Sustainable Urban Transport Research Articles

Reasonable Planning of King County's E-bus Replacement Plan

With the increasingly intensified global warming severe air pollutions, governments all over the world have begun or is right now looking for ways to fix the problem. Among all the solutions, sustainable urban transportation system is what many governments pay attention to because of their apparent contribution to the reduction in greenhouse gases emissions and pollutants. In this passage, we focus on the exact ecology impacts the promotion of e-buses will cause. On the other hand, the potential financial burdens the transitioning processes will bring are perceived by us in order to make a decent plan for the government to implement.For the first part of constructing the model to measure the ecology impact of transition in one area, we start with the identification of King County as a metropolitan area suitable for prediction. Then we collect information and data of its local bus fleet and e-bus transitioning plan, find out the exact number of each type of buses (diesel, hybrid and electric) around these years and the emissions of corresponding buses. We use both ARIMA and Least Squares Regression to predict the number these buses in the future until the year the local government aim to complete the plan but choose the result displayed by the better one. In this case, we obtain the data for emission of carbon dioxide, oxynitride and PM10 in each year and evaluate the ecological impact. At the same time, we predict the data for the emissions later if the bus fleet keep the same and observed over 90% of decline when we compare the value after transition to the control group.Afterwards, to estimate the financial cost, we identify the main parts involved in the processes of transitioning, classify them with one group of cost for long-term and the other for short-term---that is, changed as the plan is gradually implemented. We build models for each factor we identified and use Riemann Sum to unify the long-term and short-term costs. Based on the data we predict in problem one and from the local government’s website, we easily gain the financial implications of for about 50 million dollars in King County. Through the analysis of the government’s grant in other area, we roughly verify that 50 million dollars would be an acceptable cost.Finally, in our 10-year roadmap development, we explored further into the population distribution of King County and the existing traits for public transportation. Our starting point in this article is to classify the urban pattern into four types of bus operation routes, and then define the passenger flow from high to low. At the same time, we define the total number of vehicles that need to be replaced for different types to develop transportation replacement plans. Based on our assumptions, calculate the carrying capacity of each type of bus in line with the passenger flow. Eventually, it can be proven that the total carrying capacity of the bus meets the transportation needs of all King counties. Then apply to other regions.

Social Aspects of Smart Urban Mobility

There is a growing interest in sustainable urban transport solutions in cities around the world. These changes, known as “smart urban mobility”, aim to reduce the negative effects of transport on the natural environment and enhance the standard of living for urban dwellers. It should be noted that in addition to this transformation’s technological aspects, modifying the city’s structure and architecture also has a social dimension. The transformation of urban mobility has a significant impact on social relations. Introducing new modes of transport, such as city bikes and electric scooters, creates new ways of moving around the city and can impact social interactions. This can increase social integration and a community’s sense of belonging. At the same time, it is necessary to consider the differences between social groups to ensure equal access to the benefits of these changes in addition to deeper social elements, such as changing the habits and expectations of residents and adapting solutions to the specific needs of each city. This paper aims to look at the social aspects of smart urban mobility, including the impact of these changes on the lives and relationships of city residents.

Exploring Sustainable Urban Transportation: Insights from Shared Mobility Services and Their Environmental Impact

The transportation landscape is witnessing profound changes due to technological advancements, necessitating proactive policy responses to harness innovation and avert urban mobility disruption. The sharing economy has already transformed ridesharing, bicycle-sharing, and electric scooters, with shared autonomous vehicles (SAVs) poised to reshape car ownership. This study pursues two objectives: firstly, to establish a market segmentation for shared ride services and secondly, to evaluate the environmental impact of ridesharing in different contexts. To mitigate potential biases linked to stated preference data, we analysed the navette service, utilized by a research institute in Europe, closely resembling future SAVs. The market segmentation relied on hierarchical cluster analysis using employee survey responses, while the environmental analysis was grounded in the 2019 navette service data. Our analysis revealed four unique employee clusters: Cluster 1, emphasizing active transportation and environmental awareness; Cluster 2, showing openness towards SAVs given reliable alternatives are available; Cluster 3, the largest segment, highlighting a demand for policy support and superior service quality; and Cluster 4, which places a premium on time, suggesting a potential need for strategies to make the service more efficient and, consequently, discourage private car use. These findings highlight a general willingness to adopt shared transport modes, signalling a promising transition to shared vehicle ownership with significant environmental benefits achievable through service design and policy measures.

