Search

Travel mode choice (TMC) prediction, improving health parameters, and promoting sustainable transportation systems are crucial for urban planners and policymakers. Past studies show the influence of health on activities, while several studies use multitasking activities and physical activity intensity to study the association between time use and activity travel participation (TU and ATP) and health outcomes. Limited studies have been conducted on the use of transport modes as intermediate variables to study the influence of TU and ATP on health parameters. Therefore, the current study aims to evaluate urban dependency on different transport modes used for daily activities and its influence on health parameters to promote a greener and healthier society and a sustainable transportation system. Pearson's Chi-squared test was used for transport mode classification, and multinominal logit models were used for regression using R programming. A total of five models were developed for motorized, non-motorized, public transport, physical, and social health to study the correlation between transport modes and health parameters. The statistical analysis results show that socio-demographic and economic variables have a strong association with TMC in which younger, male, workers and high-income households are more dependent on motorized transport. It was found that a unit rise in high-income causes a 4.5% positive increase in motorized transport, whereas it negatively influences non-motorized and public transport by 4.2% and 2.2%, respectively. These insights might be useful for formulating realistic plans to encourage individuals to use active transport that will promote sustainable transportation systems and a healthier society. [ABSTRACT FROM AUTHOR]

This paper explores the domain of intelligent transportation systems, specifically focusing on roundabouts as potential solutions in the context of smart mobility. Roundabouts offer a safer and more efficient driving environment compared to other intersections, thanks to their curvilinear trajectories promoting speed control and lower vehicular speeds for traffic calming. The synthesis review supported the authors in presenting current knowledge and emerging needs in roundabout design and evaluation. A focused examination of the models and methods used to assess safety and operational performance of roundabout systems was necessary. This is particularly relevant in light of new challenges posed by the automotive market and the influence of vehicle-to-vehicle communication on the conceptualization and design of this road infrastructure. Two case studies of roundabouts were analyzed in Aimsun to simulate the increasing market penetration rates of connected and autonomous vehicles (CAVs) and their traffic impacts. Through microscopic traffic simulation, the research evaluated safety and performance efficiency advancements in roundabouts. The paper concludes by outlining areas for further research and evolving perspectives on the role of roundabouts in the transition toward connected and autonomous vehicles and infrastructures. [ABSTRACT FROM AUTHOR]

Urban mobility underscores the vital importance of ensuring traffic efficiency on road segments, intersections, and transportation networks, especially in challenging circumstances. In this perspective, the essential approach to improving urban intersection efficiency should involve understanding critical factors for maintaining operational performance in the face of disruptions such as storms. This paper, inspired by a systematic literature review, presents a novel heuristic for evaluating urban intersection efficiency, with resilience as its guiding principle. The methodological path was designed to address the fundamental question: How can urban intersections be designed and managed to ensure efficiency and resilience in the face of disruptions? Drawing inspiration from the Highway Capacity Manual procedure, the methodological approach encompasses both pre-storm and post-storm scenarios, comparing delay times at roundabouts and signalized intersections before and after a storm. The results reveal significant changes in delay times for traffic signals, although the choice between roundabouts and signalized intersections should be context-specific, considering factors like traffic conditions, resilience requirements, and associated trade-offs. By shedding light on the interplay between intersection design, control strategies, and urban resilience, this research provides valuable insights into integrating resilience considerations into intersection performance assessment and management strategies. It also underscores how particular intersection designs can impact efficiency and recovery, essential considerations when assessing whether a road or intersection project is resilient. [ABSTRACT FROM AUTHOR]

Multitasking activities (MTA) are typically thought to enhance general subjective well-being (SWB). However, performing MTA while operating a private vehicle is frequently challenging. Public transportation (PT) can provide an additional option to engage in more pleasurable activities while traveling. Several studies have been conducted on the engagement of different activities while using different transport modes and its influence on physical, social, and mental health. Moreover, numerous studies have been carried out on motorized transport and MTA that resulted in accidents, fatalities, injuries, and even disasters. In addition, several experts studied the influence of health parameters on daily activities. There have, however, only been a few studies on MTA while on PT and its influence on SWB. Therefore, the current study aims to investigate the travel mode choice, the performance of onboard MTA, and its influence on overall SWB. Using random sampling techniques, data on 732 individuals and 191 households—representing 0.029% of the overall population of Bandung, Indonesia—were gathered. Two different models were developed between independent, intermediate, and dependent variables. Statistical Package for Social Sciences (SPSS) was used for descriptive statistics, whereas R software was used for the multilevel linear regression analysis. The model estimation results show that MTA mediates the relationship among socio-demographic and economic variables, built environment, trip and travel parameters, and SWB. A unit increase in PT lines can provide a 1.5% greater opportunity to participate in more onboard MTA; however, a unit increase in MTA can enhance SWB by 5.1% where both the models show satisfactory coefficient of determination (R2). A unit increase in motorized transport caused a 12.9% negative association with MTA and 10.9% with SWB. A unit increase in NMT and PT are 21.7% and 10.2% positively associated with MTA and 19.2% and 13.1% positively associated with SWB. The current study helps policymakers to develop a policy based on PT which allows the individuals to engage in more MTA that enhance SWB and target sustainable transportation system. [ABSTRACT FROM AUTHOR]

