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This paper documents the in-place recycling of a high-traffic project (12,000 vehicles per day) on U.S. highway 49 (US-49). Sections built included asphalt emulsion–stabilized cold in-place recycling (CIR), portland cement–stabilized CIR, cement-stabilized fulldepth reclamation (FDR), and traditional construction. This paper’s objective is to present a case study of US-49 construction and performance through approximately 4.5 years of service. Performance was characterized by a distress survey, cored properties, and falling weight deflectometer testing. In particular, findings demonstrated performance and economic trade-offs between cement CIR and emulsion CIR, which could be directly applied to planning decisions. Emulsion CIR exhibited sufficient rutting capacity but reserve cracking capacity, at higher costs relative to cement CIR. Cement CIR, however, was more economical and exhibited excess rutting capacity but not excess cracking capacity. Because there is little need for reserve capacity of one distress when other distresses are past capacity, this paper proposes balanced binder blends (examples might include 2.5% emulsion with 2% cement, or 3% emulsion with 1.5% cement) for future consideration because they can provide sufficient capacity for multiple distresses while balancing economics. [ABSTRACT FROM AUTHOR]

Despite the fact that both traffic researchers and highway agencies have devoted considerable efforts over the past few decades to improving intersection safety, the development of effective strategies remains a challenging task. This research presents an integrated dilemma zone protection system (DZPS) for contending with the safety issues caused by the presence of a dilemma zone, a primary factor contributing to the rear-end collisions or side-angle crashes at intersections, especially at those experiencing high-speed traffic flows. The entire paper includes three parts: (1) development of an integrated system for protecting vehicles within the dilemma zone; (2) procedures to calibrate those key system parameters with field data at a candidate intersection; and (3) design of a per-deployment assessment process for evaluating such a design prior to its field deployment. The proposed DZPS, developed with a target intersection’s traffic characteristic data and geometric constraints, consists of three principal modules: variable message sign (VMS) for advanced warning or speed display, wide-range sensors to track individual vehicles in the dilemma zone, and a decision module to execute the all-red extension function. Based on a proactive design notion, the proposed DZPS can first use the VMS to inform the approaching drivers of a yellow or red phase ahead and prepare to stop, or to display the speed of the discharging traffic flows from the stop line during a green phase. The information will help compliant drivers to adjust their speeds in a timely manner so as to avoid rear-end collisions. For those aggressive/noncompliant vehicles, the DZPS system’s wide-range sensors will track the evolution of their speeds and locations within the dilemma zone at the interval of every 0.1 s, and then determine whether or not an all-red extension call shall be granted to prevent such vehicles from incurring potential side-angled crashes with vehicles from the side street. Recognizing that reliable evaluation of a deployed DZPS’s effectiveness needs the field data over a sufficiently long period, this study has presented the process for conducting a predeployment assessment with well-calibrated simulation experiments. The effectiveness of the proposed system, demonstrated with the results of the case study at the intersection of highway U.S. 301 at Croom Station Road, Upper Marlboro, Maryland, has also been summarized in this paper. Overall, the proposed system, from both the proactive and reactive perspectives to protect drivers, exhibits quite promising properties for use in practice. [ABSTRACT FROM AUTHOR]

Based on field data collected at nine roundabouts in Gold Coast, Australia, this paper evaluates the performance of the capacity estimation for single-lane roundabouts using analytical models [including the highway capacity manual (HCM) 2000 model, the German Highway Capacity Manual (GHCM) model, the signalized and unsignalized intersection design and research aid (SIDRA) model and a new roundabout capacity (NRC) model] and an empirical model (the HCM 2010 model). First, this study calibrates critical gaps, follow-up times, and conflicting flows. Compared with the capacities measured in the field, the authors carry out a study to analyze the accuracy of the HCM, GHCM, SIDRA, and NRC models. The results show that the five models underestimate capacity but the NRC model produces a smaller range of relative error (−1.07 to −5.74%) and root-mean-square deviation (47.68) than the HCM 2010 (−4.62 to −16.14% and 105.00, respectively), HCM 2000 (−5.76 to −17.21% and 115.29, respectively), GHCM (−8.95 to −21.26% and 146.82, respectively), and SIDRA (−5.15 to −17.51% and 113.48, respectively) models. Accordingly, the NRC outperforms the other four models for the surveyed roundabouts. The five models estimate a similar capacity in low and medium traffic volumes, and exiting vehicles play an important role in high traffic volumes, and at high traffic condition exiting vehicles warrant more entry opportunities that exceeds the impact of high circulating volumes on entry capacity. [ABSTRACT FROM AUTHOR]

