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Evacuation mobility of the population during military operations or emergencies is one of the most vital tasks in ensuring the safety and rescue of citizens. Planning this mobility requires a conceptual approach, system analysis, and a comprehensive preparatory stage. The primary task for organising the population’s bus transportation during evacuation is planning routes and determining their time parameters. This process requires preliminary determination of the points of traffic organisation, establishment of routes and meeting points, allocation of resources, and coordination of work with other types of passenger transport. The study aims to develop the sequence of formation of evacuation bus routes in the Saltiv residential area of Kharkiv and to establish the functional effect of operational parameters of their work on the duration of population evacuation. The methodological basis for building a network of evacuation bus routes is a developed structural model of the impact of input parameters on the general evacuation time for the population and the transport capabilities of the routes. This model describes the functional relationship between the existing volume of passenger transportation on urban transport routes, the share of passengers subject to evacuation, the number of stopping points on evacuation routes, the length of routes, the speed of movement, the time of boarding and disembarking the passengers, the capacity of buses and their number. The criterion for evaluating the efficiency of the routes is the total time of population evacuation, depending on the number of buses on the routes. Based on the analysis of the location of shelter facilities and transfer stations on the subway line, we established that it is expedient to create seven evacuation routes that ensure the timely evacuation of the population. After assessing the available passenger traffic on city transport routes, we determined the potential demand for evacuation transportation. The a

Lengthy motorised public transport travel times can decrease opportunities for physical activity. However, public transport use includes incidental exercise to, from and between stops, forming an important component of meeting physical activity recommendations. The aims of this thesis are therefore to estimate public transport commuter travel time and physical activity in Sydney, Australia. Chrono-urbanism targets, measuring time travelled from home to destinations, like the 30-minute city promise average commuting times of one hour per day. However, existing 30-minute city calculations either do not include first- and/or last- public transport segments or transfers. Most research examining public transport-related physical activity relies on expensive travel survey data. Studies using GPS or accelerometers have higher accuracy but typically smaller sample sizes. Smart card data provide a cost-effective approach to modelling door-to-door travel times for the 30-minute city and public transport-related physical activity. Travel times and physical activity were modelled using GIS and Python scripting. This involved generating and matching a synthetic population to smart card data, using a trip planning API to estimate motorised public transport times, conducting network analyses, and distance conversions to steps and/or MET minutes. The 30-minute city goal for public transport commutes in Sydney is yet to be realised when a door-to-door approach is used. For public transport commuters, while the median commute time for the analysis without the first- and last-segment was 25 minutes, the door-to-door median was 44 minutes. Such varying estimates could influence different infrastructure policies. A mean of 2400 steps per day weighted across modes was modelled for public transport commuters. A mean of 89.1 MET minutes per day from walking and/or cycling components was modelled. An additional 36.5 and 116.3 MET minutes per day could be gained by commuters with a potential

The paper is focused on discussion of logistics and transport reality, comparing current conditions with what they could have been if the Central Bi-Oceanic Railway Corridor, also known as “The Panama Canal of the 21st Century” projected to join the Pacific and Atlantic Oceans in South America linking Brazil, Bolivia and Peru, had been built. The analysis will be carried out taking into consideration different aspects of paramount importance in the economic global context, focusing on operational costs, energy consumption, environment impact and a quantification of external costs., Příspěvek je zaměřen na diskusi logistické a dopravní reality a porovnání současné podmínky s těmi, které by umožnil Centrální mezioceánský železniční koridor, nazývaný také jako "Panamský průplav 21. století", který byl plánován k propojení Atlantského a Tichého oceánu v Jižní Americe přes Brazílii, Bolívii a Peru. Analýza byla provedena s ohledem na různé aspekty prvořadého významu v globálním ekonomickém kontextu se zaměřením na provozní náklady, spotřebu energie, dopad na životní prostředí a kvantifikaci externích nákladů.

Evacuation mobility of the population during military operations or emergencies is one of the most vital tasks in ensuring the safety and rescue of citizens. Planning this mobility requires a conceptual approach, system analysis, and a comprehensive preparatory stage. The primary task for organising the population’s bus transportation during evacuation is planning routes and determining their time parameters. This process requires preliminary determination of the points of traffic organisation, establishment of routes and meeting points, allocation of resources, and coordination of work with other types of passenger transport. The study aims to develop the sequence of formation of evacuation bus routes in the Saltiv residential area of Kharkiv and to establish the functional effect of operational parameters of their work on the duration of population evacuation. The methodological basis for building a network of evacuation bus routes is a developed structural model of the impact of input parameters on the general evacuation time for the population and the transport capabilities of the routes. This model describes the functional relationship between the existing volume of passenger transportation on urban transport routes, the share of passengers subject to evacuation, the number of stopping points on evacuation routes, the length of routes, the speed of movement, the time of boarding and disembarking the passengers, the capacity of buses and their number. The criterion for evaluating the efficiency of the routes is the total time of population evacuation, depending on the number of buses on the routes. Based on the analysis of the location of shelter facilities and transfer stations on the subway line, we established that it is expedient to create seven evacuation routes that ensure the timely evacuation of the population. After assessing the available passenger traffic on city transport routes, we determined the potential demand for evacuation transportation. The a

