Multimodal Transportation System Research Articles

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode

BackgroundAchieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China.MethodsIn this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day. Additionally, accessibility values for D2D riding mode, D2D driving mode, and simple driving mode were also computed for comparison. Moreover, we introduced Lorenz curve and Gini index to assess the differences in equity of community healthcare across different times and transport modes.ResultsThe D2D public transit mode exhibits noticeable fluctuations in accessibility and equity based on the time of day. Accessibility and equity were notably influenced by traffic flow between 8 AM and 11 AM, while during the period from 12 PM to 10 PM, the open hours of community hospitals became a more significant determinant in Nanjing. The moments with the most equitable and inequitable overall spatial layouts were 10 AM and 10 PM, respectively. Among the four transport modes, the traditional simple driving mode exhibited the smallest equity index, with a Gini value of only 0.243. In contrast, the D2D riding mode, while widely preferred for accessing community healthcare services, had the highest Gini value, reaching 0.472.ConclusionThe proposed method combined the D2D model with the open OD API results is effective for accessibility computation of real transport modes. Spatial accessibility and equity of community healthcare experience significant fluctuations influenced by time variations. The transportation mode is also a significant factor affecting accessibility and equity level. These results are helpful to both planners and scholars that aim to build comprehensive spatial accessibility and equity models and optimize the location of public service facilities from the perspective of different temporal scales and a multi-mode transport system.

On the optimization of green multimodal transportation: a case study of the West German canal system

AbstractIn this study, we address a biobjective multimodal routing problem that consists of selecting transportation modes and their respective quantities, optimizing transshipment locations, and allocating port orders. In the objective functions, we minimize total transportation costs and use the EcoTransit methodology to minimize total greenhouse gas emissions. The optimization model selects the transportation mode and transshipment port where quantities are transshipped from one mode to another. We compare inland waterway transportation and trucks encountering infrastructure failures that require rerouting or modal shifting in a real-life case study on the supply of goods for the chemical industry in the West German canal system. We propose a population-based heuristic to solve large instances in a reasonable computation time. A sensitivity analysis of demand, of varying lock times, and of infrastructure failure scenarios was conducted. We show that compared with inland waterway transportation, multimodal transportation reduces costs by 23% because of longer lock times. Our analysis shows that the use of inland waterway transportation only during infrastructure failures imposes nearly 28% higher costs per day depending on the failure location compared to that of the case of no failures. We also show that the use of a multimodal transportation system helps to reduce this cost increase in lock failure scenarios.

Mining Multimodal Travel Mobilities with Big Ridership Data: Comparative Analysis of Subways and Taxis

Understanding traveler mobility in cities is significant for urban planning and traffic management. However, most traditional studies have focused on travel mobility in a single traffic mode. Only limited studies have focused on the travel mobility associated with multimodal transportation. Subways are considered a green travel mode with large capacity, while taxis are an energy-consuming travel mode that provides a personalized service. Exploring the relationship between subway mobility and taxi mobility is conducive to building a sustainable multimodal transportation system, such as one with mobility as a service (MaaS). In this study, we propose a framework for comparatively analyzing the travel mobilities associated with subways and taxis. Firstly, we divided taxi trips into three groups: competitive, cooperative, and complementary. Voronoi diagrams based on subway stations were introduced to divide regions. An entropy index was adopted to measure the mix of taxi trips. Secondly, subway and taxi trip networks were constructed based on the divided regions. The framework was tested based on the automatic fare collection (AFC) data and global positioning system (GPS) data of a subway in Beijing, China. The results showed that the proportions of taxi competition, taxi cooperation, and taxi complements were 9.1%, 35.6%, and 55.3%, respectively. The entropy was large in the central city and small in the suburbs. Moreover, it was found that the subway trip network was connected more closely than the taxi network. However, the unbalanced condition of taxis is more serious than that of the subway.

