Existing Transportation Network Research Articles

Beyond half-mile circle: Measuring the impact of subway expansion on home-based travels in Beijing, China

Subways play an important role in supporting travel needs, yet whether the benefits of subway expansion can justify the substantial investments remains a much-debated question. Existing studies have arbitrarily defined the catchment area of a subway station using walking distance and have disproportionately focused on commuting trips, potentially underestimating broader subway effects. To address these limitations, this study employed the distance-band approach to accurately define the treatment area of subway stations while incorporating both local and network effects. Based on longitudinal mobile signaling data, we used the difference-in-differences approach to estimate the average treatment effects of 32 new subway stations on different types of home-based travels in Beijing, China. We found that the opening of new subway stations has led to significant increases in subway usage, trip duration, and trip distance within a 2000-metre radius, and that commuting trips have been more affected than home-based non-commuting trips, except during the COVID-19 pandemic. Moreover, the new subway stations also enhanced the connectivity of the city-wide network, influencing the travel behavior of residents in the vicinity of existing subway stations. We further found that subway expansion is particularly beneficial for women, younger residents, and residents of low-rent neighborhoods. According to these findings, planning new subway stations in Beijing and other densely populated megacities requires an integrated approach that considers the relationships between the existing transport network and diverse travel demand.

Optimizing Dijkstra's Algorithm for Managing Urban Traffic Using Simulation of Urban Mobility (Sumo) Software

Among the challenges of urbanization is traffic management as a measure of growth and progress. Recent population growth has resulted in a significant increase in vehicles, causing traffic jams that are challenging for the existing transportation networks. This congestion affects other services, including public transit, airports, road maintenance, and pollution caused by emissions of CO2 and other gases. Furthermore, it doubles the amount of fuel used. This has negative consequences for society as well as economic losses. This paper focuses on an improved Dijkstra algorithm based on traffic congestion levels to address the above problems. Improved Dijkstra algorithm can provide (a) real data collected from the map via OpenStreetMap, (b) Add four features to SUMO(Simulation of Urban Mobility) simulator software (time period, rush-hour, number of vehicles, and routing algorithm), (c) it could know congestion level for roads (d) rerouting vehicles to avoid traffic congestion. Based on the simulation results and analysis presented in the paper, it was found that the proposed improved Dijkstra algorithm increased the performance of the road traffic flow by reducing the number of related vehicles in traffic congestion and average delay time for experiment scenarios.

АЛГОРИТМ ПОИСКА ОПТИМАЛЬНОЙ СЕТИ ПОЛИГОНОВ СБОРА ТВЕРДЫХ КОММУНАЛЬНЫХ ОТХОДОВ

The aim of the study is to develop an algorithm for constructing a network of polygons for storing, recycling and neutralizing industrial and consumer waste in a certain region, taking into account the generated mass of solid communal waste and the existing transport network, allowing one to come to an economically optimal solution. The mathematical methods presented in the scientific literature are aimed at solving problems of determining the optimal location of logistics infrastructure objects, namely a manufacturing plant, a warehouse, a distribution centre, a retail outlet. The paper formulates and implements an algorithm for constructing an optimal network of polygons, which would minimize economic costs for logistics, construction, and operation of the polygons. The main factors taken into account are the mass of generated solid communal waste, the transportation cost from the temporary accumulation site to the solid communal waste polygon, the distance between administrative centres. The basic principle of searching for the logistics extremum is based on determining the main node, that is the one with the largest mass of solid communal waste along all available road junctions and choosing the polygon location based on the condition of the maximum difference in annual logistics costs. Using the proposed algorithm, the paper solves the problem of determining the number and location of solid communal waste polygons for the southern part of the Komi Republic.