This study addresses the Distributed Flexible Job-Shop Scheduling Problem (DFJSP) while considering the delivery of customer orders and transportation time. To tackle the problem, a mathematical model is presented, and a novel variant of the Genetic Algorithm (GA), called Time-Travel GA (TTGA), is developed. The optimization objectives include minimizing the total orders’ delivery time to the related customers, reducing transportation and production costs, reducing manufacturing pollution, and maximizing the quality of completed orders. The performance of TTGA is tested by implementing it in a real-life manufacturing setting. Additionally, TTGA results are compared with those of four other algorithms over a set of test problems. Furthermore, the solutions obtained by TTGA are compared with the optimal solutions obtained by a commercial solver for small-size problems. The results of these comparisons collectively demonstrate the promising performance of TTGA in addressing the DFJSP., © 2024 Chinese Institute of Industrial EngineersPublished online: 06 Dec 2024Taylor & Francis Group an informa businessCorrespondence Address: M.A. Beheshtinia; Industrial Engineering Department, Faculty of Engineering, Semnan University, Semnan, 35131-19111, Iran; email: beheshtinia@semnan.ac.ir

Finding ways to boost transportation access for underserved populations can unlock broad social benefits. Micromobility programs, including bikesharing, offer scalable solutions. National, state, and regional housing and urban development agencies promote affordable housing and transit-accessible developments by funding programs such as the Low-Income Housing Tax Credit and Community Development Block Grants. However, these efforts are not always coordinated and the physical distance between affordable housing and transit access continues to grow. The problem is compounded by low car ownership rates in lower income urban communities. These circumstances have led to inequitable mobility access. To correct course, pairing affordable housing developments with reliable transit services is essential. This practice can increase equity and accessibility. A team at the University of California, Davis, conducted a case study in Sacramento, California, to explore bikesharing as an option for connecting affordable housing residents with transit services. This brief summarizes the findings from that research and provides implications for the field. View the NCST Project Webpage

Work zone maintenance is essential to the efficiency and safety of transportation infrastructure system. A recent technology named autonomous maintenance technology (AMT) is gaining rapid attention to eliminate fatalities of Department of Transportation (DOT) employees in work zones. Traffic flow will redistribute in the network once the link performance function (LPF) is updated after maintenance, and thus the equilibrium travel time (ETT) will change accordingly. In an extreme example, Braess’s paradox, i.e. adding or improving one roadway segment may actually lead to a worse traffic condition, may be observed. This project aims to support DOT decision-makers to determine which road segment to prioritize for maintenance, with the goal of maximizing transportation system performance. To this end, a user equilibrium (UE) model will be developed to quantify the impact of roadway segment maintenance. Sensitivity analysis will then be conducted to compute the marginal cost of ETT. Last but not the least, maintenance priority will be suggested to DOT to maximize the transportation infrastructure system performance.

Travel time reliability has direct economic impacts on the decisions of logistics firms and delivery vehicles, and the service levels ultimately experienced by shippers, firms, and consumers. Underlying all measures of travel time reliability is the variability of travel times experienced along individual links, by various modes, at junctions and intermodal terminals, and through the individual trajectories of travelers and goods. Multiple challenges can arise in estimating travel time distributions for any path in a given network with variable travel times. This reference brings together modern advances in data availability and probabilistic modeling techniques to overcome these challenges, and synthesize travel time distributions at the path level in generalized networks. These may include different facility types and potentially modal services along a particular path. This reference provides an overview of the methodology and tools that can be applied to successfully synthesize and replicate traveler- based travel time distributions along continuous paths, regardless of facility type.

Roadway performance measures are used for operating, planning, and design purposes to improve services for road users. Simple statistics of the performance metrics such as measures of central tendency (e.g., mean, median) are often used for making operational and planning decisions. Even though such statistics are useful, they are, more than often, not comprehensive enough for making insightful operational and planning decisions. Consequently, performance reliability measures, which attempt to capture the day-to-day variability in performance, have the potential to benefit the areas of operation, planning, and design. Traffic data from Intelligent Transportation System facilitates the measurement of the reliability of transportation systems. This project analyzes and verifies the accuracy of INRIX traffic data using a testbed located in Nebraska. In addition, different travel time reliability (TTR) metrics such as travel time index (TTI), planning time index (PTI), level of travel time reliability (LOTTR), buffer index (BI), and coefficient of variation (COV) were measured for Region VII highways. The project evaluates TTR metrics under various weather conditions (such as normal weather, rain, and snow), time of day (AM peak and PM peak), and global events like the COVID-19 pandemic. Out of the five TTR metrics, in general, INRIX measured the TTI, PTI, and LOTTR metrics with the most accuracy, compared to the ground truth data. In most cases, LOTTR was most accurately measured by INRIX. On the other hand, INRIX measured BI and COV with the least accuracy, compared to the ground truth data. One of the most notable findings from this project was whether the transportation system’s reliability increased or decreased or to what extent the reliability changed depended on which metric was used to measure it. Therefore, engineers and transportation agencies require a deeper understanding of the travel time related statistics and transportation system’s characteristics to u

