Elba Island14-15-01-00042/13/2026
The aim of this study is to develop a methodology to significantly reduce emissions in bus fleet renewal scenarios by investigating both technical and economic aspects. This work presents a case study based on Elba Island, Italy, which investigates optimal solutions for replacing existing Diesel buses through a total cost of ownership analysis. The investigation is carried out for four different potential scenarios: renewing the fleet with Diesel buses, renewing the fleet with electric buses, adopting fuel cell buses, and implementing a hybrid solution. The latter represents a synergistic solution that integrates fuel cell buses with the development of a hydrogen refueling station driven by a proton exchange membrane electrolyzer, unlocking the techno-economic potential of self-producing green hydrogen for bus refueling. The novelty of this study is its integrated methodology that combines a total cost of ownership analysis with a tailored design of a green hydrogen production network optimized for continuous fleet operation. A constrained optimization algorithm was employed to determine the optimal configuration of key plant components, including the proton exchange membrane electrolyzer system size, the amount of photovoltaic panels and wind turbines, and the capacity of the hydrogen storage tank. The grid-based alternative offers a simple payback period under 4 years and a total cost of ownership of 6 M€, making it more cost-effective than the 6.5 M€ electric and 7.5 M€ Diesel options. These results provide a scalable, replicable roadmap for accelerating sustainable public transport adoption in similar contexts.
Bove, Giovanni, Sorrentino, Marco, Baldinelli, Arianna, Desideri, Umberto
Assessment of Cybersecurity Risks in State-Operated Connected Electric Passenger Buses in India2026-26-06101/16/2026
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller Area Network or CAN bus) are important areas of interest. Potential interruptions to vehicle functionality and passenger safety are examined in relation to common attack techniques such spoofing, data injection, denial-of-service (DoS), and remote code execution. In comparison to international standards like ISO/SAE 21434 and UNECE rules R155/R156, the report also assesses regulatory and compliance deficiencies in India. It lists the operational difficulties that Indian STUs encounter, including as antiquated infrastructure, a deficiency in cybersecurity knowledge, and a lack of established protocols. The paper suggests a plan for installing a Cybersecurity Management System (CSMS) in STU-operated EV fleets in order to reduce these threats. Strong incident response mechanisms, focused training initiatives, and the creation of cybersecurity standards tailored to India are among the recommendations. Implementing these measures will enhance the resilience of electric vehicle infrastructure against emerging cyber risks. Furthermore, collaboration between government agencies, industry stakeholders, and academic institutions is emphasized to ensure a comprehensive cybersecurity framework.
Mokhare, Devendra Ashok
A Comprehensive Study: The Potential of Wireless Charging in Future E Mobility2026-26-01951/16/2026
Electric mobility is no longer a distant vision, it is a global imperative in the journey of fight against the climate change and the urban pollution. Yet, despite of explosive growth in the electric vehicle adoptions, a major bottleneck remains which is efficient and convenient charging. The current reliance on physical plug in charging station creates inconvenient, time consuming experience and also faces significant technical and economic challenges those threaten to stall the smooth clean transportation revolution. Without innovation in how we recharge our vehicle the promise of electric mobility appears under threat which is undermined by less efficient, less compatible, and infrastructure hurdles. Wireless charging technology stand out as the game changing breakthrough poised to tackle these all critical problems head on. By enabling the effortless, cable-free charging system across the wide spectrum of electric vehicles, from the personal cars to the public transport fleets and to the micro mobility devices, it offers a more convenient & efficient future in which powering up is as seamless as driving. Still the key challenges such as energy transfer efficiency, infrastructure investments, safety, and interoperability standards must be overcome before this technology can fulfil its transformative potential. The paper embarks on a compelling journey which start with the foundational history of wireless power & navigating through global market dynamics and emerging trends and culminating in a forensic level analysis of ten main wireless EV charging technologies. Each technology is deeply evaluated against the regressive critical criteria which including efficiency, safety, cost and scalability. Ahead a weighted multi criteria hypothesis analysis is done that predicts their future viability and application. This deep, comparative framework demystifies complex trade off and offers clear & actionable guidance for industry leaders, engineers and policymakers. The paper not only highlighting the transformative potential of wireless charging but also providing strategic insights that can reshape our urban mobility and fleet operations. As EV ecosystems evolves toward intelligence, automation and more sustainability, this research becomes indispensable not just for understanding the present but for architecting a smarter, cleaner and electrified future of transportation.
Jain, Gaurav, Premlal, P, Pathak, Rahul, Gore, Pandurang
Regenerative Braking Control Strategy for Electric Commercial Bus under Indian Road Condition Using Artificial Neural Network2026-26-06451/16/2026
The main focus of this paper is to create a more efficient regenerative braking control strategy for electric commercial buses operating under Indian road conditions. The strategy uses Artificial Neural Networks (ANNs) to optimize regenerative braking process. Regenerative braking helps to recover energy that would otherwise be lost during braking and convert it back into usable power for the vehicle. The challenge is to design a system that works effectively on the diverse and often challenging road conditions found in India, such as varying gradients, traffic patterns, and road surface types. This study begins by collecting data (which includes vehicle speed, traffic condition, etc.) from real-world driving conditions and aims to train an Artificial Neural Network (ANN) using a large set of driving data which is collected under various conditions to predict the most efficient regenerative braking settings for different driving scenarios. This research brings a new approach to the application of regenerative braking in electric buses by using Artificial Neural Networks. Previous works in this area mostly focused on passenger vehicles or did not take into account the unique challenges posed by Indian road conditions, such as heavy traffic and frequent elevation changes. This study addresses those challenges directly by focusing on electric buses, which are a growing segment of the public transportation sector in India.