Nonstructural factors, such as surface distresses and ride quality, have been commonly used as the main indicators of in-service pavement conditions. In the last decade, the concept of implementing a structural condition index in pavement management system (PMS) to complement functional condition indices has become an important goal for many highway agencies. The rolling wheel deflectometer (RWD) provides the ability to measure pavement deflection while operating at the posted speed limits causing no user delays. The objective of this study was to develop a model to predict pavement structural capacity at a length interval of 0.16 km (0.1 mi) based on RWD measurements and to assess its effectiveness in identifying structurally deficient pavement sections. Rolling wheel deflectometer data collected from 153 road sections (more than 1,600 km) in District 05 of Louisiana were used in this study. The predicted structural number (SNRWD0.16) showed an acceptable accuracy with a root-mean square error (RMSE) of 0.8 and coefficient of determination (R2) of 0.80 in the validation stage. Core samples showed that sections that were predicted to be structurally deficient suffered from asphalt stripping and material deterioration distresses. Results support that the developed model is a valuable tool that could be used in PMS at the network level to predict pavement structural condition with an acceptable level of accuracy. [ABSTRACT FROM AUTHOR]

Vehicle following has always been a hotspot of research in the transportation system. It can be used in many applications, such as unmanned ground vehicle (UGV) queue marching, traffic congestion relief, automatic driving systems, etc. Trajectory tracking has been the main consideration in previous studies, but the research about following distance is rare. In this paper, a novel vehicle-following model is proposed for independent vehicle following. In the proposed model, multisensor information is fused to promote the detection accuracy. Moreover, a virtual piecewise spline tow-bar is built between the leader vehicle and the follower vehicle. According to the state of virtual towbar, the following speed and heading can be well controlled, to keep a reasonable gap between two vehicles. The proposed vehicle-following model is designed for low speed and minor vehicle spacing case. By using the proposed vehicle-following model, the performance of multplevehicle automatic cruise can be improved, resulting in a steady traffic flow on an express way. Then the stop-and-go waves of congestion can probably be relieved. Simulation and experiment are conducted to validate the efficiency and robustness of the proposed vehicle-following model. [ABSTRACT FROM AUTHOR]

As the demand for additional capacity on urban freeways continues to increase, there is a need to better understand how to optimize the lane and shoulder configurations so as to improve capacity without adversely impacting operating speed. The overall objective for this research effort was to identify the operational implications of using reduced lane and shoulder widths on freeways. The operational analysis found speeds 3.5 km=h (2.2 mph) higher for a 3.7 m (12 ft) lane as compared to a 3.4 m (11 ft) lane. The authors developed an equation that can be used to predict speeds per lane for freeway locations with boundary conditions similar to those present in the study database. [ABSTRACT FROM AUTHOR]

This paper describes a turbo roundabout design procedure based on the rules of design vehicle movement geometry. Previous studies carried out on various junction types have shown that this design approach ensures the usage of optimal roundabout element dimensions as well as safety and comfort during driving. A five-step design procedure is suggested, including a detailed description of relevant influential parameters. They are choosing a design vehicle, implementing the initial roundabout scheme on which the vehicle swept path is analyzed, choosing a method of assigning input parameters for swept path requirements testing procedure, choosing optimal design elements of a standard turbo roundabout, and fastest path vehicle speed analysis. [ABSTRACT FROM AUTHOR]

