Urban Transportation System Research Articles

DECISION SUPPORT FOR CHOOSING A SCENARIO FOR ORGANIZING URBAN TRANSPORT SYSTEM WITH SHARE OF ELECTRIC VEHICLES

This article presents the issue of using decision support tools to select the variant of organization of urban transport system. Two scenarios for the use of electric vehicles were compared, considering not only their emissions and fuel consumption but also the limited accessibility of conventional vehicles to the city. The authors assume that the development of urban traffic organization must go hand in hand with the challenges of planning sustainable urban mobility and reducing harmful exhaust fumes. Furthermore, decision-makers should be equipped with simple decision support tools to generate the best option considering the expectations of transport users. The PTV VISUM tool was used to analyse and visualize two different organization scenarios for a selected city in Poland.

Analysis and modeling of developing passenger traffic on public transport routes of urban transport systems

Problem. To solve the problems of rational organization of work of urban passenger transport on the routes and determine the modes of vehicles work and labor of drivers of motor transport enterprises when carrying out transportation of the city population. It is necessary to know all the input conditions for creating traffic schedules on the route. One of the main parameters is the existing traffic volumes on a certain public transport route. In order to improve the management of transportation on the routes of urban passenger transport, various approaches to their survey were considered, the problem of studying traffic volumes for further drawing up traffic schedules was identified. In this article, the task was to analyze the work of a separate route and passenger traffic on it. Goal. The goal is studying passenger traffic on a separate public transport route, studying the regularities of traffic volumes and their dependence on operating time. Methodology. When fulfilling the task, the procedure by which the input data is processed is given. Having examined the known methods and principles of applying certain groups of methods to solve various types of problems, to solve the problem of organizing work on the route, namely, to distribute changes in the operation of vehicles for the transportation of passengers, we opted for a readable tabular method of examining passenger traffic. Thus, an incoming sequence of values was obtained, which we presented as time series levels. An analysis of incoming time series was carried out, their modeling using an adaptive algorithmic method. Results. A method of using computer mathematics systems for modeling and predicting input time series was developed, during which the solution process was programmed and the results of adaptive algorithmic modeling of passenger traffic dependencies on time were obtained, which can be used to build schedules for the movement of vehicles during passenger transportation by public transport. Originality. Passenger traffic on a separate route was investigated, the methodology of this study was presented, all components of the time series were taken into account and modeled. The graphic representation was provided. This article has developed programs for performing modeling and forecasting using adaptive algorithmic models. Practical value. This provides an opportunity to investigate the passenger traffic of any passenger transport route, carrying out transportation, sequences of volume whose values have similar components of the time series. The result of these studies is building a model and obtaining forecast values, which plays a large role in management of road passenger transport.

Effects of rainfall on the weekday traffic flow in major cities of the Beijing–Tianjin–Hebei region, China, in 2021

Rainfall can bring uncertainties to the traffic flow and influence the normal function of urban transportation systems. The impact of precipitation on the urban traffic flow, especially the different impacts among cities and areas within a city, is worth investigating. Here, we analysed the impact of precipitation on the traffic flow in the urban areas of the Beijing–Tianjin–Hebei region by comparing the traffic flow in non-precipitation and rainy weather with different hourly precipitation intensities in 2021. The increase in the travel time index (TTI) is chosen to represent the influence of precipitation on the transportation system. The results show that the maximum of the average TTI increases on the city scale under various rainfall intensities by 3.3%, 6.6% and 10.8% in Beijing, Tianjin and Shijiazhuang, respectively. In general, the increase in the TTI contributed by precipitation is the greatest at morning and afternoon peak hours, and the traffic congestion degree increases with the rainfall intensity. However, in the morning peak, afternoon peak and midday hours in Beijing and Tianjin, the influences of the weak rainfall intensity on the traffic flow are generally great, whereas the traffic congestion degree caused by heavy precipitation is relatively low. Particularly, in morning peak hours, the congestion reduction reaches approximately 2%, which may be related to the spatial difference in the impacts of precipitation on the traffic flow and the changes in people's travel intention under different rainfall intensities. The findings can help better understand the relationship between rainfall and urban traffic flow characteristics and also potentially contribute to the development of impact-oriented climate predictions.

