Average Daily Volume Research Articles

Bayesian Approach to Developing Context-Based Crash Modification Factors for Medians on Rural Four-Lane Roadways

Rural four-lane roadways provide important transportation accessibility and mobility to populations in rural areas. It is a challenge for practitioners to determine cross-section types when both benefits and costs need to be considered. Crash Modification Factors (CMFs) are developed to evaluate the safety effectiveness of alternative designs. However, safety effectiveness could vary significantly across contexts. Thus, this study aims to estimate CMFs for alternative cross sections of rural four-lane roadways under different contexts characterized by traffic volume, truck percentage, and access point density. Using Georgia state-wide crash data, this study developed Safety Performance Functions (SPFs) to predict crash frequencies for different contexts. Considering linearity and independence assumptions of traditional negative binomial SPFs, this study adopts Bayesian generalized negative binomial modeling approaches to relax those assumptions and only follows the Bayes rule to form SPFs for CMF estimation. This study focuses on four typical cross-sections including: (1) non-traversable medians; (2) two-way-left-turn lanes; (3) 4-ft flush medians; and (4) undivided roadways with double-yellow lines (the base cross-section design). The results show that CMFs vary significantly across different contexts. Compared with the base cross-section design, safety benefits of the other three designs can be either positive or negative under different traffic or road conditions. For example, 4-ft flush medians are found to have positive safety benefits (CMF < 1) under lower average daily traffic volumes (e.g., ≤ 6,000) and negative benefits (CMF > 1) under greater average daily traffic volumes (e.g., ≥ 15,000). The findings suggest that, to enhance roadway safety, practitioners should vary cross-section designs for different rural contexts.

Dynamic Curve Analysis of Indicators Related to Lumbar Cistern Drainage for Postoperative Meningitis

To analyze the dynamic curve of cerebrospinal fluid (CSF)-related indices in cases of postoperative meningitis after selective craniotomy and to provide reference data for the clinical treatment with lumbar cistern drainage (LCD). We conducted a retrospective study of LCD placement in 51 patients. Primary outcomes measured included dynamic changes of body temperature before and after intervention and cerebrospinal fluid biochemical parameters over the course of 13 days of catheter placement. We also assessed the bivariate correlation between white blood cell (WBC) count changes, polykaryocyte percentage, body temperature, and daily cerebrospinal fluid drainage volume. Finally, we analyzed the effect of average daily drainage volume, antibiotic choice, and surgical site on WBC count change curves. After LCD, there was a statistically significant difference (P < 0.01) between the WBC count before drainage and on the fourth day of drainage. There was a negative correlation between the change curve of the WBC count and the change curve of daily drainage volume (r=-0.56). When the daily drainage volume was 250-300 mL/day, the change curve pattern of the WBC count was consistent with the overall trend, and there was no significant difference in the curve of the WBC count between different surgical sites (P > 0.05). The WBC count can decrease significantly by day 4 after drainage, and placement of the LCD for 6-7 days is ideal. An average drainage volume of 250-300 mL/day is safe and effective.

Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China.

According to the traffic flow variation from January 2019 to August 2020, emissions of primary air pollutants from highway vehicles were calculated based on the emission factor method, which integrated the actual structure of on-road vehicles. The characteristics of on-highway traffic flow and pollution emissions were compared during various progression stages of coronavirus disease (COVID-19). The results showed that the average daily traffic volume decreased by 38.2% in 2020, with a decrease of 62% during the strict lockdown due to the impact of COVID-19. The daily emissions of primary atmospheric pollutants decreased by 29.2% in 2020 compared to the same period in 2019. As for the structure of on-highway vehicle types, the small and medium-sized passenger vehicles predominated, which accounted for 76.3% of traffic, while trucks and large passenger vehicles accounted for 19.7% and 4.0%, but contributed 58.4% and 33.9% of nitrogen oxide (NOx) emissions, respectively. According to the simulation results of the ADMS model, the average concentrations of NOx were reduced by 12.0 µg/m3 compared with the same period in 2019. As for the implication for future pollution control, it is necessary to further optimize the structure of on-highway and the road traffic vehicle types and increase the proportions of new-energy vehicles and vehicles with high emission standards.