Precise facility-specific speed correction factors (SCFs) are important parameters for direct and quick evaluation of the effect of traffic flow variations on vehicle emissions. However, the traditional method in developing SCFs is time consuming and costly, which impedes the development of SCFs and their applications. Based on massive instantaneous vehicle activity data, this paper proposes a novel method for deriving SCFs for light-duty vehicles on restricted access roadways in Beijing. First, a large sample of 60-s speed-specific trajectories is divided from the vehicle activity data, and grouped into speed-specific trajectory pools. Then, a database and two models of speedspecific and vehicle-specific power (VSP) distributions are established for different speed ranges. Further, by combining emission rates and VSP distributions, the SCFs for nitrogen oxides (NOx), hydrocarbons (HC), and carbon monoxide (CO) pollutants are derived for different emission standards. The derived SCFs from different sources of VSP distributions are compared with each other and validated by using another independent data source. The analysis result shows that, by using the VSP distribution database, the proposed method is applicable and effective in generating reliable SCFs in high resolution. The VSP distribution models can predict well SCFs within each speed range, while discontinuous predictions occur at their range boundary. Finally, several recommendations are made for future studies on developing comprehensive SCFs, which may help in practice to monitor dynamic traffic emissions when the real-time speed data are available. [ABSTRACT FROM AUTHOR]

The introduction of the passenger car unit (PCU) concept by the 1965 edition of the Highway Capacity Manual (HCM) enabled researchers around the world to deal with mixed traffic flow. Though some researchers have tried to show the dynamic nature of PCU factors, most of the studies in the world, as well as the latest standards being followed, still provide static PCU values for various types of vehicle categories. The present study demonstrates the dynamic nature of PCU factors on two-lane intercity highways under highly heterogeneous traffic composition. They are estimated based on speed and size of vehicle type in the traffic stream with respect to a standard passenger car. Simultaneous equations are formulated to calculate the speeds of different types of vehicles for a given traffic composition and traffic volume on the road, which lead to the determination of PCU factors. While many plots are made to describe the effect of traffic composition and volume on PCU of a vehicle type, it is felt that they are not enough to explain the complete variation. Therefore, the concept of a stream equivalency factor is suggested to convert a heterogeneous traffic stream into a homogeneous stream consisting of passenger cars. A simple linear equation is developed using data from three sites to calculate this factor for a known traffic volume and proportional composition of a traffic stream. Field data from a fourth site are used to validate the proposed model. The proposed model is quite simple to use and would avoid estimation of PCU factors for individual types of vehicles on a two-lane intercity highway. [ABSTRACT FROM AUTHOR]

Research on lane-changing behavior has been active for decades because of its significant impact on traffic operations. Most of the existing studies focus on generic weaving sections (e.g., on-ramps), and very few of them have investigated the lane-changing behavior along high-occupancy vehicle (HOV) facilities, especially in the context of comparing between different types of HOV-lane configuration or access control (i.e., continuous-access versus limited-access). In this study, extensive statistical analyses on lane-changing maneuvers have been conducted using a unique set of aerial photo data, which were collected from the same roadway segment before and after a conversion of HOV-lane configuration. To ensure the validity of this study, a Kalman filter smoothing algorithm was developed to clean the raw data. Results from this study indicate that the HOV-lane configuration has statistically significant impacts on lane-changing behaviors. For example, the lane-changing intensity (by location) along the continuous-access HOV facility is much more spread-out than the limited-access one. For merging into HOV-lane maneuvers, the time gap statistics (upon lane changing) are significantly different between the limited-access and continuous-access HOV-lane configuration. This study would be beneficial not only to the design of HOV lanes or other types of managed lanes, but also to the calibration of lane-changing behavior parameters in traffic microsimulation models. [ABSTRACT FROM AUTHOR]

