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Passenger car equivalency (PCE) has been used for decades to convert mixed vehicle traffic into equivalent pure passenger car traffic streams for transportation planning, design, and operational analysis purposes. The term PCE was defined by the Highway Capacity Manual (HCM) in 1965 as an adjustment factor, and many approaches have continued to be developed for refining PCE values for different types of freeway geometry and vehicle distributions since then. This paper proposes an improved data-driven state-dependent passenger car equivalency (PCE–SD) approach, initially for level terrain basic freeway segments that consider average vehicle lengths for different types of vehicles. The term “state-dependent” refers to the space headway ratio at the same speed ranges between long vehicles (trucks), that fall into the same clustered category, and passenger cars. The relatively unique data stream used in this study comes from the Portland Oregon Regional Transportation Archive Listing (PORTAL) online datahub. This rich continuous data stream provides valuable information about traffic-related data at a 20-s aggregation level. Most importantly for this effort, ranges of categorical vehicle lengths are also available. According to analysis results, PCE–SD values estimate the actual passenger car distribution at different speeds and levels of operational performance (levels of service) more accurately compared with the HCM-6 PCEs on level terrain basic freeway segments. The authors propose that a state-dependent passenger car equivalency approach bridges the conversion gap from different types of trucks to passenger vehicles and could be used as an improved supplementary methodology.

Renewable energy should play a crucial role in increasing energy supplies and achieving the potential target of reducing 50% of CO2 emissions by 2050. The main objective of this study is to propose a neuro-fuzzy modelling entitled ensemble-Adaptive Neuro-Fuzzy Inference System (ANFIS) learning to predict and analyse the interrelationship between renewable energy consumption, economic growth, and CO2 emissions of G8+5 countries. This will help the governments and industry sectors to formulate energy policies and develop energy resources sustainably. The prediction method was constructed by extracting the fuzzy rules from the real-world dataset of World Development Indicators (WDI) and generalising the relationships of the inputs and output parameters for accurate prediction of CO2 emissions. The performance of the proposed method was evaluated, and the results show its efficiency in the prediction of CO2 emissions by incorporating the import indicators, including renewable energy consumption and economic growth. The U test of Sasabuchi–Lind–Mehlum (SLM) was conducted to identify the interrelationship results obtained from the ensemble ANFIS learning and the Environmental Kuznets Curve (EKC) hypothesis. The results of SLM test found an inverse U-shape condition among all countries except Brazil. The prediction of CO2 emissions trends using the soft computing approach (ensemble ANFIS) indicated that the consumption of renewable energy reduces CO2 emissions. The proposed soft computing method was found efficient in predicting CO2 emissions. It was in line with the foreseen targets of increasing the renewable energy generation and achieving the nationally determined contributions (NDCs) objectives.

With the recent growth in markets in the U.S., freight transportation systems have become more intricate, and are affected by the variety of static and dynamic elements associated with roadways. It is imperative to find effective ways to manage freight systems with smart transportation solutions so that governments can facilitate policy decisions to use their resources more efficiently. To make such concrete policy decisions for a specific study region, freight network, supply chain, and freight transportation trends should be studied carefully. As such, this study evaluates the accessibility of freight warehouses to intermodal freight facilities using Geographical Information Systems (GIS)-based tools with a focus on Value of Time (VOT), spatial distributions of warehouses and intermodal freight facilities, and traffic characteristics. A Value of Freight Accessibility (VoFA) metric is developed for traffic analysis zones (TAZs) in the Tampa Bay region as a function of accessibility to warehouses, number of trucks, and VOT. Results indicate that there is a need for smart transport solutions such as dedicated truck-only lanes, and Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) in order to help decrease the travel time needed for freight transportation and increase the freight accessibility. Findings are critical in terms of informing Florida transportation agencies to pinpoint freight bottleneck areas and enhance their freight transportation plans and policies to alleviate these bottlenecks.

