Showing papers in "Transportation Research Record in 2006"
TL;DR: In this article, it was found that severe winter storms bring a higher risk of being involved in a crash by as much as 25 times, much higher than the increased risk brought by behaviors that state governments already have placed sanctions against, such as speeding or drunk driving.
Abstract: Weather affects many aspects of transportation, but three dimensions of weather impact on highway traffic are predominant and measureable. Inclement weather affects traffic demand, traffic safety, and traffic flow relationships. Understanding these relationships will help highway agencies select better management strategies and create more efficient operating policies. For example, it was found that severe winter storms bring a higher risk of being involved in a crash by as much as 25 times—much higher than the increased risk brought by behaviors that state governments already have placed sanctions against, such as speeding or drunk driving. Given the heightened risk of drivers' involvement in a crash, highway agencies might wish to manage better and restrict use of highways during times of extreme weather, to reduce safety costs and costs associated with rescuing stranded and injured motorists in the worst weather conditions. However, the first step in managing the transportation systems to minimize the ...
291 citations
TL;DR: By modeling the demand for two different scenarios (Zurich, Switzerland, and the German states of Berlin and Brandenburg), the framework shows its flexibility in aspects of diverse input data, interfaces to third-party products, spatial resolution, and last but not least, the modeling process itself.
Abstract: Microsimulation is becoming increasingly important in traffic demand modeling. The major advantage over traditional four-step models is the ability to simulate each traveler individually. Decision-making processes can be included for each individual. Traffic demand is the result of the different decisions made by individuals; these decisions lead to plans that the individuals then try to optimize. Therefore, such microsimulation models need appropriate initial demand patterns for all given individuals. The challenge is to create individual demand patterns out of general input data. In practice, there is a large variety of input data, which can differ in quality, spatial resolution, purpose, and other characteristics. The challenge for a flexible demand-modeling framework is to combine the various data types to produce individual demand patterns. In addition, the modeling framework has to define precise interfaces to provide portability to other models, programs, and frameworks, and it should be suitable for large-scale applications that use many millions of individuals. Because the model has to be adaptable to the given input data, the framework needs to be easily extensible with new algorithms and models. The presented demand-modeling framework for large-scale scenarios fulfils all these requirements. By modeling the demand for two different scenarios (Zurich, Switzerland, and the German states of Berlin and Brandenburg), the framework shows its flexibility in aspects of diverse input data, interfaces to third-party products, spatial resolution, and last but not least, the modeling process itself.
220 citations
TL;DR: In this article, two parameters related to bond energy (adhesive bond energy between the aggregate and the asphalt and reduction of free energy when asphalt debonds from the aggregate surface in the presence of moisture) were quantified with surface energies of both materials.
Abstract: The loss of physical adhesion between the aggregate and the asphalt binder is one of the important mechanisms that accelerate moisture damage in hot-mix asphalt pavements. In this study, two parameters related to bond energy—adhesive bond energy between the aggregate and the asphalt and reduction of free energy when asphalt debonds from the aggregate surface in the presence of moisture—were quantified with surface energies of both materials. Threshold values of these parameters to identify asphalt-aggregate combinations susceptible to premature moisture damage were derived by comparison of the values of these parameters with observed field performance for several mixes. Results show significant differences in bond energies developed between various aggregates and a given binder. This finding illustrates the importance of binder-aggregate compatibility and the sensitivity of calculated bond strength to surface energy measurements. Asphalt binders from different sources with the same performance grade were ...
190 citations
TL;DR: In this study, the problem of scheduling evacuation trips between a selected set of origin nodes and (safety) destinations was considered, with the objective of minimizing network clearance time.
Abstract: Evacuations necessitated by extreme events are usually envisioned as taking place with all people evacuating simultaneously; this leads to premature congestion on the surface streets and excessive delays. With the evacuating load onto the network staggered, the onset of congestion may be delayed, and people can evacuate more quickly. In this study, the problem of scheduling evacuation trips between a selected set of origin nodes and (safety) destinations was considered, with the objective of minimizing network clearance time. A modified system-optimal dynamic traffic assignment formulation is proposed; in it the total system evacuation time, as opposed to the total system trip time, is minimized. An iterative heuristic procedure is used to solve this problem: the method of successive averages is used to find the flow assignments for the next iteration; a traffic simulator, DYNASMART-P, is used to propagate the vehicles on their prescribed paths and determine the state of the system. Therefore, the simulator serves as a tool to satisfy the dynamic traffic assignment constraints implicitly while evaluating the objective function. The output of this model will be the departure time, route, and destination choices for each evacuee. The output is then aggregated to produce a time-dependent staging policy for each selected origin.
