Transport Operations Research Articles

A risk assessment of inhibited cargo operations in maritime transportation: a case of handling styrene monomer

Hazardous cargo handling on tanker ships involves various risks that could lead to accidents such as explosion and fire. Investigating these risks is crucial to safeguard life, property and the marine environment. This paper performs a risk assessment specific to hazardous cargoes with special requirements. It addresses the risks of inhibited cargo operation, which has not been adequately studied in the literature despite its criticality. Styrene monomer is selected as the inhibited cargo type since failures during its handling may lead to polymerisation and catastrophic consequences. Using the Failure Modes, Effects and Criticality Analysis (FMECA) 24 failures are identified, and their occurrence, severity and detection aspects are evaluated by experts familiar with the process. In addition, a rule-based fuzzy logic technique with Gaussian membership functions is employed to support the traditional FMECA application. The integration of methods helps to deal with the limitations of FMECA in the calculation of risk priority number (RPN). Based on the fuzzy RPN results, failure modes are prioritized and preventive actions are presented for the high-ranked failure modes. The outputs of the study could help to increase the awareness of operators and interested individuals concerning the risks of tanker cargo operations with special requirements.

Graph-based adaptive weighted fusion SLAM using multimodal data in complex underground spaces

Accurate and robust simultaneous localization and mapping (SLAM) is essential for autonomous exploration, unmanned transportation, and emergency rescue operations in complex underground spaces. However, the demanding conditions of underground spaces, characterized by poor lighting, weak textures, and high dust levels, pose substantial challenges to SLAM. To address this issue, we propose a graph-based adaptive weighted fusion SLAM (AWF-SLAM) for autonomous robots to achieve accurate and robust SLAM in complex underground spaces. First, a contrast limited adaptive histogram equalization (CLAHE) that combined adaptive gamma correction with weighting distribution (AGCWD) in hue, saturation, and value (HSV) space is proposed to enhance the brightness and contrast of visual images in underground spaces. Then, the performance of each sensor is evaluated using a consistency check based on the Mahalanobis distance to select the optimal configuration for specific conditions. Subsequently, we elaborate an adaptive weighting function model, which leverages the residuals from point cloud matching and the inner point rate of image matching. This model fuses data from light detection and ranging (LiDAR), inertial measurement unit (IMU), and cameras dynamically, enhancing the flexibility of the fusion process. Finally, multiple primitive features are adaptively fused within the factor graph optimization, utilizing a sliding window approach. Extensive experiments were conducted to check the performance of AWF-SLAM using a self-designed mobile robot in underground parking lots, excavated subway tunnels, and complex underground coal mine spaces based on reference trajectories and reconstructions provided by state-of-the-art methods. Satisfactorily, the root mean square error (RMSE) of trajectory translation is only 0.17 m, and the mean relative robustness distance between the point cloud maps reconstructed by AWF-SLAM and the reference point cloud map is lower than 0.09 m. These results indicate a substantial improvement in the accuracy and robustness of SLAM in complex underground spaces.

Study of the technical parameters dynamics influence on operational performance of hydraulic single-bucket excavators

Introduction. The development of automobile and road construction is a priority in the Russian economy. Timely putting construction projects in commission increases the requirements for planning of execution mechanized works. The operation of transport and technological machines in construction processes for a long time leads to a decrease in their potential capabilities, including operational productivity. The purpose of the proposed article is to improve the method of calculating the performance of a single-bucket hydraulic excavator (EO), taking into account the operating time.Methods and materials. The performance calculation method takes into account the dynamics of the working pressure in the hydraulic system of the working equipment (GRO), the speed of rotation of the crankshaft (PMVC) from the operating time, regression dependencies were used to describe them. The parameters of the law of distribution of the random value of the working pressure in the hydraulic drive and the rate of its fall for the ‘development and recruitment of soil’ operation were also obtained.Results. Processing of the results of production experiments enables to establish the dependence of changes in the working pressure in the hydraulic system during development and gathering soil, as well as for all technological operations of the working cycle, the rotational frequency of the crankshaft of a single-bucket excavator engine on the operating time. The influence of the working pressure in the hydraulic drive, the rotational speed of the crankshaft of the excavator engine on the supply and hydraulic power, the duration of technological operations is studied. The calculation of the operational productivity of a single-bucket excavator is carried out taking into account the dynamics of parameters reflecting its change over operating time.Discussion and conclusions. It has been established that with an increase in operating time, the operating pressure in the hydraulic drive decreases by an average of 12.7-13.0%, and the decrease in the average operating speed of the crankshaft is 4%. The estimated value of the drop in the average hourly operating performance of the EO, taking into account the deterioration of the technical condition, is 55% in the operating time range from 0 to 10,000 operating hours for the Japanese EO ZX 330 model.

