Sustainable Development Of Urban Transport Research Articles

Understanding the potential of taxi sharing: The case of Chengdu

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

The operation mechanism of integrating urban and rural passenger transportation and logistics under the strategy of rural revitalization–Case study of Lianhua County, China

To alleviate the pressure of government financial subsidies for urban and rural public transport, this paper analyzes the intrinsic relationship between China's rural revitalization strategy and the integrated development of urban and rural public transport, and proposes an integrated development model of public transport and logistics based on urban and rural public transport. Taking Lianhua County, China, as an example, this paper investigates the operational mechanism and pilot effects of the bus-logistics integration model, and proposes strategies to promote the development of bus-logistics integration. The results of the case study show that the urban–rural bus integration model based on the integration of public transportation and logistics can reduce the deficit of urban–rural bus enterprises by 35.8% compared with the traditional urban–rural bus integration model, which can effectively alleviate the pressure of government financial subsidies. The research results have practical significance for promoting rural revitalization in Lianhua County and alleviating government financial pressure, and also have a certain reference role for the sustainable development of urban and rural public transportation in other small and medium-sized cities.

The nonlinear impact of cycling environment on bicycle distance: A perspective combining objective and perceptual dimensions

Extending cycling distances is crucial for sustainable urban transport development and plays a role in encouraging the shift from motorized vehicles to public transport. However, there is a lack of research examining the combined impacts of both objective and perceived aspects of the cycling environment on cycling distance, and the existence of threshold effects remains unclear. This study uses 2019 cycling data from Shenzhen, China, employing the XGBoost algorithm to uncover the relative importance and thresholds of objective and perceived factors in the cycling environment. The results indicate that population density (24.8%), road network density (15.2%), the proportion of recreational facilities (9.1%), perceived accessibility (8.0%), and comfort (8.6%) hold high relative importance in predicting cycling distance. Also, maintaining road network density between 3 to 6 km/km2 and increasing the population density to exceed 22,000 people/km2 proves effective in extending cycling distances. Land use demonstrates a threshold effect, with cycling distances increasing when the recreational facilities share exceeds 8%, transport facilities share remains below 25%, and commercial facilities share stays below 30%. Perceived metrics exhibit a clear threshold effect. The study identifies that perceived safety indicates a psychological bottleneck in increasing cycling distance. Perceived accessibility is positively correlated with cycling distance when accessibility is at a low level, while comfort shows a positive correlation with cycling distance when comfort is at a high level. These findings can contribute to refining land planning and prioritizing resource allocation for organizations aiming to promote non-motorized travel and design bicycle-friendly environments.

A Quantitative Study on Factors Influencing User Satisfaction of Micro-Mobility in China in the Post-Sharing Era

In the post-sharing era, the evolution of the shared micro-mobility industry has transitioned from expanding market share to providing precise services. The focus on user satisfaction has shifted from a singular emphasis on functional utility to diversified product values. Product perceived value has emerged as a comprehensive factor for enhancing user satisfaction, aiding companies in formulating precise services, mitigating urban resource wastage, and promoting sustainable urban development. From the perspective of product perceived value, this study combined the analysis of factors affecting user satisfaction of shared micro-mobility and the interaction between these aspects and carried out the following two studies. Research No. 1: By mining the user review data on app platforms related to shared micro-mobility and adopting the latent dirichlet allocation (LDA) algorithm, we have initially identified 17 major factors affecting the satisfaction of users and summarized these factors into four research topics constituting product perceived value. Research No. 2: On the basis of Research No. 1, the content of the American Customer Satisfaction Index (ACSI) was expanded, and a user satisfaction research model focusing on the perceived value of shared micro-mobility products was constructed. Afterwards, by using the data collected in questionnaire surveys, structural equation modeling (SEM) was used to model the user satisfaction of shared micro-mobility through SEM, which was deployed to establish an empirical analysis. It is found that (1) both user expectation and product quality can positively affect the perceived value of products through interactive experience; (2) factors such as user expectation, product quality, interactive experience, and subjective consciousness can positively affect user satisfaction through the perceived value of products, with user expectation delivering the greatest influence; and (3) subjective consciousness has a direct positive effect on users’ willingness to continuously use a product but no significant effect on user satisfaction. These findings expand the user satisfaction theoretical model in the field of shared micro-mobility, constitute suggestions for product development and service promotion in the shared micro-mobility industry, and can provide new ideas and methods for the sustainable development of urban transportation.