Systematic application of traffic‐signal‐control system architecture design and selection using model‐based systems engineering and Pareto frontier analysis

AbstractThe global population rise has increased vehicles on roads, complicating traffic management. Inefficient traffic control systems cause significant economic losses owing to commuter time wastage, high energy consumption, and greenhouse gas emissions. Traffic signal control systems (TSCSs) are vital in traffic management, impacting traffic flow significantly; therefore, studies are exploring new optimization approaches that adapt to changing traffic conditions. However, they concentrate on either new technology infusion or on control algorithm optimization, and do not holistically address the architectural configuration of the system. In this study, we presented a unique case study by applying an existing systematic framework to the TSCS system architecture design and selection process. This application demonstrates that TSCS enhancement is a multifaceted process that requires a comprehensive assessment of not only technical aspects, such as the control algorithm, but also factors including system architecture, security, and data integrity. Because of the increasing reliance of TSCSs on data exchange between their various subsystems, this case study also adopted a cybersecurity perspective of the system and introduced cyber resiliency as a crucial metric for evaluating TSCS architecture performance. Furthermore, through the applied framework, an optimal TSCS architectural configuration with executable options was identified by generating multiple TSCS architectural configurations using decision option patterns and identifying those on the Pareto frontier to understand the architectural decision‐making process. Traffic engineers and transportation planners can use this case study application as a guide to optimize TSCSs employed in existing transportation networks and design more efficient transportation networks for future urban development.

Urban segregation on multilayered transport networks: a random walk approach

We present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic groups with random walks and Lévy flights. This method allows for evaluation of new transport infrastructure’s impact on segregation while quantifying each network’s contribution to interaction opportunities. The proposed random walk segregation index measures the probability of individuals encountering diverse social groups based on their available means of transit via random walks. The index incorporates temporal constraints in urban mobility with a parameter, α∈[0,1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha \\in [0,1)$$\\end{document}, of the probability of the random walk continuing at each time step. By applying this to a toy model and conducting a sensitivity analysis, we explore how the index changes dependent on this temporal constraint. When the parameter equals zero, the measure simplifies to an isolation index. When the parameter approaches one it represents the city’s overall socio-economic distribution by mirroring the steady-state of the random walk process. Using Cuenca, Ecuador as a case study, we illustrate the method’s applicability in transportation planning as a valuable tool for policymakers, addressing spatial distribution of socio-economic groups and the connectivity of existing transport networks, thus promoting equitable interactions throughout the city.

Assessing the Operation of a Multimodal Hub: A Traffic Impact Microsimulation Analysis

Creating new multimodal infrastructure in an existing transport network of an urban city is a challenging process. The responsible transport authorities have to pay special attention to the details regarding the accessibility and effectiveness of the new development, to avoid travelers’ confusion and network congestion. The subject of this paper is the assessment and optimization of the traffic network in the surroundings of the new multimodal depot of Thessaloniki’s future metro system with the use of the microsimulation software PTV VISSIM (version 2022). Five different scenarios were developed in collaboration with the city’s transport authority and evaluated into two stages, beginning with the whole traffic network, and then continuing with the analyzed intersections separately. The evaluation is based on Key Performance Indicators (KPIs), which were extracted by the software. According to the results of the base case scenario, the network functions satisfactorily, with slight delays. Regarding the future network, the operation of the new hub will strongly increase the traffic demand, while the proposed traffic network adjustments by the local authorities seem to cause significant delay problems. This paper aims to highlight the importance of using modeling tools during the design phase of a new infrastructure to create efficient, accessible, and sustainable infrastructures that enhance the public transport system.

Engineering systems analysis of mobility in Odawara city: New transportation services impacts on community engagement

AbstractLocal cities in Japan are struggling with aging and decreasing populations. Elderly people and parents with young children are uniquely challenged when accessing public transportation, a key to increasing their community engagement and improving local cities' sustainability. This research investigates the introduction of new transportation modes and fares on community engagement of both elderly people and parents of young children. An urban systems model which integrates mobility and civic functions is evaluated by agent‐based simulation to analyze various policies’ impacts on community engagement and financial performance. The model is applied to Odawara City, a typical local city of nearly 200,000 people in Japan. For this case study, two policies which strongly subsidize a community bus and partially subsidize a door‐to‐door van were predicted to generate 10% or greater engagement for the elderly without a financial loss compared to the current baseline case. More specifically, community engagement of elderly people and parents with young children are predicted to increase by 11% with positive (0.25 M yen) net present value per person when the fare of community buses is 100 yen and that of door‐to‐door vans is 300 yen. However, no synergistic effect driven by policies favoring elderly people and those favoring parents is found. Still, the measures to support elderly people's transportation accessibility do not harm the parents’ behavior but rather support their daily activities. The method is demonstrated to be useful for designing new mobility policy in light of a specific population with demographic residential distribution and existing transportation network.