187 citations
TL;DR: In this paper, the authors examined the car-sharing growth potential in North America on the basis of a survey of 26 existing organizations conducted from April to July 2005 and concluded that carsharing continues to gain popularity and market share.
Abstract: Carsharing provides members access to a fleet of autos for short-term use throughout the day, reducing the need for one or more personal vehicles. More than 10 years ago, carsharing operators began to appear in North America. Since 1994, 40 programs have been deployed—28 are operating in 36 urban areas, and 12 are now defunct. Another four are planned to launch in the next year. Carsharing growth potential in North America is examined on the basis of a survey of 26 existing organizations conducted from April to July 2005. Since the mid-1990s, the number of members and vehicles supported by carsharing in the United States and Canada has continued to grow, despite program closures. The three largest providers in the United States and Canada both support 94% of the total carsharing membership. Growth potential in major metropolitan regions is estimated at 10% of individuals over the age of 21 in North America. Although carsharing continues to gain popularity and market share, the authors conclude that increa...
181 citations
TL;DR: In this article, a branch-and-bound algorithm is proposed to solve the path enumeration problem, which is based on the branch and bound technique and belongs to the class of deterministic methods along with existing approaches that combine heuristic or randomization procedures with shortest-path search.
Abstract: An algorithm to solve explicitly the path enumeration problem is proposed. This algorithm is based on the branch-and-bound technique and belongs to the class of deterministic methods along with existing approaches that combine heuristic or randomization procedures with shortest-path search. The branch-and-bound algorithm is formulated, and a methodology is designed for the application of deterministic approaches to a real case study. Path sets generated with different methods are compared for behavioral consistency, namely, the ability to reproduce actual routes chosen by individuals driving habitually from home to work. Choice set compositions for modeling purposes are determined for the consistency of the path generation process with the observed behavior. Further, model estimates and performance for different route choice specifications are examined for both path set compositions. Results suggest that the proposed branch-and-bound algorithm generates realistic and heterogeneous routes, reproduces better the observed behavior of the interviewed drivers, and produces a good choice set for route choice model estimation and performance comparison.
180 citations
TL;DR: In this paper, a multivariate Poisson specification that simultaneously models injuries by severity is presented, and parameter estimation is performed within the Bayesian paradigm with a Gibbs sampler for crashes on Washington State highways.
Abstract: In practice, crash and injury counts are modeled by using a single equation or a series of independently specified equations, which may neglect shared information in unobserved error terms, reduce efficiency in parameter estimates, and lead to biases in sample databases. This paper offers a multivariate Poisson specification that simultaneously models injuries by severity. Parameter estimation is performed within the Bayesian paradigm with a Gibbs sampler for crashes on Washington State highways. Parameter estimates and goodness-of-fit measures are compared with a series of independent Poisson equations, and a cost-benefit analysis of a 10-mph speed limit change is provided as an example application.
179 citations
TL;DR: An initial analysis of the access and usage patterns of Chicago Transit Authority, Illinois, smart card holders during September 2004 is presented, focusing on walking access distances, frequency and consistency of daily travel patterns, and variability of smart card customer behaviors by residential area.
Abstract: New automated fare collection systems being implemented on urban rail and bus transit systems offer the potential of tapping a rich source of customer usage data to improve transit planning. This is especially true of transit systems that offer smart cards as a payment option allowing long-term individual travel behaviors to be tracked and analyzed. This paper presents an initial analysis of the access and usage patterns of Chicago Transit Authority, Illinois, smart card holders during September 2004. The types of analyses that can be conducted with smart card registration and transaction data are discussed, the potential difficulties encountered in conducting such analyses are described, and recommendations are offered for improvement and expansion of the use of smart card data sets. The findings reported focus on walking access distances, frequency and consistency of daily travel patterns, and variability of smart card customer behaviors by residential area.
169 citations
TL;DR: This project demonstrates how GPS travel data analysis can be automated and highlights the benefits brought by an interactive analysis system, providing an innovative analysis method for personal-based GPS multimodal travel surveys.