Traffic-calming measures (TCMs) are non-invasive devices designed to improve road mobility and urban areas on a human scale. Despite their potential, they have been in use for a long time and now have to deal with the latest technological innovations in the automotive field, such as cooperative driving technologies (CDTs), to improve energy efficiency in cities. The goal of this study is to explore the safety and operational performances of TCMs featuring CDTs in urban areas. An urban-scale road network close to a seaside area in the City of Mazara del Vallo, Italy, was properly redesigned and simulated in AIMSUN to assess several design solutions, where connected and automated vehicles (CAVs) have been employed as a more energy-efficient public transportation system. Preliminarily, the fine-tuning process of model parameters included CAVs and human-operated vehicles (HOVs) flowing through the network up to saturation conditions. The safety of the planned solutions was tested by using surrogate measures. The micro-simulation approach allowed us to know in advance and compare the operational and safety performances of environmentally friendly solutions involving TCMs and CDTs. These results can also support urban road decision makers in pivoting urban-traffic-calming-based design solutions featuring cooperative driving technologies toward energy efficiency transitions for smart cities. [ABSTRACT FROM AUTHOR]

There is increasing interest in connected and automated vehicles (CAVs), since their implementation will transform the nature of transportation and promote social and economic change. Transition toward cooperative driving still requires the understanding of some key questions to assess the performances of CAVs and human-driven vehicles on roundabouts and to properly balance road safety and traffic efficiency requirements. In this view, this paper proposes a simulation-based methodological framework aiming to assess the presence of increasing proportions of CAVs on roundabouts operating at a high-capacity utilization level. A roundabout was identified in Palermo City, Italy, and built in Aimsun (version 20) to describe the stepwise methodology. The CAV-based curves of capacity by entry mechanism were developed and then used as target capacities. To calibrate the model parameters, the capacity curves were compared with the capacity data simulated by Aimsun. The impact on the safety and performance efficiency of a lane dedicated to CAVs was also examined using surrogate measures of safety. The paper ends with highlighting a general improvement with CAVs on roundabouts, and with providing some insights to assess the advantages of the automated and connected driving technologies in transitioning to smarter mobility. [ABSTRACT FROM AUTHOR]

A major component of urban management is studying and evaluating urban resilience in order to minimize the effects of natural hazards. This is because of the increasing number of natural hazards occurring worldwide. A spatial decision support system is presented for modeling urban resilience and selecting resilient zones in response to natural hazards. This system is implemented based on 22 criteria, grouped into three categories: demographics, infrastructure, and environmental. The criteria are then standardized using minimum and maximum methods, and their importance is determined by the analytical hierarchy process (AHP). The resilience maps in various scenarios are prepared using the ordered weighted average (OWA) method. Flow accumulation (distance from fault), vulnerable population density (vulnerable population density), and distance from road network (material type) were regarded as the most important criteria for flood resilience (earthquake resilience) from environmental, demographic, and infrastructure criteria, respectively. There are different areas that are considered to have very low resilience depending on the risk attitude. According a pessimistic scenario, 1% of Tehran's area has very low resilience, while according to an optimistic scenario, 38% has very low resilience. This system can be used by urban planners and policymakers for the purpose of improving resilience to natural hazards in low-resilience areas. [ABSTRACT FROM AUTHOR]

E-scooters as a new form of mobility are gaining more and more popularity. This popularity results from the flexibility of this mode of transport, but above all from the positive impact on the natural environment through the much higher energy efficiency of an e-scooter compared to a motor vehicle (according to the literature the rate is 2 km per kWh equivalent for a motor vehicle and the range is 90–100 km per kWh in the case of an e-scooter). This paper introduces a discussion on the future development of an energy-efficient electric scooter sharing system based on stakeholder analysis methods. The implementation of the e-scooter sharing system involves linking several areas of human activity, including social activity. This, in turn, relates to the interactions and building of relationships with entities, particularly those influencing the provision of services and their effects. The large number of entities and the complexity of the relations between them make it a challenge both to identify stakeholders in the development of the public e-scooter system and to indicate their roles in shaping the sustainable development strategy for urban mobility. The following study was based on the methodological foundations of stakeholder theory and social network analyses. The main research objective of the article is to identify and assign to different groups the stakeholders influencing the sustainable development of energy-efficient e-scooter sharing systems based on Polish cities. An evaluation was carried out using expert methods with a stakeholder analysis, based on matrix and mapping methods, and with the MACTOR application. Relationships and cooperation suggestions were established for each of the stakeholder groups, which could become an important part of the strategic approach to supporting public transport service providers and organizers, as well as allowing for further reductions in energy consumption in the city by introducing such services on a large scale. The cooperation of the entities participating in the implementation of bike-sharing services can contribute to their greater sustainable development and assurance using the new mobility modes, which consume less energy and at the same time make the city energy-efficient. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) have a number of potential advantages, although some research indicates that this technology may increase dependence on private cars. An alternative approach to bringing such technology to market is through autonomous taxis (ATs) and buses, which can assist in making transportation more sustainable. This paper aims at examining the role of attitudinal, travel-related, and individual factors in preferences for a modal shift from conventional cars toward ATs and exclusive-lane autonomous buses (ELABs), exploring the existence of heterogeneity and its possible sources. The proposed mixed logit model with a decomposition of random coefficients uses 1251 valid responses from a stated preference survey distributed in Tehran, in 2019. Results show that there is significant taste variation among individuals with respect to ATs' travel costs, ELABs' travel times, and walking distances to ELAB stations. Furthermore, exploring the sources of heterogeneity indicates that women are more sensitive to ATs' travel costs and walking distances to ELAB stations while they are less sensitive to ELABs' travel times. Moreover, travel time in discretionary activities reduces the utility of ELABs more than it does in mandatory activities. Transportation authorities can use these findings to establish more effective policies for the successful implementation of AVs. [ABSTRACT FROM AUTHOR]