Large-scale traffic congestion often develops from local long queue in single intersections, accompanied by spillover. Current traffic control methods neglect the spillover effect, which may be one reason for the low efficiency during peak hours. A novel method for isolated intersection traffic control considering spillover is proposed here. This method distinguishes itself in three aspects: first, channelized section spillover is explicitly taken into account; second, the phase plans are enumerated, therefore flexibility is assured; third, the phase sequences are optimized as well. These features improve the effectiveness of the proposed method. Because of the nature of the established optimization model, the genetic algorithm is used to derive optimal signal settings. Numerical comparisons prove the usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a vehicle-type-specific headway distribution analysis in a freeway work zone. The goal of this paper is to provide a vehicle-type-specific model with different time periods using empirical work-zone data from highway I-91 in Greenfield, MA. A nonparametric approach with a Gaussian kernel is used to describe the vehicle-type-specific headway distribution in a freeway work zone. No assumption is required on how the headways should be distributed for nonparametric methods. The vehicles are classified into Car, Van, and Truck based on a FHWA vehicle-type classification scheme. Statistical tests indicate nonparametric distribution with Gaussian kernel outperforms the lognormal distribution in statistical sense according to the χ2 values. Further, another work zone dataset from Jacksonville, FL is utilized to examine the mixed headway scenario without specifying vehicle types. The K - S and Chi-square test results suggest the necessity of considering the vehicle types separately. Following the results, a discussion regarding why nonparametric model is better and the future research directions are presented. [ABSTRACT FROM AUTHOR]

Traffic performance of a highway is expressed in terms of level of service (LOS). It is a major input to important decisions on public fund investments. Because of its unique operational characteristics, evaluation of traffic performance on two-lane highways is a critical task. This research examines the applicability of various performance measures for two-lane highways under mixed traffic conditions and assigns threshold values for different levels of service based on the best performance measure observed. Graphical and statistical analyses are carried out among the six most popular performance measures and traffic volume, but none of the considered measures are found to be reliable. A new parameter, number of followers (NF), which is defined as the number of vehicles traveling with a gap less than 2.6 s, is found to have good correlation with traffic volume but it does not reflect the true congestion conditions of a roadway. Therefore, the NF is further modified to the number of followers as a proportion of capacity (NFPC), and this parameter demonstrates a very strong correlation with traffic volume. Threshold values are proposed for the different LOS based on NFPC for mixed traffic conditions. [ABSTRACT FROM AUTHOR]

In order to evaluate the effectiveness of different pothole patching methods and materials, it is necessary to conduct a long-term field survey of patches installed at different environmental and traffic conditions. The research reported in this paper investigated the service life of different throw-and-roll pothole patches through a 14-month field survey. Three statistical methods, including (1) logistic regression, (2) classification tree, and (3) survival analysis, were employed to characterize the influence of different factors on the service life of installed patches, and to identify the performance of different patching materials. The factors investigated in the research reported in this paper included the length, width, and depth of patches; traffic level; speed limit; and freeze times. All the three statistical methods identified similar trends of the significance of factors and performance rankings of materials. Generally, patches installed on road sections with less freeze cycles, lower speed limit, and lower traffic level had significantly longer service life. A cold bag mix had significantly longer service life. In addition, the classification tree method indicated that significant influences of weather conditions and materials on the service life of patches were only observed around 1 year after the installation, indicating the necessity of the long-term survey. [ABSTRACT FROM AUTHOR]

This paper studies different specifications of fundamental diagrams for first-order dynamic traffic modeling. The fundamental diagram, which refers to the relationship between traffic flow and density at a given location, plays an important role in modeling the dynamics of traffic propagation. Many forms of fundamental diagrams have been proposed since the seminal work of Greenshields 80 years ago. Nevertheless, empirical validation of fundamental diagrams, in particular, for dynamic modeling purposes, is limited. The study is conducted with an extensive dataset collected from the U.K. M25 motorway. This paper highlights the difficulty in modeling congested traffic with single-valued fundamental diagrams and fine-grained loop detector data. Consequently, this paper first analyzes and discusses the effect of data granularity on model calibration and application. Following this, a set-valued fundamental diagram modeling approach with fine-grained data is also presented. This paper contributes to the development and validation of dynamic traffic simulation tools. [ABSTRACT FROM AUTHOR]