Joint optimization of the inventory routing problem considering the recycling of broken bikes in the bike-sharing system

Bike-sharing system has become an indispensable element of sustainable urban transportation, effectively resolving the "last mile" transportation challenge for city dwellers. A major daily operational task in these systems is planning a fleet to rebalance the bikes over time, ensuring the optimal availability of bikes and docks to users. Recycling is also a daily work with the an increase in the number of broken bikes. However, rebalancing or recycling operation is always regarded as an independent tasks. They are separately studied in existing papers. Thus, this paper develops an operational strategy for recycling broken bikes during the rebalancing process, and studies the combination of the station inventory and vehicle routing problems. First, an inventory routing model is constructed with the aim of minimizing the total costs including procurement, expected user loss, inventory and transportation costs. Then, a two-stage iterative algorithm is developed with both exact and heuristic algorithms. We use real-world data from Capital Bikeshare to test our proposed model and approach, which shows the two-stage iterative algorithm is efficient and outperforms existing solutions in reducing total costs. Finally, the sensitivity analysis is performed on key parameters such as the vehicle’s capacity, unit penalty costs for customer dissatisfaction events, unit inventory holding costs and the observation period of rebalancing. It shows that enterprises can reduce the total cost by altering vehicle’s capacity, reducing the unit inventory holding costs or changing the observation period of rebalancing.

Research and Analysis on Policy Governance Based on Traffic Congestion in Beijing

This paper proposes three-game models to improve Beijing's traffic environment through the analysis method of game theory. First, the author examines the impact of improving drivers' moral character on alleviating traffic congestion. Second, this paper focus on the role of improving the public transportation environment in reducing road stress. Finally, this research examines the possibility of mitigating traffic congestion through a reward-punishment system. Comprehensive analysis of the results of these three game models, this paper conclude that a single policy of license restriction and traffic restriction is not enough to solve the traffic congestion problem in Beijing, and multiple policy measures need to be considered comprehensively. However, these policy measures also face some challenges and limitations, including time and education investment, people's travel needs and transportation network layout, and the design and implementation of the reward and punishment system. Therefore, future research and policy development need to further explore these issues and find more comprehensive and feasible policy solutions. Finally, this article recommends that the Beijing Municipal Government comprehensively consider the results of different game models and formulate comprehensive policy measures based on the actual situation, including improving road transportation facilities, encouraging green travel methods, and promoting intelligent transportation systems. Through these efforts, it is expected to improve Beijing's traffic environment, enhance citizens' travel experience, and achieve the goal of sustainable urban transportation.

Modeling an Investment Framework for BMTA Electric Bus Fleet Development

In Thailand, diesel buses are notorious for their poor energy efficiency and contribution to air pollution. To combat these issues, battery electric buses (BEBs) have emerged as a promising alternative. However, their high initial costs have posed challenges for fleet management, especially for agencies such as the Bangkok Mass Transit Authority (BMTA). This study aims to revolutionize BEB fleet management by developing an energy model tailored to the BMTA’s needs. The methodology consists of two crucial steps: analyzing BMTA bus routes and designing fleet management and charging systems. Through this process, the study seeks to determine the maximum number of BEBs that can be operated on each route with the fewest chargers possible. The results reveal exciting possibilities. Within the city bus landscape, two out of five BMTA bus routes show potential for transitioning to BEBs, provided they meet a maximum energy requirement of 200 kWh every two rounds. This analysis identifies routes ripe for BEB adoption while considering the limitations of battery size. In the next step, the study unveils a game-changing strategy: a maximum of 13 BEBs can operate on two routes with just four chargers requiring 150 kW each. This means fewer chargers and more efficient operations. Plus, the charging profile peaks at 600 kW from 4:00 to 8:00 p.m., showing when and where the fleet needs power the most. However, the real eye-opener? Significant energy savings of THB 10.44 million per year compared to diesel buses, with an initial investment cost savings of over 37%. These findings underscore the potential for BEB fleet management to revolutionize public transportation and save money in the long run. However, there is more work to be done. The study highlights the need for real-time passenger considerations, the development of post-service charging strategies, and a deeper dive into total lifetime costs. These areas of improvement promise even greater strides in the future of sustainable urban transportation.