Saurabh, Saurabh, Bhardwaj, Rohit, Patil, Nikhil, Gadve, Dhananjay, Amancharla, Naga Chaithanya
Powertrain Optimization of Indian City Electric Bus Using Active Learning Simulation Methodology2026-26-06571/16/2026
Public transport electrification is going to play a massive role in India’s COP26 pledge to achieve net zero emissions by 2070. India plans to electrify 800,000 buses in a push towards 30% EV penetration by 2030. Further encouraged by government incentives under National Electric Bus Program (NEBP), e-Bus market is expected to grow at a CAGR of ~86% annually over the next 5 years. With most OEMs going for fleet electrification for reducing CO2 emissions and to cater to growing demand in Indian cities for cleaner public transport, improving powertrain efficiency and performance of state-of-the-art e-Buses is a natural progression of e-mobility sector development in India. The first step in designing powertrain for an electric city bus is to determine the motor(s) size and transmission specifications (number of gears, gear ratios etc.). Complications arise due to a wider and non-linear operation range of eBus. This study focuses on powertrain optimization for a medium duty electric city bus for an Indian city. FEV’s in-house Vehicle Powertrain System Design & Controls (VPSC) tool is deployed for a structured approach. It uses backwards simulation approach to estimate energy consumption and performance of vehicle. An initial (reference) electric drive unit (EDU) is selected via local pre-simulation for detailed flux linked loss maps. This is followed by an iterative AI based Global Optimizer which uses Bayesian algorithm to arrive at subsequent designs until the objective is met within the stated constraints. Performance parameters considered include acceleration and gradeability. The simulation is performed on a high traffic Indian city duty cycle as well as a reference urban VECTO cycle. In both cycles, results show a significant improvement in energy consumption while at the same time improving upon performance with respect to initial pre-simulation selected design of motor and transmission.
Sandhu, Rouble, Chen, Bicheng, Emran, Ashraf, Xia, Feihong, Lin, Xiao, Berry, Sushil
Quantifying the Energy Consumption of HVAC Operation and Its Impact on the Range of Electric Buses Across Diverse Climatic Conditions2026-26-02041/16/2026
Electric buses (e-buses) are essential to sustainable public transport, but their real-world efficiency and range are heavily affected by auxiliary systems, particularly the Heating, Ventilation, and Air Conditioning (HVAC) system. This study investigates how ambient temperature variations and HVAC loads influence energy consumption, range, and efficiency in e-buses operating under diverse climatic conditions. The methodology combines field data collection from urban e-buses across seasons—including extreme summer and winter—with controlled laboratory testing. Field measurements included ambient temperature, HVAC demand, vehicle speed, state of charge (SOC) variation, and energy consumption. These inputs were used to develop real-world duty cycles, replicating actual thermal loads, passenger profiles, idling periods, and driving patterns. In the laboratory, these cycles were simulated using a chassis dynamometer and environmental chamber, with HVAC systems tested at controlled ambient temperatures (−5 °C to 45 °C). Energy split analysis quantified the proportion of energy used for propulsion versus HVAC, revealing the range impact under extreme conditions. Key results show a 20–40 % range reduction during peak HVAC operation, with variability tied to cabin insulation, HVAC control strategies, and route dynamics. The study compares climate control, thermal pre-conditioning, and dynamic thermal management to optimize efficiency. By bridging real-world data with laboratory validation, this research delivers actionable insights for original equipment manufacturers (OEMs), fleet operators, and policymakers to mitigate HVAC-related energy losses and ensure reliable e-bus deployment across climates.
Vishe, Prashant, Dalela, Saurabh, Saraswat, Shubham, Joshi, Madhusudan
Revolutionizing Mass Mobility: Sustainable, Safe, and Smart Transport Ecosystems2026-26-03601/16/2026
Mass Mobility Systems are critical for a sustainable and progressive society. As the world confronts the serious challenges of global warming and urban traffic congestion, efficient mass mobility solutions become critical in reducing carbon footprints and enabling equitable access. Advancement in mass mobility is not limited to electric buses alone but also includes innovations across conventional ICE vehicles, autonomous vehicles, trains, and other integrated transport networks. Safety and accessibility for users remain critical to the sustainability of future mass mobility concepts. The COVID-19 pandemic exposed vulnerabilities in public transportation, highlighting the urgent need for safer and more resilient systems. Road safety, passenger well-being, and hygienic standards must be deeply embedded into future mobility solutions. Furthermore, strong last-mile connectivity will be essential to ensure that mass mobility truly meets the needs of all citizens. An effective Mass Mobility System integrates various modes - buses, trains, and feeder services into a seamless travel experience. Cities like Singapore provide excellent examples of how integrated planning, smart scheduling, and multimodal connectivity can achieve this goal. The future of mass mobility will see an increasing adoption of EV technology, offering significant advantages in reducing emissions, noise, and vibration. However, ICE and hybrid solutions will continue to play a supporting role, especially in specific geographies and use cases. Additionally, the emergence of autonomous vehicles promises to reshape the landscape dramatically, creating an altogether new world of transport possibilities. Artificial Intelligence (AI) will become a key differentiator, enabling smarter route planning, personalized user experiences, and real-time adaptability. This paper explores how Mass Mobility Systems can evolve to balance sustainability, safety, technology, and inclusiveness, offering insights for city planners, mobility operators, and policymakers to create future-ready transport ecosystems.