Integrating accessibility into transportation planning seeks to improve policy and programming decisions that ensure congestion mitigation measures, encourage transportation equity, and improve urban livability. Traditional accessibility measures and methods have largely focused on modeling and/or estimation procedures, displaying a hypothetical universe of access—not where travel actually occurs. This research developed a suite of measures to assess accessibility, taking advantage of available crowdsourced origin destination data to identify accessibility from real data rather than a modeled approach. The measures are calculated for all U.S. urban areas to inform congestion-mitigation decision-making based on actual travel behaviors. The results of this work will help transportation planners and policy makers understand where access is (or is not) adequately provided to identify appropriate and innovative solutions for shifting travel behavior to more equitable and sustainable approaches. The 2021 Urban Mobility Report and website will include the results of the research.

The paper presents an analytical model for travel time evaluation in double-deep, triple-deep, quadruple-deep and fivefold-deep tier-captive shuttle-based storage and retrieval system (SBS/RS). Under the assumption of the deepest location rule for the storage process and the nearest neighbour rule for the retrieval process, the expressions for single-command and dual-command cycle times of the shuttle vehicle and elevator are developed, from which the SBS/RS performance can be estimated. The model based on the probability theory enables the evaluation of all individual times that make up the cycle times and assessment of the average number of totes relocated during a retrieval process. Special attention is devoted to the modelling of the relocation of totes which block access to the requested tote during the retrieval process. The validity of the analytical model is examined via the developed simulation model. The given case study shows that the proposed analytical travel time model results match the results of the simulation model. The presented modelling strategy could be applied to bigger system racking depths following the same modelling logic.

Agricultural managed aquifer recharge (Ag-MAR) is a promising approach to replenish groundwater resources using flood water and cropland as spreading grounds. However, site selection, particularly the layering of sediment deposits in the subsurface, can greatly influence Ag-MAR efficacy as it controls water flow and solute transport in the vadose zone. In this study, we use the HYDRUS-1D software to simulate water flow and solute transport from the land surface to the groundwater table in three vadose zone profiles (LS, MS, HS) characterized by differing fractions of sand (44 %, 47 %, and 64 %). For each profile, the single- and dual-porosity models (i.e., considering or not nonequilibrium water flow and solute transport) were calibrated using observed surface ponding, soil water content, and KBr breakthrough data. Water flow and bromide transport in the profile with the lowest sand fraction (LS) were best captured using the model that considered both preferential flow and nonequilibrium bromide transport. Water flow and bromide transport in the profile with the highest sand fraction (HS) was best simulated with the model that considered preferential flow and equilibrium bromide transport. Uniform water flow and nonequilibrium bromide transport provided the best fit for the third profile (MS). The degree of preferential flow was highest in the profile with the largest sand fraction (HS), which also showed the largest flow velocities compared to the profiles with lower sand amounts (LS and MS). Preferential flow did not significantly impact the overall water balance (within 3 %), but caused a significant decrease in vadose zone travel times (bromide) by up to 38 %, relative to a single-porosity model fit. Recharge efficiency varied between 88 % and 90 %, while the average travel times from the soil surface to groundwater varied up to 119 % (from 3.6 to 7.9 days) between the three sites. This study demonstrates that similar rech

Traffic congestion is a significant problem in major metropolitan areas in the United States. According to the Urban Mobility Report, in 2019 commuters on average lost about 54 hours in traffic congestion. To combat this, major infrastructure projects have been undertaken. However, expansion projects cannot keep up with the increase in usage of personal vehicles and thus fail to address the traffic congestion problem. Carpool ridesharing has shown some promise in combatting this traffic congestion problem. In this system, the drivers are regular commuters who take detours to pick up and drop off passengers to decrease their transportation costs. This system increases the efficiency of the transportation system by providing flexible commutes to people, thus reducing the need for each commuter to use their own personal vehicle. The researchers developed three approaches to rideshare routing. The researchers conducted a computational study using a San Francisco taxicab dataset to determine the effectiveness of the three approaches. To show the impact of flexible meeting points, the researchers also conducted experimental simulations with and without walking and performed sensitivity analyses.View the NCST Project Webpage

This thesis investigates how a closure of a maternity ward affects the moves intoand out of a municipality. The policy focus of a centralization of maternal care in Sweden may bring unseen consequences that matter for society in a larger sense than only births. By treating closeness to a maternity ward as a positive amenity for a municipality, these closures introduce an exogenous variation that is used to estimate how moves change over time. With the lack of data availability, utilizing Sweden’s administrative areas, the lack of data over amenities as well as other factors such as employment possibilities are compensated for, revealing the possibility of using similar areas as potential substitutes for amenities. The results indicate that closures are likely to introduce a lower mobility for the regions as both fewer moves in and fewer moves out are revealed in the estimates. The results are strongly significant, a one minute increase of travel time would be associated with a decrease of around 3 moves in and 2.7 moves out. These results are mostly robust, and findings suggest north and south of Sweden are fundamentally different.

