Urban Public Transport System Research Articles

Comparison of station-based and free-floating bikeshare systems as feeder modes to the metro

Shared micro-mobility has been booming in recent years and the coordinated development of different modes can play an important role in improving the connectivity of the urban public transport system. While most previous studies have analysed the feeder trips of individual modes, few comparative studies of different modes have been conducted. To this end, we compared the spatial and temporal patterns in the integrated use of station-based bikeshare systems (SBBS) and free-floating bikeshare systems (FFBS) with the metro. This study used the smart card data of SBBS and transaction data of FFBS from 1st to 30th September 2017, in Nanjing, China. Generalised additive mixed models were applied to examine the nuanced effects of the built environment, weather factors and temporal variables, while taking into account spatio-temporal autocorrelations. The results show that SBBS are used more as a feeder mode at downtown metro stations and exhibit pronounced rush hour patterns. FFBS-metro integrated use is spatially more dispersed at peripheral stations and covers wider periods of the day. This suggests that SBBS use is more demand-driven, while FFBS use is more efficiency-driven. The built environment shows different forms of effects: variables that have a linear relationship with SBBS-metro integrated use show non-linear effects in the FFBS model, and vice versa. Certain variables also present variations in their non-linear patterns. For instance, the plateau effect of road density for SBBS occurs at 10.5 km/km2, while the optimal employment density for FFBS is 12,000 jobs/km2. Inadequate or excessive development can lead to a decrease in integration efficiency. These findings can inform how service providers optimise fleet reallocation and how transport planners tailor spatial interventions that promote the integration of bikeshare and the metro system.

ЕВОЛЮЦІЯ ФУНКЦІОНАЛЬНО-ТЕРИТОРІАЛЬНОЇ СТРУКТУРИ РЕЙКОВОГО ГРОМАДСЬКОГО ТРАНСПОРТУ КИЄВА

Urban transport systems require increased attention as connecting elements that affect the efficiency of the functioning of cities as a whole and individual districts. Public passenger transport of a large city, which is the capital of the state – Kyiv, is one of the branches of its life support, on the functioning of which both the development of the economic complex and the lifestyle of the population depend. The problem of the rational functioning of public transport and its territorial organization become one of the main ones for our capital during the martial law and will become critical after the Victory. The development of rail transport is a priority for any European city: it has the highest carrying capacity, it is environmentally friendly and comfortable for passengers, and most importantly, it does not depend on the amount of traffic jams. In Kyiv, there are four types of rail public transport - metro, tram (including high-speed tram), city electric train and funicular. The analysis of the evolution of the territorial structure of the urban rail public transport system, carried out using the methods of graph theory and historical-geographic sections, shows that this structure developed dynamically along with the development of Kyiv. It is substantiated that the priority directions of the development of Kyiv's transport system are aimed at the formation of a highly efficient transport complex capable of meeting the needs of the population in relevant services and minimizing the negative impact on the environment. To achieve this goal, the main directions of the development of Kyiv's rail public transport system have been determined: the priority of public passenger transport in the performance of city transportation; development of high-speed off-street types of public rail transport (metropolitan, high-speed tram, city railway); provision of fast, comfortable and safe transport connections between all functional zones of the capital on the basis of increasing the density of the street network, creating a system of complex transfer nodes at the stations of the metro and city railway lines.

Analysis on the Development of Subway in a Pandemic City

The outbreak of COVID-19 poses a severe challenge to the epidemic prevention and control of urban public transport system. As the backbone of urban public transport, urban rail transit is one of the important links in the epidemic prevention and control of urban public transport system. It faces the challenge of heavy tasks and great pressure. Using the methods of questionnaire survey, field investigation and case analysis, this paper aims to find out how to improve the operation of the subway under the epidemic situation, and finally comes to a conclusion that there is need to further strengthen the control measures to deal with peak passenger flow concentration, and improve the emergency plan. Besides, a traceable and reliable epidemic prevention cooperation system should be created and a real-time dynamic interaction system should be built to open up the information barrier between passengers and operating units. Moreover, it is also important to improve the normalized and refined monitoring and early warning system for high-risk areas, as well as simplifying the display of passengers' personal information and realize automation, intelligence, and integration.