Accurate roundabout capacity models are essential for optimal roundabout designs, but there exist significant differences in the predicted capacities of various state-of-the-art models and in their included explanatory variables. An empirical study into roundabout lane entry capacity was thus performed in the U.K. using data from 35 roundabout entry lanes, where various model forms and explanatory variable sets were tested. Two regression models and an artificial neural network were developed. A negative exponential relationship with circulating flow predicted lane capacity better at high and low circulating flows, and better reflected the overall trends in the aggregated capacity data, compared to a linear model. The regression models performed relatively well and provided better information on the impacts of the variables than the neural network. The models consistently suggest that entry-exit separation and flows exiting on the same arm have stronger significant effects on capacity than variables such as entry angle and entry radius. These findings could thus contribute to an improved understanding of the variables that affect entry lane capacity and therefore the development of better roundabout capacity models. [ABSTRACT FROM AUTHOR]

Lane changing has received much attention as it is a significant component of microscopic traffic simulation. Many studies have focused on the details of the lane changing maneuver from external observation-based data which do not consider the type of driver performing the maneuver. The research reported in this paper relates the physical details of freeway lane changing to the type of driver performing the maneuver. Forty-six research participants drove an instrumented vehicle and performed a combined total of 726 freeway lane changes. Each research participant was categorized into one of four groups ranging from conservative to aggressive based on cluster analysis. The data were analyzed to identify any trends between the different driver types and their lane changing characteristics, specifically lane changing duration and gap acceptance characteristics. In general, more conservative drivers have greater lane changing durations than aggressive drivers. The gap acceptance comparison among driver types did not yield any conclusive trend. In addition, distributions were fitted to lane changing duration and gap acceptance histograms. The results suggest that driver type impacts freeway lane changing behavior, and therefore should be taken into account when developing or refining simulation-based lane changing models. [ABSTRACT FROM AUTHOR]

Incident detection algorithms, which are an essential part of traffic management systems, have been studied for several decades, but the research focus has primarily been on algorithms for incident detection on freeways and other free-flowing roads. When applied on arterial roads, the achievement of stable performance and scalability are major challenges when developing an effective incident detection algorithm. In this research, the authors propose an incident detection algorithm that utilizes travel time and traffic volume samples generated from a Bluetooth-based wireless vehicle reidentification system that has been implemented on arterial roads. The proposed algorithm is based on a moving average over time, which can recognize sample travel time and traffic volume patterns resulting from incidents. The use of a moving average overcomes limitations resulting from sparse travel time sample data collected. Within the algorithm, a threshold strategy is applied that makes the algorithm easy to implement and transfer, which is an important requirement for practitioners. The proposed algorithm is evaluated using reported accident data and the insight of two traffic engineers, and provides a good balance between detection rate and false-alarm rate. [ABSTRACT FROM AUTHOR]

This paper investigates the long-term trend of temporal distribution of roadway traffic using hourly traffic-count data collected in Seoul, South Korea, from 1995 to 2010. Interpolations using quadratic local polynomial regressions and a Gaussian mixture model were applied in order to identify changes in temporal distributions at a scale of less than one hour. The identified changes in distribution characteristics suggested that more attention should be given to outbound traffic, which appeared to be worsening because of the increased population and jobs outside of Seoul. Although this study did not attempt to thoroughly investigate the causal relationship between the changes of temporal distributions and the associated factors, the framework and methodology suggested are expected to play a foundational role in identifying the long-term trend of traffic flow using archived data. [ABSTRACT FROM AUTHOR]

A small fraction of the vehicle fleet produces a large ratio of the total mobile source emissions or the total fuel consumption due to different patterns of driving behavior based on driver characteristics. The Next Generation Simulation (NGSIM)-Federal Highway Administration (FHWA) trajectory data were used to compare the driving patterns of drivers under congested and uncongested conditions. Drivers were statistically classified into three groups; aggressive, moderate, and defensive drivers based on degree of strength of pushing pedals: gas pedal or brake. Accelerating and braking events, named as process, were counted, and strength of pushing pedal was measured in each process. In this paper, the measured strength of pushing pedal is named as target operating acceleration. Then, the emissions and the fuel consumption of each vehicle were estimated using the Virginia Tech Microscopic energy and emission model (VTMicro) model, which consequently provided the comparison of the emissions and fuel consumption of each driver group. The comparative statistical analyses indicate that aggressive drivers, who frequently used stronger acceleration pedal than other drivers, emitted more hydro carbon (HC), carbon monoxide (CO), and oxides of nitrogen (NOx), particularly under uncongested traffic conditions. The results also indicate that if aggressive drivers change their driving pattern to be defensive, the emissions are expected to decrease by 15.1% of HC, 20.8% of CO, and 16.7% of NOx under uncongested condition. [ABSTRACT FROM AUTHOR]