Mining smart card data to estimate transfer passenger flow in a metro network

AbstractMetro systems play an important role in reducing urban traffic congestion and promoting the sustainable development of urban transport in megacities. With the expansion of a metro network, transfer stations are necessary for increasing the service connectivity of a metro network. An accurate estimation of transfer passenger flow can help improve the operations management of a metro system. This study proposes a data‐driven methodology for estimating the transfer passenger flow volume of each transfer station in a metro network by mining smart card data. The estimated transfer passenger flow data are visualized to show the spatial‐temporal distribution characteristics of metro transfer passenger flow. The case study results of the Shenzhen Metro network demonstrate that the proposed data‐driven methodological framework is very effective in estimating different types of transfer passenger flows, such as total transfer passenger flow, hourly transfer passenger flow, and inbound and outbound transfer flows at each transfer station. The spatial‐temporal distribution characteristics of transfer passenger flow can be very useful for designing effective and efficient passenger flow management measures to ensure the safe and efficient operation of a metro system.

Sustainable Development of Urban Mobility through Active Travel and Public Transport

A sustainable development of urban transportation relies on our ability to offer citizens reliant and attractive alternatives to car travel, such as efficient and appealing public transport (PT) services, alongside an urban environment that is stimulating for active travel alternatives, such as walking and cycling [...]

СТРАТЕГИИ УСТОЙЧИВОГО РАЗВИТИЯ ГОРОДСКИХ ГРУЗОВЫХ ПЕРЕВОЗОК

The article examines strategies for the sustainable development of urban freight transport. Op-tions for urban freight and company actions that can be part of a sustainability strategy are out-lined, as well as non-freight policies that may have unintended consequences for the sustainabil-ity of urban freight. An analysis of the challenges that arise when trying to implement approach-es to increasing the sustainability of urban freight transport is providedm

Analyzing multi-factor effects on travel well-being, including non-linear relationship and interaction

ABSTRACT Enhancing the travel well-being of commuters is crucial for the sustainable development of urban transportation and requires a clear understanding of the factors. However, existing research on the factors affecting travel well-being has not considered travel disturbance. This research adds travel disturbance and effort to a survey in Ningbo, China. Using this dataset, machine learning algorithms were employed to explore the complex relationship of seven variables on commuters’ travel well-being. The results demonstrated machine learning algorithms such as Gradient Boosting Decision Tree and Random Forest outperform traditional linear regressions in analyzing travel well-being. The study identified built environment (Relative Importance = 24.6%) and affective effort (Relative Importance = 17.2%) were key determinants of travel well-being. Non-linear relationship between key variables and travel well-being was also investigated, and revealing a complex interaction between these variables. This research could help transportation managers provide more targeted and efficient suggestions to increase urban commuters’ travel well-being.

Autonomous vehicle market development in Beijing: A system dynamics approach

A system dynamics (SD) model for the autonomous vehicles (AVs) market development in Beijing is proposed. The model approaches the vehicle scale evolution with the marketization development of private AVs and shared AVs. Some potential factors such as trust, AV purchase willingness, AV using willingness and shared AV service accessibility, are analyzed. Based on the passenger vehicle situation in Beijing, optimistic scenarios from 2014 to 2050 are developed. The base scenario involves the marketization of private AVs and the operation of shared AV fleets, and based on the levels of driving automation, which are divided into six types. The causal feedback relationship and system flow diagram are illustrated. Results show that with the introduction of AVs in Beijing, the number of private vehicles is significantly decreased, which is dependent on the use of shared AVs. To compare with the private vehicle ownership in 2020, the total number of private vehicles has decreased and the number of the private vehicles is over 2.2 million vehicles in 2050. After 2030, the shared vehicle fleet will be dominated by the high-level shared AV and the number of high-level shared AVs is about 2 million. Further, to consider the impact of ride-sharing, the model compares the different attitudes for customers to share their rides and use the shared AV alternative ratio to approach this. The result shows that the extreme ratio will reduce the number of shared AVs, and the fleet size of shared vehicle is about 400,000 vehicles in 2050. For the low ratio scenario, the fleet size of shared vehicle will increase a lot to over 3,186,000 vehicles, which will lead to a large number of cars on the road and thus increase congestion. The introduction of AVs is expected to reduce the number of private vehicles; However, the uncertainty of residents' attitudes towards car sharing will affect the introduction of AVs. At present, the existing policies prefer to limit the number of vehicles by controlling car registration in Beijing. In the future, with the application of AVs, this could be adjusted by encouraging ride sharing, to achieve sustainable urban transport development in Beijing.