The issue related to parking lots has a multidimensional nature. For the purposes of the article, the analysis covered 113 parking lots located directly next to national roads in the Mazovian Voivodeship (Poland), which is similar in terms of economic development and conditions of the linear infrastructure to other countries in Central Europe. The conducted research included analyzing the correlation of parameters in individual parking lots and those related to nearby roads (traffic volume, technical quality) and the type of area in which they occurred (population density). In addition, the presented results describe the capacity of parking in the analyzed region in terms of the number of available parking slots for heavy goods vehicles, the size of the additional operating area, and the presence of security-related elements (fencing, lighting, physical protection, monitoring). The analysis demonstrated a correlation between some parameters (type of nearby road and security rs = 0.35, area size and number of slots rs = 0.35) and significant differences in results between private and public parking lots (average number of slots 18 versus 34, percent of most secured parkings 45% versus 69%). The obtained innovative results can be used by public institutions and entities providing parking services to reorganize the space at parking places and to conduct more effective analyses from the point of view of future investments in infrastructure accompanying the public road network. [ABSTRACT FROM AUTHOR]

In low-latitude areas less than 10° in latitude angle, the solar radiation that goes into the solar still increases as the cover slope approaches the latitude angle. However, the amount of water that is condensed and then falls toward the solar-still basin is also increased in this case. Consequently, the solar yield still is significantly decreased, and the accuracy of the prediction method is affected. This reduction in the yield and the accuracy of the prediction method is inversely proportional to the time in which the condensed water stays on the inner side of the condensing cover without collection because more drops will fall down into the basin of the solar-still. Different numbers of scraper motions per hour (NSM), that is, 1, 2, 3, 4, 5, 6, and 7, are implemented to increase the hourly yield of solar still (HYSS) of the double-slope solar still hybrid with rubber scrapers (DSSSHS) in areas at low latitudes and develop an accurate model for forecasting the HYSS. The proposed model is developed by determining the best values of the constant factors that are associated with NSM, and the optimal values of exponent (n) and the unknown constant (C) for the Nusselt number expression (Nu). These variables are used in formulating the models for estimating HYSS. The particle swarm optimization (PSO) algorithm is used to solve the optimization problem, thereby determining the optimal yields. Water that condensed and accumulated inside the condensing glass cover of the DSSSHS is collected by increasing NSM. This process increases in the specific productivity of DSSSHS and the accuracy of the HYSS prediction model. Results show that the proposed model can consistently and accurately estimate HYSS. Based on the relative root mean square error (RRMSE), the proposed model PSO–HYSS attained a minimum value (2.81), whereas the validation models attained Dunkle's (78.68) and Kumar and Tiwari's (141.37). [ABSTRACT FROM AUTHOR]

The growing traffic on city streets leads to traffic disruptions, lowering the level of road safety, as well as the problem of finding a vacant parking space. Drivers looking for a vacant parking space on the street generate so-called search traffic. Paid parking zones are introduced to increase the availability of parking spaces for more drivers in many cities around the world. The development in the technology and information sector has contributed to the development of systems guiding drivers to vacant parking spaces. This article aims to analyze drivers' subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. Data from the Municipal Roads Authority in Gliwice (Poland) were obtained for the study, covering the use of parking spaces in the paid parking zone covered by dynamic parking information. Moreover, a survey was conducted among users of the paid parking zone in Gliwice. The answers of the respondents were used to build a logit model that allows determining the probability of a driver's positive subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. The results from the model allow the characterization of drivers who positively assess the ease of finding a vacant parking space in the area equipped with vehicle detection devices. In addition, it is possible to reach a group of drivers who negatively assessed the ease of finding a vacant parking space to learn about the factors that may cause them to change their assessment to a positive one. The research results allow city authorities to better manage parking spaces equipped with vehicle detection devices in the paid parking zone. This may change the negative assessment of the ease of finding a vacant parking space into a positive one. [ABSTRACT FROM AUTHOR]

Despite the potential of connected and automated vehicles (CAVs), there are still many open questions on how road capacity can be influenced and what methods can be used to assess its expected benefits in the progressive transition towards fully cooperative driving. This paper contributes to a better understanding of the benefits of CAV technologies by investigating mobility-related issues of automated vehicles operating with a cooperative adaptive cruise control system on roundabout efficiency using microscopic traffic simulation. The availability of the adjustment factors for CAVs provided by the 2022 Highway Capacity Manual allowed to adjust the entry capacity equations to reflect the presence of CAVs on roundabouts. Two mechanisms of entry maneuver based on the entry lane type were examined to compare the capacity target values with the simulated capacities. The microscopic traffic simulator Aimsun Next has been of great help in building the "what-if" traffic scenarios that we analysed to endorse hypothesis on the model parameters which affect the CAVs' capabilities to increase roundabouts' throughput. The results highlighted that the increasing penetration rates of CAVs have greater impacts on the operational performances of roundabouts, and provided a synthetic insight to assess the potential benefits of CAVs from an efficiency perspective. [ABSTRACT FROM AUTHOR]