Pedestrian Traffic Signal Data Accurately Estimates Pedestrian Crossing Volumes

Existing methods of pedestrian travel monitoring are generally inefficient for collecting pedestrian data in many locations over long time periods. In this study, we demonstrate the validity of using a novel and relatively ubiquitous big data source—pedestrian data from high-resolution traffic signal controller logs—as a way of estimating pedestrian crossing volumes. Every time a person presses a pedestrian push button or a pedestrian call is registered at a signal, this information can be logged and archived. To validate these pedestrian signal data against observed pedestrian counts, we recorded over 10,000 h of video at 90 signalized intersections in Utah, and counted around 175,000 people walking. For each hour and crossing, we compared these observed counts to measures of pedestrian activity calculated from traffic signal data, using a set of five simple piecewise linear and quadratic regression models. Overall, our results show that traffic signal data can be successfully used to estimate pedestrian crossing volumes with good accuracy: model-predicted volumes were strongly correlated (0.84) with observed volumes and had a low mean absolute error (3.0). We also demonstrate how our models can be used to estimate annual average daily pedestrian volumes at signalized intersections and identify high pedestrian volume locations. Transportation agencies can use pedestrian signal data to help improve pedestrian travel monitoring, multimodal transportation planning, traffic safety analyses, and health impact assessments.

The coronavirus disease 2019 (COVID-19) stay-at-home order’s unequal effects on trauma volume by insurance status in Southern California

BackgroundThe rapid spread of coronavirus disease 2019 in the United States led to a variety of mandates intended to decrease population movement and “flatten the curve.” However, there is evidence some are not able to stay-at-home due to certain disadvantages, thus remaining exposed to both coronavirus disease 2019 and trauma. We therefore sought to identify any unequal effects of the California stay-at-home orders between races and insurance statuses in a multicenter study utilizing trauma volume data. MethodsA posthoc multicenter retrospective analysis of trauma patients presenting to 11 centers in Southern California between the dates of January 1, 2020, and June 30, 2020, and January 1, 2019, and June 30, 2019, was performed. The number of trauma patients of each race/insurance status was tabulated per day. We then calculated the changes in trauma volume related to stay-at-home orders for each race/insurance status and compared the magnitude of these changes using statistical resampling. ResultsCompared to baseline, there was a 40.1% drop in total trauma volume, which occurred 20 days after stay-at-home orders. During stay-at-home orders, the average daily trauma volume of patients with Medicaid increased by 13.7 ± 5.3%, whereas the volume of those with Medicare, private insurance, and no insurance decreased. The average daily trauma volume decreased for White, Black, Asian, and Latino patients with the volume of Black and Latino patients dropping to a similar degree compared to White patients. ConclusionThis retrospective multicenter study demonstrated that patients with Medicaid had a paradoxical increase in trauma volume during stay-at-home orders, suggesting that the most impoverished groups remain disproportionately exposed to trauma during a pandemic, further exacerbating existing health disparities.

Traffic Density versus Rear-End Crash Risk on Freeways: Empirical Model, Mechanism Model, and Transfer to Automated Vehicles

AbstractThe statistical models supporting the Highway Safety Manual quantify associations between aggregate traffic measures, such as average daily traffic volume or posted speed limit, and crash f...

An Examination of the Strava Usage Rate—A Parameter to Estimate Average Annual Daily Bicycle Volumes on Rural Roadways

In Spain, a new challenge is emerging due to the increase of many recreational bicyclists on two-lane rural roads. These facilities have been mainly designed for motorized vehicles, so the coexistence of cyclists and drivers produces an impact, in terms of road safety and operation. In order to analyze the occurrence of crashes and enhance safety for bicycling, it is crucial to know the cycling volume. Standard procedures recommend using data from permanent stations and temporary short counts, but bicycle volumes are rarely monitored in rural roads. However, bicyclists tend to track their leisure and exercise activities with fitness apps that use GPS. In this context, this research aims at analyzing the daily and seasonal variability of the Strava Usage Rate (SUR), defined as the proportion of bicyclists using the Strava app along a certain segment on rural highways, to estimate the Annual Average Daily Bicycle (AADB) volume on rural roads. The findings of this study offer possible solutions to policy makers in terms of planning and design of the cycling network. Moreover, the use of crowdsourced data from the Strava app will potentially save costs to public agencies, since public data could replace costly counting campaigns.