Commercial/large-truck fatal crash involvement by drivers of different age groups is a critical issue for the trucking industry. Escalating safety concerns related to these heavy vehicles serving the freight economy in the U.S. have an impact national freight reliability and economic growth. This study identifies major contributing factors leading to large-truck fatal crashes for four age groups of driver

Analyzing and visualizing traffic data in order to better understand congestion trends, safety concerns, goods movement and capacity needs is a pressing need. Broadly speaking, there is a large amount of traffic data available today, including volume, lane occupancy, speed, and travel time, which can be used to manage transportation networks, provide traveler information and produce performance measures. This broadly disseminated data almost always treats all vehicles alike, without discriminating between trucks and passenger cars. Since trucks are critical and growing components of freeway traffic, monitoring and tracking their dynamics can reveal the impacts of freight movement on current freeway operations and over time will uncover trends useful for future planning and management. This study takes advantage of a unique data stream available for the freeway network of Portland, Oregon, USA. In addition to providing continuous vehicle count, speed and lane occupancies at 20-second intervals at more than 500 stations (1,300 individual detectors), the Portland system reports volume bins at 4 length-based classifications. ( 60 ft). Given that most vehicle classification studies are done over very short time intervals at an extremely limited number of locations, this nonstop data stream enables unprecedented insight into where and when trucks are traveling on Portland’s freeways and a wealth of opportunities for performance measurement and diagnosis of their impacts. The objective of this paper is to exploit this new data stream and explore new visualization techniques that depict truck volume, truck percentage and volume-weighted average vehicle speeds along Portland’s Interstate 5 corridor, an important north-south freight route between the Canada and Mexico borders. Results confirm the merit in analyzing and tracking truck volumes, proportions, and other dynamics for traffic management, information and modeling. The results of this study and the techniques employed here can be used to better understand and visualize freight movement dynamics on a continuous basis.

The emerging environmental awareness of the public, as well as the implementation of governmental regulations, force organisations to employ corporate environmental practices such as green supply chain management (GSCM) and green innovation. Accordingly, both practices are crucial to achieve professional improvement in the environmental performance of these organisations. However, research on the relationship of GSCM, green innovation, and environmental performance is relatively rare. Therefore, this study is aimed to provide empirical evidence showing that GSCM and green innovation practices significantly improve environmental performance in order to encourage organisations to implement these practices. In addition, this study investigates the relationship between GSCM and green innovation practices and the influence of these practices on the environmental performance in 123 manufacturing organisations with ISO 14001 certification. The results of PLS-SEM revealed that there is a significant and positive relationship between GSCM and green innovation, and the environmental performance. Moreover, green innovation had a positive effect on the environmental performance. Furthermore, green innovation had a mediating relationship between GSCM and environmental performance. Therefore, the present paper confirmed the significant influence of GSCM on boosting the green innovation of organisations and on the manufacturing establishments, which eventually improve the environment. In brief, the outcomes of this study provide enhanced understanding about the significant role of green innovation in the manufacturers for improving their GSCM and organisational environmental performance.

Wrong-way crashes are a major cause for safety concern along freeways and limited access facilities. This study investigated three different aspects of the use of Rectangular Rapid Flashing Beacons (RRFBs): 1) different settings of red RRFBs and their perceived effectiveness on reducing wrong-way driving based on a public opinion survey, 2) the effect of active red RRFBs on the behavior of drivers traveling on adjacent roadways via a before-and-after study, and 3) the effectiveness of red RRFBs on alleviating wrong-way driving on freeway off-ramps by analyzing the percentage of vehicles turning back after observing the red RRFB activation. Based on the public opinion survey results, the most informative warning red RRFB combination was determined and implemented in this study. The evaluation of the impact of red RRFB implementation (at six I-275 off-ramps in Tampa, FL, USA) on driving behaviors along adjacent arterials indicated that the implementation of red RRFBs did not adversely impact driving behaviors on adjacent arterials. To determine the effectiveness of red flashing beacons and RRFBs on alleviating wrong-way driving on freeway off-ramps, video recordings of red flashing beacons and RRFBs mounted on wrong-way signs were analyzed. Red RRFBs were deemed to be a more effective countermeasure to deter wrong-way driving than red flashing beacons. Six-months of video data were collected for red flashing beacons mounted on wrong-way signs, and video data collection for red RRFBs mounted on wrong-way signs is currently underway. For red flashing beacons, a high percentage of wrong-way drivers in this study made a U-turn and went back in the correct traffic flow direction upon realizing they were traveling in the wrong direction. It is expected that red RRFBs will be more effective on alleviating wrong-way driving due to their capabilities to inform drivers of wrong-way driving than those from red flashing beacons. The video data analysis for red RRFBs will be presented in a separate paper.