Abstract: This project developed an integrated Global Positioning System-geographic information system (GPS-GIS) to automate the processing of GPS-based personal travel survey data. Two versions of the analysis system were developed in this project: a GPS-alone system, which uses only GPS travel data as input, and a GPS-GIS integrated system, which uses both GPS travel data and topologic information on GIS platform as input. The GPS-alone system includes an activity identification algorithm and a fuzzy logic-based mode identification algorithm. The GPS-GIS integrated system includes link identification on a GIS platform as well as an interactive link matching-mode identification subsystem, which further refines the results from previous identifications performed separately. This project demonstrates how GPS travel data analysis can be automated and highlights the benefits brought by an interactive analysis system, providing an innovative analysis method for personal-based GPS multimodal travel surveys.
165 citations
TL;DR: In this paper, an approach using the ratio of dissipated energy change, which is based on energy concepts, is used in order to explain the differences in fatigue behavior at normal and low strain levels.
Abstract: The healing phenomenon has been noted by pavement engineers for years, but its relation to hot-mix asphalt (HMA) fatigue behavior is still far from clear. This study conducted an analysis of healing and HMA fatigue behavior by introducing a specifically designed fatigue-healing test. These results help explain the differences in fatigue behavior at normal and low strain levels. An approach using the ratio of dissipated energy change, which is based on energy concepts, is used in this study. The results show that healing does exist, and its effect on fatigue life can be indicated by an energy recovery per second of rest period. The effect of healing is more prominent at low strain levels or in very long rest periods. At low strain conditions, the dominance of healing compared with the very low external load damage, considering the energy equilibrium, can result in full damage recovery. This full recovery of energy explains the existence of a fatigue endurance limit, below which HMA materials tend to have extraordinarily long fatigue lives that, as is shown, can be related to healing. The testing conducted clearly shows why polymer modification may extend the fatigue life in the field even though laboratory testing may show minimal differences compared with the neat binder test results.
163 citations
TL;DR: In this paper, the authors focus on the impact of life-course events on car ownership and, ultimately, on travel behavior to provide a basis for measures influencing people toward a more sustainable mobility.
Abstract: This study focuses on the impact of life-course events on car ownership and, ultimately, on travel behavior to provide a basis for measures influencing people toward a more sustainable mobility. The theoretical background for the analysis is the mobility biographies approach. This approach assumes that travel behavior is mainly habitual, and therefore, only relatively seldom do windows of opportunity open for behavioral changes when travel decisions are considered more intensively. Car ownership is used in the analysis as a proxy for actual travel behavior. Hence, the results may deliver some insight on the effect of key events in a person's or household's life on travel behavior and, further, the potential of soft policy intervention measures to change daily mobility. The German Socioeconomic Panel is used for the empirical analysis. The results show the importance of life-course events for travel behavior. Besides the household status variables of age, number of cars, and weighted monthly income, four k...
TL;DR: A tabu search-based heuristic approach is introduced here that can be applied on realistic-size networks and relies on insights from an analytical formulation of optimal reversibility design that reduces total system travel time.
Abstract: In urban evacuations, especially in response to an expected disaster, capacity reversibility (also known as contraflow) has been considered a workable strategy to reduce traffic congestion and to meet evacuation time deadlines Currently, contraflow strategies are mostly planned by relying on engineering judgment because of the lack of appropriate large-scale decision support tools A tabu search-based heuristic approach is introduced here that can be applied on realistic-size networks The approach relies on insights from an analytical formulation of optimal reversibility design that reduces total system travel time Computational results on a hypothetical and an urban network example network are presented and discussed
TL;DR: This paper introduces a new method that can quickly extract the background image from traffic video streams for both freeways and intersections in a variety of prevailing traffic conditions.
Abstract: Traffic monitoring cameras are widely installed on streets and freeways in U.S. metropolitan areas. Video images captured from these video cameras can be used to extract many valuable traffic parameters through video image processing. A popular way to capture traffic data is to compare the current traffic images with the background image, which contains no vehicles or other moving objects, just background such as pavement. Once the moving vehicle images are separated from the background image, measurements of their number, speed, and so on can be obtained. Typically, background images are extracted from a video stream through image processing because it may be hard to find a frame without any vehicles for normal traffic streams on urban streets. This paper introduces a new method that can quickly extract the background image from traffic video streams for both freeways and intersections in a variety of prevailing traffic conditions. This method has been tested with field data, and the results are promising.