Нарушения на транспорте по Уголовному уложению России 1903 г.

Purpose. Criminal legislation has the task of protecting the state system and social system, their individual structures and institutions. The peculiarity of the Criminal Code of 1903, regarding these tasks, is that it was adopted in an exceptional and special historical period of time. First of all, this circumstance is associated with the period of time that covered the development of criminal legislation during the 19th century, which was reflected in its system, structure and criminal law norms. Secondly, as noted in the preamble of the Criminal Code of 1903, it is adopted in the context of the ongoing state and social transformations, taking into account the requirements of new decisions. Significant changes related to the formation of criminal law provisions providing for liability for violation of the rules of management, use, maintenance and disposal of transport. It should also be noted that the Criminal Code of 1903 represented and was the basis for the development of criminal legislation of the new century, including criminal liability for transport crimes. Methodology: dialectics, abstraction, analysis, synthesis, deduction, — formal legal method, comparative law method. Conclusions. Firstly, the second half of the nineteenth century is characterized by the active construction of the transport system and its infrastructure; secondly, the need arose to form special governing bodies that were not previously provided for in the structure of government bodies of the Russian Empire; thirdly, the safety of traffic and operation of transport required full legal support for the management of the transport system; fourthly, the organization of transport traffic required the formation of institutions and employees for the training of specialized specialists; fifthly, the task of uninterrupted operation of the transport system and the movement of vehicles predetermined the need for systematic maintenance and repair of vehicles and transport infrastructure, sixthly, points/ stations for the formation of trains, loading/reloading of goods and boarding/transfer of passengers deserved to be formed and provided; seventhly, the need arose to form transport teams, determine for them the place and time of meals, rest and interchangeability, and then, as a necessary component of any activity, the function of monitoring the movement of vehicles, especially their technical equipment, was predetermined in order exclusion of accidents. Scientific and practical relevance. To specify the categories of the Criminal Code of 1903 under consideration in order to determine their meaning and place in the current national criminal legislation and in the science of criminal law. Use the results in the preparation of regulations providing for liability for encroachment on the safety of traffic and operation of vehicles, in a complex modern management system in the field of organization and operation of transport, especially in international and related areas, as well as in the educational process when training specialists in the field law enforcement.

Flying High: Revealing the Sustainability Potential of Women in Aviation

This paper explores the predominantly male-dominated aviation sector and highlights the benefits of increasing female representation. The key objectives are to analyze the gender pay gap, assess the current gender imbalance, and explore how addressing these issues could contribute to the sector’s sustainability and operational success. A combined quantitative and qualitative methodology is employed, including scenario-building based on monetary indicators and achievements from other industries where female workforce participation has been enhanced. The results demonstrate that closing the gender pay gap and boosting female participation in air transport operations, in line with supranational recommendations, can lead to significant financial gains and operational improvements. The study concludes that promoting gender equity is not only a social imperative but also a crucial factor for achieving sustainability goals within aviation.

Modeling cost-optimal fuel choices for truck, ship, and airplane fleets: The impact of sustainability commitments

For the next 25 years, numerous transport operators have introduced sustainability commitments to mitigate carbon emissions. However, static goals to reduce fossil fuel usage and adopt renewable fuel technologies pose economic risk. This study analyzes the costs of strategic fleet replacement through a mixed integer linear program. Comparing three Norwegian transport operators, we determine cost-optimal investments in fossil and renewable fuel technologies for two approaches: One integrating and the other neglecting sustainability commitments. Our findings reveal that the truck operator’s sustainability commitments incur minimal additional costs, with battery-electric trucks proving cost-effectiveness early. In contrast, ship and airplane operators exhibit significant differences in fleet replacement decisions, resulting in additional costs ranging from +6% to +31% for ships and +4% to +11% for airplanes, across fuel cost and carbon price scenarios. Norwegian carbon price regulations fall short in incentivizing a cost-competitive technology transition for ships and airplanes. Additional policies are needed to encourage gradual fleet replacement.