Multiobjective-Based Decision-Making for the Optimization of an Urban Passenger Traffic System Structure

Urbanization has aggravated the conflict between continuously increasing urban travel demands and limited supply. Moreover, the inability to expand urban roads due to previous land planning and utilization has resulted in significant traffic congestion, traffic safety issues, and environmental problems. To address these problems, this work attempted to develop a multiobjective model to optimize the passenger traffic system while considering carbon emissions, transport costs, and resource utilization. In addition, the ideal point method and entropy weight method were combined to obtain the optimal solution. Based on the operational data on traffic modes and travel data on passengers in Harbin, the northern capital of China, the proposed method was used to solve the case in Harbin. The results show that the proportion of buses increased by 1.05%, that of subways increased by 36.60%, that of taxis decreased by 11.86%, and that of private cars decreased by 25.78% after optimization. Furthermore, the analyses of the results show that the optimized passenger traffic system structure can promote the sustainable development of urban transport and demonstrate the practicality of the proposed method for solving multiobjective optimization problems. Relative to the ideal point method and genetic algorithm, the proposed method is more applicable for optimizing the passenger traffic structure in Harbin. In addition, this study explored the sensitivity of the optimization goals to the four motorized modes. The results show that subways and private cars are the key areas to prioritize in adjusting the urban passenger traffic system structure. Based on the analysis results, recommendations for the development of transportation in Harbin are given. This study provides a reference for decision-makers to formulate policies for the urban sustainable development of Harbin as well as for transportation development in other cities.

Evaluation of urban public transport sustainability in China based on the Driving Force-Pressure-State-Impact-Response (DPSIR) framework——A case study of 36 major cities

With urbanization and motorization, the sustainable development of urban transport has drawn extensive attention worldwide. As one of the key components of the transport system, urban public transport is the breakthrough. This study focused on the characteristics of public transport, analyzed the causal and restrictive relationships between anthropogenic activities and urban public transport sustainability based on the Driving Force-Pressure-State-Impact-Response (DPSIR) framework, and decomposed the interaction to establish an evaluation index system. An improved set pair analysis-variable fuzzy set model (ISPA-VFSM) was constructed to evaluate urban public transport sustainability in China's 36 major cities in 2020 and analyze the critical influence factors and restriction modes according to the contribution degree and obstacle degree. The results show that: (1) The sustainable development of urban public transport is a systematic process, and public transport sustainability in 36 major cities shows the spatial distribution characteristics of “high in the southeast and low in the west;” Most megacities are at the forefront, benefiting from outstanding state and response levels, with Shenzhen ranking first; while the megapolises generally display moderate sustainability. Cities in Northeast and Northwest China present lower levels of sustainability. (2) Public transport sustainability in China is deficient, exhibiting a certain gap from the target. The levels of the driving force, pressure, state, impact, and response of public transport sustainability in 36 major cities are unbalanced; (3) The restriction mode of urban public transport sustainability in 36 major cities can be roughly divided into three categories: pressure-impact restriction mode, driving force-impact restriction mode, and state-response restriction mode; (4) State and response play a crucial role in achieving public transport sustainability. Public transport infrastructure, electrification substitution, and efficiency of public transport operations are the primary contributing factors to public transport sustainability. This study enriches the indicators and methods for sustainability evaluation and provides a reference for urban public transport sustainable development.

Evaluation of Bus Lane Layouts Based on a Bi-Level Programming Model—Using Part of the Qingshan Lake District of Nanchang City, China, as an Example

Bus lanes have gradually become an indispensable infrastructure for the development of urban public transportation networks. A bi-level programming model is used herein to compare the total travel time of social vehicles and buses before and after the bus lane is set up to judge whether the bus lane layout plan is scientific and reasonable considering the road network. The model’s effectiveness is verified using areas of Qingshan Lake in Nanchang City, and the operational efficiency of one bus lane before and after establishing the dedicated bus lane is analyzed. The case results show that the bus lane layout evaluation needs to consider the traffic benefits of a specific road and also judge whether the total travel time of the network traffic volume is improved from the macroscopic road network level. The research results provide theoretical support for the rational layout of bus lanes and are of practical significance for prioritizing the development of public transportation and promoting the sustainable development of urban transportation.