Predicting household vehicle ownership (HVO) is a crucial component of travel demand forecasting. Furthermore, reliable HVO prediction is critical for achieving sustainable transportation development objectives in an era of rapid urbanization. This research predicted the HVO using a support vector machine (SVM) model optimized using the Bayesian Optimization (BO) algorithm. BO is used to determine the optimal SVM parameter values. This hybrid model was applied to two datasets derived from the US National Household Travel Survey dataset. Thus, two optimized SVM models were developed, namely SVMBO#1 and SVMBO#2. Using the confusion matrix, accuracy, receiver operating characteristic (ROC), and area under the ROC, the outcomes of these two hybrid models were examined. Additionally, the results of hybrid SVM models were compared with those of other machine learning models. The results demonstrated that the BO algorithm enhanced the performance of the standard SVM model for predicting the HVO. The BO method determined the Gaussian kernel to be the optimal kernel function for both datasets. The performance of the SVM#1 model was improved by 4.27% and 5.16% for the training and testing phases, respectively. For SVM#2 model, the performance of this model was improved by 1.20% and 2.14% for the training and testing phases, respectively. Moreover, the BO method enhanced the AUC of the SVM models used to predict the HVO. The hybrid SVM models also outperformed other machine learning models developed in this study. The findings of this study showed that SVM models hybridized with the BO algorithm can effectively predict the HVO and can be employed in the process of travel demand forecasting. [ABSTRACT FROM AUTHOR]

The paper presents a discussion concerning the development of projects regarding active travel with the policy of sustainable mobility, with active school transport in southern Poland being taken into special consideration. The implementation of the idea of sustainable school travel planning involves linking several social groups, including traffic planners and organizers, school administrators, governments, parents, and children. This, in turn, requires considering the criteria reported by all parties when choosing a scenario for the region's development in terms of transport solutions. The following study was based on the methodological foundations of multicriteria decision-making analysis. The research purpose of this paper is to identify and classify the actions, policies, and scenarios of active travel projects for the sustainable development of mobility based on the cities of southern Poland. The evaluation was carried out through expert methods with multicriteria decision-making tools based on the MULTIPOL (MULTI-criteria and POLicy) prospective analysis technique. It allowed for the selection of the most probable policy, which covered the six actions considered by the experts to be the most significant for the development of the active school transport system in the analyzed region. Such actions are as follows: identification of walking school bus routes, modernization of crosswalk lines, planning of walking and cycling routes to schools, promoting safety educational programs, distribution of active school transport booklets and cycling, and pedestrian skills training workshops. The paper presents a new method to evaluate the policies and actions regarding promoting sustainable (active) travel to school. The innovative approach results from assembling a mixed group of people (stakeholders) as experts. The mix of experts consisting of users (pupils and parents), practitioners, and scientist experts in this field allowed us to score policies, actions, and scenarios, enabling a wider spectrum of assessment than before. [ABSTRACT FROM AUTHOR]

Numerous studies have reported the effective use of artificial intelligence approaches, particularly artificial neural networks (ANNs)-based models, to tackle tunnelling issues. However, having a high number of model inputs increases the running time and related mistakes of ANNs. The principal component analysis (PCA) approach was used in this work to select input factors for predicting tunnel boring machine (TBM) performance, specifically advance rate (AR). A reliable and precise forecast of TBM AR is desirable and critical for mitigating risk throughout the tunnel building phase. The developed PCAs (a total of four PCAs) were used with the artificial bee colony (ABC) method to predict TBM AR. To assess the created PCA-ANN-ABC model's capabilities, an imperialist competitive algorithm-ANN and regression-based methods for estimating TBM AR were also suggested. To evaluate the artificial intelligence and statistical models, many statistical evaluation metrics were evaluated and generated, including the coefficient of determination (R2). The findings indicate that the PCA-ANN-ABC model (with R2 values of 0.9641 for training and 0.9558 for testing) is capable of predicting AR values with a high degree of accuracy, precision, and flexibility. The modelling approach utilized in this study may be used to other comparable studies involving the solution of engineering challenges. [ABSTRACT FROM AUTHOR]

10.3390/en14216931 15 Pérez-Acebo H., Ziólkowski R., Gonzalo-Orden H. Evaluation of the radar speed cameras and panels indicating the vehicles' speed as traffic calming measures (TCM) in short length urban areas located along rural roads. The effects were identified for the local road transportation system by comparing freight road transportation performance in two options: (i) with investment and (ii) without investment. Sustainable economic, social, and environmental effects concerned generalized freight road transportation costs, i.e., truck operating costs and costs of truck drivers' working time, as well as freight transit time, energy consumption, greenhouse gas emissions, and environmental savings. However, transport consumes enormous energy resources; hence, all solutions in the scope of improving transportation infrastructure, vehicle construction, as well as modeling users' and drivers' behavior may constitute an element contributing to broadly saving energy. [Extracted from the article]