A learning-driven multi-objective cooperative artificial bee colony algorithm for distributed flexible job shop scheduling problems with preventive maintenance and transportation operations

In recent years, distributed production scheduling problems receive much attention from both scholars and practicers. Nevertheless, existing research on such problems commonly ignores machine maintenance and job transportation operations. This work proposes a distributed flexible job shop scheduling problem with preventative maintenance and transportation operations in consideration of sequence-dependent setup time. First, a mixed integer programming model is formulated to minimize maximum completion time of jobs and maximum workload of factories. Second, a learning-driven multi-objective cooperative artificial bee colony algorithm is developed to deal with the model. A Q-learning-based cooperation strategy between population and obtained non-dominated individuals is devised to strengthen the exploration and exploitation performance. Furthermore, heuristic-based population initialization, crossover operations in employed bee phase and iterated local search methods in onlooker bee phase are specially developed considering the problem characteristics. Finally, the proposed method is compared against three well-known meta-heuristics from existing literature and an exact solver CPLEX by using a set of benchmark instances. The results confirm the competitive performance of the developed model and algorithm for addressing the studied problems.

From policy mix to pavement: Exploring individual actor-internal factors in zero-emission truck adoption

Despite regulatory efforts and market availability, the adoption of zero-emission vehicles (ZEVs) in the road freight sector is limited. This paper investigates the influence of managers' policy mix perceptions on the uptake of ZEVs in Sweden. Based on a survey of transport operation managers, we analyse the interaction between their perceptions of how technology-neutral the prevailing policy mix is, the anticipated regret of premature technology adoption, the rate of technology change and their mutual influence on the decision to delay ZEV adoption. The study's findings reveal a positive correlation between managers' perceptions of technology neutrality and adoption delay. We further explain the mechanism in this relationship by confirming that anticipated regret mediates the positive correlation between perceived technology neutrality and the ZEV adoption delay decision: The more technology-neutral the policy mix is perceived, the more anticipating regret over adopting ZEVs is expressed by the managers, which, in turn, increases the likelihood to delay ZEV adoption. Moreover, managers' perceptions of the rate of technological change affect their anticipated regret. The work contributes to the transition literature by unveiling how a specific policy mix perception, namely technology neutrality, could delay the adoption of ZEVs and calls for a nuanced re-evaluation of the current policy mix to facilitate a faster transition towards net-zero goals. It also underscores the importance of paying closer attention to how individual actor-internal factors (such as perceptions and emotions) of individual decision-makers in organisations may influence transition processes.

Investigating Rural Logistics and Transportation through the Lens of Quadruple Bottom Line Sustainability

Background: An alternative to unsustainable urban developments, rural living is on the rise, but it already has its challenges. To that end, rural logistics and transportation (RLT) calls for a comprehensive analysis of its context, especially in a climate-changed and socially turbulent world. Unlike urban logistics, there is limited focus on RLT in academic literature. However, rural areas’ lack of transportation and limited logistics operations negatively affect rural residents’ daily lives, especially socially disadvantaged groups such as older people, children, women, and low-income households. Methods: This study first identifies the key literature on RLT and sustainability using a systematic literature review. Then, it synthesizes from the extant literature the challenges in RLT and proposed solutions to understand how to improve accessibility and address some barriers to implementation, all through the perspective of quadruple bottom line (QBL) sustainability pillars. Results: The lack of opportunities presented to rural residents due to limited RLT leads to inequality between rural and urban populations, requiring academic attention. Moreover, despite the growing emphasis on sustainability in academic literature, there is a noticeable lack of attention to sustainability in RLT. Conclusions: This study leads policymakers toward a better understanding of rural communities’ complexities, directs practitioners to adopt the QBL perspective in decision-making, and aims to stipulate innovative RLT topics for further research for academicians.

A seamless bus network without external transfers using autonomous modular vehicles

Recently, autonomous modular vehicles (AMVs) capable of enabling in-motion transfer (IMT), i.e. passengers moving between vehicles while the vehicles are traveling, have been developed. IMT allows new paradigms for public transport operations that can enhance the speed, flexibility, and reliability of the system. We leverage IMT technology to propose the first network-wide seamless, stop-less bus service concept. We recently introduced the concept of a Stop-Less Autonomous Modular (SLAM) bus service, which eliminates the need for passengers to stop at each bus stop while traveling along a bus line. The current work extends this paradigm to the network level by developing a bus service framework in which multiple SLAM bus lines operating on main arterials interact by exchanging pods among each other to provide passengers with a travel experience that not only eliminates most extra passenger stops within a single line, but also eliminates external transfers, i.e. it removes the need to disembark at a bus stop to change buses when transferring from one bus line to another. The result is a high-speed service that provides a completely seamless journey from the passenger’s origin stop to destination stop anywhere in the coverage area, with integrated (i.e. internal) transfers that take place inside the vehicles themselves while they are in-motion. Our results show that while the proposed service has more stringent operating requirements than a comparable conventional bus service, it provides significantly superior performance, reducing passengers’ travel cost by up to 35% under realistic system settings.