Can Urban Air Mobility become reality? Opportunities and challenges of UAM as innovative mode of transport and DLR contribution to ongoing research

AbstractUrban Air Mobility (UAM) is a new air transportation system for passengers and cargo in urban environments, enabled by new technologies and integrated into multimodal transportation systems. The vision of UAM comprises the mass use in urban and suburban environments, complementing existing transportation systems and contributing to the decarbonization of the transport sector. Initial attempts to create a market for urban air transportation in the last century failed due to lack of profitability and community acceptance. Technological advances in numerous fields over the past few decades have led to a renewed interest in urban air transportation. UAM is expected to benefit users and to also have a positive impact on the economy by creating new markets and employment opportunities for manufacturing and operation of UAM vehicles and the construction of related ground infrastructure. However, there are also concerns about noise, safety and security, privacy and environmental impacts. Therefore, the UAM system needs to be designed carefully to become safe, affordable, accessible, environmentally friendly, economically viable and thus sustainable. This paper provides an overview of selected key research topics related to UAM and how the German Aerospace Center (DLR) contributed to this research in the project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Center (DLR)". Selected research results on the topics of market potential and public acceptance, vehicle design (including battery degradation, onboard systems, cabin design, cabin simulation), infrastructure, operations (including U-space, safe autonomy, navigation, communication, cost modeling) and overall system modeling are briefly presented.

ASSESSMENT OF BARRIERS AND CHALLENGES OF SUSTAINABLE LOGISTICS

ABSTRACT This study investigates the various challenges faced by firms in their pursuit of sustainable logistics strategies. First, we need to catalog all the obstacles that keep the logistics sector from becoming more socially and environmentally conscious so that we can assess the challenges of sustainable logistics. Establishing sustainable logistics practices is not without its challenges, including but not limited to: cost, lack of knowledge, infrastructure, legislation, technology, complexity of the supply chain, reluctance to change, problems with measurement and reporting, competitive pressures, and unpredictable customer behavior. "Green logistics" refers to a comprehensive strategy for managing supply chains with an eye toward minimizing negative impacts on the environment. Reduce emissions, waste, and resource consumption at every stage of the supply chain using green logistics. This method covers everything from acquiring raw materials to final disposal. Implementing measures like as route optimization, fleet modernization, and packaging can help businesses save money, run more efficiently, and reduce their environmental impact. Some sustainable transportation options include using alternative fuels and vehicle technology, optimizing last-mile delivery solutions, and encouraging multimodal transportation systems. KEYWORDS : Barriers of Sustainable logistics, Sustainable transportation, Green logistics, Sustainable supply chain, Best and worst method

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

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

Design and analysis of ride-sourcing services with auxiliary autonomous vehicles for transportation hubs in multi-modal transportation systems

Autonomous vehicles (AVs), which can be fully controlled by remote/online operators, could be an extension of ride-sourcing services provided by transportation network companies (TNCs). Meanwhile, substitutive and complementary relationships between ride-sourcing and public transit could also help TNCs increase their profit under certain strategies. Unlike previous studies that generally ignored either AVs or interactions between public transit and ride-sourcing, we introduce AV-involved operational strategies into a multi-modal system. In this paper, we focus on transportation hubs in an urban area and let the TNC assign AVs to these hubs for serving only within that particular hub at a differentiated fare; meanwhile, passengers could choose among AVs, human-driven vehicles (HVs), combined modes with public transit and AVs or HVs, or other travel modes to fulfill their travel needs. We develop a mathematical model to investigate the impacts of such an operational strategy, and formulate an optimisation problem to maximise the TNC's profit and minimise total waiting time simultaneously by adjusting AV fare and fleet size. We further propose a comprehensive modeling framework with the analytical model, optimisation problem, calibration method, and heuristic algorithm, making it a general approach for different real-world scenarios. Following the framework, we conduct a case study based on real-world datasets of public transit and ride-sourcing services in Hangzhou, China. Different market schemes are analyzed and compared with the currently existing situation. The results demonstrate that by adopting this auxiliary-AV-oriented operational strategy, the TNC's profit and public transit ridership can both be increased, and passengers could enjoy a shorter waiting time for HV ride-sourcing trips. Moreover, the TNC is more inclined to allocate more AVs to hubs with large commute needs and uncongested traffic, leading to a high profit for the TNC and a short waiting time for passengers. Societal preferences towards AV trips are also analyzed. The results provide in-depth references for real-world AV-related ride-sourcing operational problems.