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born.

Despite substantial federal and state investments made to promote the National Diabetes Prevention Program (NDPP) as a population health strategy for diabetes prevention it remains underutilized. Research has pointed to a variety of factors that have contributed to low uptake of this evidence-based lifestyle change program. However, the role neighborhood socioeconomic disadvantage plays in NDPP access and use has been underexplored. The state of Maryland is an ideal setting to investigate how neighborhood socioeconomic disadvantage impacts various dimensions of NDPP access due to the significant investments in primary care transformation and NDPP. This dissertation examines: (1) the relationship between neighborhood socioeconomic disadvantage and potential access to the NDPP using primary care providers geographic proximity to the NDPP sites in Maryland, (2) the relationship between neighborhood socioeconomic disadvantage and potential access to the NDPP based on geographic proximity of individuals with prediabetes to the nearest NDPP site in Maryland, and (3) the relationship between neighborhood socioeconomic disadvantage and utilization of diabetes prevention intervention such as NDPP, metformin, or both among individuals with prediabetes in Maryland. Findings from this work underscore how targeted statewide public health and health care initiatives can enhance NDPP access and utilization in neighborhoods with higher levels of socioeconomic disadvantage.

This research studies the potential of bikeshare services to bridge the gap between Affordable Housing Communities (AHC) and transit services to improve transport accessibility of the residents. In doing so, the study develops an agent-based simulation optimization modeling (ABM) framework for the optimal design of the bikesharing station network considering improving accessibility as the objective. The study discusses measures of accessibility and uses travel times in a multi-modal network. Focusing on the city of Sacramento, CA, the study gathered information related to affordable housing communities, detailed transit services, demographic information, and other relevant data. This ABM framework is used to run three stages of travel demand modelling: trip generation, trip distribution and mode split to find the travel time differences under the availability of new bikesharing stations. The model is solved with a genetic algorithm approach. The results of the optimization and ABM-based simulation indicate the share of bike and bike & transit trips in the network under different scenarios. Key results indicate that about 60% of the AHCs are within 25-minute active travel time when the number of stations range from 25 to 75, and when the number of stations is increased to 100, most AHCs are within 40 mins of active mode distance and all of them are less than an hour away. In terms of accessibility, for example, having a larger network of stations (e.g., 100) increases by 70% the number of Points of Interest (for work, health, recreation, and other) within a 30-minute travel time. This report then provides some general recommendations for the planning of the bikesharing network considering information about destination choices as well as highlighting the past and current challenges in housing and transit planning.View the NCST Project Webpage

Connected Vehicles (CV) technology offers significant potential for managing traffic congestion and improving mobility along transportation corridors. This report presents a novel approach using integrated corridor management (ICM) technology to divert CVs to underutilized park-and-ride facilities where drivers can park their vehicle and access public transportation. Using vehicle-to-infrastructure (V2I) communication protocols, the system collects data on downstream traffic and sends messages regarding available park-and-ride options to upstream traffic. A deep reinforcement learning (DRL) program controls the messaging, with the objective of maximizing traffic throughput and minimizing CO2 emissions and travel time. The ICM strategy is simulated on a realistic model of Interstate 5 using Veins simulation software. The results show marginal improvement in throughput, freeway travel time, and CO2 emissions, but increased travel delay for drivers choosing to divert to a park-and-ride facility to take public transportation for a portion of their travel.

The experience of urban users is shaped by cities—by their shapes, components, and how they function. An immense quantity of data is included in the process of how the city functions, how it affects its inhabitants, and how its residents view its components. Researchers need an extensive number of datasets on land use (type & quantification) and geometric dimensions of the built environment (3D, form, & pattern) to fully grasp this relationship. In addition to the need to collect data about users’ experience via using web-based/location-based surveys. The acquisition, exploration, and analysis of these datasets contributes to enabling a better understanding, operation, and monitoring of the city’s systems. Thus, facilitating the design, implementation, and operation of functional, efficient, and reliable smart cities. This paper focuses on transportation and mobility, and how can open-data sources be utilized for data acquisition for urban mobility studies. This highlights possible, simple, and accessible open-data acquisition tools for urban planners. It further outlines the limitations and challenges for data acquisition related to the global south context. The main aim is to explore the potential of integrating different open-data sources, web-based tools, and data analytics in defining travel time map and accessibility with respect to modality of mobility. It examines the accessibility, availability, and obtainability of data from these open-data sources (i.e., OpenStreetMap, Uber Movement, Jupyter Notebook) to be further used in urban studies, specifically in the context of the selected case study area. An exploratory approach is adopted to perform an analysis between the built environment and travel time during mobility, using Isochrone map acquired from open-data sources. The aim is to delineate an approach that could be adopted by urban planners who are not well acquainted with open-data sources, python scripts and codes. This approach could be utili

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born.