Traffic flow modeling is one of the fundamental keys to solving a traffic engineering problem. Among many parameters, time headway is frequently used to model traffic flow characteristics. A statistical analysis of time headways is immensely important to both theoretical traffic modeling and simulation-based traffic modeling. Basically, it allows researchers to describe an inherently random pattern of traffic flows. Past studies have mainly focused on the time headways of vehicles on highways, freeways, and arterials. However, studies of time headways on urban expressways are rather limited and still need further investigation. In this paper, the author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand. Particularly, the exponential distribution, the lognormal distribution, and the generalized extreme value (GEV) distribution are used to model the time headways. It is found that the GEV distribution is most effective in modeling time headways. In fact, the GEV distribution can describe more than 90% of the empirical distributions on most lanes and sections of the expressway. On the other hand, the exponential distribution is the least effective distribution. It can only describe the empirical distributions during the periods when the traffic is extremely light. [ABSTRACT FROM AUTHOR]

In recent years, there has been a widespread diffusion of roundabout intersections in the Italian road network; their undoubted popularity is attributable not only to their proven performance in terms of safety but also to their guarantee of smooth traffic flow. However, safety-related requirements of geometric designs are occasionally placed in a subordinate position; therefore, the success achieved by some foreign experiences has not been reached in every area. A model of potential crash rates may indicate how to modify the geometry of intersections to ensure safety. With regard to this, an example model based on the conflict opportunity technique has been developed for estimating crash rates at rural roundabouts. The model appears to respond well to traffic conditions and the geometry of roundabouts. Development of the model and results are described and analyzed in this paper. [ABSTRACT FROM AUTHOR]

On freeway corridors, traffic flow is limited by active bottlenecks. Weaving maneuvers (i.e., intensive lane changes) are a major cause of bottlenecks during high-demand periods. To relieve bottleneck severity, ramp metering (RM) is implemented as an active traffic control method. Ample research has been devoted to developing RM control algorithms and to exploring weaving impacts; however, RM control that is considerate of dynamic weaving impact and its evaluation has received little attention in the published literature. This paper aims to bridge that gap by proposing a proactive control algorithm that uses as inputs dynamic weaving capacity (as opposed to traditional fixed capacity values) for RM control at weaving segments. The control goals are to reduce networkwide travel time and improve traffic flow. Capacity and capacity drop were estimated through fundamental diagrams (FDs). Then, capacity drop sensitivities to on-ramp and mainline demand were analyzed within a field-data-based microsimulation model. The findings were applied to dynamically estimate weaving capacity within a macroscopic traffic flow model. The proposed traffic flow model conducted estimation in a model predictive control (MPC) framework. The RM rates were optimized by sequential quadratic programming (SQP). The proposed RM algorithm was evaluated in macrosimulation and compared with a no-control scenario as well as with a control scenario that used static (as opposed to dynamic) weaving capacity. This analysis contributes to efficient and effective field applications and freeway operational improvements. [ABSTRACT FROM AUTHOR]