Who are those fast cyclists? An analysis of speed pedelec users in the Netherlands

In many regions, conventional bicycles and electrically assisted bicycles (e-bikes), are gaining popularity and becoming a commonly used sustainable mode in the urban transportation system. Speed pedelecs are a type of high-speed e-bike with motorized pedal assistance up to a maximum speed of 45 km/h. This relatively new mode is most often used for trips that range from 10 to 40 kilometers, making it a promising mode for promoting drivers to switch to using sustainable and active transportation. The goal of this study is to assess speed pedelec usage in the Netherlands. We set out to understand who the users are, what motivates them, and whether they experience any barriers to speed pedelec usage. Using a factor-cluster analysis we group users based on their attitudes and preferences regarding the physical environment they cycle in, their sociodemographic characteristics, personal attitudes, and social environments. The analysis revealed four primary user groups: Enthusiastic riders, Efficient riders, Concerned riders and Relaxed riders. Across the groups, 85% of the respondents reported using a speed pedelec at least once a week for a trip they would have previously made by car. However, each group has specific travel habits, motivations, and safety concerns. In contrast to previous literature about the use of conventional bicycles, attitudes about competition play an important role for speed pedelec users. Stress reduction and being outside in nature also play an important role for certain segments of speed pedelec users. In addition, believing that other road users have a negative image of speed pedelecs also determines how speed pedelec users use their bicycles. While infrastructure preferences are often cited as being a distinctive factor for users of conventional bicycles, this did not clearly apply to speed pedelec users. However, all user groups reported that on average the cycling infrastructure on their regular routes was insufficiently developed for speed pedelecs. To motivate continued speed pedelec usage, each user groups requires specific policy interventions that are aligned with their personal values related to preference, safety, and image. By understanding the specific needs and desires of different segments it becomes possible to develop effective policy interventions aimed at improving the experiences of all speed pedelec users.

Selection of an Electric Scooter for Shared Mobility Services Using Multicriteria Decision Support Methods

In recent years, the electromobility market has been growing faster and faster. Electric scooters and scooter-sharing services offered for them, available in many cities around the world, have a special impact on its intensification. The constantly growing number of scooters and service operators brings many problems related to the proper functioning of services. In the literature, one can find attempts to solve the problems of scooters with references to the issues of transport, modeling and optimization, as well as legislative and social aspects. Technical issues, however, are overlooked. Among them, however, there is a problem with the appropriate selection of scooter models that can be used in scooter-sharing systems. Solving this type of problem may allow systems to be better matched to urban transport systems, increase the development of electromobility and encourage societies to transition from current means of transport (e.g., cars) to scooters. Paying attention to this research niche, the article is devoted to the selection of electric scooters for scooter sharing. This paper presents the author’s own research for the Polish market of scooter-sharing services. As part of the work, the author’s own list of factors from the point of view of which scooters can be assessed was developed; social research was conducted, considering the opinions of experts in the field of scooter sharing; and it was proposed to treat the problem of selecting scooters as a complex multicriteria decision-making problem. Moreover, the ELECTRE III method was used to solve this research problem in an innovative way. The research results indicate that when choosing a scooter, you should be guided primarily by such factors as the greatest range, equipping the vehicles with safety systems and the most powerful engine. Interestingly, the price of vehicles does not have to be the lowest possible. The article presents guidelines that support operators when upgrading or equipping systems with scooters and support individual users at the stage of deciding to buy a scooter.