TL;DR: Analysis shows that interdriver differences cannot be caught by different parameter settings alone; driving styles of individual drivers appear to be inherently different in that various car-following models are needed to model them satisfactorily.
Abstract: This paper examines the car-following behavior of individual drivers in real traffic on the basis of vehicle trajectory data extracted from high-resolution digital images collected at a high frequency from a helicopter. These data are used to cross-compare seven car-following models regarding their average performances as well as their specific performances for all individual drivers observed using a simulation approach. The prime objective of this cross-comparison is to study interdriver differences; both optimal parameter settings and model performances are compared between drivers. Average model performances reveal that the simplest models are generally not able to capture the dynamics of car-following behavior correctly, whereas individual estimates show that the performances of more elaborate models differ between drivers. The most important contribution of this paper is that analysis shows that interdriver differences cannot be caught by different parameter settings alone; driving styles of individual drivers appear to be inherently different in that various car-following models are needed to model them satisfactorily.
TL;DR: FHWA's Manual on Uniform Traffic Control Devices for Streets and Highways includes a walking speed of 4.0 ft/s (1.2 m/s) for calculating pedestrian clearance intervals for traffic signals, but there is a statistical difference in walking speeds between older (older than 60 years) and younger (60 years and younger) pedestrians.
Abstract: Pedestrians have a wide range of needs and abilities. FHWA's Manual on Uniform Traffic Control Devices for Streets and Highways includes a walking speed of 4.0 ft/s (1.2 m/s) for calculating pedestrian clearance intervals for traffic signals. It also includes a comment that where pedestrians who walk slower than normal, or pedestrians who use wheelchairs, routinely use the crosswalk, a walking speed of less than 4.0 ft/s should be considered in determining the pedestrian clearance times. A 2005 TCRP-NCHRP study found a 15th percentile walking speed for young pedestrians of 3.77 ft/s (1.15 m/s) and a 15th percentile walking speed for older pedestrians of 3.03 ft/s (0.92 m/s). The study also determined that there is a statistical difference in walking speeds between older (older than 60 years) and younger (60 years and younger) pedestrians. Using population projections and the 15th percentile walking speeds for each population group more than 15 years old, the proportionally weighted 15th percentile walking...
TL;DR: In this article, the authors examined the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR), and found that nonstationarity existing in the relationship of transport accessibility to land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others.
Abstract: In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.
TL;DR: Preliminary explorations of average traffic speeds before a crash showed that rear-end crashes can be placed into two mutually exclusive groups: first, those that occur under extended congestion and, second, those with relatively free-flow conditions prevailing 5 to 10 min before the crash.
Abstract: Rear-end collisions are the single most frequent type of crash on freeways. Their impact on freeway operation is also most noticeable because almost all of them occur during periods of medium to heavy demand. Preliminary explorations of average traffic speeds before a crash measured at loop detector stations surrounding the crash location showed that rear-end crashes can be placed into two mutually exclusive groups: first, those that occur under extended congestion and, second, those that occur with relatively free-flow conditions prevailing 5 to 10 min before the crash. With loop detector data preceding these two groups of rear-end crashes contrasted with randomly selected noncrash data, it was found that the first group can be attributed to parameters such as the coefficient of variation in speed and average occupancy measurable through loop detectors at stations in the close vicinity of the crash location. For the second group, traffic parameters such as average speed and occupancy at stations downstream of the crash location were significant as were off-line factors such as the time of day and presence of an on-ramp in the downstream direction. It was also observed that traffic conditions belonging to the first segment occurred rarely on the freeway but still made up about half the rear-end crashes. This observation, along with neural network–based classifiers, has been used to propose a strategy for real-time identification of conditions prone to the rear-end crashes. The strategy can potentially identify almost 75% of rear-end crashes, with reasonable false alarms.
TL;DR: In this paper, the authors examined the driver demographics, driver travel characteristics, and driver adherence to survey protocol considerations that affect the likelihood of underreporting in a household travel survey and provided important insights about underreporting tendencies in household travel surveys.