Urban arterials in Shanghai usually have high intersection densities, which can lead to frequent and severe congestion. Research in this area of study focuses on urban arterial operating speed and its relationship with road geometry, traffic control, and traffic volume, and more study is needed before remedies to the congestion problems can be identified. In Shanghai, an opportunity exists to investigate urban arterial operating speed by accessing continuously updated global positioning system (GPS) data from taxis, hereafter called floating car data (FCD). With more than 50,000 taxis equipped with GPS running in the Shanghai road network, it is feasible to acquire comprehensive, citywide arterial speed measurements throughout the network. In this study, 45 arterials in Shanghai, which comprised of 177 two-direction segments bounded by signalized intersections, were selected for study. GPS data from taxis were captured during peak and off-peak hours to enable the calculation of the mean operating speed for each selected segment. Information of road geometry, traffic control, and traffic volume data was also acquired to examine their influence on operating speed. Multilevel linear regression models were utilized to analyze operating speed with the arterial level's unobserved heterogeneity accounted for as well. It was identified that roadway design variables, including segment length, number of lanes, and horizontal degree of curvature, left-turn lane types, and presence of median along with saturation degree, are all significantly related to the operating speed. The results of this study shed some light on roadway design, roadway improvement, and traffic management. [ABSTRACT FROM AUTHOR]

A simulation process is presented for providing a point estimate of average traffic delay on minor roads at urban unsignalized intersections during peak hours. A performing process of microsimulation was carried out, and a good level of conformity was obtained between the traffic simulated in the peak hours and the corresponding amount of traffic measured in the field. Traffic performance measures expressed in terms of average delay suffered by vehicles on minor roads were used in the statistical analysis. A negative binomial regression model, jointly applied to conflict traffic volume (VHPc) and traffic volume entering intersection from minor roads (), was used to model the average delay. A dummy variable was also introduced to test the adequacy of the regression model through the range of hourly conflict traffic volumes. Regression parameters were estimated by the maximum likelihood method and the significance of the covariate was evaluated by using the likelihood ratio test (LRT). The results show that the average delay on minor roads is positively associated with VHPc, VHPe and D, and these variables are all statistically significant. The regression model was found to fit well the average delays computed in simulation. Additionally, a stop-time model and a maximum queue length model were also developed. [ABSTRACT FROM AUTHOR]

The ability of a pavement to withstand traffic loads and serve the motoring public in a safe and efficient manner is adversely affected by the observable pavement surface distresses. Therefore, monitoring the performance of pavement will help to objectively determine the current condition of the pavements and, consequently, a management plan for maintenance, rehabilitation, or reconstruction. The current study builds a complete vision system and integrates its output into geographic information systems (GIS) for automated pavement monitoring and management. The system consists of an image retrieval algorithm which increases the sampling of pavement image data and reduces the computational time for processing acquired data. Also, a novel model method for edge detection, called active contours or snakes, is introduced. The active contour models show promise in detecting pavement distresses in very noisy environments. Their ability to split and match different topologies of the image data is essential for accurate crack location and shape detection. Finally, the output of the vision system is successfully integrated into GIS through concepts such as automated georeferencing and vectorization. Overall, the system is designed to overcome challenges associated with platform differences, complete automation, and processing of massive data sets. [ABSTRACT FROM AUTHOR]

Toll plazas create a number of bottlenecks on highways. They can induce motor vehicle crashes and also put workers such as toll collectors at risk. Enhancing safety at toll plazas is crucial to improving safety on tolled roadways. This study aims to evaluate the safety effects of removing mainline barrier toll plazas on highways using empirical Bayesian (EB) methodology. Recent removals of barrier toll plazas on the Garden State Parkway in New Jersey were used as a case study. Multiple-year traffic and crash data before and after the removals of the barrier toll plazas were used for evaluation. Toll plaza crash frequency models as a function of traffic flow and other relevant factors were developed, with the modeling results suggesting that there is a nonlinear relationship between toll plaza crash occurrences and both traffic flow as well as tollbooth configurations. The EB approach is also used to predict crash frequency assuming that the barrier tollbooths were not removed. These EB-based estimates were compared with the observed number of crashes after the removals of the toll plazas. Individual comparisons show reductions in crash occurrence at almost all of the toll plazas and an estimated reduction of 42.1% overall at all toll plazas due to the removal of the barrier tollbooths. The estimated crash cost was reduced by 40.1%. These estimated reductions demonstrate that the removal of barrier toll plazas is a very beneficial countermeasure towards improving safety of toll roads. As the study was performed based on multiple sites along a highway, it would be helpful to learn more lessons from other locations given the availability of reliable data for model development and validation. [ABSTRACT FROM AUTHOR]