Развитие узловой терминально-складской инфраструктуры: модификация методов исследования и прогнозы

Purpose: Development of an economic-geographical method in finding the optimal locations of logistics freight distribution centers in the territory under consideration and its application to the construction of a geometric routing model for the distribution of cargo flows. Methods: The economic-geographic method of dividing the ‘areas of influence’ of transportation process participants. Statistical methods for processing empirical data. Monte Carlo method. Results: A geometric routing model has been developed for the distribution of cargo flows generated by participants in the transportation process competing in a territorial oligopolistic freight transportation market. Practical significance: The constructed model allows for a proper assessment of the existing transportation network to identify the ‘areas of influence’ of transportation process participants, considered as oligopolists in the regional freight transportation market.

Exploring willingness to use shared autonomous vehicles

Although multiple studies have modeled and predicted the potential effects of shared autonomous vehicles (SAVs), the research on the adoption of SAVs by riders with actual ridership experience is still limited. In addition, the increasing tendency towards operating SAV technology requires understanding its efficiency while integrating it into the existing transportation network infrastructure. This study aims to identify the factors affecting the user's willingness to ride the SAVs based on the data collected from a comprehensive survey distributed among users and non-users of a self-driving pilot project called RAPID (Rideshare, Automation, and Payment Integration Demonstration) in Arlington, Texas. Using structural equation modeling (SEM), we identify the effects from vehicle ownership, RAPID usage, existing modes of transportation, RAPID service attributes (comfort and safety), and sociodemographic variables on individuals' willingness to use SAVs in the future. Results indicate that most riders of the RAPID service are young Asian individuals and students from low-income households with limited or no access to a private vehicle. Furthermore, SEM results show that RAPID usage directly impacts willingness to use SAVs, implying that people start developing trust for the technology with an increase in the frequency of using the service. Our model suggests that sociodemographic attributes of the SAV riders indirectly influence the willingness to use SAVs through the mediators, including RAPID usage, existing modes of transportation, and vehicle ownership. This study provides crucial insights about individual travel behavior after integrating SAVs into existing transportation infrastructure to assist policymakers and transportation planners in developing AV-related policies.

Gender perspectives on electric micromobility use

AbstractElectric micromobility (e‐micromobility) offers the potential to enhance the sustainability of first‐ and last‐mile journeys in urban areas by reducing the number of private vehicle trips. As a new mode of transport, it is imperative that it is not subject to the same male bias that has been evidenced across our existing transport networks. An in‐depth qualitative study was conducted with 24 UK participants (12 females) to assess the gender factors that relate to the incentives and barriers of e‐micromobility (electric bike and electric scooter) use. Focus groups and interviews were conducted and the data analysis was disaggregated by gender to reveal the differences and similarities between female and male perspectives on e‐micromobility use. Differences in the types of trips made and perceptions of fear were prevalent. Key gender‐related findings and recommendations are made. By reviewing, and acting upon, the different perspectives that males and females have towards e‐micromobility they can be made more inclusive for all. This can enhance their uptake and reduce the dependence on private vehicles.

Does ridesourcing respond to unplanned rail disruptions? A natural experiment analysis of mobility resilience and disparity

Urban rail transit networks provide critical access to opportunities and livelihood in many urban systems. Ensuring that these services are resilient (that is, exhibiting efficient responses to and recovery from disruptions) is a key economic and social priority. Increasingly, the ability of urban rail systems to cope with disruptions is a function of a complex patchwork of mobility options, wherein alternative modes can complement and fill occurring service gaps. This study analyzes the role of ridesourcing in providing adaptive mobility capacity that could be leveraged to fill no-notice gaps in rail transit services, addressing the question of distributional impacts of resilience. Using a natural experiment, we systematically identify 28 major transit disruptions over the period of one year in Chicago and match them, both temporally and spatially, with ridesourcing trip data. Using multilevel mixed modeling, we quantify variation in the adaptive use of on-demand mobility across the racially and economically diverse city of Chicago. Our findings show that the gap-filling potential of adaptive ridesourcing during rail transit disruptions is significantly influenced by the station-, community-, and district-level factors. Specifically, greater shifts to ridesourcing occur during weekdays, nonholidays, and more severe disruptions, in community areas that have higher percentages of white residents and transit commuters, and in the more affluent North district of the city. These findings suggest that while ridesourcing appears to provide adaptive capacity during rail disruptions, its benefits do not appear to be equitable for lower-income communities of color that already experience limited mobility options. Research implications for mobility operator collaborations to support mobility as a service are discussed. This study builds a more comprehensive understanding of transit service resilience, variation in vulnerability, and the complementarity of ridesourcing to existing transport networks during disruptions.