Bus Drivers’ Behavioral Intention to Comply with Real-Time Control Instructions: An Empirical Study from China

Developing intelligent bus control systems is crucial for fostering the sustainability of urban transportation. Control instructions are produced in real time by the bus control system; these are important technical commands to stabilize the order in which buses operate and improve service reliability. Understanding the behavioral intention of bus drivers to comply with these instructions will help improve the effectiveness of intelligent bus control system implementation. We have developed a psychological model that incorporates decomposed variables of the theory of planned behavior (TPB) and other influencing variables to explain the micromechanisms that determine bus drivers’ behavioral intention to comply with real-time control instructions during both peak and off-peak-hour scenarios. A total of 258 responses were obtained and verified for analysis. The results showed that the influential factors in the peak- and off-peak-hour scenarios were not identical. Female drivers had greater off-peak-hour behavior intention to comply than male drivers, and there were significant differences in peak-hour behavior intention among drivers of different ages. In both peak and off-peak-hour scenarios, perceived benefit positively and perceived risk negatively affected behavioral intention. Perceived controllability positively affected behavioral intention only during peak hours. Self-efficacy only negatively affected behavioral intention during off-peak hours. Three antecedent variables (i.e., trust, mental workload, and line infrastructure support) influenced drivers’ behavioral intentions indirectly via the decomposed variables of TPB. These results provide profound insights for the improvement and implementation of real-time control technology for bus services, thereby facilitating the development of smart and sustainable urban public transport systems.

Assessment of passenger safety risk level on the Transjakarta public transportation system

Passenger safety is a crucial factor in public transportation, especially now when people prefer using public transport due to its cost-effectiveness compared to private vehicles. This study aims to identify and assess the hazards that can occur in the passenger cabin of a bus and the procedures to be followed in the event of an accident. The assessment of passenger safety levels is conducted using the Hazard and Operability (HAZOP) and Hazard Identification (HIRADC) methods, which are designed to identify and evaluate these potential hazards. This research, after thorough examination and study, aims to establish new protocols that can further enhance passenger safety. With the actions suggested by the author to ward off all these potential hazards, it is hoped that the hazard level will be reduced from extreme to medium and so on. The research study, “Assessment of Passenger Safety Risk on the Transjakarta Public Transportation System,” has the potential to make a substantial contribution to sustainable transportation. In line with sustainable development goals, it immediately tackles safety concerns in the Transjakarta system, improving all-around safety and promoting public transportation over private vehicles. By lowering accident-related expenses, promoting inclusiveness, and enhancing community well-being, the study also indirectly increases resource efficiency. In essence, it contributes to a more secure, egalitarian, and sustainable urban transportation system while advancing Jakarta’s sustainable mobility strategy by placing safety first.

Sustainable urban transportation performance in Ankara: A comparative study

Urban mobility is increasing rapidly due to the increasing population, number of motor vehicles and economic developments in Türkiye. Private vehicles are given priority in ur-ban transportation policies and practices in metropolitan municipalities. Therefore, prob-lems such as traffic congestion, delays, air pollution, noise, improper land use, traffic ac-cidents and decrease quality of life are experienced. Although sustainable transportation is generally referred to with air pollution, global warming and climate change; It refers to a wide transportation structure that is sustainable in terms of economic, social and envi-ronmental effects. In this study, Ankara's sustainable urban transportation performance was compared with İstanbul, İzmir, Konya and Antalya, using the Sustainable Urban Transportation Index (SURKENT), which was previously developed by the author. In SURKENT, 15 sub-indicators are defined under 4 main indicators. The main indicators are Environmental Performance (EP), Transportation Performance (TP), Energy Perfor-mance (EnP) and Municipality Governance Performance (MGP). 4 sub-indicators were used under Environmental Performance, 7 under Transportation Performance, 2 under Energy Performance and 2 sub-indicators under Municipality Governance Performance. Minimum-maximum normalization was used for sub-indicators containing quantitative data, and 0-100 scoring was used for qualitative data. The ranking of cities with the high-est sustainable urban transportation performance was found as follows: İstanbul, İzmir, Konya, Ankara, Antalya. Ankara; it is 3rd in EP, 3rd in TP, 5th in EnP and 2nd in MGP.