A Model Proposed For Sakarya Integrated Public Transportation System Through The Analysis Of Kahramanmaras And Kayseri Applications

Public transportation systems of city of Sakarya are carried out by differentstakeholders. Daily travel demands are met with private-public buses, paratransit minibusses, and buses operated by municipality. Factors such as the independence of theoperating systems of each operator and the provision of services without optimizingthe number of trips and vehicle capacities according to travel demands cause theexisting urban public transport system to result in inefficient operation as a whole. Itis, therefore, necessary to integrate the different elements of the urban public transportsystem for creating an efficient operational system considering the integrated needs ofthe all available systems. In this sense, Kahramanmaraş and Kayseri applications areto be examined to propose the integrated model proposal for Sakarya province througha SWOT analysis.

Understanding the determinants for predicting citizens' travel mode change from private cars to public transport in China.

Rapid urbanization and motorization have generated increasing social and environmental challenges to the urban transport sector in China, such as traffic congestion, car accidents, air pollution, and global warming. Prioritizing the development of urban public transport system has been adopted as a primary strategy by Chinese government. However, the problems caused by large numbers of private cars are still far from being solved, and the ridership of public transport in China is relatively low. Therefore, the current study proposes a new comprehensive framework by enhancing the norm activation model (NAM) and theory of planned behavior (TPB) with the perceived accessibility to public transport, to better understand the determinants for predicting citizens’ choice of public transport as a sustainable travel mode. An online survey concerning travel mode change was conducted among citizens in Hangzhou, China. Based on 341 valid samples, partial least squares structural equation modeling (PLS-SEM) was employed to verify the proposed framework. The analytical results confirm that awareness of consequences and subjective norms are the two key constructs for connecting the two theories as a whole. Further, the examination of intention-behavior relationship shows that perceived accessibility to public transport could strengthen the relationship between behavioral intention and actual behavior in using public transport. The findings not only contribute to the development of pro-environmental theories, but also have meaningful implications for governments to develop relevant policies to encourage citizens to use public transport as a sustainable travel mode.

A Data-Driven Approach for Electric Bus Energy Consumption Estimation

Along with the battery technology advancements and government policy support, the penetration level of electric buses (EBs) in the urban public transportation system has been increasing in recent years. Considering the potential influence of the increasing EB charging demand on power systems, estimating the real-time energy consumption of EBs has become a principal issue. In this work, a data-driven approach for EB energy consumption estimation is proposed. In particular, a detailed physical model of EB is constructed to model its energy consumption considering the randomness in EB operation, including speed, acceleration, and passenger count. In order to improve the estimation accuracy, the conventional Kalman filter (KF) is modified involving EB mass estimation considering stochastic real-time passenger count, motion data dimension deduction based on EB operation route. To estimate the EB acceleration accurately and reduce the noise caused by the unimportant features, we extended the feature discarding algorithm of decision trees to the regression trees. In the case study, an Android application is developed to collect the EB motion data so that any general Android smartphone can be used for data collection. The performance of the proposed approach is evaluated based on real-world EB operation data collected from St. Albert Transit, AB, Canada. According to the results, our APP can track the real-time EB trace, and the proposed modified KF can filter most of the noises caused by the GPS data collection process and stochastic passenger count. Also, with the extended random forest algorithm, the unimportant features can be discarded and the real-time EB acceleration is estimated efficiently with a small sum of square error (SSE). Compared with the existing approaches, the proposed approach achieves a more accurate real-time energy consumption estimation of EBs, which in turn, provides a better characterization of power system loading and voltage variation.