Construction of Commuters’ Multi-Mode Choice Model Based on Public Transport Operation Data

Travel mode selection is a crucial aspect of traffic distribution and forecasting in a comprehensive transportation system, which has significant implications for resource allocation and optimal management. As commuters are the main part of urban travel, studying the factors that affect their choice of transport mode plays a crucial role in urban traffic management and planning. Based on public transport operation data, a travel chain is created by identifying boarding stations, alighting stations, and transfer behaviors, and includes detailed travel information. The regression and correlation coefficients of departures and arrivals at stations are confirmed to be 0.98 and 0.92 in the presented data, indicating the viability of the recognition method. Then, multiple travel modes are identified based on the origin and destination, and the proportion of mode selection is determined by the actual travel chain. Using maximum likelihood estimation (MLS) and NLOGIT software, the random parameter logit (RPL) mode is used to estimate the relationship between travel mode selection and characteristic variables such as travel time, distance, cost, comfort, walking distance, and waiting time. The results indicate that walking distance, travel distance, and comfort have a greater influence on travel choice, and that walking distance is a random parameter with a normal distribution, reflecting the diversity of commuters. In addition, this paper discusses the influence degree of the change of characteristic variables of a transport mode on the choice between it and other modes. These results can be used as reference for relevant departments to make measures to improve the overall efficiency of the urban transportation system.

Analysis of Intelligent Transportation System Application Based on Internet of Things and Big Data Technology under the Background of Information Society

With the growth of national economic strength, urban modernization has become an indispensable part. Among them, urban road traffic congestion has become the main problem affecting work and traffic. Traffic pressure promotes the massive use of Internet of Things and other technologies in the transportation system. The integration of computer, Internet of Things and transportation system forms a new intelligent transportation concept. With the advent of intelligent information society, the application of intelligent transportation is imminent. In view of the shortcomings of urban intelligent transportation, this paper uses Internet of Things technology and big data technology to study it. Firstly, it analyzes the function and value of IoT intelligent transportation, analyzes the system components from the construction principle, and makes full use of intelligent technology to improve the transportation system. Secondly, the optimal path algorithm is proposed in the IoT urban intelligent transportation system model. The advantages and disadvantages of genetic algorithm and heuristic algorithm are analyzed, and ant colony algorithm is used for further optimization. In order to verify the feasibility of the intelligent transportation system, technologies such as big data edge computing are also used to comprehensively evaluate and study the use of the system. Finally, we analyze the results of the practical application of the intelligent transportation system under the Internet of Things technology. The research results show that the urban intelligent transportation system, supported by the Internet of Things technology, can realize the dynamic planning of the optimal route, help the people to improve their driving experience in the high safety and intellectualization, and greatly avoid a series of problems caused by congestion.

Challenges of post-conflict urban transportation reconstruction in Mogadishu, Somalia

Mogadishu has experienced continuous internal conflicts in the past two decades, which has destroyed most parts of the city. As a result, it faces daunting development challenges to overcome the legacy of the sustained conflicts and fragility. The capital city, Mogadishu, is a significant pillar in building statehood as it forms an integral part of the growth and development of the country. It essentially provides an environment for the revival of socio-cultural activities and economic productivity in post-civil war reconstruction. Urban sprawls from the influx of displaced populations have extended city and town limits in Somalia, and the capital city Mogadishu bears the blunt of this expansion. Urban transportation in Mogadishu is a significant challenge requiring critical attention. Massive investment in urban transportation infrastructure and networks is vital for the city's urban recovery and economic development. However, the literature shows the lack of information and relevant statistics to support transport planning. Many NGOs (non-governmental organisations) and international development agencies are currently conducting surveys to improve the data resource for the post-conflict planning, development and management of the city. This paper evaluates the urban transportation in Mogadishu by providing an assessment of the challenges and opportunities for the new Mogadishu City Transport Planning Approach (MCTPA). The paper's findings could serve as a template for reconstructing the other urban transport systems in other parts of the country.