Abstract: This paper examines the driver demographics, driver travel characteristics, and driver adherence to survey protocol considerations that affect the likelihood of underreporting in a household travel survey. The research considers both the likelihood of vehicle driver trip underreporting and the level of vehicle driver trip underreporting by using a joint binary choice-ordered response discrete model. The empirical analysis uses the Global Positioning System-equipped sample of households from the 2004 Kansas City (Kansas and Missouri) Household Travel Survey which also provided travel diary information. The empirical results provide important insights about underreporting tendencies in household travel surveys. In particular, adults younger than 30 years of age; men; individuals with less than a high school education; unemployed individuals; individuals working in clerical and manufacturing professions; workers employed at residential land uses; individuals who make many trips, travel long distances, and tr...
TL;DR: In this paper, the authors compare two types of regression techniques: the traditional negative binomial (TNB) and the modified negative binometric (MNB) for identifying and ranking of accident-prone locations.
Abstract: There are several regression techniques to develop accident prediction models. Model development and subsequently the results are affected by the choice of regression technique. The objective of this paper is to compare two types of regression techniques: the traditional negative binomial (TNB) and the modified negative binomial (MNB). The TNB approach assumes that the shape parameter of the negative binomial distribution is fixed for all locations, while the MNB approach assumes that this shape parameter varies with the location's characteristics. The difference between the two approaches in terms of their goodness of fit and the identification and ranking of accident-prone locations is investigated. The study makes use of a sample of accident, volume, and geometric data corresponding to 392 arterial segments in British Columbia, Canada. Both models appear to fit the data well. However, the MNB approach provides a statistically significant improvement in model fit over the TNB approach. A total of 100 locations were identified as accident-prone by both approaches. A comparison between the ranks showed a close agreement in the general trend of ranking between the two models. While the MNB approach appears to fit the data better than the TNB approach, there was little difference in the results of the identification and ranking of accident-prone locations. This is likely due to the nature of the application and the data set used. The difference in results will depend on the extent to which deviant sites exist in the data set.
TL;DR: In this article, a TCRP project that provided a wide-ranging analysis of carsharing in North America, direct contacts with carharing members through focus groups and a web-based survey were used to determine demographic characteristics of users, their travel patterns, and their attitudes about car-sharing.
Abstract: Carsharing offers access to cars and other vehicles without ownership of those vehicles. This transportation option is growing rapidly in the United States and Canada. In appropriate community settings, carsharing can increase mobility, reduce vehicle travel, and complement other transportation modes. In a TCRP project that provided a wide-ranging analysis of carsharing in North America, direct contacts with carsharing members through focus groups and a web-based survey were used to determine demographic characteristics of users, their travel patterns, and their attitudes about carsharing. Special attention was paid to why members joined carsharing organizations, how they used the services, and what they liked and disliked about carsharing. With descriptive statistics from the Internet survey and qualitative analyses of focus group results (both checked against previous literature), it was determined that carsharing appeals to individuals who can be considered to be social activists, environmental protectors, innovators, economizers, or practical travelers. Carsharing companies and their partners could conceivably increase their membership by targeting such individuals and others with certain demographic characteristics.
TL;DR: In this paper, a comparison of the measured autogenous shrinkage is made by using four measurement methods: a sealed membrane, a corrugated tube, a noncontact measurement in a rigid mold, and the ASTM C 157 standard.
Abstract: Early-age cracking in concrete bridge decks, pavements, and superstructure elements has served as the impetus for substantial research on early-age shrinkage in cementitious materials. Much of this research has indicated how mixture proportions, constituent materials, and construction operations can be altered to reduce the risk of cracking. Unfortunately, many unrestrained shrinkage-testing protocols do not provide a comprehensive picture of the early-age shrinkage exhibited by cementitious materials, especially those used in higher-strength concrete. In this paper, the authors review several early-age shrinkage testing procedures. A testing protocol is presented to show how chemical shrinkage can be measured by using buoyancy measurements. A comparison of the measured autogenous shrinkage is made by using four measurement methods: a sealed membrane, a corrugated tube, a noncontact measurement in a rigid mold, and the ASTM C 157 standard. The results of the autogenous and chemical shrinkage tests are compared with one another to describe fully early-age length change. It is shown that through careful experimentation and interpretation, the results of these tests can be completely correlated with one another. This can provide the end user with reliable test procedures to compare different paste compositions and different admixtures and can provide inputs for models that quantify cracking potential.
TL;DR: A framework is presented for a stochastic network model with Poisson-distributed demand and uncertain route choice and the analytical derivative of the TTR is derived with the sensitivity analysis of the equilibrated path choice probability to solve the RNDP.