Heat-related illness among workers in British Columbia, Canada: Extreme hot weather in 2021 compared to 2001-2020.

British Columbia (BC), Canada, experienced an unprecedented summer with record-breaking high temperatures in 2021. Yet the health impact has not been examined in occupational settings. This study aimed to characterize occupational heat-related illness (HRI) among BC workers estimated by incidence rates and associations between heatwaves and HRI, compare risks from 2021 and prior summers of 2001-2020, and assess differential impacts on worker groups by demographics and occupations. We identified HRI from workers' compensation claims that occurred between June and August from 2001-2021 in BC. Incidence rates were calculated using working population estimates from Statistics Canada's Labour Force Survey. A time-stratified case-crossover design with conditional Poisson regression was used to examine the impact of heatwaves on occupational HRI. All analyses were stratified by year (2021 versus 2001-2020), age, sex, and occupation. Of the 521 claims identified, 107 (21%) occurred in 2021. Incidence rates for 2021 and prior summers were 3.97 [95% confidence interval (CI) 3.26-4.80] and 0.93 (95% CI 0.85-1.03) claims per 100 000 workers, respectively. This difference represents a 327% increase. Rates were higher in health occupations in 2021 versus 2001-2020. During 2001-2021, the risk of HRI during heatwave days was 4.33 (95% CI 2.98-6.27) times that during non-heatwave days, and the risk was higher among middle-aged workers and workers in trades, transport, and equipment operations. The 2021 heatwaves had greater impact on younger and female workers than those from prior summers. Heat is a crucial workplace hazard. Prevention strategies should prioritize at-risk workers and not be limited to heatwaves.

Development of a framework for assessing train passengers' post‐boarding behaviours based on their perceptions

AbstractWhile existing literature has focused on modelling pedestrian movement on platforms, there is a lack of understanding of passengers' perceptions, motivations, and influential factors that shape their on‐board behaviours and choices. This study developed a conceptual framework to assess passengers' post‐boarding behaviours and perceptions, specifically focusing on their actions and choices inside the train carriages. The conceptual framework was tested through survey data of 429 passengers in Melbourne, Australia. The result shows that door access is the most influential factor when passengers choose where to stand or sit on board, followed by comfort, safety, privacy, and random factors. Furthermore, the study explores the relationship between the post‐boarding behaviour variables and travellers’ personal and trip characteristic variables. The analysis shows that carrying large items has a more significant effect on many post‐boarding behaviour variables. Gender, age group, travel frequency, waiting time, and carrying small items also play significant roles. However, variables such as travel time and frequency of group travel have lesser effects. These novel findings offer valuable insights, laying the groundwork for future modelling activities. Moreover, the understanding derived from passenger perceptions can guide transport agencies and operators in shaping strategies to improve onboard services.

Managing oversaturation in BRT corridors: A new approach of timetabling for resilience enhancement using a tailored integer L-shaped algorithm

Bus rapid transit (BRT) is a high-capacity public transport system that typically operates along urban transit corridors with dense travel demand. Maintaining the efficiency and stability of the BRT is paramount for daily transport operations. Owing to the difficulty in ensuring an exclusive right-of-way along the entire route, stochastic congestion events may occur resulting from road segments without dedicated BRT lanes. This may lead to volatility in travel time and resulting in passenger stranding, determined as common-case disruptions in this study. These common-case disruptions frequently occur in the daily operation of oversaturated BRT routes. To manage and mitigate their negative impacts, a novel timetabling problem for enhancing the resilience of a BRT system was proposed to assess the ability of the system to withstand and recover from these disruptions. We formulated the problem as a two-stage stochastic mixed-integer optimization model and designed an exact algorithm based on a tailored integer L-shaped method. We then analyzed the structural properties of our model and developed several acceleration techniques to further improve the efficiency of the algorithm. The computational results show that the proposed algorithm outperforms the commercial solver in large-scale instances and can provide near-optimal solutions when the commercial solver is invalid. Besides, external comparisons with dynamic programming also demonstrate the superiority of the proposed algorithm in solution efficiency. Compared with the benchmark timetabling problem, which aims to reduce passenger waiting time, the proposed method can efficiently reduce the duration of the oversaturation period by 35.3%.