Study on the Location-Routing Problem in Network-Type Tractor-and-Trailer Transportation Mode

Under the trend of developing green transportation in China, tractor-and-trailer transportation has received more attention. This paper focuses on the network-type tractor-and-trailer transportation mode in the port hinterland, aiming to tackle the problems of low efficiency and customer satisfaction in the existing transportation network. The authors recommend considering opening several alternative depots and making vehicle scheduling decisions simultaneous in order to optimize the existing transportation network. Therefore, this paper constructs a bi-level programming model with a generalized total cost minimization as the objective function. The solution to the original problem is divided into two stages: the location-allocation problem and vehicle scheduling; a two-stage hybrid heuristic algorithm is designed to solve the problem. Through the continuous iteration of the upper genetic algorithm and the lower hybrid particle swarm algorithm, the overall optimization of the problem is achieved. Finally, a specific example verifies the model and the algorithm’s effectiveness. The results show that the method proposed in this paper can significantly improve customer satisfaction and reduce transportation costs to a certain extent. It can also provide effective theoretical decision support for logistics enterprises to carry out tractor-and-trailer transportation business and develop green transportation.

Designing a GIS‐based supply chain for producing carinata‐based sustainable aviation fuel in Georgia, USA

AbstractCarinata is a potential crop for sustainable aviation fuel (SAF) production in the southern USA. However, as a novel crop, the cost‐effectiveness and environmental feasibility of carinata feedstock are unknown, and there are questions about the optimal supply chain configuration for carinata‐based SAF production. This study aims to design a supply chain model for carinata‐based SAF production by optimizing the location of farms and facilities (e.g. storage units, crushing mills, biorefineries) for a minimum transportation cost under a set of supply and demand conditions. An integrated mixed‐integer linear programming (MILP) model was combined with geographical information system (GIS) analysis to design a spatially explicit supply chain configuration. The GIS‐based network analysis considered all of the counties in Georgia to set the candidate locations of carinata farms and facilities, and determined minimum cost and emission routes between those counties and the airport using existing transportation networks and modes (e.g. road, rail and pipeline). The MILP model determined the final selection of the farms and the number of facilities and their locations over those minimum‐cost routes. With this supply chain configuration, the minimum price of SAF was $0.92 L−1, which is $0.44 higher than conventional aviation fuel (CAF). The associated carbon intensity of SAF was estimated at 940.7 g CO2e L−1, a reduction of 66% relative to the carbon intensity of equivalent CAF. The study found that a carbon tax (or subsidy) of $230.48 t CO2e−1 would be needed to overcome the cost differential with CAF and promote carinata‐based SAF in Georgia.

Hybrid transportation system using trucks and drones

In recent years, the use of drones has gained significant attention as a potential solution for delivering goods and services in a variety of industries. Drones offer advantages over traditional delivery methods, including faster delivery times, increased efficiency, and reduced costs. However, their adoption has been limited by challenges related to their operation and regulation, as well as by the complexity of integrating them into existing transportation networks. To address some of these challenges, we present a novel approach to dispatching a hybrid truck and drone delivery system for serving a set of clients. Our proposal uses OR-Tools, an open-source optimization toolkit, for providing an initial truck tour, and a greedy heuristic method for introducing drone service into this route. We consider that at the starting point, the drone is on the truck. During the tour, the hybrid tandem of vehicles ensures that all the nodes of the initial tour are visited, either by the truck, or by the drone. When both vehicles arrive at final node, the time needed is computed. To evaluate the effectiveness of our proposal, we tested it on an instance of the Traveling Salesman Problem in Romania and compared our results with those based on the Concorde solver, a widely used exact algorithm for solving this problem. Our results demonstrate that our solution is stable, and performs well, indicating that our approach can be a useful tool for efficiently programming the service of hybrid delivery systems.

