Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.

线上中文学习平台Lingo Bus和Lingo Ace比较研究

Lingo Bus和Lingo Ace平台是当前受到市场青睐的知名线上中文学习平台。对两个学习平台的建设、教学和管理营销三个方面的情况进行比较研究后发现:两个平台均通过线上直播课程面向海外青少儿教授中文,均建立了各自的官网和客户端,在品牌定位、课程资源体系、选课方式和学习者服务模式等方面的设计上都有差异,针对教师选拔、培训的侧重点和严格程度也有不同的标准;两个平台均注重通过口碑、新闻软文和社交媒体等途径进行营销,但在推广方式和营销经费投入力度方面做法不同。线上中文学习平台应建设本土化和标准化教学资源,提升系统稳定性和智能化水平,完善教师管理机制,建立良好服务体系,组建本土团队,实施精准营销等发展策略。

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

Point Cloud Based Semantic Segmentation Method for Unmanned Shuttle Bus

The complexity of application scenarios and the enormous volume of point cloud data make it difficult to quickly and effectively segment the scenario only based on the point cloud.In this paper,to address the semantic segmentation for safety driving of unmanned shuttle buses,an accurate and effective point cloud-based semantic segmentation method is proposed for specified scenarios(such as campus).Firstly,we analyze the characteristic of the shuttle bus scenarios and propose to use ROI selection to reduce the total points in computation,and then propose an improved semantic segmentation model based on Cylinder3D,which improves mean Intersection over Union(mIoU)by 1.3%over the original model on SemanticKITTI data;then,a semantic category division method is proposed for road scenario of shuttle bus and practical application requirements,and then we further simplify the model to improve the efficiency without losing the accuracy.Finally,the nuScenes dataset and the real gathered campus scene data are used to validate and analyze the proposed method.The experimental results on the nuScenes dataset and our data demonstrate that the proposed method performs better than other point cloud semantic segmentation methods in terms of application requirements for unmanned shuttle buses.Which has a higher accuracy(82.73%in mIoU)and a higher computational efficiency(inference speed of 90 ms).

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Autonomous bus services:current research status and future recommendations

Implementing autonomous bus services in several cities has garnered substantial research attention worldwide.However,the benefits and challenges of this emerging mode remain insufficiently understood.Consequently,VOSviewer was employed for a bibliometric analysis involving 300 publications,investigating the associations among authors,journals,and keywords.Subsequently,we comprehensively reviewed the current state of research on two topics and proposed future recommendations.Results indicate that the first document related to autonomous bus services was published in 2009.Most user attitude-related research data are obtained via questionnaires and analyzed using statistical techniques.Autonomous bus services are expected to benefit passengers regarding travel time,cost,safety,etc.,while passenger preferences are inconsistent.However,integrating the service into existing bus systems requires careful consideration of the schedule sequences.Notably,modular autonomous bus services present a new opportunity for the further optimization of bus services.In future studies,standardized data acquisition procedures should be developed to achieve comparable results.Regarding traveler choice behavior,the effect of specific autonomous bus service policies over time and the heterogeneity due to cultural or social contexts across regions should be assessed.To further promote autonomous bus services,based on fluctuating travel demands,the effects of vehicle capacity,speed,and cost of fleet composition should be evaluated comprehensively to optimize the bus network and schedule sequence.Owing to the protracted nature of the transition from conventional to fully autonomous buses,one should prioritize semi-autonomous bus services.Another essential future research direction is to integrate modular autonomous bus assembly or disassembly strategies with different fine-grained operation optimization techniques in various scenarios.

Shaping a New Level of Bus Service under a Novel Concept of Bus Interaction: A Meta-Review

Public transport services, particularly bus services, play an important role in a sustainable transportation system. However, despite various efforts, bus ridership has decreased. The appearance of shared and on-demand vehicle services is one of the main reasons for this issue. In addition, bus tourism services have been successfully developed to meet the exigent needs of tourists. Therefore, a new level of daily bus service is necessary to adapt to the changing demands of customers. Bus interaction (BI) plays an important role in bus services. Nevertheless, the conventional concept of BI mainly refers to users, physical interaction, and safety, but it does not address non-users, non-physical interactions, service quality, and other aspects. This study aims to elaborate on a new concept of bus services. Based on this, we developed a theoretical framework for BI. A meta-analysis was then conducted to identify the achievements and untouched aspects. The results of this study provide three main contributions. First, an unprecedented novel concept of BI is defined, including 13 types of interactions. Second, a comprehensive theoretical framework of BI is established based on the relationships between eight sustainable bus system sub-aspects and 13 BI types. Third, based on the theoretical framework and findings of the reviewed studies, a common finding comprehensive framework of BI is completed, which is accompanied by 1) key findings of the 13 BI types, 2) conclusions of traffic conditions affecting BI research, 3) BI research gaps, and 4) 16 main suggestions for future BI research.