A Survey of Wireless Charging System for Electric Vehicles and Fire Protection

Wireless charging for electric vehicles offers convenient power replenishment without physical connections. Fire protection measures are integral to ensure safety during wireless charging, mitigating potential risks of overheating or electrical malfunctions. The integration of wireless charging systems for electric vehicles (evs) alongside effective fire protection measures presents a promising avenue towards enhancing the sustainability and safety of urban transportation. In this survey work, we meticulously examine the state-of-the-art advancements, methodologies, and challenges pertaining to the fusion of wireless charging technologies with robust fire protection mechanisms for evs. In this survey encapsulates a synthesis of methodologies, technical architectures, and regulatory frameworks, providing researchers and practitioners with valuable insights to navigate the intricate landscape of wireless charging systems for evs and fire protection

Research Progress and Prospects of Transit Priority Signal Intersection Control Considering Carbon Emissions in a Connected Vehicle Environment

Transit priority control is not only an important means for improving the operating speed and reliability of public transport systems, but it is also a key measure for promoting green and sustainable urban transportation development. A review of signal intersection transit priority control strategy in a connected vehicle environment is conducive to discovering important research results on transit priority control at home and abroad and will promote further developments in urban public transport. This study analyzed and reviewed signal intersection transit priority control at four levels: traffic control sub-area divisions, transit signal priority (TSP) strategy, speed guidance strategy, and the impacts of intersection signal control on carbon emissions. In summary, the findings were the following: (1) In traffic control sub-area divisions, the existing methods were mainly based on the similarity of traffic characteristics and used clustering or search methods to divide the intersections with high similarity into the same control sub-areas. (2) The existing studies on the TSP control strategy have mainly focused on transit priority control based on fixed phase sequences or phase combinations under the condition of exclusive bus lanes. (3) Studies on speed guidance strategy were mainly based on using constant bus speeds to predict bus arrival times at intersection stop lines, and it was common to guide only based on bus speed. (4) The carbon emissions model for vehicles within the intersection mainly considered two types of vehicles, namely, fuel vehicles and pure electric vehicles. Finally, by analyzing deficiencies in the existing studies, future development directions for transit priority control are proposed.

A data-driven framework for natural feature profile of public transport ridership: Insights from Suzhou and Lianyungang, China

Urban public transport systems, characterised by their complexity, generate vast data sets that pose challenges to traditional analytical methods. To address this issue, our research introduces an innovative natural feature profile framework, leveraging a comprehensive, data-driven approach that incorporates big data, data mining, machine learning, and correlation analysis. This approach provides detailed insights essential for transport planning and policy development. The framework's core is its three-layered structure: the data layer, the feature layer, and the application layer, complemented by a unique four-level feature tagging system. This system investigates correlations, significance, and sensitivities amongst feature tags. It facilitates the extraction of natural feature profiles from voluminous data sets, rendering the framework highly applicable in practical scenarios. The implementation of this framework in Suzhou and Lianyungang demonstrated its adaptability and effectiveness. The findings underscored distinct city-specific transport patterns, highlighting the necessity for customised transport strategies. Furthermore, our framework excels at capturing spatial–temporal dynamics, offering essential insights grounded in evidence. Overall, this paper introduces a methodical, adaptable, and data-oriented framework, signalling a promising future for the development of intelligent and sustainable urban public transport systems.

Travel Characteristics of Urban Residents Based on Taxi Trajectories in China: Beijing, Shanghai, Shenzhen, and Wuhan

With the advancement of urban modernization, more and more residents are flocking to large cities, leading to problems such as severe traffic congestion, uneven distribution of spatial resources, and deterioration of the urban environment. These challenges pose a serious threat to the coordinated development of cities. In order to better understand the travel behavior of metropolitan residents and provide valuable insights for urban planning, this study utilizes taxi trajectory data from the central areas of Beijing, Shanghai, Shenzhen, and Wuhan. First, the relationship between daytime taxi drop-off points and urban amenities is explored using Ordinary Least Squares (OLS). Subsequently, Geographically Weighted Regression (GWR) techniques were applied to identify spatial differences in these urban drivers. The results show that commonalities emerge across the four cities in the interaction between external transport stops and commercial areas. In addition, the average daily travel patterns of residents in these four cities show a trend of “three peaks and three valleys”, indicating the commonality of travel behavior. In summary, this study explores the travel characteristics of urban residents, which can help urban planners understand travel patterns more effectively. This is crucial for the strategic allocation of transport resources across regions, the promotion of sustainable urban transport, and the reduction in carbon emissions.