Exploring the Relationship between Urban Form, Mobility and Social Well-Being: Towards an Interdisciplinary Field of Sustainable Urban Planning and Transport Development

This Special Issue focuses on exploring the relationship between urban form, mobility, and social well-being across neighbourhoods, cities, and regions [...]

Exploring Public Transportation Supply–Demand Structure of Beijing from the Perspective of Spatial Interaction Network

A comprehensive understanding of the relationship between public transportation supply and demand is crucial for the construction and sustainable development of urban transportation. Due to the spatial and networked nature of public transportation, revealing the spatial configuration and structural disparities between public transportation supply and demand networks (TSN and TDN) can provide significant insights into complex urban systems. In this study, we explored the spatial configuration and structural disparities between TSN and TDN in the complex urban environment of Beijing. By constructing subdistrict-scale TSN and TDN using urban public transportation operation data and mobile phone data, we analyzed the spatial characteristics and structural disparities of these networks from various dimensions, including global indicators, three centralities, and community structure, and measured the current public transportation supply and demand matching pattern in Beijing. Our findings revealed strong structural and geographic heterogeneities of TSN and TDN, with significant traffic supply–demand mismatch being observed in urban areas within the Sixth Ring Road. Moreover, based on the percentage results of supply–demand matching patterns, we identified that the current public transportation supply–demand balance in Beijing is approximately 64%, with around 18% of both excess and shortage of traffic supply. These results provide valuable insights into the structure and functioning of public transportation supply–demand networks for policymakers and urban planners; these can be used to facilitate the development of a sustainable urban transportation system.

Identification and Spatiotemporal Analysis of Bikesharing-Metro Integration Cycling

An essential function of dockless bikesharing (DBs) is to serve as a feeder mode to the metro. Optimizing the integration between DBs and the metro is of great significance for improving metro travel efficiency. However, the research on DBs–Metro Integration Cycling (DBsMIC) faces challenges such as insufficient methods for identification and low identification accuracy. In this study, we improve the enhanced two-step floating catchment area and incorporate Bayes’ rule to propose a method to identify DBsMIC by considering the parameters of time, distance, environmental competition ratio, and POI service power index. Furthermore, an empirical study is conducted in Shenzhen to verify the higher accuracy of the proposed method. Their spatiotemporal behavior pattern is also explored with the help of the kernel density estimation method. The research results will help managers improve the effective redistribution of bicycles, promote the coupling efficiency between transportation modes, and achieve sustainable development of urban transportation.

Passenger Satisfaction Evaluation and Achieving Sustainable Integrated Urban Transport: Structural Equation Analysis Based on Macau Data

The sustainable development of urban transport is the key to sustainable urban development. This study analyses and identifies the evaluation indicators affecting Macau’s transport, and analyses the relationship between the relevant evaluation indicators and passenger satisfaction, thus contributing to the improvement and the sustainable development of Macau’s public transport services. This study uses a questionnaire to collect data. Based on the current situation of Macau’s social groups, the mainland students in Macau who were selected as the target group are significantly different from residents and tourists in Macau; their needs and perceptions of public transport are more intense. This group’s needs and perceptions of public transport are significantly different from those of residents and tourists. The set indicators of satisfaction with public transport in Macau reflect them. After analyzing and determining the evaluation indicators, structural equation modeling was applied to establish the structural models of Macau’s three public transport services. Finally, the shortcomings of the three public transport services were reflected through the standardized coefficient weights and passenger satisfaction. The study results show that the seating arrangement and smoothness of travel of Macau’s public transport services need to be improved, and the dial-a-ride service’s price setting and waiting time need to be improved. The price setting, convenience of hailing, and payment method of the taxi service need to be improved. In contrast, overall, the satisfaction level of the dial-a-ride service is significantly higher than that of the taxi service. Therefore, the findings of the study have important policy implications for relevant policymakers, who should not only focus on optimizing daily operations but, more importantly, on improving the shortcomings mentioned above, which are of great value in enhancing the passengers’ perception of public transport in Macau and are also crucial to achieving the sustainable development of public transport in Macau.