From constraints fusion to manifold optimization: A new directional transport manifold metaheuristic algorithm

The ascent of geometry-based models and methodologies, exemplified by geometric deep learning and manifold numerical optimization algorithms, has inaugurated a novel domain across various applications that grapple with geometric data complexities, such as electroencephalogram signals represented by symmetric positive definite matrix manifold, hierarchical data represented by hyperbolic manifold. The imperative fuels this inevitable paradigm shift to encapsulate the intricacies and richness inherent in data, areas where traditional methods prove inadequate. While metaheuristic algorithms are renowned for their versatile adaptability across applications, offering practical solutions within reasonable timeframes. However, the conventional metaheuristic algorithms fail on manifold applications with meaningless solutions. From an extrinsic optimization perspective, we treat manifold optimization problems as general optimization problems with multiple fused constraints that limit the optimization path to the manifold. This study pioneered the proposal and implementation of a metaheuristic manifold optimization, introducing a novel directional transport operator to rectify previously identified issues. Through experimentation across five sets of 25 problems, comparing against five algorithms, including both gradient-free and gradient-dominant counterparts, our proposed algorithm emerges as the optimal performer within the gradient-free category, demonstrating competitiveness even against gradient-dominant algorithms. Furthermore, we applied the proposed algorithm to the robot dynamic manipulation problem, achieving a close-optimal solution that eludes gradient-dominant approaches. This paper delves into the inherent capabilities and establishes the generalization of a metaheuristic algorithm within non-Euclidean functional landscapes. The source code will be available at https://github.com/lingping-fuzzy/metaheuristic-manifold-optimization.

Mathematical models and algorithms for designing main pipeline for transporting georesources

Relevance. The practical importance of the tasks of utility networks design, namely, the problems of optimizing the structure of the main pipeline according to given criteria, such as efficiency, reliability etc., under conditions of limitations, for example, the compatibility of various types of utilities. Since the main pipeline is laid on the ground with various physical and geological factors, natural and situational conditions, it is advisable to take the reliability of its operation as a global criterion. The task of network optimization is proposed in the form of displaying the main pipeline along the selected routes in three-dimensional space, which considers various existing communications and objects, as well as elevation marks of the area. The paper presents the problems of optimizing networks, both in the continuous case and in the discrete case, and also studies various indicators of the reliability of the operation of the main pipeline. Aim. To develop a model for laying the main pipeline in three-dimensional space, considering the reliability of the pipeline transport; to conduct a comparative analysis for various reliability indicators and topologies of the main pipeline. Objects. Utility communications and networks laid in three-dimensional space. Methods. Calculus of variations, discrete optimization methods, graph theory and hypernet theory methods, network reliability analysis methods. Results. The task of optimizing the main pipeline transport is given taking into account its nesting along the route in three-dimensional space with the choice of an optimization criterion (economic efficiency, reliability, etc.). The problem is presented in the form of continuous and discrete formulations, which is important for its development both within the theory of the calculus of variations and discrete optimization. In this work, the problem was studied within the framework of the theory of graphs and hypernets, which allow, firstly, taking into account the nesting of one structure (main pipeline) into another (a discrete analogue of three-dimensional space) and, secondly, clearly illustrating the results of numerical experiments. It is shown that under the conditions of a given variants for laying a secondary network along the primary channels, various optimal structures are obtained when considering various reliability indicators as a criterion, which can be used to implement a design solution for the construction and operation of pipeline transport for various purposes.

Secure and Privacy-Protected Bioinformation Implementation in Air Passenger Transport Based on DLT

Aviation information systems are a key component in ensuring efficient and smooth air transport operations. In this regard, the transfer of passenger information between parties is of paramount importance. With the continuous improvement of biometrics technology, this kind of individual identification that can provide accurate and unforgeable identification is widely used in various fields. This research presents the significance and effective application scenarios of facial recognition in biometrics in air transport operations. Due to the characteristics of aviation information systems, Distributed Ledger Technology (DLT) is used in this study for secure and private transmission of facial recognition information. Distributed systems can give a transparent and secure platform to multiple parties to access sensitive passenger data. This study uses the Corda framework as the DLT that supports CorDapp development. Based on the above techniques, this study proposes two feasible application scenarios. One is a baggage match detection system to prevent misplaced baggage, and the other is an iAPIS system that transmits passenger information in real-time communication between airlines and border control agencies. This article details how to apply the research in these two scenarios, as well as the benefits and implications of the applications. Finally, this article presents an outlook for future development and feasible directions for improvement.