Beyond fear and abandonment: Public transport resilience during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic challenged urban public transport systems to maintain accessibility and service for daily users while adapting to local health and safety regulations. Developing sustainable and resilient urban policies under such crisis conditions requires understanding the different feelings, experiences and expectations of passengers and how these relate to socio-economic inequalities. Drawing on a mixed-method study in Berlin (Germany), Brussels (Belgium), Stockholm (Sweden) and Tallinn (Estonia), we show how the pandemic outbreak has changed both who uses public transport and how users experience their journeys. Challenging the narratives that portray public transport as a place of fear, we find that remaining passengers assess the risk of contagion lower than those who avoided it completely. We argue that promoting resilient public transport requires policies that address the needs of passengers relying on public transport services. Therefore, we question the current policies under the sustainable mobility paradigm for not taking sufficient account of the feelings, experiences and emotions and particularly of transport-dependent users.

Influence of TOD Modes on Passenger Travel Behavior in Urban Rail Transit Systems

Transit-oriented development (TOD) mode refers to the integrated development of high-density and multi-functional land in the vicinity of core public transportation stations to increase public transportation rates and address problems such as traffic congestion and land shortages. Therefore, it is crucial to comprehend the relationship between TOD areas and the travel behavior of rail transit residents. However, the income level and occupation of residents have a significant impact on their travel behavior, as people tend to choose their residential, work, and entertainment areas based on their economic characteristics. This paper focuses primarily on two aspects: how to distinguish TOD areas from non-TOD areas (specifically, rail stations) and the variations in the travel behavior of the people residing in these areas. Rail stations were first classified via cluster analysis according to the selected TOD indexes; then, a propensity score matching method was applied to control the influence of self-selection behavior. Based on this, the matched results were analyzed to study the difference in the travel behavior characteristics of residents in TOD and non-TOD areas. The results indicate that residents in TOD areas are more likely to travel by public transportation than those from non-TOD areas. The findings of this study promote a people-oriented urban planning concept and would have practical implications for applications of TOD modes on urban public transportation systems.

MGCAF: A Novel Multigraph Cross-Attention Fusion Method for Traffic Speed Prediction.

Traffic speed prediction is an essential part of urban transportation systems that contributes to minimizing the environmental pollution caused by vehicle emissions. The existing traffic speed prediction studies have achieved good results, but some challenges remain. Most previously developed methods only account for road network characteristics such as distance while ignoring road directions and time patterns, resulting in lower traffic speed prediction accuracy. To address this issue, we propose a novel model that utilizes multigraph and cross-attention fusion (MGCAF) mechanisms for traffic speed prediction. We construct three graphs for distances, position relationships, and temporal correlations to adequately capture road network properties. Furthermore, to adaptively aggregate multigraph features, a multigraph attention mechanism is embedded into the network framework, enabling it to better connect the traffic features between the temporal and spatial domains. Experiments are performed on real-world datasets, and the results demonstrate that our method achieves positive performance and outperforms other baselines.

Capacity reduction on urban main roads: How truck drivers adapted, and what effects and consequences they experienced

Urban freight transport is an important issue in sustainable mobility discussions. It constitutes a significant proportion of urban traffic, and expected negative impacts for urban freight transport can be arguments against implementing restrictive measures targeting passenger traffic. The scarcity of empirical studies might lead to over- or underestimation of consequences for urban freight transport. This might slow shifts towards more sustainable mobility or cause unintended negative consequences. A long-planned 14-month capacity reduction in a main road tunnel in Oslo, Norway, causing significantly increased congestion, offered an excellent opportunity to study urban freight transport adaptations, effects and consequences. With truck drivers and logistics professionals as key informants, the study amplifies voices not often heard in research. Truck drivers adapted by avoiding the tunnel during rush hours only to a limited degree, and less than general traffic did. They reported limited flexibility, as routes and trip timing are strongly defined by customer contracts. The wider consequences for drivers were more stress and less predictable workdays. The findings might improve understandings of how truck drivers can and do adapt, and what consequences they experience. This will help authorities and freight companies plan for changes in urban transport systems aimed at sustainable mobility.