Modified Satin Bowerbird for Distributed Generation in Remotely Controlled Voltage Bus

The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency.These Distributed Generators control the PV bus;it is converted as a remote controlled PVQ bus.This PVQ bus reduces the power loss and reactive power.Initially,the distributed generators were placed in the system using mathematical modelling or the optimization.This approach improves the efficiency but it has no effect in loss minimization.To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work.This approach minimizes the loss effectively;but the genetic algorithm takes more time for DG placement.Hence,in this,the network reconfiguration is performed using a modified Satin bower bird algorithm after DG placement and DG sizing.Initially,the sensitive analysis applied the loadflow analysis to identify the optimal placement for the distributed generator.Then,the modified Satin Bowerbird(SBO)used for the network reconfiguration.This approach minimizes the loss of effectively by combining the network reconfiguration process.The proposed modified SBO-based network reconfiguration implemented on standard bus systems 33 and 69 using MATLAB R2021b version under Windows 10 environment.The proposed approach compared with the existing work in terms of real power loss and loss reduction.

Investigating the Effects of Slack Bus Selection in Load Flow Studies: A Comparative Analysis of Robust and Weak Grids

Load flow studies play a critical role in the analysis of power systems. They enable the computation of voltage, current, and power flows in a power system. They provide valuable insights into the steady-state performance of the power system under different operating conditions. Choosing a slack bus is a vital step in conducting load flow simulations. A slack bus is a PV bus that includes a generator and is used to balance real and reactive power during load flow studies. Many studies have been conducted on the selection of slack buses in load flow analysis. However, varied conclusions regarding the impact on system losses and power flows were obtained during these studies. Therefore, using the IEEE-14 bus test system, this study investigated the effects of slack bus selection in strong and weak grids by alternating slack buses among PV buses and observing the effects on bus voltage magnitude, bus voltage phase angle, total power flows, and active and reactive power losses. The study noted that the effect of slack bus selection on these system quantities is contingent upon the voltage stability of the grid. Whereas in a robust grid, system losses and power flows remained constant irrespective of the choice of slack bus, a weak grid experienced some variations in these system quantities under similar circumstances. The simulation results led to the conclusion that, to a large extent, the voltage stability of the grid plays a significant role in determining the degree to which slack bus selection affects system losses and other quantities in load flow studies.

Exploring the Commuters’ Willingness-to-Pay and Its Influencing Factors for an Improved Public Bus Service in Dhaka City

Improved transportation services are a crucial component of urban growth, particularly in emerging cities like Dhaka. Ensuring an improved public bus service quality is a challenge for the city’s transport planners and policy makers. Nevertheless, this challenge can’t be met without the support of the residents of this city. This study intends to evaluate the commuters’ willingness to pay (WTP) for an improved and better public bus service quality in Dhaka city. It also attempts to explore the factors affecting the commuters’ WTP amounts. In order to accomplish the study’s goals, a stated preference survey was designed to enquire into the whys and wherefores of female passengers’ harassment on public buses and also to prefer some influential service quality features. WTP values of respondents were calibrated using binary and ordinal logistic models, and these models were developed using SPSS version 26. The results indicate that the majority of respondents were willing to pay more for better service facilities, and they point to security as the most important factor in determining how much extra fare commuters are willing to pay. The results also demonstrate that commuters’ WTP amounts are highly influenced by the respondents’ monthly income. Results from this study have important policy implications, such as protecting women’s safety on public transportation and taking commuters’ socio-demographic characteristics into account before enacting any legislation or increasing fares.

中国工厂来了!Busch普旭最大海外投资项目落户武汉!