Stock markets and female participation in the labor force

This paper examines the relation between female participation in the labor force and stock market trading volume. We focus on the first teaching day of the year at kindergartens and primary schools, treating it as an event with characteristics that resemble an exogenous event, and verify this using a web-based survey. We find that the first day of school has lower trading volume than the average daily trading volume during the rest of the year. Moreover, we document that female workforce participation is negatively associated with the trading volume on this day and that, in societies that have legislated gender nondiscrimination laws that govern hiring, this negative effect is even more pronounced. Our main findings document a significant societal phenomenon with a profound effect on stock markets, and specifically on the quality of the information environment, and therefore merit further attention.

Sensitivity Analysis to Determine the Prospect of Tollroad Investment: Case Study Krian-Legundi-Bunder-Manyar Tollroad

PT Waskita Bumi Wira as the Toll Road Business Entity (BUJT) is investing in the Krian-Legundi-Bunder-Manyar Toll road with a viability gap fund (VGF) scheme. In the 2016 Toll Road Concession Agreement (PPJT) between BPJT-BUJT-PII, several acceptable investment variables have been agreed, namely: total investment value = Rp12,224,389,000,000, average daily traffic volume (LHR) = 21,874 vehicle / day, loan interest = 12.5%, toll tariff for group 1 = Rp1,250 / km, internal rate of return on equity (IRRonEquity) = 17.64%, payback period of 14 years and net present value (NPV) = Rp. 3,731,695,000,000. During the construction, there was a design change and a delay in land acquisition, this causes cost overrun. With a concession period of 45 years, inaccurate risk factors in the prediction of traffic volume growth rates, specific and non-specific risk factors and other uncertainties greatly affect the investment prospects. Therefore investment needs to be reviewed before this toll road is divested in 2025 by sharpening the minimum attractive rate of return (MARR) and LHR variables, then comparing them with the initial business plan. The estimated selling price of the divestment is also examined in this study. The investment valuation criteria that will be used in the sensitivity analysis are NPV and IRRonEquity. The approach in determining MARR is the use of MARRpremium = 15.81%. Sensitivity analysis with a deterministic approach is carried out to obtain limits on changes in investment costs, land acquisition costs, LHR traffic, loans (syndicated loans) to NPV in several tariff scenarios. This research shows that the NPV value is very sensitive to changes in investment costs. It is also known that in the toll tariff scenario according to PPJT compensation can be given in one of the conditions: investment costs increase by more than 7%, LHR traffic is less than 75%, or an increase in loans (syndicated loans) of more than 9%. The analysis of the stochastic approach shows that the probability of not exceeding the investment budget revenue limits due to changes of 37.29% to 46.56%.

Research on the Development of Rail Transit Based on Cluster Analysis

This article analyzes the current development status of rail transit in various cities in China. Most cities are still dominated by subways. Then the relevant data is processed to obtain the linear relationship between transfer stations and rail mileage, rail stations and summarize the domestic rail Establish quantitative standards and conclude that rail transit has not yet become a transportation network. Then use the five indicators of line mileage, number of stations, number of interchange stations, average daily passenger volume, and passenger transport intensity to cluster the domestic urban rail transit using the method of cluster analysis, combining spatial Euclidean distance and compactness and other indicators Analysis, the classification results obtained have certain reference value.