Integrating singular value decomposition with deep learning for enhanced travel time estimation in multimodal freight transportation networks

AbstractMultimodal freight transport allows switching among various modes of transportation to efficiently utilize transport facilities. A multimodal transport system incorporates geographical scales from global to local. Travel time estimation in a multi‐modal cargo transportation network is essential for enhancing supply chain (SC) and logistics operations. Accurate travel time prediction is of great importance for cargo transportation, as it enables SC participants to increase logistics efficiency and quality. It requires adequate input data, which can be generated. In recent times, the machine learning (ML) algorithm has been well‐suited to resolve complex and nonlinear relationships in the collected tracking data. This study designs a deep learning‐powered travel time estimation in multimodal freight transportation networks (DLTTE‐MFTN) technique. The goal of the DLTTE‐MFTN technique is to estimate the travel time using a hyperparameter‐tuned ensemble learning approach. To achieve this, the DLTTE‐MFTN method initially undergoes data pre‐processing to convert the input raw data into a useful format. In addition, the singular value decomposition (SVD) model can be applied for feature dimensionality reduction in multimodal transport data, considerably improving travel time prediction. Besides, the DLTTE‐MFTN method estimates travel time using an ensemble of three DL approaches including one‐dimensional convolutional neural network (1D‐CNN), stacked autoencoder (SAE) attention, and recurrent neural network (RNN). Finally, the hyperparameter tuning of the DL models takes place using the whale optimization algorithm (WOA). The performance analysis of the DLTTE‐MFTN method takes place using the Kaggle dataset. The experimental results stated that the DLTTE‐MFTN technique attains superior performance over other ML and DL models.

SVD-based adaptive fuzzy for generalized transportation

This research stems from the urgent need to address the complex challenges faced in multimodal transportation within the cargo sector, particularly concerning the reduction of transportation costs and CO2 emissions. Existing transportation systems often struggle to efficiently balance economic and environmental concerns, necessitating innovative solutions. In this paper, we have introduced a novel mathematical model that integrates Singular Value Decomposition (SVD), Genetic Algorithms (GA), and the Adaptive Neural Fuzzy Inference System (ANFIS). The synergy of GA and the ANFIS forms a dynamic learning system that continually refines solutions by adapting to historical decisions and aligning with supply-demand dynamics. This integrated approach aims to optimize cost allocation and resource utilization while simultaneously minimizing CO2 emissions. Deploying the ANFIS+GA+SVD model in multimodal scenarios yields impressive results, with a minimal average percentage error (MAPE) of 0.28% for transportation costs and a remarkable coefficient of determination R2 of 0.992 for the Truck + Ship scenario. Similarly, a MAPE of 0.11% for CO2 emissions, supported by an impressive R2 of 0.989, underscores the model's accuracy. Observations of people's transportation choices in response to emission price changes reveal a significant decrease in truck usage, plummeting from 84% to below 50%. Alternative transportation methods, especially in the 3S-3 M-3 C scenario, show a substantial surge, with railways leading at a remarkable 30% increase in utilization. The combined quantity and cost comparison, utilizing the ANFIS+GA+SVD model, emphasizes the suitability of the Truck + Ship scenario for Iraq's transportation network, reinforcing the case for sustainable and efficient multimodal transportation systems.

Multicast Routing Based on Data Envelopment Analysis and Markovian Decision Processes for Multimodal Transportation

In the context of Iraq’s evolving transportation landscape and the strategic implications of the Belt and Road Initiative, this study pioneers a comprehensive framework for optimizing multimodal transportation systems. The study implemented a decision-making framework for multimodal transportation, combining data envelopment analysis (DEA) efficiency scores and a Markov decision process (MDP) to optimize transportation strategies. The DEA scores captured decision-making unit (DMU) performance in various aspects, while the MDP rewards facilitated strategic mode selection, promoting efficiency, cost-effectiveness, and environmental considerations. Although our method incurs a total cost approximately 29% higher than MRMQoS, it delivers a nearly 26% reduction in delay compared to MCSTM. Despite MRMQoS yielding an 8.3% higher profit than our approach, our proposed scheme exhibits an 11.7% higher profit compared to MCSTM. In terms of computational time, our method achieves an average CPU time positioned between MCSTM and MRMQoS, with MCSTM showing about 1.6% better CPU time than our approach, while our method displays a 9.5% improvement in computational time compared to MRMQoS. Additionally, concerning CO2 emissions, the proposed model consistently outperforms other models across various network sizes. The percentage decrease in CO2 emissions achieved by the proposed model is 7.26% and 31.25% when compared against MRMQoS and MCSTM for a network size of 25, respectively.