Vasudevan, M, Kumar S, Ashok, Sridevi, M, Kumar, Rajiv, Kumar, Om
Study on the Influence of Liquid Composite Swivel Arm Positioning Nodes on the Dynamic Performance of High-Speed Trains2025-99-025512/23/2025
Rubber components are an important part of the suspension system of high-speed trains, and the complex nonlinear characteristics of rubber parts have a significant impact on the vehicle dynamic performance. This paper establishes a nonlinear dynamics model of the liquid composite swivel arm positioning node, which can reflect the dynamic stiffness and dynamic damping characteristics of the rubber components that change nonlinearly with the frequency and amplitude, and also has a fast calculation speed. The vehicle dynamics simulation model considering the longitudinal stiffness nonlinear characteristics of the arm node is established, and the influence of the stiffness nonlinearity of the liquid composite arm positioning node on the dynamic performance of the vehicle, such as straight-line stability and curve passing ability, is studied in depth through numerical simulation.
Cheng, Junqiang, Yang, Chen, Li, Longtao, Cong, Rilong, Hu, Tingzhou
Pure Electric Bus of Operational Consulting and Analysis Transit: A Case Study of Wuhu City2025-99-025212/23/2025
As China’s socio-economic progress accelerates, residents’ mobility preferences are growing more varied. Owing to their eco-friendliness, high capacity, fixed routes and low prices, pure-electric buses have become a key component of urban transit. Yet day-to-day service is hindered by low fleet availability, limited daily kilometres and poor service quality, all of which erode operation efficiency. Taking Wuhu’s public transport network as a case study, this paper builds a performance-assessment framework for electric bus routes. Using stop-level topology, vehicle specifications and spatiotemporal passenger-flow data from eight representative routes, the study applies the Analytic Hierarchy Process (AHP). A three-tier hierarchy—goal, criteria and alternatives—is constructed; index weights and pairwise comparison matrices are then computed to rank overall route effectiveness. The findings accurately pinpoint operational bottlenecks and furnish quantitative guidance for adaptive network redesign and resource reallocation, offering a transferable benchmark for enhancing the performance of medium-sized city transit systems.
Hu, Tingting, Liang, Zijun, Li, Xiaoyan, Zhang, Xinyi, Wang, Mengru, Hu, Yufeng, Jiang, Kang
Optimization Model of Express–Local Train Schedules under Cross-Line Operation of Suburban Railway2025-99-024512/23/2025
Cross-line operation is a key direction for the integrated development of multi-level rail transit systems in urban agglomerations. Optimizing train operation under cross-line conditions is essential for improving the overall efficiency and service quality of rail networks. This paper addresses the joint problem of suburban railway cross-line operation and express–local train coordination. This paper develops a train scheduling optimization framework that jointly selects service patterns and departure schedules, with the objective of reducing overall costs, including passenger travel time and operating expenses. To solve the model efficiently, an extended Adaptive Large Neighborhood Search (ALNS) algorithm is developed. The proposed approach provides a practical framework for timetable planning in complex cross-line rail systems and contributes to enhancing integrated transit operations.
Zhu, Jingyi, Guo, Xin, Pan, Jianju
Study on the Environment of Subway Stations from the Passengers’ Perception: A Case Study of Shenzhen Metro2025-99-023012/23/2025
As a part of high-capacity public transportation system, subway stations necessitate evaluations from passengers’ perspective, which is the goal of this study. It took Shenzhen Metro as an object, employing field observations and questionnaire interviews as primary methods. The questionnaire was structured across four dimensions: subjects demographics, travel routines and in-station experiences, evaluations of wayfinding systems and facilities, and suggestions for improvements. Data analysis reveals that the majority of the subjects use the subway for daily commuting, and the congestion spots are concentrated at station entrances/exits, security checkpoints, vertical circulation points, and train door zones. The subjects’ overall satisfaction with Shenzhen Metro is quite high, driven primarily by wayfinding signage efficacy, route fluency (entry/exit/transfer), and safety perceptions. Subway station design should take spatial layouts and passenger flow optimization into consideration to alleviate congestion, while ensuring clear passenger awareness of emergency evacuation routes. Additionally, integrating auxiliary functions such as luggage storage, cultural exhibition, dining/retail and so on are expected. These findings can be references for metro station plan, design, and operational management.