Bike-sharing is known as a sustainable form of transportation. This travel mode is able to tackle the "last mile" transit issue and deliver financial, well-being, and low-carbon lifestyle advantages to users. To date, many studies have analysed the influence of various factors, including built environments, on bike-sharing ridership. However, no study has exclusively synthesised these findings regarding the association between built-environment attributes and bike-sharing ridership. Thus, in this study, a systematic literature review was conducted on 39 eligible studies. These studies were assessed with respect to (1) bike-sharing usage, (2) studies' geographical distribution, (3) data collection and analysis method, and (4) built environment factor type. Most studies were carried out in the US and Chinese cities. Variables associated with diversity, density, and distance to public transport stations and public transport infrastructure were frequently employed by the studies reviewed. It was found that BS stations with an average capacity of 24.63 docks and street network systems with an average length of 12.57 km of cycling lanes had a significant impact on the bike-sharing ridership. The findings of these studies were combined, and a series of recommendations were proposed based on them for bike-sharing service providers and researchers in academia. The findings of this evaluation can help practitioners and scholars understand the important built environment elements that influence bike-sharing ridership. Knowledge in this field will enable bike-sharing service providers to direct their resources sufficiently to enhance the more essential aspects of bike-sharing users' satisfaction. [ABSTRACT FROM AUTHOR]

Increasing private car ownership and car dependency has led to a low share of walking as an active mode as well as congestion, air pollution, and health problems in developing countries. This paper aims to identify and compare the impacts of a selection of socio-economic, travel-related, and built environment variables on walking likelihood and respondents' sensitivity to the walking distance, both for discretionary and mandatory trips. The analysis drew its origin from 14,463 responses acquired through an extensive travel survey conducted in the city of Qazvin, Iran. The estimated binary logit coefficients show people's heterogeneity in the walking behavior for discretionary and mandatory trips. The results report a higher likelihood of walking on mandatory trips at almost all distances than the discretionary ones. Furthermore, investigating individual heterogeneity in different trip distances reveals that people aged less than 14 are more likely to choose walking on mandatory trips longer than 2400 m. Besides, those aged 25–44 years old or above 65 have less tendency to choose walking on mandatory trips with distances of 2000–2400 m and 800–1200 m, respectively. These findings are almost different on discretionary trips; compared to other age groups, people aged 15–24 years are less likely to choose walking on discretionary trips with a distance of 800–1200 m. Moreover, in trip distances of 1200–1600 m, the elderlies have a greater tendency to choose walking compared to other age groups. Some implications for more sustainable mobility in human-oriented urban environments are also presented and critically discussed. [ABSTRACT FROM AUTHOR]

In line with globally shared environmental sustainability goals, the shift towards citizen-friendly mobility is changing the way people move through cities and road user behaviour. Building a sustainable road transport requires design knowledge to develop increasingly green road infrastructures and monitoring the environmental impacts from mobile crowdsourced data. In this view, the paper presents an empirically based methodology that integrates the vehicle-specific power (VSP) model and microscopic traffic simulation (AIMSUN) to estimate second-by-second vehicle emissions at urban roundabouts. The distributions of time spent in each VSP mode from instantaneous vehicle trajectory data gathered in the field via smartphone were the starting point of the analysis. The versatility of AIMSUN in calibrating the model parameters to better reflect the field-observed speed-time trajectories and to enhance the estimation accuracy was assessed. The conversion of an existing roundabout within the sample into a turbo counterpart was also made as an attempt to confirm the reproducibility of the proposed procedure. The results shed light on new opportunities in the environmental performance evaluation of road units when changes in design or operation should be considered within traffic management strategies and highlighted the potential of the smart approach in collecting big amounts of data through digital communities. [ABSTRACT FROM AUTHOR]

The paper introduces a discussion regarding the development of a public bike-sharing system, considering random factors, based on selected external environmental analysis methods. The global energy crisis is forcing scientists to continuously improve energy-efficient sustainable methods and scientific solutions. It is particularly important in transportation since transport activities and the constant increase in the number of vehicles have a large share in global energy consumption. The following study investigates the social, technological, economic, environmental, and political aspects of bike-sharing systems in cities. The research purpose of the article is to select the most important macro-environmental factors and their mutual interaction influencing the sustainable development of bike-sharing systems based on the Polish cities case study. The evaluation was carried out through expert methods with STEEP environmental analysis, evaluation of factors with the weighted score, and structural analysis method with MICMAC computer application. The classification of key factors influencing the development of a bike-sharing system has divided them into five groups. It can support public transport service providers and organizers. This can optimize the planning process with decision-making based on future environmental trends. [ABSTRACT FROM AUTHOR]