State monopoly on urban transport system and human (in)security in Harare during the COVID-19 pandemic

ABSTRACT This study discusses the human security costs and benefits generated by the coronavirus (COVID-19) pandemic-induced state monopoly on the urban public transport system in Zimbabwe through the Zimbabwe United Passenger Company (ZUPCO) since March 2020. Using empirical evidence from Harare, it argues that the ZUPCO initiative had far-reaching safety and security implications on urban residents’ lives during the COVID-19 pandemic. The study found that though the ZUPCO initiative mainly benefited commuters through affordable fares, it had many human security costs. The costs included reduced safety and decreased and unreliable services, which exposed the commuting public to the risk of contracting COVID-19 and other security challenges. The state monopoly on urban transport exacerbated the social and economic impact of COVID-19, promoted inequalities, police corruption and urban residents’ use of informal transport services, which were unsafe and costly. The study concludes that the Zimbabwean government lacks the capacity to provide services in the urban transport sector, akin to nearly every sector in the country. As a stop-gap measure, the government is encouraged to regulate and allow private players to complement its efforts for the benefit, convenience, security, and safety of commuters until it develops an efficient urban public transport system.

Spatial temporal pattern analysis on on-demand cab services in urban areas using GIS

As an important component of the urban public passenger transportation system, cabs / taxi offers an all-weather, convenient, comfortable, and personalized travel services for the urban residents, as well as playing a key role in the urban passenger transportation development. Cab market has gained prominence over last 2-3 years in India, in the backdrop of entry of app based aggregators which has not only disrupted auto-rickshaw and traditional taxi market but also forced automotive Original Equipment Manufacturers (OEMs) to revise their growth and marketing strategies. There is a randomness and lack of regularity of cab operation characteristics, to describe cab travel activity pattern. Inorder to plan and effectively manage on-demand cab services, and to improve better facility to public, there is a need to understand the underlying relationship between supply and demand. This study analyzed the urban cab location distribution characteristics from different temporal and spatial levels. In the time level, the difference with daily location and operation pattern (weekday versus weekends) is identified; in the space level, the cab location pattern over a space are explored. Cab coverage index and Standard deviation ellipse are the tools used in analysing the patterns over time and space frames. This research can be helpful for understanding urban cab behavior pattern, as well as the contribution to the geographical activity space analysis. GIS has been used as a supportive tool in the study

Communication-Based Train Control with Dynamic Headway Based on Trajectory Prediction

Rail transit plays a significant role in the operation of an efficient and effective urban public transportation system. Safety and capacity are some of the most crucial objectives in railway operations. The communication-based train control (CBTC) system is a continuous and automatic train control system that realizes constant and high-capacity train ground two-way communication. In this study, a dynamic headway model of the ‘softwall’ moving-block approach is proposed for CBTC to increase the track capacity and improve dispatching efficiency based on the train trajectory prediction. For this precise trajectory prediction task, we introduce a hybrid trajectory prediction model to combine Long Short-term memory (LSTM) and Kalman Filter (KF) to extract the train’s local data features and learn the long-term dependencies, respectively. Then we present a dynamic headway model to maximize the train headway and reduce the track distance. The leading trains’ information is used to construct the iterative learning control strategy, and the predicted trajectory is input into the algorithm of the headway model. We use a simulation model of the rail network in Chengdu to demonstrate the effectiveness of our proposed approach. The results show the Mean Absolute Error (MAE) of the predicted trajectory retreated to 93.97 cm and reductions in operation headway of at least 64.33% under the dynamic headway model versus the traditional moving-block model.