新春伊始,万象更新,众多用户期待的Busch普旭中国制造工厂终于来了!江城武汉,将成为Busch普旭继德国、瑞士、英国、捷克、美国、韩国和印度后的全球第8家制造工厂所在地。2月10日,Busch普旭与武汉市蔡甸区人民政府正式签订项目投资协议,将在武汉市蔡甸区中德国际产业园建设Busch普旭真空设备亚太生产及销售基地。

Influences of Mixed Traffic Flow and Time Pressure on Mistake-Prone Driving Behaviors among Bus Drivers

Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mixed traffic flow (MTF) environments with time pressure (TP). However, there is a lack of sufficient research exploring the relationships among these factors. This study consists of two papers that aim to investigate the impact of MTF environments with TP on the driving behaviors of bus drivers. While the first paper focuses on violated driving behaviors, this particular paper delves into mistake-prone driving behaviors (MDB). To collect data on MDB, as well as perceptions of MTF and TP, a questionnaire survey was implemented among bus drivers. Factor analyses were employed to create new measurements for validating MDB in MTF environments. The study utilized partial correlation and linear regression analyses with the Bayesian Model Averaging (BMA) method to explore the relationships between MDB and MTF/TP. The results revealed a modified scale for MDB. Two MTF factors and two TP factors were found to be significantly associated with MDB. A high presence of motorcycles and dangerous interactions among vehicles were not found to be associated with MDB among bus drivers. However, bus drivers who perceived motorcyclists as aggressive, considered road users’ traffic habits as unsafe, and perceived bus routes’ punctuality and organization as very strict were more likely to exhibit MDB. Moreover, the results from the three MDB predictive models demonstrated a positive impact of bus route organization on MDB among bus drivers. The study also examined various relationships between the socio-demographic characteristics of bus drivers and MDB. These findings are of practical significance in developing interventions aimed at reducing MDB among bus drivers operating in MTF environments with TP.

Users’ Perception on Operation and Performance of Public Transport Systems in African Developing Countries: The Case of Bus Rapid Transit (BRT) in Dar es Salaam City, Tanzania

Public transport system has been a means of addressing transportation challenges in urban areas, such as traffic congestion, traffic jam and long travel time in cities worldwide. Transportation in Africa is unique in that it has the least developed public transport systems in the world, while also being one of the fastest urbanizing continents. Bus Rapid Transit being one of the public transport systems was introduced in Africa in 2008 as a means to provide solution on urban transportation challenges. Despite of public transport being the main means of transport in African developing countries, there have been a number of challenges that affects efficiency of performance of the system and makes its users uncomfortable. Therefore, the study aimed at exploring the setbacks or challenges associated with operation and performance of the BRT system in the African developing countries and address them. The study employed mixed methods research design that integrates both qualitative and quantitative data collection methods and analysis. The study findings reveal that, there is an improvement on the perspectives of the commuters on public transport after introduction of BRT system. However, some challenges such as long waiting time, passengers overcrowding during peak hours, as well as safety and security can slowly change the perspective of the commuters. Therefore, to address these challenges it is recommended to reduce the long waiting time and improve accessibility by introduction of passenger information displays (bus information system) and automated fare collection system;reduce travel time by introduction of bus priority signal;and improve safety and security by introduction of signage and CCTV Camera within the bus and bus stops.

Route Search Method for Railway Replacement Buses Adopting Ant Colony Optimization

In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.

Method for calculating the capacity of bus bay

The bus operating characteristics are analyzed at the bus bay using the trajectories depending on the current status of buses. On this basis, a method for calculating the capacity of the bus bay is developed, which considers the queue probability, the dwell time distribution and the waiting time for a gap in the traffic stream at the curb lane. Then, the distribution model of the dwell time is developed using the survey data of Hangzhou city. And the log-normal distribution shows the best fitting performance. The capacities of the bus bay are computed with the Matlab program under different distribution parameters of the dwell time and different traffic volumes at the curb lane. The results show a large range of traffic capacity as the distribution parameters and traffic volumes change. Finally, the proposed model is validated by measurement and simulation, and the average relative errors between the calculated values and the measured and simulated values are 8.78% and 5.28%, respectively.

基于M-BUS的智能采集器的设计与应用

针对目前煤矿井下各类传感器智能化程度不高的现状,设计了一种智能信号采集器,它可以采集煤矿井下通用传感器的频率信号,并通过M-BUS总线上传测量结果。由该采集器构成的矿井安全监测系统可以实现频率信号的低功耗、智能采集和可靠的网络传输。

M-BUS二线制总线

介绍了M -BUS二线制总线 ,它是一种用于远程仪表读取数据的欧洲标准 ,主要用于耗能测量仪表。对M -BUS总线的功能、原理、安装和使用进行了说明 ,重点阐述了其在计量仪表中应用的优势 ,如远程供电及自由拓扑特性等。指出M -BUS在我国的应用虽处于起步阶段 ,但基于其在计量应用中独特的优势 ,应用前景十分广阔。

Bus transit travel time reliability evaluation based on automatic vehicle location data

In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.