PECULIARITIES OF THE DEVELOPMENT OF AIR TRANSPORT IN THE ENERGY ASPECT IN THE CONTEXT OF THE POST-WAR RECONSTRUCTION OF UKRAINE

The article emphasizes that the question of researching the place of air transport in the aspect of multimodal transportation in the aspect of the post-war reconstruction of Ukraine is relevant. An analysis of the pre-war dynamics of the development of the transport industry of Ukraine is presented, which showed the insufficient level of development of the transport infrastructure and the organization of transport operations for both the transit country. Directions and approaches to the implementation of elements of a multimodal transport system using air transport are presented. It is proposed for further implementation on the territory of Ukraine, the schemes of multimodal transportation with the involvement of air transport, which are popular in the world practice. The proposed directions for the use of air transport in relation to cargo transportation in the aspect of multimodal transportation in the conditions of Ukraine have been determined. The study identifies the peculiarities of the integration of air transport into the transport system during the post-war reconstruction of Ukraine. For the development of aviation transport in the context of the development of transportation on the territory of Ukraine, it is necessary first of all to determine the strategic directions of the post-war development of the transport industry of Ukraine and potential resource opportunities for their solution. A method of increasing the energy efficiency and reliability of the power supply of aviation enterprises is proposed, which will allow performing a high-quality reconfiguration of the existing energy networks of aviation enterprises and performing a high-quality design of new modern infrastructure networks of the aviation industry.

A low-cost automatic people-counting system at bus stops using Wi-Fi probe requests and deep learning

AbstractCounting people is an important part of people-centric applications, and the increase in the number of IoT devices has allowed the collection of huge amounts of data to facilitate people counting. The present study seeks to provide a novel, low-cost, automatic people-counting system for the use at bus stops, featuring a sniffing device that can capture Wi-Fi probe requests, and overcoming the problem of Media Access Control (MAC) randomization using deep learning. To make manual data collection considerably easier, a “People Counter” app was designed to collect ground truth data in order to train the model with higher accuracy. A user-friendly, operating system-independent dashboard was created to display the most relevant metrics. A two-step methodological approach was followed comprising device choice and data collection; data analysis and algorithm development. For the data analysis, three different approaches were tested, and among these a deep-learning approach using Convolutional Recurrent Neural Network (CRNN) with Long Short-term Memory (LSTM) architecture produced the best results. The optimal deep learning model predicted the number of people at the stop with a mean absolute error of ~ 1.2 persons, which can be considered a good preliminary result, considering that the experiment was done in a very complex open environment. People-counting systems at bus stops can support better bus scheduling, improve the boarding and alighting time of passengers, and aid the planning of integrated multi-modal transport system networks.

Perceptions of vulnerable roadway users on autonomous vehicle regulations

Introduction: Development and implementation of autonomous vehicle (AV) related regulations are necessary to ensure safe AV deployment and wide acceptance among all roadway users. Assessment of vulnerable roadway users’ perceptions on AV regulations could inform policymakers the development of appropriate AV regulations that facilitate the safety of diverse users in a multimodal transportation system. Method: This research evaluated pedestrians’ and bicyclists’ perceptions on six AV regulations (i.e., capping AV speed limit, operating AV in manual mode in the sensitive areas, having both pilot and co-pilot while operating AVs, and three data-sharing regulations). In addition, pedestrians’ and bicyclists’ perceptions of testing AVs in public streets were evaluated. Statistical testing and modeling techniques were applied to accomplish the research objectives. Results: Compared to the other AV regulations assessed in this research, strong support for AV-related data sharing regulations was identified. Older respondents showed higher approval of AV testing on public roadways and less support for regulating AVs. AV technology familiarity and safe road sharing perceptions with AVs resulted in lower support for AV regulations. Conclusions: Policymakers and AV technology developers could develop effective educational tools/resources to inform pedestrians and bicyclists about AV technology reliability and soften their stance, especially on AV regulations, which could delay technology development. Practical Applications: The findings of this research could be used to develop informed AV regulations and develop policies that could improve pedestrians’ and bicyclists’ attitudes/perceptions on regulating AVs and promoting AV technology deployments.

Account based ticketing (ABT) integration for seamless multi-modal transport systems in smart cities

The digital transformation of urban transportation systems remains a critical challenge in Smart Cities' development. This paper addresses the pervasive issue of inadequate digitalization within public transportation systems. The paper highlights the promise of Account Based Ticketing (ABT) as a pivotal solution for integrating diverse public and private transportation modes allowing users to access different transportation services with a single account, without the need for new physical tickets or cards. ABT approach represents a breakthrough in seamlessly amalgamating various transportation operators' systems, transcending city limits into broader metropolitan spheres, and fostering integration and interoperability across transportation modes operated by disparate entities. Emphasizing beyond-city-scale integration, it explores the potential value of ABT to connect transportation networks extending into metropolitan influences. The proposed approach involves analyzing the implementation and functionality of ABT systems, underlining their capacity to overcome existing barriers in multi-modal transportation. The results anticipate enhanced accessibility, increased ridership, and streamlined user experiences, contributing to the realization of efficient and interconnected urban transport networks. This study not only underscores the value of ABT in revolutionizing contemporary transportation systems but also examines its broader implications for future urban planning and smart city development, highlighting the transformative potential and essential role that ABT plays in shaping the future of integrated transportation and Mobility as a Service in Smart Cities.

