Elizabeth G. Jones

Development of Bicycle Compatibility Index for Rural Roads in Nebraska

The development of a rural bicycle compatibility index (RBCI) is described. A recent FHWA research project developed a Bicycle Compatibility Index (BCI). This index was developed for urban and suburban roadway segments, and it incorporated those variables that bicyclists typically use to assess how compatible a roadway segment is for travel by bicycle. The FHWA BCI can be used by bicycle coordinators, transportation planners, traffic engineers, and others to evaluate existing facilities. With it, they can determine what improvements may be required, as well as the geometric and operational requirements for new facilities to achieve the desired level of bicycle service. No such tool exists for the rating of rural roadway segments, however. There was work done to develop a rural equivalent of the BCI. Roadways in rural Nebraska were used to develop the RBCI. Although the specific results of this work are clearly applicable to Nebraska and other similar rural areas, the general methodology and concepts could easily be used to develop a more general RBCI that would have national applicability. An RBCI will provide bicycle coordinators, transportation planners, traffic engineers, and others with the capability to better plan and design bicycle-compatible roadways. Specifically, an RBCI model can be used for operational evaluation, design, and planning.

VALIDATION OF TWO-FLUID MODEL OF URBAN TRAFFIC FOR ARTERIAL STREETS

A series of vehicular traffic experiments conducted in Omaha, Nebraska, shows that the two-fluid model of urban traffic is valid not only at the network scale but also at the arterial street scale. The data collected support the validity of the two assumptions of the two-fluid model for traffic on arterial streets. The two-fluid parameters are effective in assessing the quality of traffic between different arterial streets, over time on the same arterial street, and on portions of an arterial street. The scalability of the two-fluid model also permits systemwide effects of localized changes to a traffic network to be assessed.

COMPARISON OF OPERATIONS OF SINGLE-POINT AND TIGHT URBAN DIAMOND INTERCHANGES

Single-point urban interchanges (SPUIs) and tight urban diamond interchanges (TUDIs) are alternatives typically considered in locations where roadway right-of-way is constrained. The body of research comparing these two interchange types is limited, and operational comparisons are varied in their findings. It is believed that the traffic operation performance of these two interchange types does not differ significantly, which makes it challenging for transportation practitioners to select a preferred interchange type for a specific location. The operations of the geometrically similar SPUIs and TUDIs were compared using microscopic simulation analysis for a wide range of volume conditions. The analysis was conducted with CORSIM using optimum signal phasing and timing for both interchange types. Three specific test volume cases and five varying volume levels were developed for both interchange types to evaluate the interchanges over a range of capacity conditions. The 30 cases were analyzed using microscopic simulation, and results were summarized to compare the two interchange types. The findings show that for the geometric and volume conditions tested, the SPUI provides greater traffic operation performance than the TUDI. Over the range of tests, the SPUI provided higher average travel speeds, fewer phase failures, a lower percentage of stops, and a considerably higher capability to serve traffic. The results typically show that the TUDI will reach capacity conditions when the SPUI is operating at average conditions.

Wind/solar hybrid generation-based roadway microgrids

This paper presents the concept and design of a novel roadway microgrid. It operates as a smart microgrid that optimally utilizes the public right-of-way and roadway infrastructure to provide cost-effective, highly efficient, and reliable wind/solar electric power production, distribution, storage, and utilization. The fundamental unit of the microgrid is called the energy-plus roadway/traffic signal light (EPRTL), which contains a grid-connected wind/solar hybrid generation system installed on the pole of a roadway/traffic signal light for clean electric power production. The term “energy-plus” stands for annual energy consumption that is less than production. The generated electric power will be consumed locally by the roadway/traffic signal light; the excess power generated will be stored in batteries, optimally distributed in the microgrid, and supplied to the utility main grid. The deployment of the proposed roadway microgrid will dramatically change the role of the public right-of-way from an energy consumer to an energy producer, leading to energy-plus roadways. This will not only reduce the roadway agency operating costs but also generate new revenues for the Highway Trust Fund. The use of renewable electric power will also promote the development of green roadways.

Managing Containers in a Marine Terminal: Assessing Information Needs

The research addresses questions about how intelligent transportation systems technologies that are being used to track and manage containers in transit can also be used to manage the stacked storage of containers in marine terminals. The research focuses on import container storage. The objective is to assess whether and how more accurate and timely information about the departure times of containers can be used to more efficiently and effectively manage import containers in stacked storage. An “informed” import storage strategy along with performance analyses of this strategy in relation to typical storage strategies used by ports is presented. The strategy for organizing import stacked storage is described. The study methodology used and subsequent analysis of these options regarding performance and economics follow. Results indicate that using a reservation system similar to the crescent system used by the port of New Orleans would significantly reduce import container–handling efforts. The system would enable a port operator to gather enough information about when import containers would leave the port to allow careful ordering of import container storage, which would result in reduced handling.

In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks.