Raylı Sistem Araçlarında Enerji Verimliliğinin İyileştirilmesi

Over the years, due to traffic, environmental problems associated with fossil fuels and related economic problems, the demand for urban rail transit system such as trams, light rail systems and metro has increasing rapidly not only in our country but also all over the world. Since rail public transportation systems require high power, the energy efficiency of the railway system is of great importance. The energy consumption on tram lines is different. Therefore, the factors affecting electricity consumption of trams and metro, especially in metropolitan cities should be examined carefully and the new methods for enhancing energy efficiency of the rail transportation systems should be developed. In this study, tests including different driving styles were carried out for 2 CNR railway vehicles owned by SAMULAŞ A.Ş., which serve in the urban public transportation system in Samsun. The test results were analyzed in terms of traction power and relationship between energy consumption and vehicle weight using the Concerto Maintenance program. The simulation results showed that 20% energy saving was achieved by using the suggested driving scenarios, compared to practical driving at similar vehicle weight. For example, an average of 14 million kWh of energy is consumed annually for rail public transportation systems in Samsun. For this reason, it is thought that the findings obtained in this study will contribute to the reduction of energy consumption of urban rail systems in Turkey.

IoT sensory platform for monitoring temperature, relative humidity of the air and CO2 in situ

This article addresses the development of a sensory platform capable of measuring temperature, relative humidity, and carbon dioxide. The system is based on concepts of an IoT (Internet of Things) platform using the ESP8266 microcontroller connected to DHT21 and CSS811 sensors, the power system has lithium batteries. An App (Application) in Blynk technology was used to display the collected information and georeferenced the data, which in turn are stored in a digital cloud. Two experiments were carried out to determine the environmental quality in a forest and urban area within Belém, showing the quality of the developed system and the influence that trees have on air quality in relation to carbon dioxide and thermal comfort. Furthermore, a reformulation of the urban public transportation system must be employed, enabling it to be used in an efficient and less polluting way, since transportation is the leading emitter of pollutants that contribute to the greenhouse effect and aggravates factors related to public health. The description of the developed device allows its reproducibility and has as main differentials: optimized power system, possibility of integration with renewable energies, low cost platform; connection with several sensors; easy programming and operation; internet access and, last but not least, low cost.

A Partial-Fréchet-Distance-Based Framework for Bus Route Identification

The integrity of bus route information is fundamental to the analysis of operating status and travel pattern of urban public transport system. However, due to the malfunction of bus positioning devices or delayed update of database, the route information stored in positioning devices might be lost or erroneous. To address this issue, this paper designs a framework matching the bus trajectory with a set of predefined bus routes. The trajectories are first partitioned into segments using the spatio-temporal DBSCAN. Then, the curve similarity between trajectories and bus routes is calculated based on the metric of partial Fréchet distance, which searches for a best mapping between curves that minimizes the maximum distance between vertex pairs. A directed-acyclic-graph-based method is also proposed to compute the partial Fréchet distance. Finally, the best match for each trajectory is given based on the relative ranking. The proposed framework is evaluated on the bus trajectory data of Fuyang and Shenzhen in China. The experimental results demonstrate that the framework can well identify the underlying routes according to the recorded bus trajectories and suggest which route information needs updating.

Exploring the spatiotemporal pattern of traffic congestion performance of large cities in China: A real-time data based investigation

The socioeconomic costs of traffic congestion are crippling in urbanising China. This study is a first attempt to explore the spatiotemporal pattern of traffic congestion performance in 77 Chinese large cities by using real-time big data. Based upon the hourly real-time traffic performance index data collected between August 27, 2019 to September 27, 2019, four clusters of cities have been captured in line with their urban traffic congestion pattern between different days of the week. Empirical results unveil that urban traffic congestion performance varies substantially between surveyed cities on the same day of the week. Cities with advanced planning and delivery of urban road network, and well-developed urban public transportation system exhibit better traffic performance. Cities with relatively smaller scale of urban population, higher per capita road area and less amount of vehicles have also achieved relatively smooth traffic congestion performance. Particularly, cities in Northeast China tend to have earlier morning and evening peak hours than other sample cities, and the Northeastern cities are overwhelmingly diagnosed with more severe traffic congestion. Moreover, the traffic congestion patterns of surveyed large cities in China present obvious variations between different days of the week. This study provides valuable lens to understand the variegated pattern of traffic congestion performance between different regions in urban China, based upon which targeted policy recommendations have been synthesised to help alleviate urban traffic congestion and further improve urban well-being across the country.