The role of noninvasive hemodynamic monitoring in the evaluation of acute and severe pesticide poisoning

Objective: To explore the method of noninvasive hemodynamic monitoring system (NICaS) in monitoring the hemodynamics of patients with acute pesticide poisoning, and to analyze the clinical guiding value of NICaS in hemodynamics of patients with severe pesticide poisoning. Methods: In August 2019, 200 patients with severe acute organophosphorus pesticide poisoning (AOPP) or moderate severe acute paraquat pesticide poisoning (APP) admitted to Harrison international peace hospital from January 2017 to August 2019 were randomly divided into NICaS group (n=68) , transpulmonary thermodilution method (n=67) and empirical treatment group (n=65) . The relationship between acute physiology and chronic health score (APACHE Ⅱ) , heart rate, hemodynamic indexes, survival rate and complications were analyzed. Results: There were no significant differences in age, sex ratio, body mass index, heart rate, systolic blood pressure, no treatment period and admission APACHE II score between NICaS group, Picco group and experience group (P>0.05) ; Compared with the experience group, the mortality of AOPP and app in NICaS group and Picco group were lower, and the differences were statistically significant (P<0.05) .The cardiac output (CO) had a significant correlation in the interval of 2.8-6.7 L·min(-1) (r=0.738, r(2)=0.545, P<0.01) , and peripheral vascular resistance index (SVRI) had a significant correlation in the interval of 410-1 950 d·s·cm(-5)·m(2) (r=0.792, r(2)=0.627, P<0.01) . Bland Altman analysis showed that CO and SVRI measured by Picco and NICaS had 97.01% and 95.52% consistency, respectively. Compared with the experience group, the average daily infusion volume and daily colloid infusion volume of NICaS group and Picco group were lower, the differences were statistically significant (P<0.05) . Conclusion: NICaS can effectively monitor the hemodynamic indexes of patients with acute pesticide poisoning.

Random-Parameter Multivariate Negative Binomial Regression for Modeling Impacts of Contributing Factors on the Crash Frequency by Crash Types

Highways provide the basis for safe and efficient driving. Road geometry plays a critical role in dynamic driving systems. Contributing factors such as plane, longitudinal alignment, and traffic volume, as well as drivers’ sight characteristics, determine the safe operating speed of cars and trucks. In turn, the operating speed influences the frequency and type of crashes on the highways. Methods. Independent negative binomial and Poisson models are considered as the base approaches to modeling in this study. However, random-parameter models reduce unobserved heterogeneity and obtain higher dimensions. Therefore, we propose the random-parameter multivariate negative binomial (RPMNB) model to analyze the influence of the traffic, speed, road geometry, and sight characteristics on the rear-end, bumping-guardrail, other, noncasualty, and casualty crashes. Subsequently, we compute the goodness-of-fit and predictive measures to confirm the superiority of the proposed model. Finally, we also calculate the elasticity effects to augment the comparison. Results. Among the significant variables, black spots, average annual daily traffic volume (AADT), operating speed of cars, speed difference of cars, and length of the present plane curve positively influence the crash risk, whereas the speed difference of trucks, length of the longitudinal slope corresponding to the minimum grade, and stopping sight distance negatively influence the crash risk. Based on the results, several practical and efficient measures can be taken to promote safety during the road design and operating processes. Moreover, the goodness-of-fit and predictive measures clearly highlight the greater performance of the RPMNB model compared to standard models. The elasticity effects across all the models show comparable performance with the RPMNB model. Thus, the RPMNB model reduces the unobserved heterogeneity and yields better performance in terms of precision, with more consistent explanatory power compared to the traditional models.

OBSŁUGA TRANSPORTOWA MAŁYCH MIAST

The main problem connected with transport in small towns is an efficient passage of the transit route through the town. Road traffic planning is considered to be vital, which in many cases is not possible due to high costs. Another effective solution is calming the traffic along the route through towns, especially in the central areas, with lowering the speed limit to 30-40 kph (exceptionally allowing 50 kph). In this way, a consensus is achieved between the needs of traffic and town’s functioning. In consequence, the status of “priority for the town” is thus given. Ample experience confirms that there is a significant improvement in traffic safety on the main road, including: decrease in the number of deaths, reduction of traffic speed, improvement in the safety of vulnerable road users, improvement in the aesthetics and appearance of public space, improving parking conditions and reducing air pollution. Effects are achieved by reducing the speed and rebuilding of street sections. In the cross-sections of streets, new solutions for pedestrian and bicycle traffic develop the public space, which in this way becomes friendly to residents. Linear infrastructure for bicycles may be limited only to a road with a high car traffic density. The planned road solution must be integrally connected with spatial development. The threshold of road nuisance perceptible on the street in a small town is lower than in medium-sized and large cities. The average annual traffic daily volume should not exceed 5000 vpd. In the aspect of protection of living environment conditions, traffic intensity on small town streets should be by half lower (&lt;2000 vpd), which means a moderate traffic function of the street.&#x0D;