The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency’s MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NOx and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks × 6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO2 emissions are similar to those of the real world, while NOx and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions. Implications: In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.

Local Polynomial Regression Models for Average Traffic Speed Estimation and Forecasting in Linear Constraint Databases

Constraint databases have the specific advantage of being able to represent infinite temporal relations by linear equations, linear inequalities, polynomial equations, and so on. This advantage can store a continuous time-line that naturally connects with other traffic attributes, such as traffic speed. In most cases, vehicle speed varies over time, that is, the speed is often nonlinear. However, the infinite representations allowed in current constraint database systems are only linear. Our article presents a new approach to estimate and forecast continuous average speed using linear constraint database systems. Our new approach to represent and query the nonlinear average traffic speed is based on a combination of local polynomial regression and piecewise-linear approximation algorithm. Experiments using the MLPQ constraint database system and queries show that our method has a high accuracy in predicting the average traffic speed. The actual accuracy is controllable by a parameter. We compared the local linear regression model with the local cubic model by using a field experiment. It was found that the local cubic model follows more closely the raw data than the linear model follows.

Economic Analysis of Using a Renewable Wind Power System at a Signalized Intersection

The transportation sector consumes about 28% of the total energy expended by all sectors in the United States, according to the U.S. Energy Information Administration. This article proposes a renewable wind power system (RWPS) as an alternative power source for a signalized traffic intersection. The RWPS can be mounted on existing transportation infrastructure to provide green energy. Large-scale implementation of such a system has the potential to change the role of the public right-of-way from an energy consumer to an energy producer. This article provides a framework to investigate the physical and economic feasibility of installing an RWPS. Methodologies to conduct a structural analysis, site selection, and economic analysis are developed. A case study for an intersection in Lincoln, Nebraska, is used to demonstrate the application of evaluation procedures. The benefits of an RWPS are twofold: (a) the power generated by such a system can support the operation of traffic signals and any excess power produced can be sold back to the power grid; and (b) an RWPS provides a source of backup power in case of grid failure and thus increases the traffic network reliability. This article presents the methodologies to determine the economic value of an RWPS for both cases just described. The costs and benefits of providing RWPS are stated in dollar values. The decision to install an RWPS at an intersection can be made using a benefit–cost ratio. The case study shows that the RWPS is economically feasible at the subject intersection. The results also show that intersections with frequent power failures will have higher benefit–cost ratios. In the event of budget constraints, the methodologies developed in this article can be used to prioritize the investments.

Median model for background subtraction in intelligent transportation system

This research is generally divided into two phases: the first phase deals with background image generation and vehicle detection, the second phase deals with vehicle tracking and video handoff. In the first phase we view the image as a mixture of three data distributions: vehicle, background and shadow. Thus the problem is modeled as a mixture of Gaussian problem and our goal is to separate the background data from other data distributions. We proposed a median model and an improved median model to separate the background data from mixture data and to generate background reference images. In median model we keep track of deviation between the median and its neighbors in a reordered pixel sequence. When sample size is big enough, the reordered pixel sequence is in what we called balanced-median model. This model is indicated by a very small deviation value. In this case the median of the pixel sequence falls in background set and could be used for background estimation. When sample size is not big enough, the reordered pixel sequence is in what we called shifted-median model. This model is indicated by a much bigger deviation value. In this case the median falls out of background set and are excluded for background estimation. This median model has an impressive performance to handle slow moving or even stationary vehicles. But the time complexity is still expensive for real time image processing. The improved median model is proposed to reduce the time complexity to a reasonable level. In improved median model, we take samples in a bigger time interval to make it capable of dealing with slow moving and stationary vehicles. The sample size from experimentation is obtained as a small constant value between 5 and 20. This small sample constant size could dramatically reduce the time complexity. As a complementary to this improved median model, a mask-classified updating method is introduced to update the background image in a short term and only classified background pixels are being used for updating. Threshold, erosion, dilation and connected components labeling are used for noise removing and object labeling. After the first phase, the vehicle information is separated from image and input to the second phase for video hand-off and vehicle tracking. In the second phase, the weighted intensity information and shape information for each vehicle is scored and minimum-distance classification method is used for vehicle match. More than 400 vehicles are tested. An overall detection rate of 100% and tracking rate of 74% are obtained in this system.

Sensitivity analyses of stopping distance for connected vehicles at active highway-rail grade crossings

This paper performs sensitivity analyses of stopping distance for connected vehicles (CVs) at active highway-rail grade crossings (HRGCs). Stopping distance is the major safety factor at active HRGCs. A sensitivity analysis is performed for each variable in the function of stopping distance. The formulation of stopping distance treats each variable as a probability density function for implementing Monte Carlo simulations. The result of the sensitivity analysis shows that the initial speed is the most sensitive factor to stopping distances of CVs and non-CVs. The safety of CVs can be further improved by the early provision of onboard train information and warnings to reduce the initial speeds.