ROAD TRANSPORT AS A COMPONENT OF AGRICULTURAL CARGO TRANSPORTATION

The article reviews a vital role played by road transport in meeting the cargo transportation needs of the agricultural sector. It discusses and outlines the distinctive aspects of using road transport to address directly the industry's specific challenges. The role of road transport is to ensure the uninterrupted supply of goods directly from the supplier to the consumer. The article also discusses problematic areas in the field of road freight transport, the criteria for transported goods. The article delves into the specifics of transporting grain crops. It also highlights the use of mobile applications, facilitating enhanced communication among agricultural producers, suppliers, and consumers. This contributes to the enhancement of agricultural logistics, reducing the costs and increasing productivity of agricultural output. In light of the foregoing, the research findings can be described as a reflection of the crucial role of road transportation in agriculture. It became evident that, in order to establish and develop a high-quality modern transportation and logistics system, it is vital to monitor and enhance the efficiency of existing transportation networks and improve the management of road transport utilization, which serves as a pivotal component in agricultural freight operations.

ANALYSIS OF THE STATE OF PUBLIC TRANSPORT IN ALMATY

Public transport today is again gaining relevance as a means of transportation in connection with the personal cars that have flooded urban spaces. The city of Almaty is no exception and since the beginning of the last decade has taken a course to organize pilot projects to create a priority for the movement of public transport. The difficulty of implementing such innovations is the public, accustomed to crossing long distances by private vehicles, and in most cases city streets are loaded from nearby agglomerations. The emergence of such a trend is directly related to the expansion of the city in breadth, i.e. from east to west, because the natural uniqueness of the urban area in the south is limited by the mountain ranges of the Trans-Ili Alatau. This paper is presented taking into account the existing initial data for the study of public transport issues through the introduction of the GTFS scientific methodology, which can give a new angle of view on the current situation with the organization of bus and trolleybus routes. This paper focuses on studying the potential of public transport in Almaty for consistent growth, because with the help of the restructuring of route networks and the creation of a priority traffic network, there is a chance to achieve an increase in capacity and an increase in the number of users. The aim of this article is to provide information about the current state of the public transport network and to discuss the potential of geographic information systems (GIS) within the urban space, which are guided by spatial analysis approaches related to the processing of General Transit Feed Specification data (GTFS), since statistical data are based on providing a complete picture of the existing transport network, and afterwards can become the basis for subsequent optimization of public transport traffic. This paper creates new perspectives for future development of public transport and restructuring of the understanding how to create public network according to necessity in Almaty city.

Comprehensive analysis of the state of the transport infrastructure of the Republic of Kazakhstan

In the modern world, the importance of the transport industry in the economy of each state is increasing. Transport is an important sector of the domestic economy of Kazakhstan, which occupies a significant share in the structure of GDP. The significant territory of the republic and the low population density, the high rate of economic development of Kazakhstan achieved in recent years, form the growing demand for transportation. The state of the transport complex in Kazakhstan is in the zone of special attention of domestic and foreign experts, they have identified its main disadvantages. The article discusses the rationale for the role of transport infrastructure in the development of the territories of the Republic of Kazakhstan and the ways of its development. The study used such research methods as generalization, comparison, systematization and statistical analysis.Within the framework of the work, the role and importance of transport infrastructure were determined, the impact of transport infrastructure development on the country's economy was considered, transit opportunities in the republic were considered, the advantages and disadvantages of Kazakhstan's transport infrastructure were analyzed, transport infrastructure issues and ways to solve it were considered. The issues related to the quality of road repairs and vehicle upgrades in the republic are identified by providing the transport complex with qualified personnel and scientific institutions of the transport profile. As a result of the conducted research, it was proposed to develop international cooperation in the field of transport, that is, to introduce new equipment and technologies, international experience into the country, as well as to attract public and private investments for the implementation of projects provided for by state programs aimed at the development and improvement of infrastructure, construction of new transport facilities and repair of existing transport networks. The results of the research contribute to the development of the theory of transport infrastructure and can be used to prepare lectures on relevant disciplines, as well as serve as a basis for in-depth research.