Inter- and Intra-Fractional Target Changes During Stereotactic Body Radiotherapy to the Prostate Bed With an Endorectal Balloon

Mature toxicity outcomes from the first phase I trial using stereotactic body radiotherapy (SBRT) to the prostate bed for recurrent prostate cancer have been recently reported. From that study, we herein report inter- and intra-fractional positional changes in the clinical target volume (CTV) and rectum with the use of an endorectal balloon. Prostate bed SBRT was delivered over 5 fractions in escalating doses of 35, 40, and 45 Gy. Three fiducial markers were planted in the CTV volume. A subset of 10 patients on the trial received both pre- and post-treatment CBCT for each fraction and were the subject of this analysis. An endorectal balloon was placed during both simulation and daily treatments. Patients were instructed to maintain a full bladder. On pre-treatment CBCT we localized to the anterior surface of the balloon to align the anterior rectal wall and CTV. Inter-fractional variation was measured using registrations based on pelvic anatomy. Intra-fractional changes in balloon position were assessed with soft-tissue registration. The t-test was used to evaluate the significance of correlation coefficient with significance level set at 0.05. The average daily air-filled balloon volume (±standard deviation) was 77.0±5.0 cc (range: 60.6 cc – 88.5 cc), and the average pre-treatment bladder volume was 235.0±109.7 cc. Compared to the planning CT, the pre-treatment bladder volume changed by -35.0±87.9 cc (range: -227.1 – 123.1 cc). Relative to the planning positions, the anterior rectal wall had an average inter-fractional shift of -1.6±5.6 mm (range: -15.2 – 7.5 mm) in the antero-posterior (AP) direction at the mid-section of the balloon (negative value: shifts posteriorly), with ≥ 3mm shift in 66% of total fractions. Correlation between daily bladder volume variations and anterior rectum position variations in the AP direction was statistically significant (Pearson’s correlation coefficient = 0.76, p = 0.02). The average time between the pre- and post-treatment CBCT scans was 9.8±4.0 minutes (range: 6 – 29 minutes). The post-treatment bladder volume increased significantly (p < 0.01) by an average of 58.9±51.6 cc. The balloon volume changed by <5% in each treatment. The center-of-mass of the balloon had average intra-fractional variation of 0.3±0.8 mm in the left-right (LR) direction (range: -1.3 – 2.5 mm), -0.9±2.4 mm in the AP direction (range: -11.0 – 3.0 mm), and -1.7±2.2 mm in the superoinferior (SI) direction (range: -10.9 – 0.7 mm) (negative value: shift anteriorly). No correlation was seen between increased bladder volume and intrafractional AP shifts, since the majority of greater than 3 mm shifts were attributed to one patient. Although not statistically significant, we observed higher than expected intrafractional AP and SI shifts. Our future phase II trial will incorporate larger margins to account for this finding.

A New ASCVD Risk Factor Management Model after Health Examination in China -- Based on 259 Cases Under 15-Month Diversified Health Intervention