Wu, Xiangyang, Gan, Xuanci
Current Challenges and Technological Opportunities for Implementing Autonomous Vehicles in Urban Public Transport2025-36-008512/18/2025
Driven by technological advances in artificial intelligence, sensors, connectivity and sustainable mobility, autonomous buses are a reality in many contexts where their application is viable and efficient. The potential of the technology is a clear theme and has been widely discussed over the last two decades, due to various factors such as reducing accidents, increasing operating cost efficiency, improving the efficiency of public transport, reducing environmental impact and offering mobility solutions for increasingly congested urban areas. Due to the implementation of the General Safety Regulation (GSR II) in the European Union, with the aim of reducing traffic accidents and paving the way for fully autonomous vehicles, autonomous vehicles are getting closer to becoming a viable reality on the streets and highways of developed countries [1]. In order to guarantee the necessary safety in autonomous systems, data reliability is fundamental. To this end, it is essential to implement electronic architecture technologies that are responsible for sensor redundancy, preventing isolated failures from damaging the perception of the environment. ISO 26262 is the standard responsible for this international standardization and security. While there are other standards that regulate the levels of vehicle automation, such as the Society of Automotive Engineers (SAE) classification, which defines six levels, from 0 (no automation) to 5 (full automation) [2]. The article is an up-to-date analysis of the challenges and opportunities for implementing this technology in urban public transport vehicles, identifying the main obstacles and possible solutions. It also discusses the regulatory and technical aspects, seeking to understand how the project can be developed in a safe and beneficial way for the population. Through an approach that considers the status quo of current technologies and challenges so that autonomous buses can, in fact, become a reality in public transportation.
Gameiro, João, Pirocchi, Amanda, Matias, Brenda, Paterlini, Bruno, Souza, Kerylli de, Angelone, Luca, Gama, Ulisses
Experimental Study on Key Technologies of Prefabricated Fuel Hydrant Well2025-99-036312/17/2025
With the rapid development of the aviation industry, there is an increasing demand for safe apron operations and support capabilities. As a key facility in the apron fuel supply pipeline network, the performance and stability of the fuel hydrant well are crucial. However, the traditional repair and replacement process for fuel hydrant wells faces challenges, including lengthy construction times and significant impacts on airport operations. To address these issues, this article proposes a prefabricated refueling hydrant well technology, aimed at achieving rapid replacement of hydrants under non-stop construction conditions. Through on-site experiments, we have verified the feasibility of this prefabricated fuel hydrant well technology, determined the minimum dismantling boundary, and studied the rapid dismantling process, prefabricated pavement structure and installation process, as well as the application of self-compacting and fast-setting high-strength wellbore filling materials. The experimental results demonstrate that this technology can complete all processes within 12 hours and 34 minutes, including cutting the pavement, breaking the pavement, dismantling the old fuel hydrant well, installing a new type of hydrant well, installing prefabricated pavement, grouting, and filling joints, etc., without affecting oil pressure. The grouting material and the strength of the prefabricated pavement meet the design requirements, and the grouting effect is satisfactory. The connection between the fuel hydrant well and the pavement meets the operational requirements. This study provides a new technical solution for the repair and replacement of fuel supply hydrant wells in civil airports, which is expected to significantly enhance the safety guarantee capability of fuel supply in civil airports.
Ren, Yucheng, Zhao, Kunyang, Chang, Lingsu, Wang, Xiangjun, Han, Tianhui, Li, Zonghe
Key Construction Technology of Subway Station In Urban Narrow Area2025-99-035812/17/2025
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Liu, Yao
Optimization Method for the Layout of Sponge-Like Drainage Ditches in Large Airports Based on BIM-3DGIS Coupling2025-99-035612/17/2025
The control of rainfall runoff drainage in large airports presents significant challenges, particularly in terms of real-time coupling with meteorological warnings. This paper proposes an optimization method for the layout of sponge-like drainage ditches in large airports under BIM-3DGIS coupling. A BIM water supply and drainage model is constructed, with detailed inspections conducted on the functions and connections of the pipeline system in Revit software. The flow velocity and equivalent water supply pressure within the pipelines are analyzed, and collision detection is performed on the components. Based on 3DGIS technology, an optimization model for the layout of sponge-like drainage ditches is established, taking into comprehensive consideration various factors such as airport topography, rainfall characteristics, and surrounding environment. By calculating the water level changes within the infiltration and drainage ditches under different design rainfall scenarios, the storage ranges, water levels, and waterlogging duration curves of various facilities during rainfall events with different return periods are simulated. Case studies demonstrate that this method can effectively improve airport drainage efficiency, reduce peak drainage flow, mitigate the risk of waterlogging, and decrease the number of collision points in drainage pipelines. It provides a scientific basis and technical support for the planning and design of sponge-like drainage ditches in large airports.
Geng, Liangsui, Zhao, Zhenyu, Hu, Jing
Digital Site Selection Analysis of Airport Control Tower Based on BIM2025-99-035912/17/2025
This paper analyzes the problems encountered in the site selection of large domestic airport towers. Combined with the site selection results of many large airports in China and a large number of scenarios simulated by FAA VIS software, multiple key factors such as line of sight angle, lateral resolution angle, target detection probability, and target recognition probability are analyzed, and quantitative calculation formulas are given. Finally, BIM software is used to simulate the airport and tower, and give coverage analysis for runways, taxiways, and aprons.
Shi, Yongtao, Wang, Shuo
Research on Risk Analysis of Emergencies in Heavy-Haul Railway Operations Based on Knowledge Graph2025-99-034712/17/2025
Heavy-haul railways are a critical component of China’s dedicated freight rail network, serving as the primary land transport channel for energy and resource intermodal transportation. Their safe operation and transportation is essential for ensuring the reliable delivery of energy and raw materials. Taking the Shuohuang Heavy-haul Railway as a case study, based on the hazards identified across its entire operational chain, an ontology model structured as "professional module–task–process–hazard–risk attribute–management object" is constructed in this paper. Based on this model, a knowledge graph for heavy-haul railway operational emergencies is established. The study analyzes the connectivity between different nodes (e.g., work processes and hazards) in the knowledge graph and their potential relationships with risk values. Using directed graph-based degree centrality analysis, a risk assessment method incorporating node centrality is proposed. Risk values are computed at both the hazard and process levels, followed by risk ranking and analysis. The risk ranking results demonstrate that considering node centrality yields rankings that better reflect the complex division of labor in heavy-haul railway transportation system, thereby providing more effective support for emergency risk management. The research results can provide decision-making support for the prevention and control of emergencies in heavy-haul railway operations, as well as safety management.