The main purpose of this article to present a comprehensive review of the application of the Structural Equation Modelling (SEM) in the assessment of sustainable and green supply chain management (SCM). In this paper, we systematically identified, reviewed, and categorized the selected papers in various key perspectives, including application area, research problem and study purpose and gap, type of method and technique, name of variables, name and country of authors, related theory, unit of analysis, publication year, number of hypotheses, number of sample and scope, respondents, measure validation, data collection method, and finally, findings and results. The findings of this review study demonstrated that previous works have used the SEM in the field of green SCM. In addition, it appears the manufacturing sector had the highest rank among other sectors. Results report the majority of published papers have used SmartPls and the resource-based theory (RBV) theory achieved first rank among other theories. With 16 records, Journal of Cleaner Production stands out as the most prominent outlet, and scholars published 16 papers in the year of 2016 as the most influential year. According to the findings, we identified the United States with 16 records, as the most prominent country compared to other countries. This review paper proves to be a valuable source of information for readers and practitioners in the field of SCM because it presents useful insights into green and sustainable SCM development and offers a better understanding of the current body of knowledge in these fields.

Nighttime crashes are overrepresented on United States and state roadway systems. Nighttime safety at signalized intersections in urban areas receives more attention because of frequent and serious vehicle-to-vehicle, vehicle-to-pedestrian, and vehicle-to-bicyclist traffic conflicts at night. Street illumination has proved to be an effective countermeasure to increase visibility at intersections and to reduce nighttime crashes. However, the safety effects of illuminance at urban signalized intersections are not well documented. This study investigated the impacts of illuminance on nighttime crash occurrence and nighttime crash injury severity at urban signalized intersections. Illuminance data and crash data for a sample of 91 signalized intersections were collected from the Tampa Bay region in Florida. The negative binomial model and the probit model were developed to examine the safety effects of intersection illuminance in terms of crash frequency and the risk of fatality and severe injury, respectively. The models showed that an increase in intersection illuminance from low (

The current version of the Highway Capacity Manual 2010 (HCM 2010) gives guidance on commercial truck speeds on grade through the use of truck speed versus distance–grade curves, which are located in the HCM 2010, Chapter 11. These curves are designed to allow the analyst to estimate a commercial truck's speed after it travels on a known distance of roadway with a certain grade. Typically, these curves are used to determine an equivalent grade (incline–decline and length) that will result in the same final speed of commercial trucks as would the series of grades making up a composite grade. The HCM 2010 curves were developed as a result of studies that used simulation tools. These simulation tools used a simple lookup table approach for maximum acceleration versus speed and did not account for commercial truck transmission gear–changing capabilities. These shortcomings, along with changes in truck performance over the past 20 years, necessitate an update to the HCM 2010 speed versus distance–grade curves. This study presents the development of updated speed versus distance–grade curves for commercial trucks by using TRUCKSIM. This simulation tool uses a modeling approach of full-vehicle dynamics, which ensures that commercial truck performance is accurately represented for field conditions. The results show that the performance of commercial trucks, as presented in the HCM 2010, is worse than that currently observed. Therefore, the authors recommend that the current speed versus distance–grade curves included in the HCM be replaced with those presented in this study.

Wrong-way crashes are a major cause for safety concerns along freeways and limited-access facilities. Although wrong-way crashes account for a relatively small portion of total crashes, the impact between two cars crashing into each other at high speeds in opposite directions often results in severe injuries or fatalities compared to any other type of crash. To seek solutions for mitigating wrong-way driving (WWD), multiple field tests involving a number of countermeasures using Intelligent Transportation Systems (ITS) technologies have been conducted in Florida. This study was aimed to evaluate these WWD countermeasures in Florida and develop recommendations regarding the most effective and informing WWD countermeasures through (1) analysis of existing data and studies, (2) field WWD testing using focus groups, (3) a public opinion survey, and (4) capturing human factors elements using simulation via a driving simulator. The results proved that red Rectangular Rapid Flashing Beacons (RRFBs) are the top countermeasure for mitigating WWD at freeway off-ramps, with wigwag flashing beacons as the second best, and detection-triggered blank-out signs and detection-triggered LED lights around “WRONG WAY” signs (tie) as third best. Red flush-mount Internally Illuminated Raised Pavement Markers (IIRPMs) were found to be statistically significantly effective for possible consideration as a supplemental countermeasure for mitigating WWD at freeway off-ramps. The countermeasure of delineators along off-ramps was found to be the least effective and was not considered for recommendation for deterring WWD at freeway off-ramps. This study further confirms that the newly-developed signing and pavement marking standards in Florida are a positive countermeasure on arterials to mitigate wrong-way entries onto freeway off-ramps.