Object: This study aimed to report our experience in setting up the new health management model after medical examination in our center for those examinees with risk factors of ASCVD and in need of some supervision. Method: 259 examinees enrolled underwent medical examination, ASCVD risk assessment, health education and management. Health education consisted of individual and group, and management characterized in integration of medicine and nursing, connection with the clinical, intervention in grades, combination of offline and online management and periodical evaluation. After 15 moths, comparison was made in the following aspects: ASCVD awareness rate, cardiovascular health condition, lifestyle (diet, exercise, diet, etc.), biochemical indicators (fast blood sugar, HbAlc, cholesterol, LDL, etc) and ASCVD risk. Result: ASCVD related disease awareness was raised significantly, diabetes from 6.56% to 14.29, hypertension from 30.50% to 43.24% and hyperlipidemia from 3.47% to 37.07%, as well as cardiovascular health condition with its score from 8.67±2.19 to 9.66±2.01. Healthy lifestyle was basically built, with diet standard-reaching rate from 22.78% to 45.95%, exercise standard-reaching rate from 20.85% to 62.93% and average daily tobacco consumption volume from 13.27±5.63 cigarettes down to 10.49±5.35 (P>0.05). However, the standard reaching condition in biochemical indicators ( fast blood sugar, HbAlc, cholesterol, LDL ) did not improve significantly, neither was ASCVD risk (P<0.05).3 Conclusion: Through 15 months’ operation, the new ASCVD risk factor management model proved to be of significant effect in disease awareness raising, cardiovascular health condition improving, healthy lifestyle establishing. More time is needed for biochemical indicator bettering and ASCVD risk decreasing. Funding Statement: None. Declaration of Interests: The authors declare that they do not have any commercial or associative interest that represents a conflict in connection with work submitted. Ethics Approval Statement: A consent form was signed by each participant. After obtaining the approval of institutional review board, the medical reports of all participants were reviewed to collect corresponding clinical information.

Impact of the COVID-19 pandemic on emergency CT head utilization in Ontario-an observational study of tertiary academic hospitals.

PurposeTo determine the impact of the Coronavirus disease-2019 (COVID-19) pandemic on the volume, indications, and results of CT heads performed in the emergency department (ED) at Canadian tertiary academic centers in Ontario.MethodsA retrospective review of consecutive CT head examinations ordered through the ED during the early stages of the COVID-19 pandemic in Canada (March 12–April 8, 2020) was performed and compared with that during the pre-COVID-19 period (February 12–March 10, 2020). CT reports were reviewed for the exam indication and the presence of predefined acute findings. A two-sample t test was utilized to compare the cohorts. Daily averages were calculated for all measures to control for the sample size difference between each period. A p value < 0.05 was considered significant.ResultsOf the total 751 CT head reports, 290 (38.6%) were ordered during the pandemic and 461 (61.4%) were ordered pre-pandemic. The average daily volume of CT head orders decreased significantly during COVID-19 compared with that during pre-COVID-19 (10.4 scans/day vs 16.5 scans/day; p = 0.001). In terms of indications, the frequency of “non-traumatic ICH” was significantly lower during COVID-19 compared with that during pre-COVID-19 (p = 0.01). Also, there was a significant increase in acute findings on CT during COVID-19 compared with that during pre-COVID-19 (p = 0.001).ConclusionThe decreased volume of emergency CT heads performed during the COVID-19 pandemic was associated with a significant increase in the proportion of cases with acute findings. This could be a result of the pandemic’s influence on the health-seeking behavior of patients as well as the decision-making process of ordering clinicians.

Study on Underground Logistics System Planning in the Jinan Prior Zone

In recent years, logistics demands in Jinan have shown clear growth trends. By 2020, Jinan city has proposed that the volume of express deliveries will reach 800 million packages, with revenue reaching 7 billion CNY. As an innovative logistics system, an underground logistics system (ULS) can provide new developmental ideas for urban logistics in Jinan. Although there are no actual cases of ULS construction projects in the world at present, as a first demonstration area driven by innovation in Jinan City, the Jinan Prior Zone for Replacing Old Growth Drivers with New Ones (Jinan Prior Zone) will be the first to attempt its implementation, thus providing an advanced model for sustainable development of urban logistics around the world. Based on the urban master plan of the Jinan Prior Zone, the logistics plan of Jinan city and other urban subject plans, this study proposes ULS planning for the Jinan Prior Zone, including demand forecasting, logistics architecture, planning principles, construction forms, and short/long term construction plan. The ULS planning will provide small batch, high frequency, and high timeliness for express delivery services in the central area of the Daqiao Group in the Jinan Prior Zone. In the long term, it will serve 500,000 people, with an average daily logistics volume of 1300 tons. This study views the introduction of ULS into the Jinan Prior Zone will both improve the efficiency of logistics and reduce the pressure of ground traffic and improve the level of green logistics, which is of great significance for the promotion of high-quality development of urban logistics.