Abstract: In the reliable network design problem (RNDP) the main sources of uncertainty are variable demand and route choice The objective is to maximize network total travel time reliability (TTR), which is defined as the probability that the network total travel time will be less than a threshold A framework is presented for a stochastic network model with Poisson-distributed demand and uncertain route choice The travelers are assumed to choose their routes to minimize their perceived expected travel cost following the probit stochastic user equilibrium condition An analytical method is presented for approximation of the first and second moments of the total travel time These moments are then fitted with a log-normal distribution Then the design problem is tackled in which the analytical derivative of the TTR is derived with the sensitivity analysis of the equilibrated path choice probability This derivative is then supplied to a gradient-based optimization algorithm to solve the RNDP The algorithm is tes
TL;DR: In this article, the relationship between land use, population, employment by sector, economic output, and motor vehicle accidents is explored in a uniform 0.1-mi2 (0.259-km2) grid structure and with various linear regression models.
Abstract: In this study, the relationships between land use, population, employment by sector, economic output, and motor vehicle accidents are explored. Through the use of comprehensive data from the largest county in Hawaii, the relationships are modeled in a uniform 0.1-mi2 (0.259-km2) grid structure and with various linear regression models. This method has an advantage over other approaches that have typically used unevenly sized and shaped traffic analysis zones, census tracts, or block groups. Positive, statistically significant relationships among population, job counts, economic output, and accidents are identified. After some of the general effects are sorted through, a negative binomial (NB) model is used to look at the absolute and relative effects of these factors on the number of pedestrian, bicycle, vehicle-to-vehicle, and total accidents. With a multivariate model, the different effects can be compared and the specific nature of the relationships between zonal characteristics and accidents can be id...
TL;DR: In this paper, the authors used generalized estimating equations (GEE) to account for the spatial correlation among signalized intersections, especially closer ones along a certain corridor, and divided the intersections along the 41 corridors into 116 clusters.
Abstract: Intersections could be considered as isolated when the distance between them is long because, the influence between them is negligible. Signalized intersections, especially closer ones along a certain corridor, are spatially correlated and will influence each other in many respects. Use of the basic negative binomial regression for correlated crash frequency data leads to invalid statistical inference due to incorrect test statistics and standard errors that are based on the misspecified variance. Generalized estimating equations (GEE) provide an extension of generalized linear models to the analysis of correlated data and can account for the spatial correlation among signalized intersections. In this study, 476 signalized intersections from 41 corridors are selected in Orange, Brevard, and Miami-Dade Counties in Florida. Because the distance between some intersections along some corridors is very long, the intersections along the 41 corridors were divided into 116 clusters. The spatially correlated crash...
TL;DR: In this article, a simulation model is developed, with an emphasis on operator-based relocation techniques, to help operators identify measures to maximize resources and enhance service levels, and three performance indicators are proposed to evaluate the effectiveness of different relocation techniques.
Abstract: A shared-use vehicle system has a small number of vehicles reserved exclusively for use by a relatively larger group of members. Challenged by accessible and economical public transportation systems, multiple-station shared-use vehicle companies are driven to gain a competitive edge by using an operator-based relocation system to ensure privacy, simplicity, and convenience to their users. To help operators identify measures to maximize resources and enhance service levels, a simulation model is developed, with an emphasis on operator-based relocation techniques. A qualitative analysis conducted on operator-based relocation systems provides insights on the key issues involved and their influences over each other. On the basis of this analysis, a time-stepping simulation model is developed, and three performance indicators are proposed to evaluate the effectiveness of the different relocation techniques. The model has been validated by using commercially operational data from a local shared-use vehicle company. With the existing operational data as the base scenario, two proposed relocation techniques, namely, shortest time and inventory balancing techniques, and various operating parameters are studied. The simulation results have shown that if the inventory balancing relocation technique is used, the system can afford a 10% reduction in car park lots and 25% reduction in staff strength, generating cost savings of approximately 12.8% without lowering the level of service for users.
TL;DR: The developed best-fit statistical distribution (lognormal) can be used to compute and predict travel time reliability of freeway corridors and report this information in real time to the public through traffic management centers.