The goal of smart cities and sustainable transport is to ensure the efficient movement of people while minimizing a negative impact on the environment. Many cities around the world conduct a policy aimed at limiting parking spaces; however, the complete elimination of parking spaces in cities currently does not seem possible. Parking vehicles cause disturbances in road traffic by searching for a parking space and performing the parking maneuver. This article analyzes the impact of the parking maneuver on the capacity of the inlets of intersections with traffic lights, and the significance of the time it takes to enter and exit a parking space on road traffic disturbance areas under Polish conditions. The research is carried out in on-street parking, characterized by different positions of the parking space to the road, the different surfaces of parking spaces, and the geometry of the road next to which the parking spaces are located. Differences in the time of entry to and exit from the parking space between the research areas indicate that different characteristics of the parking spaces affect the time of the parking maneuver. Drivers wait for the acceptable distance between vehicles on the road into which the vehicle can exit from the parking space. Drivers exiting from perpendicular parking spaces more often cause traffic disruptions than in the case of parallel parking spaces, due to limited visibility. The occupancy of parking spaces directly next to the analyzed ones also affects the time of entry to and exit from the parking space. However, between the time of entry to or exit from the parking space, and the use of the parking space, there is no relationship. This finding indicates that more factors determine the time of entry to and exit from the parking space. The results presented in the article show the need to conduct further research on the impact of parking maneuvers on the capacity of intersections with traffic lights for road traffic conditions in Poland. The results of the research will allow for the design and construction of an optimal parking infrastructure that will meet the needs of road users, while minimizing the negative impact on road conditions and the natural environment following sustainable development. [ABSTRACT FROM AUTHOR]

Transportation and technological development have for centuries strongly influenced the shaping of urbanized areas. On one hand, it undoubtedly brings many benefits to their residents. However, also has a negative impact on urban areas and their surroundings. Many transportation and technological solutions lead, for example, to increased levels of pollution, noise, excessive energy use, as well as to traffic accidents in cities. So, it is important to safe urban development and sustainability in all city aspects as well as in the area of road transport safety. Due to the long-term policy of sustainable transport development, cycling is promoted, which contributes to the increase in the number of this group of users of the transport network in road traffic for short-distance transport. On the one hand, cycling has a positive effect on bicyclists' health and environmental conditions, however, a big problem is an increase in the number of serious injuries and fatalities among bicyclists involved in road incidents with motor vehicles. This study aims to identify factors that influence the occurrence and severity of bicyclist injury in bicyclist-vehicle crashes. It has been observed that the factors increasing the risk of serious injuries and deaths of bicyclists are: vehicle driver gender and age, driving under the influence of alcohol, exceeding the speed limit by the vehicle driver, bicyclist age, cycling under the influence of alcohol, speed of the bicyclist before the incident, vehicle type (truck), incident place (road), time of the day, incident type. The obtained results can be used for activities aimed at improving the bicyclists' safety level in road traffic in the area of analysis. [ABSTRACT FROM AUTHOR]

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics. [ABSTRACT FROM AUTHOR]

The use of a Model Predictive Controller (MPC) in an urban traffic network allows for controlling the infrastructure of a traffic network and errors in its operations. In this research, a novel, stable predictive controller for urban traffic is proposed and state-space dynamics are used to estimate the number of vehicles at an isolated intersection and the length of its queue. This is a novel control strategy based on the type of traffic light and on the duration of the green-light phase and aims to achieve an optimal balance at intersections. This balance should be adaptable to the unchanging behavior of time and to the randomness of traffic situations. The proposed method reduces traffic volumes and the number of crashes involving cars by controlling traffic on an urban road using model predictive control. A single intersection in Tehran, the capital city of Iran, was considered in our study to control traffic signal timing, and model predictive control was used to reduce traffic. A model of traffic systems was extracted at the intersection, and the state-space parameters of the intersection were designed using the model predictive controller to control traffic signals based on the length of the vehicle queue and on the number of inbound and outbound vehicles, which were used as inputs. This process demonstrates that this method is able to reduce traffic volumes at each leg of an intersection and to optimize flow in a road network compared to the fixed-time method. [ABSTRACT FROM AUTHOR]

Challenges that emerge in roundabout design are mostly related to space constrictions and provision of appropriate deflection around the central island. This can result in speed profiles on roundabouts that might reduce their potential as a noise abatement measure. Because of this, the impact of a roundabout on noise levels and its applicability as a traffic calming device and a noise abatement measure should be investigated in the early design stage, by modeling noise levels. In this paper, the following hypothesis is tested: vehicle movement trajectories, defined during the fastest path performance check in roundabout early design phase, can be used as the road traffic noise sources when modeling noise at roundabouts using static noise model. This procedure (1) simplifies the preparation of the noise model, (2) results in a model that is closer to the real-world in terms of traffic flow conditions, (3) allows the noise calculations in the early stages of roundabout design, and (4) includes the influence of roundabout deflection on calculated noise levels. The abovementioned simplifications of the road traffic noise modeling process should encourage the optimization of roundabout geometry in terms of its noise reduction capabilities in the preliminary design phase of these intersections. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic created an enormous disruption to the everyday life of the modern society. Among the various urban systems, transportation services were among those that suffered the most significant impacts, particularly severe in the case of highways. This paper addresses the challenges and responses to the pandemic from a private highway operator's perspective and from a multidisciplinary perspective. Highway operators faced two main challenges: on one hand, the need to cope with the potential disruption caused by the pandemic and a national lockdown for almost three months, the provision of road services, and the requirement to ensure the proper operation and maintenance, and on the other hand, the strong negative impact of the pandemic on levels of traffic. Our case study shows that the operator's management response in question is essentially characterised by being a first response to short term impacts while balancing for workers health and safety, engineering and management, internal business management, and overall economic impact. Highway operators were hardly prepared for such an event and became more focused on prioritising their employees and clients' safety to avoid service disruption. Regarding levels of traffic, the pandemic has had severe effects, although to a varying degree, depending on the different types of vehicles (heavy, light, passenger, freight, among other types of vehicles) and the location of highways (coastal vs. interior). The lessons learnt can be valuable in future disruptive events and for other highway concession operators. [ABSTRACT FROM AUTHOR]