Exploring the Spatiotemporal Impacts of the Built Environment on Taxi Ridership Using Multisource Data

Taxis are an important component of the urban public transportation system, with wide geographical coverage and on-demand services characteristics. Thorough understanding of the built environment affecting taxi ridership can enable transportation authorities to develop targeted policies for transportation planning. Previous studies in this field had few data sources and did not consider the spatiotemporal variability. This study aims to develop an analytical framework for understanding the spatiotemporal correlation between the urban built environment and taxi ridership, which is empirically analyzed in New York City. The built environment is defined through multisource data in terms of density, design, diversity, and destination accessibility. Besides the exploration of travel patterns, the spatiotemporal heterogeneity of taxi ridership is modeled using geographically and temporally weighted regression (GTWR). The result shows that GTWR outperforms ordinary least squares (OLS), geographically weighted regression (GWR), and temporally weighted regression (TWR) in both goodness of fit and explanatory accuracy. More importantly, our study found that land use diversity is negatively correlated with taxi ridership, while transportation diversity is positively correlated with it. A highly accessible road network improves the people’s demand for taxis in the morning rush hours. Moreover, the density of railway stations is positively correlated with taxi ridership on weekdays but adversely on weekends. These findings provide practical insights for urban transportation policy development and taxicab regulation.

Fuel economy optimization of diesel engine for plug-in hybrid electric vehicle based on equivalent operating points

The plug-in hybrid electric vehicle (PHEV) has been progressively penetrated in the urban public transport system for its special advantages of energy saving and emission reduction potential. In order to improve the fuel economy of PHEV engine, an optimization study on the engine control parameters is carried out and applied on a PHEV with a rule-based energy management strategy (EMS) in this paper. Firstly, the mathematical model of diesel engine is established on GT-Power platform to accurately reflect the fuel consumption characteristics of engine. Secondly, a control parameter optimization method based on engine equivalent operating point is proposed and four key engine control parameters are optimized by genetic algorithm (GA). Thirdly, the optimization and calibration of the PHEV engine is performed under ChinaCity driving cycle. The results show that the maximum reduction of engine brake specific fuel consumption (BSFC) on the optimal operation line is 3.56%, and the equivalent fuel consumption of PHEV under ChinaCity, WVUCITY and WVUSUB driving cycles is reduced by 2.62%, 2.24% and 2.05%, respectively.

A capacity matching model in a collaborative urban public transport system: integrating passenger and freight transportation

Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passenger revenue over a longer period. Considering the collaborative urban public transport services achieve a seamless movement for both passengers and goods, and could reduce the adverse effects of the existing urban public transport systems. Therefore, a mixed-integer linear programming model introducing the concept of capacity matching is proposed to assist this collaborative urban freight service network in minimising total freight transport time at station hubs and not affecting passenger transportation in this paper. Moreover, an efficient improved optimisation algorithm based on the Artificial Bee Colony Algorithm (ABC) is designed, and the numerical examples and real cases are illustrated to demonstrate the feasibility and effectiveness of the proposed model and algorithm. The performance evaluations suggest that the coordinated operating strategy of the collaborative freight transportation system supports increasing mobility demands for freight, resulting in declining congestion levels and reducing transport emissions, while no influence in passenger transport, notably in urban areas.