This thesis investigates how a closure of a maternity ward affects the moves intoand out of a municipality. The policy focus of a centralization of maternal care in Sweden may bring unseen consequences that matter for society in a larger sense than only births. By treating closeness to a maternity ward as a positive amenity for a municipality, these closures introduce an exogenous variation that is used to estimate how moves change over time. With the lack of data availability, utilizing Sweden’s administrative areas, the lack of data over amenities as well as other factors such as employment possibilities are compensated for, revealing the possibility of using similar areas as potential substitutes for amenities. The results indicate that closures are likely to introduce a lower mobility for the regions as both fewer moves in and fewer moves out are revealed in the estimates. The results are strongly significant, a one minute increase of travel time would be associated with a decrease of around 3 moves in and 2.7 moves out. These results are mostly robust, and findings suggest north and south of Sweden are fundamentally different.

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born.

Práce se zabývá možnostmi posílení propojení centrální části pražského Smíchova s Jižním Městem II veřejnou hromadnou dopravou, a to pomocí úprav stávajícího vedení autobusových linek. Jako nástroj pro zpracování položené otázky byl vybrán krok traffic assignment používaný v rámci konstrukce 4stupňového dopravního modelu. Výpočty jsou realizovány v softwaru Microsoft Excel, s využitím modifikovaného Floydova algoritmu. Návrhová část představuje varianty, jakým způsobem lze posílení integrovat do stávajícího systému veřejné dopravy. Vyhodnocení je založeno na porovnání časové náročnosti absolvování jednotlivých cest pomocí individuální automobilové dopravy a veřejné hromadné dopravy, a to v režimu "door-to-door". Závěr obsahuje posouzení, na základě kterých by se případná posílení mohla realizovat i z hlediska ekonomické náročnosti., The work deals with the possibilities of strengthening the connection of the central part of Smíchov of Prague with the South City II by public transport, by means of modifications to the existing routes of bus lines. The traffic assignment step used in the construction of the 4-stage traffic model was chosen as a tool for processing the question asked. The calculations are performed in Microsoft Excel software, using a modified Floyd algorithm. The proposal part presents variants of how the reinforcement can be integrated into the existing public transport system. The evaluation is based on a comparison of the time required to complete individual journeys using individual car transport and public transport in a "door-to-door" mode. The conclusion contains the assessment on the basis of which any strengthening could be implemented in terms of economic demands., Dopravní fakulta Jana Pernera, výborně (výborně mínus) Student přednesl ucelenou a logicky uspořádanou obhajobu své diplomové práce. V ní dokázal přesvědčivým způsobem obhájit závěry svých řešení. Na připomínky reagoval správně a v plném rozsahu je zodpověděl. U doplňkových otázek prokázal schopnost logického myšlení, pohotové reakce, jasného a srozumitelného vysvětlení., Dokončená práce s úspěšnou obhajobou

It is generally considered that a well-designed on-demand ride-pooling service can reduce the vehicle fleet size required to satisfy a given level of passenger demand and thus achieve a variety of societally beneficial objectives, such as decreased traffic congestion. In turn, this decreases the travel time of ride-sourcing passengers and other road users. Accordingly, this chapter examines the extent to which a ride-pooling service can decrease traffic congestion and people's travel time by establishing an analytical model for ride-pooling services in the presence of traffic congestion. The model confirms that a ride-pooling service can indeed create a win–win situation for ride-sourcing passengers and other road users. The chapter also discusses optimisation of the matching-time window for pool-matching.

The experience of urban users is shaped by cities—by their shapes, components, and how they function. An immense quantity of data is included in the process of how the city functions, how it affects its inhabitants, and how its residents view its components. Researchers need an extensive number of datasets on land use (type & quantification) and geometric dimensions of the built environment (3D, form, & pattern) to fully grasp this relationship. In addition to the need to collect data about users’ experience via using web-based/location-based surveys. The acquisition, exploration, and analysis of these datasets contributes to enabling a better understanding, operation, and monitoring of the city’s systems. Thus, facilitating the design, implementation, and operation of functional, efficient, and reliable smart cities. This paper focuses on transportation and mobility, and how can open-data sources be utilized for data acquisition for urban mobility studies. This highlights possible, simple, and accessible open-data acquisition tools for urban planners. It further outlines the limitations and challenges for data acquisition related to the global south context. The main aim is to explore the potential of integrating different open-data sources, web-based tools, and data analytics in defining travel time map and accessibility with respect to modality of mobility. It examines the accessibility, availability, and obtainability of data from these open-data sources (i.e., OpenStreetMap, Uber Movement, Jupyter Notebook) to be further used in urban studies, specifically in the context of the selected case study area. An exploratory approach is adopted to perform an analysis between the built environment and travel time during mobility, using Isochrone map acquired from open-data sources. The aim is to delineate an approach that could be adopted by urban planners who are not well acquainted with open-data sources, python scripts and codes. This approach could be utili