The Walking Bangkapi: Inclusive Pedestrian Network’s Integrated Design and Implementation Study on Bangkok’s Emerging Transportation District

With a city growing in size, capacity, density, and intensity, walkability in the Bangkapi district (Bangkok, Thailand) represents a challenge to produce more inclusive transportation through mobility planning that suits the multimodal transportation system (skywalk, MRT lines, water transportation) and the walking experience of the pedestrian. Drawing from Bangkok’s Transit-Oriented Development (TOD) strategic plan, the challenge lies in the balancing point of efficiently and effectively elevating walkability while keeping the local urban identity. This study investigates the notion of walkability as both a ground-up participatory design process and within the overall mobility planning framework by reviewing both Thai and international sidewalk standards and through interviews with stakeholders. We conclude by producing an experimental design guide and policy recommendations on how area-specific sidewalks have the potential in shaping more feasible and equitable mobility planning from the ground up.

ПІДХОДИ ДО ФОРМУВАННЯ ЗБІРНИХ ВІДПРАВЛЕНЬ У МУЛЬТИМОДАЛЬНИХ ТРАНСПОРТНИХ СИСТЕМАХ

The article notes that the volumes of transportation of consolidated cargo by different transport modes in the world are constantly increasing. Some distinctions in the interpretation of the concept of "consolidated cargo" by different transport modes were identified. The interest in consolidated cargoes has increased with the spread of e-commerce services, growing competition, higher requirements of the cargo clientele, and the complexity of supply chains. The analysis of scientific researches allowed to identify the problems of multimodal cargo transportation that were previously studied. At the same time, no effective approaches to the formation of consolidated shipments in multimodal transport systems have been identified. The present study attempts to summarize the existing definitions of the concepts of "groupage cargo" and "consolidated cargo" and to provide a definition of these concepts. In particular, groupage cargo is defined as a combined (consolidated) cargo when several smaller cargo shipments from different shippers that are sent to the same or different consignees are combined into one cargo shipment. The definitions of Less than Container Load and Less than Truck Load have also been specified. Based on a generalization of other studies, the advantages of cargo consolidation for the client, consolidator and carrier in the transportation of consolidated cargo by various transport modes were highlighted. The requirements for cargo units in different modes of transport are schematized and it is noted that air transport has the strictest restrictions. The benefits of consolidation for customers, consolidators, and carriers were characterized, and the environmental effect of cargo consolidation was described. The features of cargo consolidation were identified and it was noted that they can be manifested in the form of both disadvantages and conditions of consolidation. The specifics of ensuring effective servicing and delivery of consolidated cargo were presented, and the complexity of preparation of transport and shipping documentation for consolidated cargo was noted.

Multimodal logistics chains for international transportation of dangerous and perishable goods

The overview article delves into the critical area of emergency logistics and supply chain management. Analyzing research conducted by experts in the field, the authors explore the potential benefits and challenges associated with the use of multimodal and intermodal international transportation of dangerous and perishable goods, and assess the potential challenges as well as the importance of emergency logistics for disaster relief and recovery. It is noted that traditional unimodal transport systems may be insufficient for swift and efficient response to emergency situations, which makes the integration of multimodal and intermodal chains an increasingly attractive alternative. Emergency logistics play a key role in ensuring the uninterrupted flow of goods during crises and disasters, especially when it comes to dangerous and perishable goods. One of the purposes of this article is to highlight the importance of vehicle diversification during such disasters. Multimodal transport involves the use of several modes of transport, such as road, rail, sea and air, under the direction of one transport operator or several carriers that cooperate in a coordinated manner. On the other hand, such transportation involves the use of standardized containers that can be easily moved between different modes of transport, offering increased flexibility and cost-effectiveness. The article provides an overview of the challenges faced by emergency logistics and the potential problems when transporting dangerous and perishable goods. It emphasizes the importance of building robust supply chains that can withstand disruptions and provide rapid response to effectively mitigate risks. The need to increase the stability and efficiency of emergency logistics chains is emphasized. The study aims to shed light on which approach offers the best balance between timeliness, adaptability and overall efficiency in the international transport of hazardous materials and perishable goods. The article refers to case studies and real-world cases of emergency logistics operations where multimodal and intermodal transport systems have been successfully applied. These cases highlight their practicality and effectiveness in mitigating potential disasters and minimizing the negative impact of accidents such as spills, explosions or spoilage, and the consequences of war. The authors note the special relevance of multimodal container transportation of dangerous and perishable goods, especially during the war that Ukraine is waging against russian aggression, since in these conditions the principle of logistics “just in time” is most in demand, and modern containers allow to ensure complete safety, speed and accuracy, and in necessary cases, the secrecy of the delivery of goods in the conditions of hostilities and other emergency situations.