Fu, Liqiang, Ren, Xiaolin, Rong, Lifan
Analysis of the Effect of High-Speed Train Travel on The Characteristics of Flow Field Distribution Near Wrist Arm Insulators in Tunnels2025-99-032712/17/2025
With the continuous progress of modern high-speed railroad technology, the speed of train operation is increasing, and its aerodynamic effect when traversing the tunnel is also getting more and more attention from researchers. In this paper, we constructed a three-dimensional flow field model of the wrist-arm insulator in the tunnel and considered the train speed, tunnel structure, size and position of the wrist-arm insulator, and other factors, and then through the simulation software, we simulated the change of the airflow in the tunnel when the high-speed train enters the tunnel. Through the simulation analysis, we obtained the characteristics of the flow field distribution around the wrist-arm insulator in the tunnel when the high-speed train crosses the tunnel. The results show that when the train crosses the tunnel at a high speed, the airflow inside the tunnel is strongly squeezed and disturbed by the train, forming a complex airflow field. When the train passes by, the wrist insulator will be impacted and squeezed by the high-speed airflow generated from the train, resulting in significant changes in the airflow velocity and pressure distributions on its surface. These changes not only affect the electrical performance of the arm insulator but also have a direct impact on its structural stability and service life.
Zhang, Kangkang, Ma, Jianqiao
Spatial Distribution Pattern and Accessibility Analysis of Hexi Corridor2025-99-034512/17/2025
In order to better understand the development level and the degree of development of the transportation network in different areas of the Hexi Corridor, the accessibility of the transportation network in the Hexi Corridor is studied. Firstly, calculate the road density of each county and district in the Hexi Corridor. Then, in view of the topographic characteristics of the Hexi Corridor, introduce the shortest travel time and travel cost into the gravity model, consider the accessibility of both road and railway transportation modes between nodes, construct a comprehensive accessibility model, and analyze the spatial characteristics of the comprehensive accessibility of each county and district in the Hexi Corridor. Secondly, the gravitational model is used to analyze the economic connection intensity among the counties and districts in the Hexi Corridor. Finally, calculate the Gini coefficient, draw the Lorenz curve, and analyze the fairness of the comprehensive accessibility of the Hexi Corridor. Research shows that the comprehensive accessibility and economic connection centrality of each county and district in the Hexi Corridor present a spatial structure of “one belt and one core”, and both the comprehensive accessibility and economic connection centrality show a attenuation from the core area to the strip-shaped area. Liangzhou District of Wuwei City is the main core area of the Hexi Corridor. The Gini coefficient of comprehensive accessibility based on the cumulative proportion of population and GDP is all within the unfair range, and the overall development of the Hexi Corridor and the distribution of the transportation network are unfair. The research results can provide decision support for the optimization of the transportation network, economic development and tourism development in the Hexi Corridor.
Jiang, Ping, Mu, Haibo, Peng, Zhiwei
Identification of Runway Friction Coefficient Using Extended Kalman Filter09-13-02-001212/11/2025
Aircraft operations during landing or takeoff depend strongly on runway surface conditions. Safe runway operations depend on the tire-to-runway frictional force and the drag offered by the aircraft. In the present research article, a methodology is developed to estimate the braking friction coefficient for varied runway conditions accurately in real-time. To this end, the extended Kalman filtering technique (EKF) is applied to sensor-measured data using the on-ground mathematical model of aircraft and wheel dynamics. The aircraft velocity and wheel angular velocity are formulated as system states, and the friction coefficient is estimated as an augmented state. The relation between the friction coefficient and wheel slip ratio is established using both simulated and actual ground roll data. Also, the technique is evaluated with the simulated data as well as real aircraft taxi data. The accuracy of friction estimation, with and without the measurement of normal reaction force on the landing gear, is analyzed using the simulated data. The friction coefficient vs slip ratio curve, derived from the empirical “Magic formula”, compares well with the estimated maximum tire-to-ground braking friction, and a shift in optimal slip is observed in actuality compared to the predictions. The brake disc friction coefficient is also estimated during the process since the brake torque measurements are not available in the actual data. The estimated friction coefficient, which represents the real characteristics of the runway, can be used to tune the control algorithms of the aircraft’s anti-skid brake management system for various runway conditions. While improvements in anti-skid efficiency alone may not directly prevent all runway excursions, accurate real-time friction estimation enhances the predictability and reliability of braking action, supporting safer operations under degraded or uncertain runway conditions. Moreover, the real-time estimation of tire-to-ground friction coefficient vs slip ratio curves can be used to develop adaptive control algorithms for the brake management system.