Abstract: Travel time reliability is an important system performance measure for freeway traffic operations It captures the variability experienced by individual travelers, and it is an indicator of the operational consistency of a facility over an extended period Real-life transportation data were used to develop a new methodology for estimating travel time reliability of the 1-4 corridor in Orlando, Florida Four different travel time distributions were tested: Weibull, exponential, lognormal, and normal The developed best-fit statistical distribution (lognormal) can be used to compute and predict travel time reliability of freeway corridors and report this information in real time to the public through traffic management centers When compared with existing Florida and buffer time methods, the new reliability method showed higher sensitivity to geographical locations, which reflects the level of congestion and bottlenecks Another advantage of the new method is its ability to estimate the travel time reliabil
TL;DR: In this article, the safety of pedestrians crossing in marked crosswalks on busy arterial streets was evaluated using a set of engineering treatments, including red signal or beacon devices, active when present devices, and enhanced and high-visibility treatments.
Abstract: This paper evaluates engineering treatments that can be used to improve the safety of pedestrians crossing in marked crosswalks on busy arterial streets. The research team collected extensive data at 42 study sites in different regions of the country to gauge the effectiveness (as measured by motorist yielding or stopping) of various engineering treatments. Motorist yielding data were collected for crossing pedestrians from the general population as well as for crossings staged by the research team. In preliminary analyses, the treatments were grouped into three categories based on function and design: (a) red signal or beacon devices, (b) "active when present" devices, and (c) enhanced and high-visibility treatments. The authors found the red signal or beacon devices to be the most effective, with yielding rates exceeding 94% for all study sites. Other treatments had various rates of motorist yielding, and several variables (number of lanes and speed limit in particular) were statistically significant in...
TL;DR: In this article, the authors proposed a cell-based network model to capture critical characteristics associated with staged evacuation operations and showed the ability to reflect incident impacts and arrival patterns of evacuees in computing the optimal starting time and routes for each evacuation zone.
Abstract: Staged evacuation is widely used in emergency situations in which different parts of the target network may suffer different levels of severity over different time windows. By evacuating those populations in the network via an optimized sequence, the staged evacuation strategy can best use available roadway capacity, optimally distribute the total demand over the evacuation time horizon, and thus minimize the network congestion level. This study proposes a cell-based network model to capture critical characteristics associated with staged evacuation operations. The proposed model shows the ability to reflect incident impacts and arrival patterns of evacuees in computing the optimal starting time and routes for each evacuation zone. Preliminary numerical results have demonstrated the potential for applying the proposed staged evacuation model in real-world emergency management and planning.
TL;DR: In this paper, a clustered distinct element (DEM) approach is presented as a research tool for modeling asphalt concrete microstructure, which involves the processing of high-resolution optical images to create a synthetic, reconstructed mechanical model that appears to capture many important features of the complex morphology of asphalt concrete.
Abstract: A clustered distinct element method (DEM) approach is presented as a research tool for modeling asphalt concrete microstructure. The approach involves the processing of high-resolution optical images to create a synthetic, reconstructed mechanical model that appears to capture many important features of the complex morphology of asphalt concrete. Uniaxial compression tests in the laboratory were employed to measure the dynamic modulus of sand mastic (a very fine sand-asphalt mixture) and asphalt mixtures at three temperatures and four loading frequencies. For a coarse mixture considered in this study, it was found that a two-dimensional (2-D) clustered DEM provided good estimates of mixture dynamic modulus across a range of loading temperatures and frequencies without calibration. However, for a fine-grained mixture, the uncalibrated predictions of the 2-D model were found to reside near the lower theoretical bounds and well below experimentally determined moduli, most likely because of current limitation...
TL;DR: The overall framework and components of an in-vehicle data recorder (IVDR) called DriveDiagnostics is described and results from a study to validate its performance are presented and show significant correlations between the two data sets.
Abstract: This paper describes the overall framework and components of an in-vehicle data recorder (IVDR) called DriveDiagnostics and presents results from a study to validate its performance. This IVDR has been designed to monitor and analyze driver behavior not only in crash or precrash events but also in normal driving situations. It records the movement of the vehicle and uses this information to indicate overall trip safety. A validation study involved 33 drivers whose vehicles were instrumented with the IVDR. The experiment first included a blind profiling stage in which drivers did not receive any feedback from the system; that stage was followed by a feedback stage in which drivers had access to personal web pages with the information recorded by the system. Data collected in the blind profiling stage was used to investigate the connection between driver safety indices as captured by the system and historic crash data. The results show significant correlations between the two data sets, suggesting that the ...