The green concept in operations is becoming an inevitable part of global maritime logistics activities and has an important influence on the improvement of efficiency and environmental performance. This paper aims to assess the continuous monitoring and tracking of container shipments at the ports in order to reduce carbon emissions thus improving environmental performance. In this research, near real-time RFID data tracing and tracking container cargo are shared by the automated monitoring system. The collected data gathered via digitalization is further analyzed to ensure a greener maritime logistics system. The significant findings of the study for the literature show that the actual fuel consumption is reduced when automated monitoring systems are used at the ports (Ports and CFS (Container freight station)). The reduced fuel consumption during the transit between the ports and CFS has resulted in a reduction in carbon emissions of environmental performance. The results show a 6 % reduction in emissions from port to CFS and 23% from CFS to ports. Thus, effective practices in Green Logistics are considered to be beneficial for carbon emissions. These findings contribute to the understanding and development of effective strategies for logistic operations using technologies to create a green performance. The study was performed in a certain set of environmental dimensions and the results may vary depending on the organization, which can be studied further in future research.

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born.

The experience of urban users is shaped by cities—by their shapes, components, and how they function. An immense quantity of data is included in the process of how the city functions, how it affects its inhabitants, and how its residents view its components. Researchers need an extensive number of datasets on land use (type & quantification) and geometric dimensions of the built environment (3D, form, & pattern) to fully grasp this relationship. In addition to the need to collect data about users’ experience via using web-based/location-based surveys. The acquisition, exploration, and analysis of these datasets contributes to enabling a better understanding, operation, and monitoring of the city’s systems. Thus, facilitating the design, implementation, and operation of functional, efficient, and reliable smart cities. This paper focuses on transportation and mobility, and how can open-data sources be utilized for data acquisition for urban mobility studies. This highlights possible, simple, and accessible open-data acquisition tools for urban planners. It further outlines the limitations and challenges for data acquisition related to the global south context. The main aim is to explore the potential of integrating different open-data sources, web-based tools, and data analytics in defining travel time map and accessibility with respect to modality of mobility. It examines the accessibility, availability, and obtainability of data from these open-data sources (i.e., OpenStreetMap, Uber Movement, Jupyter Notebook) to be further used in urban studies, specifically in the context of the selected case study area. An exploratory approach is adopted to perform an analysis between the built environment and travel time during mobility, using Isochrone map acquired from open-data sources. The aim is to delineate an approach that could be adopted by urban planners who are not well acquainted with open-data sources, python scripts and codes. This approach could be utili

Background: Closing delivery units increases travel time for some women. Whether increased travel time is associated with maternal outcomes is important for understanding the consequences of such closures. Previous studies are limited in measuring travel time and restricted to the outcome of caesarean section. Methods: Our population-based cohort includes data from the Swedish Pregnancy Register for women giving birth between 2014 and 2017 (N = 364,630). We estimated travel time from home to the delivery ward using coordinate pairs of actual addresses. The association between travel time and onset of labour was modelled using multinomial logistic regression, and logistic regression was used for the outcomes postpartum haemorrhage (PPH) and obstetric anal sphincter injury (OASIS). Findings: Over three-quarters of women had ≤30 min travel time (median 13.9 min). Women who travelled ≥60 min arrived to care sooner and laboured there longer. Women with further to travel had increased adjusted odds ratio (aOR) of having an elective caesarean section (31–59 min aOR 1.11; 95% confidence interval [CI] 1.07–1.16; ≥60 min aOR 1.25; 95% CI 1.16–1.36) than spontaneous onset of labour. Women (at full term with spontaneous onset) living ≥60 min away had reduced odds of having a PPH (aOR 0.84; 95% CI 0.76–0.94) or OASIS (aOR 0.79; 95% CI 0.66–0.94). Interpretation: Longer travel time increased the odds of elective caesarean section. Women with furthest to travel arrived sooner and spent more time in care; although they had a lower risk of PPH or OASIS, they also tended to be younger, have a higher body mass index and were Nordic born.

The paper presents the results of evaluating the performance measures of the newly developed and implemented in practice plan for coordinating the work of six local traffic lights on a 1.8 km long fragment of Nauki Avenue in Kharkiv. The analysis of existing methods of coordinated traffic light management has shown that at present they do not provide high performance and are roughly equal in effect to adaptive traffic light management methods. The main instrument of evaluation was the comparison of the results of the application of new parameters of traffic lights operation on the fragment of the street and road network, surrounding the coordinated section, with the traffic situation existing before its implementation. For this purpose, a study of travel time and the number of vehicle stops at intersections was conducted using the "floating car" method, and the speed of vehicles was calculated using TomTom service data. Each of these methods has its own advantages and disadvantages, and therefore they complemented each other in assessing the direct impact of the coordination plan on the state of traffic management on the studied fragment of the road network. The dual evaluation of the performance measures proved to be very appropriate in light of the operating conditions of the coordinated fragment of Nauki Avenue and the road network around it, which recorded a significant increase in traffic intensity during 2021 and after the implementation of the coordination plan in early 2022. The evaluation of its effectiveness in both ways convincingly showed the high efficiency of this measure, in terms of the number of stops and travel time, and the TomTom service data showed that even with an increase in traffic volume by almost one and a half times, the speed of cars in general increased by more than 14%. Taking into account the minimal costs for the implementation of the coordination plan, this testifies in favor of the means of arterial coordination in the Ukraine citi