Comparative Analysis of Sustainable Electrification in Mediterranean Public Transportation

The Mediterranean region is a hot spot for climate change, with transportation accounting for a quarter of global CO2 emissions. To meet the 2030 Sustainable Development Goals (SDGs), a sustainable urban transport network is needed to cut carbon emissions and improve air quality. This study aims to investigate the electrification of public transport in both developed and underdeveloped countries by examining the existing public transport network of two modes of transportation (buses and trams) across the Mediterranean region. This study suggests that the electrification of public transportation could result in a significant additional demand for more than 200 GWh of electricity, depending on the size and congestion of the city. It also studies the potential reduction of greenhouse gas (GHG) emissions through the electrification of buses. Results show that electrification significantly impacts decreasing GHG emissions, helping achieve SDG 13. Furthermore, a financial analysis was conducted to determine the feasibility of using different bus fuel technologies. Regarding economic benefits, electric buses are not consistently optimal solutions, and diesel buses can be advantageous. Our finding shows that, at a 5% discount rate, the diesel bus is most favorable for Marseille, and, as discount rates increase, the advantage of electric buses diminishes. However, the high purchase price of electric buses compared to diesel buses is currently a major obstacle in achieving SDG 11, particularly for developing countries.

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.

Towards sustainable urban transport—Political agenda formation and policy windows in Helsinki, Oslo, and Stockholm

AbstractThis paper examines the development of urban transport political agendas in three Nordic capital cities, Helsinki, Oslo, and Stockholm, that strive towards urban sustainability. Utilising the Multiple Streams framework as a basis for analysis, an overview of local problems, policy solutions, and politics that have characterised transport systems and the related policy development processes over time is constructed. The attention is then drawn towards the points in time where the streams connect, and policy windows occur, to detect formative changes and their enablers towards sustainability. The data consists of 18 semi‐structured expert interviews, conducted amongst municipal policymakers and planners. The results reveal several policy windows that have transformed the local transport systems towards sustainability and an increasingly people‐oriented approach. The relevance of global climate change awareness, international planning trends for liveability and cycling, public pressure, individual political decisions, and establishment of modal hierarchy is evident across the case cities, while car traffic regulation is politically challenging and addressed through very different means at very different times. The findings of this paper outline diverse ways for advancing sustainability in local policy development but also detect methods for politically halting the process.

Enhancing sustainable urban air transportation: Low-noise UAS flight planning using noise assessment simulator

Low-altitude flights of unmanned aircraft systems (UASs), such as drones, can cause substantial noise pollution in urban areas. This study aims to tackle the crucial issue of noise in UAS flight planning and analyze the feasibility of implementing low-noise urban flights at a micro level. We employ a virtual flight simulator to accurately model the UAS noise impact in realistic flights and optimize the flight path via a heuristic algorithm accordingly. The flight noise assessment incorporates a sound source modeling technique for practical UAS models and an efficient Gaussian beam tracing method for outdoor noise propagation in realistic environments. Case studies for flight simulations are conducted in a representative resident community and metropolitan area to evaluate the noise impact resulting from different flight paths. By comparing our approach with benchmark shortest-distance paths, we validate its effectiveness in significantly reducing en-route noise exposure, encompassing both instantaneous and continuous noise levels. This method holds great potential for contributing to the planning and management of urban air transport systems. It effectively mitigates noise impact, promoting quieter and more environmentally friendly UAS operations and sustainable urban transportation.

Mediating Role of Environmental Awareness for the Nexus between Perceived Risks of COVID-19 Pandemic and Use of Sustainable Transportation: Evidence from Urban Passengers in Ethiopia, 2022