MODEL OF TRANSPORT SAFETY ASSESSMENT IN MULTIMODAL TRANSPORTATION SYSTEMS

In this paper methods, criteria and models of safety assessment of multimodal transportation systems are investigated. Today, new types of transportation systems are formed – multimodal transportation systems, which may be defined as the result of the synthesis of several transport systems, where different modes of transport are effectively interact. The need for such systems was formed due to the peculiarities of each mode of transport, its technological and technical characteristics, which restrain the ability to compete and promote transport interaction. In this context, the problem of transport safety assess of multimodal freight transportations becomes highly important. An analysis of modern scientific researches on topic of transport safety is conducted. Unfortunately, the considered approaches to transport safety have a set of disadvantages if the complex systems are considered in form of, for example, combined, multimodal or intermodal transportations: the problem of local optimum; the problem of safety management in case of transport company is not the actual infrastructure owner; the problem of unifying estimates for several modes of transport, and so on. The system’s safety depends on its integrity and sustainable development, which is directly dependent on the objective conditions of its formation, development and operation. At the same time, the state of safety is directly dependent on subjective factors, the purpose of which is to ensure security, i.e., to preserve the integrity and maintain sustainable development and optimal functioning of the system. Thus, there is a conditional field of protection of transport system objects, which provides counteraction to a set of existing or perceived threats. In this context, modelling the transport safety assessment of multimodal freight is relevant and requires appropriate scientific developments. In the research, methods of mathematical modelling of transport systems were used in order to develop methodological approach that could be potentially used in improving the multimodal freight transportation safety. A methodical approach to safety assessment on the example of multimodal transportation, which takes into account the drawbacks of existing studies, is proposed. The practical application of developed model was demonstrated on the existing system of multimodal transportation. The developed safety assessment method may be potentially used both to assess the transportation route safety level and as key factor in optimal transportation route designing.

Are all bike lanes built equal? Using bike share GPS data to quantify cycling infrastructure investments’ ridership effects in Hamilton, Ontario

Separated cycling infrastructure, together with other investments such as bike share systems, are increasingly seen as important tools for planners and policy makers to promote urban cycling and multi-modal transportation systems. However, determining causality – that the construction of separated cycling infrastructure promotes higher levels of ridership – presents a significant challenge to researchers. This study uses 495,084 Hamilton Bike Share (HBS) trip routes, derived from GPS trajectories and a custom map-matching algorithm, to inform a longitudinal analysis concerning the influence of 10 separated cycling infrastructure investments made by the City of Hamilton between January 2019 and March 2022. Monthly bicycle kilometers traveled (BKT) along the segments, to account for variability in level of segment use per trip, was modeled using fixed effects regression, which controls for time and location-specific effects, climatological, and contextual factors. A suite of variables indicating completion of the various interventions were included, and of the 10 interventions, five were found to have highly positive impacts (71.60% to 441.95% increases) on monthly BKT. Heterogeneity across the investments was explored. Concrete-barrier separated cycle tracks were the most common interventions with significant and positive coefficients in the model, as were segments more connected with other separated cycling infrastructure, and more accessible to system ridership. This study provides an empirical, longitudinal, city-wide examination of the effects of cycling infrastructure on bike share ridership, setting a framework for further study of private cycling and the nature of the increases in bike share traffic across the interventions of interest.

Optimizing Multimodal Transportation Systems Using the Teaching–Learning-Based Algorithm

Optimizing Multimodal Transportation Systems Using the Teaching–Learning-Based Algorithm