Pollutant concentration measurement and emission factor analysis of highway tunnel with mainly HGVs in mountainous area

In recent years, with the rapid growth of traffic flow in highway tunnels, the in-tunnel environmental pollution problem has aroused widespread concern in China. Previous studies mainly focused on the emission factors in tunnels dominated by passenger cars (PCs) and light commercial vehicles (LCVs). However, this study concentrated on the characteristics of traffic flow dominated by heavy-goods vehicles (HGVs), environmental monitoring and assessment in highway tunnels in mountainous areas. To explore the emission characteristics of vehicle pollutants in highway tunnels in such regions, a field measurement was conducted in Qinling No. 3 Tunnel in China, focusing on the traffic volume, air velocity, and pollutant concentration. Measurement results show that the average daily traffic volume in Qinling No. 3 Tunnel is 22,218 pcu/d, with the HGVs comprising more than 65%. The average air velocity in case tunnel reaches 5.09 m/s. The average concentrations of NH3, SO2, CO, and NOx in the tunnel are 4.54 ppm, 0.06 ppm, 6.22 ppm, and 4.39 ppm, respectively. The single vehicle emission rates of measured pollutants are calculated based on collected data, among which, the emission factor of NOx is the largest (average: 9.37 g/(km·veh)), while that of SO2 is the lowest (0.09 g/(km·veh)). The results show that the dilution of NO2 in the tunnel should be considered in the ventilation design of highway tunnels.

Socioeconomic impacts with the implementation of the railroad EF-118 RJ/ES: comparison of cargo logistics at the Port of Açu

Since the beginning of operations in 2014, Port of Açu has shown significant growth in relation to cargo handling, with all demand dependent on road transport. However, there is a proposal for the implementation of the EF-118 railway that would interconnect Rio de Janeiro and Vitória, serving the region of Port. This work seeks to economically evaluate the advantages of the implementation of the railway modal compared to the roadway already used in the region. Due to the intense flow of cargo in the Industrial-Port Complex, the possibility of building a new highway, the RJ-244, is being studied, extending from the industrial district to BR-101. For this purpose, surveys were conducted to determine the average daily volume of vehicles circulating in the region, in addition to the different types of cargo transported and their relationship with Port. Based on the information collected in the Traffic Studies Report issued, it was possible to relate data and achieve at the value of the average annual daily volume for each category of cargo handled in the Port. Bearing in mind that in 2019, Port of Açu handled approximately 751 thousand tons of cargo and analyzing the estimated costs by ABIFER for road and rail transport, the approximate cost values for each one per ton of cargo per kilometer were reached. Comparing values, it is possible to notice that the cost of transporting cargo by rail corresponds to about 16.6% of the amount spent on transporting of the same weight of cargo by road, which means a considerable advantage for its implementation.

Surveying annual average daily traffic volumes using the trip connectivity function of vehicle GPS in an urban road network

ABSTRACT Vehicle-trajectory big data, collected through vehicle-GPS systems, is one of key information sources for road traffic volumes because the vehicle-trajectory volume represents a certain portion of the total traffic volume. This renders a promising opportunity in surveying annual average daily traffic (AADT) volumes. Devising viable means of surveying AADT volumes for all road segments with limited budgets and resources remains one of the main challenges in urban transportation studies. This paper proposes a new methodology for directly surveying AADT volumes using vehicle-GPS trajectory data. The methodology consists of two sub-methods: a nonlinear spatial clustering method based on trip connectivity between observed road sections and a target road section for selecting effective road sections from a road network, and a direct conversion method to understand the nonlinear relationship between the annual average daily probe (AADP) volumes and the observed AADT volumes for the selected road sections, with the subsequent expansion of the AADP volume of the target road section into the AADT volume. In a case study with real-world vehicle-GPS trajectory data, the performance of the method was found to be highly acceptable for actual applications in terms of its estimation accuracy. Therefore, it appears that the proposed method is and will be feasible in the present and near future.