T.K., Khadeeja Nusrath, Singh, Jatinder
Resilience Evaluation Method for Rail Transit Networks Considering Dynamic Passenger Flows2025-99-043812/10/2025
This study proposes an urban rail transit network resilience assessment method based on dynamic passenger flow, which quantifies the overall system performance from the structural and functional dimensions. At the structural level, the relative size of the largest pass subgraph is introduced to measure the network integrity, and the average node degree is used to evaluate the network connectivity; At the functional level, the passenger travel efficiency ratio is used to measure the operation efficiency of the supply side, and the proportion of unaffected passengers is used to evaluate the service support capability of the demand side. The weight of each index is determined by entropy weight method, and then the comprehensive performance evaluation model of rail transit system is constructed. Taking Nanjing Metro as an example, the empirical study shows that the performance change trend reflected by the introduction of dynamic passenger flow is significantly different from the evaluation results based on structural topology only, and the decline and recovery process of network performance after disturbance is closer to the actual operation. This study provides a theoretical basis for quantifying the resilience of rail transit network, and provides a reference for improving the system resilience and formulating optimization strategies.
Wang, Junhang, Shao, Jiayu, Yang, Haofan, Zhang, Ning
A Cosine-Based Dynamic Pushback Control Method Considering Airport Traffic Congestion2025-99-043112/10/2025
The rapid growth of the civil aviation industry has placed significant pressure on limited airport runway resources, leading to increased taxiing delays and excessive fuel consumption. These challenges are exacerbated by the constant rise in air traffic, which necessitates more efficient management of airport operations. To mitigate these issues, this study proposes a flexible management approach that categorizes busy periods based on airport traffic density, taking into account the fluctuating load demand at different times of the day. This approach ensures that resource allocation aligns with actual traffic conditions, optimizing operational efficiency. Additionally, leveraging the existing dynamic pushback control framework, this research develops a cosine-based dynamic pushback control model, which incorporates parking stand waiting penalties. This model aims to reduce departure costs by dynamically adjusting the pushback rate according to congestion levels. To further optimize the model, a novel genetic algorithm combined with continuous Markov chains is introduced. This algorithm is designed to determine the optimal control thresholds for different congestion levels throughout the day, ensuring that resources are used effectively while minimizing delays. Simulations conducted using actual operational data from Beijing Capital International Airport demonstrate the effectiveness of the proposed approach. Compared to the uncontrolled pushback method, the cosine-based dynamic pushback control method significantly reduces average taxiway waiting times by 42.92%. Furthermore, this method also reduces fuel consumption and emissions associated with taxiing delays, offering a more sustainable solution to managing airport congestion. This research provides a comprehensive strategy for improving airport operations in high-density air traffic environments.
Wu, Yingzi, Lian, Guan, Luo, Weizhen, Li, Wenyong, Zhao, Yeqi, Zhang, Hao
Collaborative Pushback and Taxiing Coordination Departure Control Method for Multi-Runway Airports2025-99-043612/10/2025
In order to improve the operational efficiency of a multi-runway airport, an aircraft pushback and taxiing cooperative departure operation control method is proposed. First, a Markov decision process (MDP) model for dynamic pushback control is established based on the two-runway model. Then, the genetic simulated annealing algorithm is used as the optimization algorithm, and the DPC-GSAA algorithm solution model is proposed to find the conflict-free path with the least fuel consumption for the aircraft and runway selection. Finally, the effectiveness of the model and algorithm is verified by simulation experiments in Beijing International Airport, and the results show that the method can significantly reduce the taxiing waiting time of aircraft and improve the overall operational efficiency of the airport.
Luo, Weizhen, Lian, Guan, Wu, Yingzi, Li, Wenyong, Huang, Haifeng
4D Trajectory Prediction and Vertical Guidance Algorithm for Fuel-Optimal2025-99-040412/10/2025
It is necessary to save fuel, shorten flight time and reduce cost in order to achieve maximum economic benefits. In this paper, based on the flight performance of aircraft, a database based on the optimal index of fuel saving is established, and the corresponding four dimension (4D) trajectory prediction information and vertical profile are generated on this basis. Finally, the vertical guidance simulation is carried out to verify the effectiveness of the algorithm. The algorithm can reduce air traffic congestion and improve airport operation efficiency while saving fuel.
Hui, Huihui, Li, Zhiyi
Aircraft Cross Taxiing Conflict Prediction and Avoidance Methods2025-99-042312/10/2025
With the rapid development of the civil aviation industry, the increasing number of flights has made ensuring the safety and efficiency of airport surface movements a pressing issue. This study establishes a mathematical model to predict the collision risk of aircraft in the intersection area in real time, and proposes appropriate intervention zones for avoidance, implementing a deceleration avoidance strategy. The model is validated using historical operational data from Beijing Capital International Airport, and the results indicate that the proposed model effectively reduces the collision probability to below 0.3. It demonstrates strong performance in predicting cross-path conflicts and reducing conflict risks. Additionally, the deceleration avoidance strategy further lowers the collision probability, improving both the safety and efficiency of airport surface operations. This research offers valuable insights for enhancing the operational efficiency and proactive safety levels of civil aviation airports.