Simulation Study on the Coupling Relationship between Traffic Network Model and Traffic Mobility under the Background of Autonomous Driving

Autonomous driving technology will bring revolutionary changes to the development of future cities and transportation. In order to study the impact of autonomous driving on urban transportation networks, this paper first summarizes the development status of autonomous driving technology, and then three space–traffic network coupling models are proposed based on the differences of speed and space, which are the traditional difference type, scale variation type, and slow-guided type. On this basis, a new 4 * 4 km grid city model is constructed. Based on the MATSim multi-agent simulation method, the traffic parameters of the three models are studied. The results show that under the same traffic demand, the service scale and level of the three traffic networks are significantly different. The optimal service level of the traditional differential type is 2.15 times the efficiency of the slow-guided type. Under the same demand and road network mode, the travel speed of the autonomous driving mode is 1.7–2.8 times that of the traditional mode. Under the same lane area ratio, the travel speed of traditional driving is much smaller than that of autonomous driving, which is about 2.6–3.6 times greater than the former. The research conclusion has certain reference significance for formulating urban spatial development strategies and policies under autonomous driving environments and for promoting the sustainable development of urban transportation.

Reasons of university students' susceptibility to intelligent mobility and the use of mobility-as-a-service schemes

The transition from the current transportation system to intelligent mobility and the MaaS concept, through the introduction of Big Data analytics and digital innovation, is underway. Perceptions, attitudes and other internal factors often have a significant impact on the choice of human behavior in transportation. This paper discussed the characteristics of vehicle choice by type and depending on the goal of the trip. Private car drivers noted that they choose a car mainly because of accessibility, flexibility of use, safety and comfort. For public transportation passengers, safety and cost of travel were determining factors in their choice of public transportation. The main differences between trips with different goals were found for the indicators "time of a trip", "company trip", and "prestige". The results show that there is a positive perception of intellectual mobility among student youth, a tendency to switch from owning vehicles to other ways of using them and participating in MaaS schemes. It can be concluded that MaaS is positively perceived by the young generation of students. Based on the data obtained, proposals for the directions of sustainable development of urban public transport are made.

Evaluation of EV penetration level limit in distribution system applying charging and scheduling strategies

Traveling by electric vehicles (EVs) instead of conventional fuel cars is strongly supported by a lot of governments for the sustainable development of urban transportation. However, EVs increase the load in the distribution system which impacts the voltage stability in the distribution network. In this paper, a method for evaluation the largest EV number to be accommodated in the distribution system is proposed. First of all, a Monte Carlo charging model for electric vehicles is established. Then the EV charging schedule is determined with the TOU electricity price and the dispatch method to suppress the maximum peak load is presented. Ultimately, Considering the temporal and spatial features of EV charging, the maximum vehicle access capacity of the distribution network is calculated by the continuous power flow method. The developed method was tested in the PG&E 69-bus distribution system, and the results show that the EV penetration level evaluation method proposed is an efficient tool for the distribution system planning, as well as the voltage stability analysis with the fast increasing EVs in the distribution system.

Dynamic Path Planning Based on Service Level of Road Network

Vehicle–road coordination is an important application scenario in the sustainable development of urban transportation. In this scenario, by navigating the vehicles in the road network, the vehicles can run more smoothly in the city, reduce unnecessary detours and parking, and realize energy savings and emission reductions. Although vehicle–road coordination in a large area has not been fully realized, people’s travel is increasingly dependent on navigation. If the trips of most vehicles follow the same navigation suggestion in a short period of time, some sections in the given route of the navigation will bear excessive traffic load. In order to solve this potential problem, this paper relies on the vehicle–road collaboration scenario and combines the service level of the road network factors between vehicles to plan the travel path of the vehicle. This keeps the traffic load of each road section in the path at a reasonable level. Within the scope, considering the overall utilization of road resources and the efficiency of road network traffic, we established the road network evaluation index through the simulation comparison with the Dijkstra algorithm. Under the path planning method proposed in this paper, the total travel time of the vehicle is reduced by 23.4%, and the road network operation efficiency is improved by 6.6%, which proves that the method can be used. This method can effectively alleviate the load of the road network, improve operation efficiency, and finally achieve the purpose of energy saving and emission reduction.