The European Union policy strategies on the sustainability of the transport system pursue the goals of maximizing safety and environmental benefits and reducing the severity and frequency of crashes, congestion, and pollutant emission rates. A common issue is the planning of the most effective solution for operational and safety management at intersections. In this study, an egg turbo roundabout is proposed as the alternative solution to a conventional roundabout in Southern Italy which suffers from traffic congestion. A comparative analysis is carried out using microsimulation techniques to investigate the safety effects and operational improvements of converting a traditional priority intersection into standard roundabout or turbo roundabout layout. In particular, the VISSIM software is used to explore the most relevant operational performance measures: queue length, travel times and delays. The lowest values of these measurements are recorded for the simulated turbo roundabout, thus making this scheme more appropriate in terms of operational performances. With regard to safety analysis, the Surrogate Safety Assessment Model (SSAM) is used to collect information on the predicted number of conflicts, the probability, and severity of the potential collisions. The results suggest that, for the specific case study, the safety levels of the standard roundabout and the turbo roundabout are approximately comparable. [ABSTRACT FROM AUTHOR]

This paper presents the synthesis and validation of multidimensional driving cycles represented by vehicle velocity, vehicle acceleration, and road slope profiles. For this purpose, a rich set of city bus driving cycles has been recorded. First, a Markov chain model is established based on velocity, acceleration, road slope and road slope time derivative states. Next, a large set of synthetic driving cycles is generated by using a corresponding 8D transition probability matrix, which is implemented in a sparse form based on a dictionary of keys to improve computational efficiency and reduce memory requirements. In support of synthetic driving cycles validation, a number of time- and frequency-domain statistical features are considered, including unique cross-correlation velocity–acceleration–road slope indicators. To predict fuel consumption related to synthetic driving cycles, an accurate neural network model is introduced which uses a fixed 3D histogram of counted discrete velocity, acceleration, and road slope inputs. The significance of each nominated statistical feature and its impact on fuel consumption is revealed by means of linear regression modelling and least absolute shrinkage and selection operator (LASSO) feature selection method. A model having only several most significant features as inputs and fuel consumption as output is proposed to be used for unambiguous single-criterion validation of synthetic driving cycles with respect to recorded ones. Finally, the proposed validation approach is verified against a widely used method relying on minimization of statistical feature deviations with respect to true values. The results point out that, by applying the proposed synthesis and validation method, it is possible to extract most representative synthetic driving cycles in a straightforward and computationally efficient way. The main anticipated applications include various simulation-based analyses that require representative synthetic driving cycles and/or accurate vehicle energy consumption predictions. [ABSTRACT FROM AUTHOR]

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes road potential, lane potential and obstacle potential. Considering the driving distinction between an ambulance and a regular vehicle, especially in congested traffic, an adaptive potential function for a lane line is constructed in association with traffic conditions. The attractive potential is constructed with target potential, lane-velocity potential and tailgating potential. The design of lane-velocity potential is to characterize the influence of velocity on other lanes so as to prevent unnecessary lane-changing behavior for the sake of time-efficiency. The results obtained from simulation demonstrate that the proposed method yields a good performance for ambulance driving in an urban area, which can provide support for designing an ambulance support system for the ambulance personnel and dispatcher. [ABSTRACT FROM AUTHOR]

Keeping the basic principles of sustainable development, it must be highlighted that decisions about transport safety projects must be made following expert preparation, using reliable, professional methods. A prerequisite for the cost–benefit analysis of investments is to constantly monitor the efficiency of accident forecasting models and to update these continuously. This paper presents an accident forecasting model for urban areas, which handles both the properties of the public road infrastructure and spatial dependency relations. As the aim was to model the urban environment, we focused on the road public transportation modes (bus and trolley) and the vulnerable road users (bicyclist) using shared infrastructure elements. The road accident data from 2016 to 2018 on the whole road network of Budapest, Hungary, is analyzed, focusing on road links (i.e., road segments between junctions) by applying spatial econometric statistical models. As a result of this article, we have developed a model that can be used by decision-makers as well, which is suitable for estimating the expected value of accidents, and thus for the development of the optimal sequence of appropriate road safety interventions. [ABSTRACT FROM AUTHOR]

In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the number of passengers and vehicles on the road and the capacity limitations of transport networks, it has become necessary to use new technologies for intelligent control and traffic management. Intelligent transport systems use advanced technologies in the field of data gathering, information processing, and traffic control to meet current transport needs. To be able to effectively control and manage road traffic, it is necessary to have reliable mathematical models that allow for a faithful representation of the real traffic conditions. Models of this type are usually the basis of complex algorithms used in practice in road traffic control. The application of appropriate models reflecting the behavior of road users contributes to the reduction of congestion, the vehicles travel time on the transport network, fuel consumption and the emissions, which in turn support broadly understood energy savings. The article proposes a model that allows for the estimation of the maximum queue size at the signal-controlled intersection approach (so-called: maximum back-of-queue). This model takes into account the most important traffic characteristics of the vehicles forming this queue. The verification allowed for the conclusion that the proposed model is characterized by high compliance with the actual traffic and road conditions at the intersections with signal controllers located in built-up areas in Poland. The obtained compliance confirms the possibility of using the model for practical applications in calculating the maximum back-of-queue at signal-controlled intersections located in built-up areas in Poland. [ABSTRACT FROM AUTHOR]