Economic, Ecological and Social Analysis Based on DEA and MCDA for the Management of the Madrid Urban Public Transportation System

The aim of this research is to help public transport managers to make decisions on the type of buses that should compose their public transport fleet, taking into account economic, environmental and social criteria from the point of view of sustainability. This paper fills a knowledge gap by including the social dimension of sustainability in addition to the economic and environmental dimensions. The original nature of this study lies in analyzing complementarities in the structuring of an efficiency and multicriteria problem. Our research analyzes Madrid public bus system data; the problem is structured in a comparative way between two analytical methods, a Data Envelopment Analysis (DEA) and an ELimination Et Choice Translating REality (ELECTRE) III. Our research results show that two main groups of vehicles could play a part in part the theoretical solution. The main conclusions of this research are that (a) plug-in and induction electric vehicles are not comparable to GNC and diesel–hybrid vehicles in terms of cost, pollution and service; and (b) the ELECTRE III model provides more information in solving this problem than the DEA model.

Spatial and Temporal Characteristics of Bike-Sharing Trips at Street Scale: A Case Study of Chengdu City

In the context of the policy goal of "carbon neutrality and carbon peaking", bicycle sharing, as a low-carbon and convenient way to travel, not only effectively meets the demand of the "last mile" of urban public transportation system, but also is one of the main ways to solve the problem of urban carbon emissions. It is also one of the main ways to solve the problem of urban carbon emission. This paper takes five urban areas in the center of Chengdu as an example, and uses Mobike order data and multi-source urban open data to conduct statistical analysis and spatial distribution visualization of shared bicycle data through Python and GIS, summarizing the spatial and temporal characteristics of shared bicycle travel activities at the street scale, and providing some data reference and theoretical basis for the placement and management of shared bicycles in the streets. It is of great significance to improve the efficiency of shared bicycle travel, achieve the goal of "carbon neutrality and carbon peaking" and improve the urban public transportation system.

Research on Optimization of Urban Public Transport Network Based on Complex Network Theory

The urban public transportation system is an important part of urban transportation, and the rationality of public transportation routes layout plays a vital role in the transportation of the city. Improving the efficiency of public transportation can have a positive impact on the operation of the public transportation system. This paper uses complex network theory and the symmetry of the up and down bus routes and stations to establish an urban public transit network model and calculates the probability of passengers choosing different routes in the public transit network according to passenger travel impedance. Based on passenger travel impedance, travel path probability and passenger travel demand, the links are weighed, and the network efficiency calculation method is improved. Finally, the public transit network optimization model was established with network efficiency as the objective function and solved by the ant colony algorithm. In order to verify the effectiveness of the model and the solution method, this paper selects areas in Nanguan District of Changchun City for example analysis. The result shows that the efficiency of the optimized network is 8.5% higher than that of the original network, which proves the feasibility of the optimized model and solution method.

Developing an indicative spatial accessibility analysis tool for urban public transportation system

This study proposed a simplified and indicative methodology for spatial accessibility analysis using limited data to specify areas where Public Transportation (PT) is mostly needed. It was based on the difficulties associated with previously used methodologies that required complicated mathematical functions and intensive origin-destination data. Amman city, Jordan, was selected to apply the proposed methodology and find the optimal routes for running a PT system.Canny Spatial Accessibility Analysis (CSAA) was used to identify PT routes that were most in demand and provide route classifications based on the route importance for running PT. CSAA was performed by combining three models: Gravity Model, Weighted Overlay, and Space Syntax. It examined the factors behind achieving an efficient PT system (land use, population density, population income level, primary services in the city, and street network hierarchy) with accessibility measurements and connectivity estimates to identify the network's priority routes. The comparison between the existing PT routes and the proposed routes showed that the latter was more efficient in covering higher demand percentages of the population, points of interest, and land-use, which resulted in classified routes by the need for PT system.The adopted novel methodology exhibited the attractiveness weight of the city's primary services, gave a clear image of the city's existing conditions, and identified areas where PT system is highly demanded. It outlined a crucial step for designing PT system based on easily accessible information, presenting a key PT planning tool that delineated the demanded PT despite the lack of funding and exhaustive statistical information.