Car or Cargo Bike? Determinants for the Use of a Small Vehicle Type in Urban Logistics: A Stated Preference Survey Among Commercial Transport Operators

To address the adverse effects of urban freight, downshifting to smaller vehicles, such as cargo bikes, has been indicated as a viable solution. Existing literature on freight mode choice rarely considers vehicles smaller than truck size. We aimed to fill this research gap by quantifying how vehicular, operational, trip-based, contextual, and individual determinants influenced the decision between cargo bikes and cars in urban logistics. To that end, a stated preference survey was conducted among 537 German organizations after they had been familiarized with cargo bikes through a 3-month vehicle trial period. Participants then took part in a survey in which they had to choose between the modes cargo bike, car, or neither of these two alternatives. The survey data were analyzed using a mixed logit model with 4,833 observations. The model estimations demonstrated that the values and signs of parameters were in accordance with both our expectations and the literature. The results indicated that cargo bikes were an attractive alternative to cars for delivery and service trips of short duration in fair weather. The probability of choosing a cargo bike over a car could be further increased by improving bike infrastructure or imposing parking limitations. The preference for cargo bike could be observed for respondents in dense urban centers and low-density parts of the country alike. Around 3 out of 10 respondents decided to buy their own cargo bike after the study, demonstrating the effectiveness of low-threshold testing programs in changing habits toward more sustainable mobility solutions.

The Management of Railway Operations during the Planned Interruption of Railway Infrastructure

A planned interruption of railway infrastructure is a situation where the operation of the track line or the operation of railway transport is limited. If there is also a restriction on the railway infrastructure, it means there will be complications not only for passengers but, above all, for railway undertakings operating freight transport. However, because of the planned railway infrastructure interruption, the quality of services provided not only to passengers but also to freight transport is decreasing. The aim of this paper is to propose effective planned maintenance works based on the analysis and evaluation of the processes performed during the planned railway infrastructure interruption or restriction. The research describes the process of affected railway infrastructure from technical, cost, and safety points of view. A methodological procedure is proposed under the condition of the Czech infrastructure manager. The main method is the calculation of the costs for the railway infrastructure manager and railway operator during the infrastructure interruption. The application part is undertaken using two interrupted lines according to the established alternative timetable in the area of České Budějovice.

Prediction of cyber-attacks in air transport using neural networks

This article addresses the topic of cyber-attacks in air transport, which is crucial for ensuring the safety and reliability of airports and air transport operations. The aim of the article was to present a new method for predicting cyber-attacks in air transport based on neural networks. The task of the neural network was to determine the multiple regression function based on which the probability of a cyberattack occurring at a specified hour and on a specific day of the week is predicted. The probability, depending on the time of the cyberattack occurrence, was determined using theoretical distributions. The method was verified with real data. Verification of the method confirmed its high effectiveness, determined at the level of 92%. The study examined the effectiveness of using the classical multiple regression method in predicting cyber-attacks in air transport. The classical multiple regression model covered only 0.14 of the input data, while the regression model generated by the neural network covered 0.99, indicating the high efficiency of the developed neural network.

Mobility on demand in the United States – Current state of integration and policy considerations for improved interoperability

The concept of Mobility on Demand (MOD) aims to create a safe and convenient ecosystem for transportation and goods delivery. Despite offering various services, the integration and seamless data exchange among different modes of transportation remain challenging. To address this, research was conducted to examine the current state of integration in the MOD ecosystem, identify gaps in data exchange, and propose policy considerations. The research highlighted the limited integration and inconsistent data structures in the United States (U.S.), attributed to the absence of policy directives and high costs of traditional standards development. Industry-led initiatives are driving progress in standards and specifications. Deep linking and deep integration were distinguished, emphasizing the importance of a truly user-centric MOD solution. Emerging mobility models leveraging blockchain technology show promise in facilitating efficient data sharing and collaboration among various operators. Transportation policy makers play a crucial role in supporting open-source standards and integration efforts. An initial framework utilizing open-source efforts such as Transport Operator Mobility-as-a-service Provider (TOMP), Mobility Data Specification (MDS), General On-demand Feed Specification (GOFS), Transactional Data Specification (TDS), Operational Data Standard (ODS), and City Data Standard for Mobility (CDS-M) was proposed to drive the advancement of scalable and user-centric MOD systems.