This paper focuses on effects of implementing zero-emission buses in public transport fleets in urban areas in the context of electromobility assumptions. It fills the literature gap in the area of research on the impact of the energy mix of a given country on the issues raised in this article. The main purpose of this paper is to identify and analyse economic effects of implementing zero-emission buses in public transport in cities. The research area was the city of Szczecin, Poland. The research study was completed using the following research methods: literature review, document analysis (legal acts and internal documents), case study, ratio analysis, and comparative analysis of selected variants (investment variant and base variant). The conducted research study has shown that economic benefits resulting from implementing zero-emission buses in an urban transport fleet are limited by the current energy mix structure of the given country. An unfavourable energy mix may lead to increased emissions of SO2 and CO2 resulting from operation of this kind of vehicle. Therefore, achieving full effects in the field of electromobility in the given country depends on taking concurrent actions in order to diversify the power generation sources, and in particular on increasing the share of Renewable Energy Sources (RES). [ABSTRACT FROM AUTHOR]

The basic function of the Park and Ride (P&R) facility is to allow users to leave their vehicle on the outskirts of the city and to continue their journey to the city center using means of public transport, e.g., bus, tram, trolleybus, subway, train, or bike. In the first part of the paper, an analysis of the selected factors related to the functioning of P&R facilities in Warsaw (Poland) was performed. The main purpose of this paper was to identify and quantify the influence factors determining the choice of P&R facility during a journey. This analysis was performed for three hypothetical journey scenarios. A list of potential factors determining the choice of P&R facility during travel was compiled after conducting previous research in this area and studying the worldwide scientific literature on the subject. The structural parameters of the multinomial logit model were estimated based on the data from the survey conducted in Warsaw. The results of the analyses indicate that the decision to choose a hypothetical journey scenario depends on many factors, but primarily on the level of education, the number of years of having a driving license, age, the number of kilometers traveled during the year, and the performed activity. [ABSTRACT FROM AUTHOR]

The park and ride (P&R) parking type is usually located near peripheral public transport stops. These parking places are dedicated to people who, after leaving their vehicle in the parking, continue their journey to the city center using some form of public transport such as bus, metro, rail or tram systems. This article aims to examine the features associated with P&R parking locations in use in Cracow (Poland). The analysis included the number of entries and exits to and from parking during particular periods of the day, week and year, parking time of vehicles, and parking space use. A parking peak hour factor was also calculated, which expresses the crowding degree of vehicle entries/exits in/out parking during a particular period. In addition, the paper presents an analysis of factors determining users to P&R parking use. In the modeling process, logit models were used, which, as stated after analyzing the literature on the subject, were already used in various countries around the world to describe the behavior of P&R parking users. However, so far, such research relating to Polish conditions has been not published in the available literature. The obtained results allowed to state that the most important factors determining the likelihood of using P&R parking in Cracow are age, number of years having a driving license, monthly income (gross), and an average number of trips made during a day. Other variables, which not included in the study, can influence the P&R parking use. However, the presented results are the basis for conducting furtherer, more in-depth analyses based on a larger number of independent variables that may determine the P&R parking use. [ABSTRACT FROM AUTHOR]

The bike-sharing system allows urban residents to rent a bike at one of the rental stations located in the city, use them for their journey, and return them to any other or the same station. In recent years, in many cities around the world, such systems were established to encourage their residents to use bikes as an element of enhancing sustainable mobility and as a good complement to travel made using other modes of transport. The main purpose of this article is to present the results of an analysis of the functioning of the bike-sharing system in Warsaw (Poland). Moreover, the article presents an analysis of the accessibility to individual stations. An important aspect is that the bike-sharing system has been popular among users and that more people use it. Therefore, the city should be provided with a dense network of conveniently located bike-sharing stations. Also, the quality of the bike-sharing system should be an adjustment to the user's expectations. In connection with the above, the article also presents the results of the analysis of factors affecting bike-sharing system usage as well as the level of satisfaction connected with bike-sharing system usage. The results of the analysis showed that there is a strong positive correlation between these variables. The obtained results can be helpful for carrying out activities whose purpose is to increase the bike-sharing system usage as well as to increase the level of satisfaction connected with bike-sharing system usage. [ABSTRACT FROM AUTHOR]

The article presents the calculation of roundabout entry capacity as a case study based on roundabouts located in Tokyo, Japan, and Tokyo surroundings. The analysis was conducted as part of the project entitled "Analysis of the applicability of the author's method of roundabouts entry capacity calculation developed for the conditions prevailing in Poland to the conditions prevailing at roundabouts in Tokyo (Japan) and in the Tokyo surroundings". The main aim and the research question was whether the author's model of roundabouts entry capacity calculation constructed for the conditions prevailing in Poland after calibration is suitable to calculate roundabout entry capacity of roundabouts located in Tokyo and in the Tokyo surroundings. In order to perform the calibration in 2019, measurements were taken at the single-lane roundabouts located in Tokyo and Tokyo surroundings. The model calibration revealed that it is possible to evaluate the entry capacity of roundabouts located in Tokyo and in Tokyo surroundings using the author's model. [ABSTRACT FROM AUTHOR]