The paper presents the results of evaluating the performance measures of the newly developed and implemented in practice plan for coordinating the work of six local traffic lights on a 1.8 km long fragment of Nauki Avenue in Kharkiv. The analysis of existing methods of coordinated traffic light management has shown that at present they do not provide high performance and are roughly equal in effect to adaptive traffic light management methods. The main instrument of evaluation was the comparison of the results of the application of new parameters of traffic lights operation on the fragment of the street and road network, surrounding the coordinated section, with the traffic situation existing before its implementation. For this purpose, a study of travel time and the number of vehicle stops at intersections was conducted using the "floating car" method, and the speed of vehicles was calculated using TomTom service data. Each of these methods has its own advantages and disadvantages, and therefore they complemented each other in assessing the direct impact of the coordination plan on the state of traffic management on the studied fragment of the road network. The dual evaluation of the performance measures proved to be very appropriate in light of the operating conditions of the coordinated fragment of Nauki Avenue and the road network around it, which recorded a significant increase in traffic intensity during 2021 and after the implementation of the coordination plan in early 2022. The evaluation of its effectiveness in both ways convincingly showed the high efficiency of this measure, in terms of the number of stops and travel time, and the TomTom service data showed that even with an increase in traffic volume by almost one and a half times, the speed of cars in general increased by more than 14%. Taking into account the minimal costs for the implementation of the coordination plan, this testifies in favor of the means of arterial coordination in the Ukraine citi

The emergence of travel time reliability as an approach to traffic analysis has drastically enhanced the understanding of factors influencing transportation system performance and impacts to users. Reliability analysis methods provide a more accurate representation of real-world travel experiences than traditional traffic analysis approaches.

The emergence of travel time reliability evaluation has drastically enhanced the understanding of factors influencing transportation system performance and impacts to users. This analysis is frequently performed on historical data sets, but how do you predict future reliability? FHWA’s reliability analysis video series introduces the essential concepts and technical steps to evaluate reliability for your next project.

Many cities are focused on increasing bicycle use through development of infrastructure such as bicycle lanes and multi-use paths. Traditionally, travel demand models (TDMs) are used to evaluate the demand for (and impact of) proposed transportation projects. However, the vast majority of TDMs cannot be used to evaluate the impact of bicycle projects. Improved TDMs are needed to help estimate the impacts of new bicycle projects on cycling activity and prioritize the construction of the most beneficial bicycle projects with limited transportation department resources.To more accurately model bicycle travel, preference-based route assignments are needed. Researchers at the Georgia Institute of Technology created a semi-automated process for developing an all-streets network to be used in TDM applications. The researchers combined detailed roadway characteristic information from three different transportation networks in GIS shapefile format and used BikewaySim, Georgia Tech’s newly developed shortest-path calculator for cycling trips, to compare shortest-path routing on the newly created all-streets network versus the simplified TDM network for a 12-square-mile study area in Atlanta. View the NCST Project Webpage

This research project examines the link between job access and stop/station level transit ridership. Job access, following recent literature, is measured as the number of jobs that can be reached within a 30-minute transit travel time, including transfers and walk time to access jobs once exiting a transit station. Cumulative opportunity job access measures of this sort—i.e., the number of jobs that can be reached within 30 minutes—have become common in the recent access literature, and those measures have often focused on access via transit. Yet there have been few studies that examine the link between transit job access and transit ridership, and of those none that examine the link at a station or stop level. This study uses station and stop level ridership data for the Los Angeles Metro bus and rail system and the BART rail system in the San Francisco Bay Area. The research team calculated transit job access as jobs that can be reached within 30 minutes, using the Remix software tool. Regression analysis of 1,000 randomly selected Los Angeles bus stops reveals a robust relationship between stop-level ridership and job access. The association between transit job access and bus stop ridership (embarkations and disembarkations at the stop) is statistically significant. Converting that association into an elasticity, if the number of jobs accessible within 30-minutes were to increase by 1 percent, on average stop-level ridership would increase between 0.6 to 0.8 percent. The same association, with similar magnitudes, exists for Metro rail stations and BART rail stations, but due the smaller sample sizes, those relationships are not statistically significant when control variables are added to the regression. The findings show that job access is closely related to ridership at the bus stop level, suggesting transit agencies can increase job access by increasing bus frequency, reducing transfers, siting lines that connect job concentrations to residents, and by improvi