The Highway Capacity Manual 2010 (HCM 2010) contains a significantly revised automobile analysis and level-of-service (LOS) methodology for arterials. This study compared the arterial LOS results of the HCM 2000 and HCM 2010 methodologies for an experimental set of arterial segments and analyzed the effects of the revised methodology. In addition, existing Florida field data sets were also analyzed with arterial segments obtained from Gainesville, Tallahassee, and Tampa, all in Florida, as well as data received from the Florida Department of Transportation Districts 2 and 3. The HCM 2010 results showed that for shorter, lower-speed arterial segments [such as in central business districts (CBDs)] it was not possible to obtain LOS Ratings A or B. Therefore, many CBD arterials that had good LOS values under the HCM 2000 methodology would now have moderate to poor LOS values. Consequently, the research team tested several revisions of the HCM 2010 methodology to find an approach that would not be as punitive to arterials with shorter segment lengths and that would provide a good balance of LOS values across a range of segment lengths, posted speeds, and traffic demands. Suggested revisions to the HCM 2010 methodology that allowed this objective to be achieved consisted of the following: the use of two classes instead of one (on the basis of the posted speed); the use of the average travel speed as the service measure instead of the ratio of the average travel speed to the base free-flow speed; and the setting of the free-flow speed to equal the posted speed plus 5 mph, instead of using the free-flow speed computations in the HCM 2010 methodology.

Despite providing the necessary required signage and pavement markings as per the Manual on Uniform Traffic Control Devices (MUTCD), wrong-way entries onto freeway and limited access facilities continue to occur and lead to wrong-way crashes, which can be severe and even fatal. Yellow rectangular rapid flashing beacons (RRFBs) have been proven to be effective to alert drivers to yield to pedestrians crossing streets; however, the effectiveness of red RRFBs with specific configurations installed at freeway off-ramps on reducing wrong-way driving onto freeway mainlines were unknown. This research investigated various combinations of RRFBs and wrong-way signs and their location placement to determine the RRFB combination most preferred by the motoring public for implementation and to assess their perceived effectiveness via a detailed public opinion survey. Comprehensive analyses were conducted based on 296 participants’ answers to a series of survey questions after their reviews of field videos recorded from a driver’s angle. The survey results showed that a vast majority (69.5%) of survey participants selected the combination of placing “WRONG WAY” signs on both the left and right sides of an interstate off-ramp with red RRFBs activated at the top and bottom as the method that most gets their attention and informs them of wrong-way driving. Additionally, approximately 58% of participants selected the non-dimmed flashing red RRFBs over the dimmed option. This study offers important findings essential for the future determination of using red RRFBs as an optional supplement to the existing standards in MUTCD to reduce wrong-way driving.

This paper documents a study sponsored by the Florida Department of Transportation and conducted to create a model that reflects bicyclists' perceptions of how a shared-use path adjacent to a roadway meets their needs. A user-validated level-of-service (LOS) model for shared-use paths adjacent to roadways (sidepaths) has been created. The resulting model will enable transportation professionals to translate the geometric, physical, and operational characteristics of a sidepath into a reliable LOS measure for the proposed facility. Data for the new sidepath LOS model were obtained from the Video Ride for Science (VRFS) 2009 event, held at the Museum of Science and Industry in Tampa, Florida. The data consist of participants' perceptions of how well roadways met their needs as they viewed video simulations from a bicyclist's eye view on the selected segments. The sidepath LOS model is based on Pearson correlation analyses and stepwise regression modeling of approximately 1,700 combined real-time video perceptions (observations) from VRFS 2009 participants. The study participants represented a cross section of individuals by age, gender, riding experience, and residency. This model has a fairly high correlation coefficient (R2 = .68) with the average observations and is transferable to the vast majority of metropolitan areas in the United States.