Modeling Autonomous Vehicles Deployment in a Multilane AV Zone With Mixed Traffic

The advancement of technologies has fast-tracked the deployment of autonomous vehicles (AVs), however, they necessitate the modernization of the existing road infrastructure to meet the technical and safety requirements of AVs. Due to the high cost and prolonged time required for upgrading infrastructure, it is expected that AVs will be introduced gradually into the existing transport network of human-driven vehicles (HVs) either jointly or separately in a special area or zone within that network. In this paper, we propose a mathematical framework for modelling and deployment of multi-lane AV zone in a mixed-user traffic network that takes into account the different route choice decisions of HVs and AVs. The model is used to study two different designs for a multi-lane AV zone, where in Design 1, both lanes are dedicated for AVs inside the AV zone; while in Design 2, one lane is dedicated for AVs, and another lane is for the HV traffic. We then derive an equivalent convex formulation and develop a novel solution method for this complex problem, as well as evaluate and compare the performance of the designs in a realistic large-scale transportation network. Numerical results show that the deployment of a multi-lane AV zone improves network performance in terms of the total system travel time (TSTT). The proposed framework can be used to assist transportation planners and decision-makers to successfully deploy AVs seamlessly with mixed traffic.

A novel rough numbers based extended MACBETH method for the prioritization of the connected autonomous vehicles in real-time traffic management

Digital transformation can help to make better use of existing transportation networks that are congested. One solution to the road congestion problem is real-time traffic management, which focuses on enhancing traffic flow conditions. The advantages of real-time traffic management systems have developed significantly as a result of connected autonomous vehicle (CAV) innovations. CAVs can act as enforcers for managing the traffic. This study aims to propose a novel rough numbers-based extended Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method for prioritizing real-time traffic management systems. Furthermore, a new approach for defining rough numbers is proposed, based on an improved methodology for defining rough numbers' lower and upper limits. This allows consideration of mutual relations between a set of objects and flexible representation of rough boundary interval depending on the dynamic environmental conditions. In this study, three main alternatives are defined for real-time traffic management systems: real-time traffic management, real-time traffic management integrated with CAVs, and real-time traffic management by using CAVs. For these alternatives, 5 main criteria and 18 sub-criteria are defined and then prioritized using the fuzzy multi-criteria decision-making (MCDM) approach. The proposed method's performance is validated through scenario analysis. The findings demonstrate that the proposed method is effective and applicable to real-world conditions. According to the study's findings, real-time traffic management with CAVs is the most advantageous alternative, while real-time traffic management integrated with CAVs is the least advantageous

Estimating wider economic impacts of transport infrastructure Investment: Evidence from accessibility disparity in Hong Kong

Much recent work on transport and the economy has focused on ‘Wider Economic Impacts’ (WEIs) of infrastructure investment, the impacts other than time savings benefiting those actually using the transport network. Differential effects of transportation infrastructure by mode such as urban rail and road are relatively well known. However, impacts of other mode such as walking are scarce. This paper estimates wider economic impacts related to productivity from full rail, road and walking transport networks in Hong Kong in 2016. To the best of our knowledge, this is the first paper that makes use of complex network science indicators with spatial cognition-weighted accessibility combining full urban rail network, road network, and pedestrian network in capturing wider economic impacts. We use an instrumental variable approach to identify the causal effect of transport network centralities on productivity measured by gross value added. Our identification strategy largely relies on the exogenous variations from historical planned and existing transport networks. A first specification confirms the significance of urban rail and road. Specification with pedestrian network shows that pedestrian and rail networks can statistically significantly increase productivity in Hong Kong while roads play a less significant but still meaningful role. Our findings are robust to a variety of sensitivity tests such as using night-time light intensity and residential wage as alternative measures for productivity. The research suggests a key planning policy implication: place-based policies in a dense city require improvement in pedestrian and rail network structure that impacts local and global transport accessibility.