Travel speed is an intrinsic feature of transport, and enlarging the speed is considered as beneficial. The benefit of a speed increase is generally assessed as the value of the saved travel time. However, this approach conflicts with the observation that time spent on travelling is rather constant and might not be affected by speed changes. The paper aims to define the benefits of a speed increase and addresses two research questions. First, how will a speed increase in person transport work out, which factors are affected? Second, is the value of time a good proxy for the value of speed? Based on studies on time spending and research on the association between speed and land use, we argue that human wealth could be the main affected factor by speed changes, rather than time or access. Then the value of time is not a good proxy for the value of speed: the benefits of a wealth increase are negatively correlated with prosperity following the law of diminishing marginal utility, while the calculated benefits of saved travel time prove to be positively correlated. The inadequacy of the value of time is explained by some shortcomings with respect to the willingness to pay that is generally used for assessing the value of time: people do not predict correctly the personal benefits that will be gained from a decision, and they neglect the social impacts., Transport and Planning

With rapid population growth and urban development, traffic congestion has become an inescapable issue in large metropolitan regions. Research studies have proposed different strategies to control traffic, ranging from roadway expansion to transportation demand management programs. Among these strategies, congestion pricing and incentive offering schemes have been widely studied as reinforcements for traffic control in traditional traffic networks where each driver is a “player” in the network. In such a network, the “selfish” behavior of individual drivers prevents the entire network to reach a socially optimal operation point. In future mobility services, on the other hand, a large portion of drivers/vehicles may be controlled by a small number of companies/organizations. In such a system, offering incentives to organizations can potentially be much more effective in reducing traffic congestion rather than offering incentives directly to drivers. This research project studies the problem of offering incentives to organizations to change the behavior of their individual drivers (or individuals using their organization’s services). The incentives are offered to each organization based on their aggregated travel time loss across all their drivers. This step requires solving a large-scale optimization problem to minimize the system-level travel time. We propose an efficient algorithm for solving this optimization problem. To evaluate the performance of the proposed algorithm, multiple experiments are conducted by Los Angeles traffic data. Our experiments show that the proposed algorithm can decrease the system-level travel time by up to 6.9%. Moreover, our experiments demonstrate that incentivizing organizations can be up to 8 times more efficient than incentivizing individual drivers in terms of incentivization monetary cost.View the NCST Project Webpage

With rapid population growth and urban development, traffic congestion has become an inescapable issue. Future mobility services may offer a new and very effective opportunity to incentivize congestion-reducing behavior. Ridesourcing, food delivery, and package delivery companies make decisions that directly or indirectly affect routing for an increasing number of drivers. These organizations have more flexibility and more power to affect traffic, and targeting them with incentives may be more efficient than incentivizing individual drivers.Motivated by this idea, researchers at the University of Southern California developed a distributed algorithm for offering incentives to organizations to make socially optimal routing decisions. The algorithm is designed to lower the traffic flow of congested roads without creating new congestion in other parts of the road network. This policy brief summarizes the findings from that research and provides research implications.View the NCST Project Webpage

Many cities are focused on increasing bicycle use through development of infrastructure such as bicycle lanes and multi-use paths. Traditionally, travel demand models (TDMs) are used to evaluate the demand for (and impact of) proposed transportation projects. However, the vast majority of TDMs cannot be used to evaluate the impact of bicycle projects. Improved TDMs are needed to help estimate the impacts of new bicycle projects on cycling activity and prioritize the construction of the most beneficial bicycle projects with limited transportation department resources.To more accurately model bicycle travel, preference-based route assignments are needed. Researchers at the Georgia Institute of Technology created a semi-automated process for developing an all-streets network to be used in TDM applications. The researchers combined detailed roadway characteristic information from three different transportation networks in GIS shapefile format and used BikewaySim, Georgia Tech’s newly developed shortest-path calculator for cycling trips, to compare shortest-path routing on the newly created all-streets network versus the simplified TDM network for a 12-square-mile study area in Atlanta. View the NCST Project Webpage

This research project examines the link between job access and stop/station level transit ridership. Job access, following recent literature, is measured as the number of jobs that can be reached within a 30-minute transit travel time, including transfers and walk time to access jobs once exiting a transit station. Cumulative opportunity job access measures of this sort—i.e., the number of jobs that can be reached within 30 minutes—have become common in the recent access literature, and those measures have often focused on access via transit. Yet there have been few studies that examine the link between transit job access and transit ridership, and of those none that examine the link at a station or stop level. This study uses station and stop level ridership data for the Los Angeles Metro bus and rail system and the BART rail system in the San Francisco Bay Area. The research team calculated transit job access as jobs that can be reached within 30 minutes, using the Remix software tool. Regression analysis of 1,000 randomly selected Los Angeles bus stops reveals a robust relationship between stop-level ridership and job access. The association between transit job access and bus stop ridership (embarkations and disembarkations at the stop) is statistically significant. Converting that association into an elasticity, if the number of jobs accessible within 30-minutes were to increase by 1 percent, on average stop-level ridership would increase between 0.6 to 0.8 percent. The same association, with similar magnitudes, exists for Metro rail stations and BART rail stations, but due the smaller sample sizes, those relationships are not statistically significant when control variables are added to the regression. The findings show that job access is closely related to ridership at the bus stop level, suggesting transit agencies can increase job access by increasing bus frequency, reducing transfers, siting lines that connect job concentrations to residents, and by improvi