The COVID-19 pandemic has been a global pandemic and a threat to humankind. In addition to many cases of illness and millions of deaths, the economy and social interactions have suffered. It remarkably declined overall transportation and mobility in most countries. However, given that there is a gap between environmental sustainability awareness and what is practiced by transport users, the goal of this study was to empirically assess the mediating role of environmental awareness in the casual links between perceived risks of the COVID-19 pandemic and ecologically sustainable transportation use. The study identified relevant theories, conceptual frameworks, and variables. Mixed research and surveys were carried out on the public and private transport service users in Addis Ababa, Ethiopia. Comparative analysis, structural equation modeling, and structural causal model framework were applied to estimate casual relationships among variables and test the hypotheses. Despite the rising of human-caused climate change denial beliefs, findings revealed that a large part of the causes of the COVID-19 pandemic are climate change, biodiversity misuse, and wildlife degradation, all of which are environmental in nature and anthropogenic. People perceived the COVID-19 pandemic as more of a risk to others than to themselves, and climate change or global warming has become a danger to humanity, mainly during the pandemic. Accordingly, the pandemic risks increased people’s mainly passengers’ awareness of the environment, and this caused them to give greater consideration to the environmentally attractiveness of the transport they use. This, in turn, encouraged people to take personal climate-friendly measures and pro-environmental behavior, mainly greater willingness to use public transportation than private transportation during the COVID-19 pandemic than before. Thus, the total effect of the COVID-19 pandemic anxiety on the use of public transportation is completely mediated by enhanced environmental awareness. These are evidence that COVID-19 has strengthened environmental awareness and promoted sustainable action in the context of the transportation industry of developing countries. The study informs that urban planning and policy need to consider pandemic-sensitive and innovative public health and transport systems, integrated public health education, one health approach, and smart city. It suggests that maintaining the environmental awareness of societies and encouraging them to mitigate climate change through urgent climate actions and modal shifts to the use of sustainable urban transport such as public transportation.

OPTIMAL TRAFFIC CONTROL SYSTEM FOR TRAFFIC CONGESTION

A smart city's traffic management system is regarded as one of its primary components. Traffic jams are a common sight on the roadways in metropolitan areas due to the rapid increase in population and urban mobility. In order to address road traffic management issues and assist authorities with appropriate planning, an intelligent traffic management system utilizing the Yolo algorithm and Open CV approach is proposed in this project. A workable model for counting automobiles in traffic was developed using image processing as the basis. image processing methods classified and tallied moving vehicles in traffic scene video streams captured by stationary cameras. The following is the detection and tracking methodology. The adaptive background subtraction technique is initially used to separate the moving vehicles from the traffic scene. Using videos to isolated picture blobs are recognized as individual vehicles once the background is subtracted. Following blob identification, vehicles in a certain area are counted and classified. A count of vehicles was observed with an accuracy of ideal camera calibration. To support the goal, data is gathered from video footage of vehicles traveling toward and away from the camera in order to count and use signal switching. The created system's results demonstrate that, with more enhancements, it applicable to count and categorize vehicles in real-time. After that, an optimization framework makes use of these predictions to dynamically modify signal timings in response to shifting traffic conditions. The optimization method seeks to increase overall traffic flow efficiency, decrease delays, and shorten travel times. To sum up, utilizing real-time traffic data to optimize signal control presents a viable approach to improving urban traffic management. This method makes use yolo techniques to facilitate the creation of flexible and effective traffic control, which in turn helps to create more sustainable and seamless urban transportation networks. KEYWORDS: Image classification, Video tracking, Information analysis, Vehicle detection, Signal Switching.

How does the urban built environment affect dockless bikesharing-metro integration cycling? Analysis from a nonlinear comprehensive perspective

The multi-modal combination of "dockless bikesharing (DBs) + metro" can effectively addresses the "last mile" challenge, and its importance to improve the quality of metro integration and residents' commuting efficiency is becoming increasingly prominent. As one of the important determining factors of transportation, the urban built environment directly affects the integration travel behavior of residents. To better understand this issue, it is necessary to conduct in-depth research on the influence mechanism of urban built environment on DBs-metro integration cycling (DBsMIC), and reveal its complex nonlinear characteristics and spatial heterogeneity. Therefore, taking Shenzhen as a case study, this study first introduced the OLS regression model to detect the significant built environmental impact factors of DBsMIC. Secondly, the random forest regression model was used to analyze its nonlinear influence. Finally, aiming at the problem of spatial non-stationarity of influencing effects, the spatial heterogeneity is analyzed from both global and local perspectives based on the MGWR model. The results show that the significant impact indices of the built environment of the integration cycling volume vary in different time periods. Overall, seven factors such as road and residential density have a significant impact on DBsMIC. Among them, the job-housing balance and the bus line density have a negative impact, while the rest have a positive impact. Meanwhile, the nonlinear effect of the built environment on DBsMIC is obvious, and there is an obvious marginal effect. In addition, the nonlinear impact of the built environment on DBsMIC in different time periods has spatial heterogeneity and spatial marginal effects. For example, the influence of road density shows a global positive correlation effect in multiple time periods, and the promotion effect increases from southwest to northeast. This study can provide auxiliary decision-making support for the construction of an efficient, green and sustainable urban transportation system according to local conditions.