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.

Modeling the capacity of multimodal and intermodal urban transportation networks that incorporate emerging travel modes

Given the increasing prevalence of new urban transport modes such as ridesharing, e-hailing, and combined transport, it is essential to evaluate their effects on the capacity of transportation networks. Hence, this paper develops a novel transportation network capacity model to capture the travel behaviors of inter-multimodal mobility in an urban transportation system that incorporates emerging travel modes. The novel model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) problem based on mathematical programming. The CMSTA problem adopts the cross-nested logit model to account for intermodal travel behavior in the modal split phase and the path-sized logit model to account for route overlap in the traffic assignment phase. Moreover, the logit-based trip distribution model is used to capture the dispatch of the e-hailing traffic flow and the matching of ridesharing drivers with passengers. Besides, we consider flow interactions (e.g., cars and buses sharing the same link) in the road network. We customize a solution framework for solving this novel model that adopts the recently developed fast path-based algorithm with the Barzilai–Borwein stepsize strategy to efficiently solve the CMSTA problem, and derive a sensitivity analysis-based (SAB) algorithm to solve the entire bi-level programming problem. The effectiveness of the novel model is verified in numerical experiments that demonstrate the effects of intermodal transportation, e-hailing, and ridesharing on the capacity of a multimodal transportation network.

How do adverse weather conditions affect demands on urban transport systems?

Mode choice research in urban transportation constitutes a very important part of transportation planning in terms of studies such as decision-making on public transportation policies, mode-shifting and traffic calming practices, etc. Mode choice researches, which are usually made for an ordinary day within the scope of transportation masterplan studies, are also carried out for some special cases such as public holidays, adverse weather conditions, and the day of sports competitions, in order to shed light on the decisions that policy-makers and local governments will take in different scenarios. In this study, the changes in the daily user counters of the public transportation systems in Izmir, Turkey, according to the weather conditions were examined. The mode shifts and changes in demands were evaluated according to the adverse weather conditions, and the measures to be taken are discussed.

Analysis of Trip Attraction Models in Morotai CBD (Central Business District)

The development of an area in land use can increase along with the increase in population in Morotai Island Regency, including the Morotai CBD area. In terms of urban transportation systems, generation and attraction have an important role in defining the development of a city, region, or area. The purpose of this research is to analyze of trip attraction modeling in the CBD area of Morotai. The concept of trip attraction modeling is analyzed using regression analysis, with various independent variables. The modeling analysis was carried out with the help of SPSS software using Stepwise multiple linear analysis methods. The results of the study show that the factors that influence the attraction of vehicle in the Morotai CBD area are : the number of visitors (X4), the ratio of visitors against the building area (X10), the ratio of employees against the number of rooms (X13), the number of rooms(X5), the ratio of employees against the building area (X11), as well as the ratio of employees against the number of rooms(X12). And from the results of linear regression analysis, the best transport attraction model was found to be Y 1 = 86.790 + 0.422X 4 – 558.735X 10 + 1.949X 13  for the motorcycle (SM) attraction model and Y 2 = 12.183 + 0.091X 5 – 26.265X 11 + 0.292X 12 for the light vehicle (KR) model.

Recovery Analysis and Maintenance Priority of Metro Networks Based on Importance Measure

The metro network plays a vital role in the urban transportation system. However, the metro network is easily damaged by humans and natural disturbances. This can cause serious economic damage, such as the suspension of metro station operations and line disruptions. Therefore, we conducted this study in order to minimize the loss caused by the damage to the metro network and improve the performance of the network after recovery. Based on the cascading failures of metro networks, this paper proposes a recovery model for metro networks considering the value of time. Then, considering the time value, a new node importance measure is proposed using the determination of maintenance priorities. The maintenance priorities of nodes with different importance values are investigated to minimize network losses. Lastly, the applicability of the method is verified by a metro network in Zhengzhou city.