Zhang, Ting, Lian, Guan, Zhang, Guoxin, Zhao, Yeqi
Micro-Circulation Bus Route Area Identification under the TOD Concept2025-99-013611/11/2025
Based on the TOD (Transit-Oriented Development) concept, this paper addresses the “last mile” issue in urban public transportation. It proposes a multidimensional decision-making model for identifying micro-circulation bus route areas. By integrating indicators such as the TOD comprehensive index, short-distance demand intensity, and branch network density, relevant data is processed using FME linking ArcGIS. The model combines entropy-weighted TOPSIS and unsupervised consensus clustering analysis techniques, utilizing ArcGIS spatial analysis functions to accurately identify priority deployment areas for micro-circulation buses. Taking Jiangbei District in Chongqing as an example, the model divides the study area into four types of traffic zones: (1) Core high-density areas, which require an increase in micro-circulation bus routes due to extremely high short-distance travel demand; (2) Periphery active population areas, which require flexible shuttle services due to transit gaps and tourist peak demands; (3) Two other areas that do not require micro-circulation bus routes at this stage. The supply-demand targeted optimization strategy based on clustering analysis can enhance the resilience of the bus network, alleviate pressure on trunk transportation, and promote the coordinated development of land use and public transport services. It balances the sustainable direction of the TOD concept with the precise adaptation of micro-circulation buses, promoting green travel and efficient urban space governance.
Jiang, Tao, Jia, Xiaoyan, Li, Jie
Vehicle to Vehicle Recharge and Power Sharing for Modular Public Transportation Systems: Design and Testing of the UNIFI fleet at ENEA CASACCIA Research Center2025-32-009511/3/2025
The synergistic adoption of automated driving technologies and the electrification of the vehicle power train offers the possibility of proposing new and innovative solutions for public transportation systems. In particular, an interesting solution is represented by modular systems in which multiple autonomous vehicles/transportation modules can be aggregated to form reconfigurable compositions according to desired transportation demand. In this work, a configurable connection between vehicles is adopted, as convoying ensures the possibility of power sharing between vehicles, allowing coordinated power management throughout the composition. Connected vehicles can also share power between batteries for battery recharge that is performed using a custom solution from a tram-like catenary. In this work, the authors design a demonstrator to investigate the feasibility of the proposed solution. Once designed, the proposed system has been assembled and tested at the ENEA Casaccia Research Center, preliminarily validating the proposed solution.
Alessandrini, Adriano, Berzi, Lorenzo, Fabbri, Marco, Franci, Michael, Gulino, Michelangelo Santo, Pugi, Luca, Ortenzi, Fernando, Vitiello, Francesco
SAE TOMORROW TODAY - Fast-Tracking Hydrogen's Role in Aviation1354110/31/2025
If you still think hydrogen was the cause of the Hindenburg disaster, allow Danielle McLean, Founder and Executive Director of HYSKY Society, to debunk that myth for you. What first began as a hydrogen-powered eVTOL startup quickly revealed a bigger challenge for the aerospace engineer: the need for scalable, affordable clean hydrogen. In response, Danielle united engineers, entrepreneurs, and energy experts to form HYSKY Society -- a global nonprofit advancing hydrogen aviation through collaboration, education, and advocacy. Listen in as Danielle busts myths about the Hindenburg disaster, explains why regional airports could be the launchpad for hydrogen-powered planes, and details what it will take for hydrogen to go mainstream by 2045. You'll also get a sneak peek at FLYING HY, the world's largest hydrogen aviation event, and learn why "I want my hydrogen" just might be the future slogan of the aviation. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube.
Patterson, Lori
2025 5th International Conference on Smart City Engineering and Public Transportation (SCEPT)2025-99-000110/17/2025
TOC
Research on the Degree of Airport Intelligence Level Based on Three-Scaled Hierarchical Analysis Method2025-99-003710/17/2025
Smart airport is a key driver for the future development of civil aviation and a cornerstone of China’s ongoing “Four Airport” construction initiative. It is important to improve technology in many areas. This includes airport building, daily work, management, and making decisions. As air travel changes, using new tools like artificial intelligence, big data, and the Internet of Things (IoT) is very important. These tools help make airports more efficient, safe, and better for the environment. Because of this, building smart airports is not just a big goal but also a new way to deal with the challenges in today’s air travel systems. A key part in building smart airports is making a full evaluation system to check how well the projects are working. When a strong index system is made for smart airports, people involved can see clearly what is working well and what is not. So, chose using a three-scale hierarchical analysis method gives a clear and step-by-step way to look at different parts of smart airport building. This method helps check many things, like how well the technology fits in, how smoothly the airport works, how it affects the environment, and how users feel [1]. To check if this evaluation framework works in real life, a case study of Beijing Daxing International Airport is used. Daxing Airport is one of the top examples of smart airport building. It uses new technology and modern ways to manage the airport. So it is a good choice for this study. The case study shows that the evaluation system can work. It also gives useful advice for airport managers to make construction projects better.
Li, Shi-ling, Fu, Lu
Finite Element-Based Study on the Frangibility of Airport Navigation Light2025-99-006210/17/2025
This study establishes models of airport vertical navigation lights and aircraft vulnerable components (wings and landing gear) using SOLIDWORKS. Based on the frangibility standards for airport navigation facilities, the control dimensions of the circular tube model for navigation lights are determined. Numerical simulations are conducted in ANSYS Workbench to analyze collisions between aircraft wings/landing gear and navigation lights under three different velocity conditions. Internal energy analysis, bidirectional force response, and stress nephograms during the impact process are evaluated. The results indicate that current standards ensure that collisions with vertical navigation lights during takeoff and landing do not cause deformation or damage to aircraft vulnerable components, thereby guaranteeing the safety of aircraft and pilots.
Wang, Jianwu, Song, Xiaobo, Wei, Yan, Liu, Hongwei, You, Shengnan, Sun, Jinkun
Baltimore Urban Road Network Research: The Impact of Bridge Collapse on Different Groups of People and Transportation System Improvement Strategies2025-99-004310/17/2025
This paper studies the transportation demands of different stakeholders, namely urban residents, entrepreneurs and tourists. It also studies the construction of network model optimization functions and corresponding indicators, and analyzes what kind of impact the bridge collapse will have on different stakeholders. Urban residents attach great importance to convenience in their daily lives. They usually like to travel by walking or cycling. They also prefer to use public transportation facilities. Entrepreneurs mainly rely on the efficiency of goods transportation to develop their businesses. They pay more attention to the accessibility of commercial and industrial areas. Tourists, on the other hand, prefer convenient connections between tourist attractions and hotels, as this makes their visits more convenient. After the bridge collapsed, the traffic pressure shifted to other main roads, such as I-95 and I-895. This led to longer commuting times and a significant increase in transportation costs, exerting varying degrees of impact on the travel demands of residents, entrepreneurs and tourists. Based on the analysis of the network model, this study gives targeted optimization suggestions. For urban residents, it is necessary to build pedestrian lanes and bicycle lanes and improve the existing travel network. In this way, the accessible travel range of urban residents can be expanded. This article also suggests improving the connection of public transportation to make residents’ travel more convenient. For entrepreneurs, it is necessary to optimize the layout of main and secondary roads, so that the pressure of goods transportation can be relieved. For tourists, it is necessary to enhance the transportation facilities near tourist areas to improve their travel experience. These optimization measures aim to increase the resilience, efficiency and fairness of the transportation system, providing more convenient and sustainable transportation services for residents, enterprises and tourists.
Xiang, Xiaohong, Ying, Rongrong, Zhou, Lin
Influence of MPC Based Driver Types on the Energy Consumption of Battery Electric Vehicles2025-24-01139/7/2025
Electric vehicles are increasingly important for emission reduction and the promotion of sustainable mobility. Despite their advantages over conventional vehicles, the energy consumption of electric vehicles is heavily influenced by various factors such as driving behavior, elevation profile, and environmental conditions. In particular, the driving style plays a crucial role in determining range and energy consumption. This influence is also observed in the context of the Interreg project FreeE-Bus. This project focuses on the development of optimized charging management for electric buses in the public transport system of the Lake Constance region. Due to strict data protection regulations that prevent a detailed analysis of driver data, assessing the impact of driving styles is difficult. This paper addresses this issue by developing an innovative driver model that simulates different driver types and analyzes their effects on energy consumption. The driver model employs a Model Predictive Control approach, and two driver types are implemented and tested on a real vehicle. The results of this study demonstrate that a simulation of different driving styles is possible and highlight significant differences in energy consumption, providing valuable insights into improving driving strategies. Therefore, this approach represents a valuable addition to the existing range of driver control modeling methods.
Konzept, Anja, Reick, Benedikt, Miller, Marius, Rautenberg, Philip, Störzer, Martin
SAE TOMORROW TODAY - How Buses Are Leading the Self-Driving Revolution135298/8/2025
Thanks to their fixed routes and predictable environments, commercial vehicles like airport shuttles and public transit buses are proving to be the perfect match for SAE Level 4 automation. One company at the forefront of this transformation is Fusion Processing, a global leader in automated driving, situational awareness, and control systems. Fusion has logged over 90,000 kilometers of on-highway autonomous driving -- more than any other AV company in Europe. Their innovative technologies, including CAVstar and CycleEye, are already delivering tangible benefits in real-world commercial vehicle fleets, from freight to passenger services. To learn more, we sat down with Jim Hutchinson, Co-Founder and CEO, to discuss the future of transit and how Fusion is working to scale autonomous buses globally. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Patterson, Lori
The Automation Concept of the U-Shift II Vehicle2025-01-02817/2/2025
Autonomous driving technology enables new and innovative driverless vehicle concepts to emerge, like U-Shift. Designed from the ground up, the U-Shift II platform, called driveboard, exemplifies the advantages of separating a vehicle’s driving capability from the intended transportation task. It allows different so-called capsules, such as public transport or cargo, to be transported using the same U-shaped driving platform. The driveboard can change the capsules autonomously, thus providing high flexibility for fleet operators. This novel approach introduces new challenges to the task of autonomous driving. On one hand, changing sensor and vehicle configurations, e.g., when transporting a capsule with its own sensors to compensate for occlusions of the driveboard sensors by the capsule itself, requires an adaptive approach to environmental perception. On the other hand, different environments and driving tasks, as well as the augmented motion capabilities of the driveboard, require novel motion planning and control algorithms that also adapt to changing vehicle configurations. For example, the driveboard’s automatic pick-up of capsules places high demands on perception and planning precision. In this paper, we first present our automation concept for the U-Shift II vehicle, which comprises environment perception and motion planning, emphasizing the modifications and enhancements compared to state-of-the-art autonomous vehicles. Second, we present a proof of concept focusing on flexibility and adaptivity based on a software-in-the-loop simulation using CARLA.
Buchholz, Michael, Wodtko, Thomas, Schumann, Oliver, Authaler, Dominik
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