Barriers to the adoption of the mobility-as-a-service concept: The case of Istanbul, a large emerging metropolis

Megatrends such as urbanization, digitalization, and decarbonization have created the necessity for new and creative approaches to the urban transportation system. As a solution to the problems of the increasingly digitalized urban transportation environment, “Mobility-as-a-Service” (MaaS) was proposed as a new sustainable transportation concept in Helsinki in 2014. With the use of the MaaS concept, residents of a large emerging metropolis, such as Istanbul, Turkey, can be offered a fast, efficient, environment-friendly, and inexpensive way of travel. However, despite the significant benefits of MaaS, there are several factors that can hinder the adoption of MaaS. This paper aims to analyze these barriers and their contextual relationships with each other using Total Interpretive Structural Modeling (TISM) and Matrix-based-Multiplication-Applied-to-a-Classification (MICMAC) methods. The case study has been conducted on an expert group to explore which significant barriers might be encountered during the adoption of a MaaS system in Istanbul. This study also addresses how these barriers should be overcome, and the MaaS concept should be adopted in Istanbul. The results showed that the most significant barrier to adopting the MaaS concept in Istanbul are Laws, Regulations, and Guidelines that primarily include the legal nature of this mobility service. The least important barriers are found to be Customer Acceptance and Labor Shortage. Therefore, the case study results provided a unique perspective for emerging countries in terms of barriers to successful MaaS implementations and revealed significant differences from the developed countries.

Personal Public Transport in Australia: Developments and Prospects

The environmental, social, and economic cost of current car dependence is well known. But people tend to be unwilling to forgo the convenience of private transport. Personal Public Transport (PPT) is a new concept combining the environmental advantages of public transport with the flexibility of the car. The key elements of PPT are new multi-hire modes provided by maxitaxis and taxibuses to supplement single-hire taxis and scheduled services; integration of all modes into a single system; and provision of real-time information and booking systems enabling individual passengers to communicate with the transport system, whether they be at home, on street or in transit.This paper describes how PPT will integrate various technologies, such as automatic vehicle location systems, multi-hire dispatching systems, advanced passenger information systems, and smart card billing systems, together with some of the latest developments in Personal Public Transport.While the technical aspects of PPT are expected to be solvable relatively easily, establishing a complete PPT system will require institutional and regulatory change and a willingness to innovate by both transport operators and regulators. The paper describes changes occurring in Australia in the taxi and bus industries and in regulatory arrangements that will facilitate PPT, and sets out models for establishing PPT systems. It also assesses the potential for PPT from a marketing perspective and its relationship to new developments in urban planning. The paper concludes with a prognosis of how urban transport systems will evolve under the influence of environmental pressures, social values and technological developments, and of how our cities will emerge from the mass transit and private transport eras of the past to the new era of Personal Public Transport and Personal Rapid Transit.

How do technology-enabled bike-sharing services improve urban air pollution? Empirical evidence from China

Technology-enabled bike-sharing services are increasingly being regarded as effective means of reducing air pollution. However, their actual impact on urban air pollution, especially the factors that might amplify these environmental benefits, is still not well understood. Taking advantage of Ofo and Mobike's staggered entry into 98 major Chinese cities as a quasi-natural experiment, this study empirically examines the impact of technology-enabled dockless bike-sharing services on air pollution and its heterogeneity using a difference-in-differences approach. The results show that there is significant heterogeneity in the impact of the entry of bike-sharing services on urban air pollution, while the overall effect is not significant. Specifically, the reduction effect of dockless bike-sharing service entry on air pollution is greater in cities with larger urban populations, longer average commute times, and higher public transit use, and the increase in traffic congestion further amplifies such effects. This study serves as the first empirical analysis of the impact of bike-sharing services on air pollution, providing important and valuable references for policymakers to better utilize these services to improve air quality and develop sustainable urban transport systems.