Single-interval forecasting of traffic variables plays a key role in modern intelligent transportation systems (ITSs). Despite the achievements of advanced ITS forecasting in literature, forecast modeling of urban signalized traffic flow, which shows rapid-intensive fluctuations associated with the nonlinear and nonstationary behavior of temporal evolution, is still one of its big challenges. From the perspective of field experts, the mathematical complexity of an advanced model is also a renewal obstacle in practice. On the other hand, the accessibility of large volumes of historical data and the concurrent advanced data management systems used to access them provide data-driven nonparametric regression with a renewal opportunity in practice. In order to address these problems effectively, this paper proposes a nearest neighbor nonparametric regression (KNN-NPR) forecasting methodology to be tested against vast quantities of real traffic volume data collected from urban signalized arterials. The results show that the KNN-NPR model is clearly superior to two parametric models, Kalman filtering and seasonal autoregressive integrated moving average (ARIMA), in terms of both prediction accuracy and the construction of the directionality of temporal state evolution without a time-delayed response. Consequently, it appears that KNN-NPR, even though it is very simplified, is able to efficaciously capture the complex behavior of urban signalized traffic flow. [ABSTRACT FROM AUTHOR]

The purpose of this study is to assess the adherence of buses to their schedules when they are operating in specific conditions made by separating buses from fast general traffic by median islands, but still sharing curbside lanes with slow traffic (e.g., cars and motorcycles) on an urban arterial road with heavy traffic in Taiwan. This study uses real-time traffic data (e.g., travel time, speed, and traffic volume) collected for a 3-month period in 2010 from buses equipped with a global positioning system (GPS) and inductive loop vehicle detectors buried under the road. The ordered probit and multinomial logit models are applied to examine variables contributing to trip time between two adjacent stops being later than the scheduled trip time during different time periods of the day. The findings indicate that variables significantly influence variations in adherence to schedule, including buses operating in mixed-traffic curbside lanes, the number of bus routes passing through a stop, bus dwell time at a stop, bus headway, traffic volume, the number of intersections without traffic signals, spacing of bus stops with fewer than 300 m between them in densely populated areas, and rainy weather. [ABSTRACT FROM AUTHOR]

Statistical and heuristic models have been proposed as applications that are well suited to short-term traffic flow prediction. However, traffic flow data often contain both linear and nonlinear patterns. Therefore, neither statistical nor heuristic models are adequate to model and predict traffic flow data. This paper discusses the relative merits of statistical and heuristic models for traffic flow prediction and summarizes the findings from a comparative study for their performances. Based on that, a hybrid support vector machine for regression (SVR) methodology that combines both statistical and heuristic models is proposed to take advantage of their unique strength in linear and nonlinear modeling. In addition, the dynamics of spatial-temporal patterns in traffic flow are considered in this study, and they are treated as part of the input data. The experiment results based on the real field data of a test region in Beijing suggest that the proposed method is able to provide accurate and reliable flow rate predictions under both low- and high-flow traffic conditions. The benefit from combining statistical and heuristic models as opposed to not combining [autoregressive integrated moving average (ARIMA) model or Elman neural network (NN)] is much more evident in all cases, and the accuracy can be improved by 9.04% on average. Regarding the incorporation of a combination of temporal and spatial characteristics, the use of the hybrid model is found helpful in a one-step-ahead flow rate prediction under high-flow traffic conditions, with a maximum 9.52% improvement on accuracy. [ABSTRACT FROM AUTHOR]

Safety performance functions (SPFs) are commonly used to correlate geometric, traffic, and environmental characteristics with total crashes, and to identify hotspots that have excessive overall crash frequencies. However, different crash types are associated with different vehicle maneuvers and therefore different risk factors. At signalized intersections, geometric design, signal control, traffic flow, and traffic crash occurrences vary across different approaches of a single intersection. This study developed approach-level SPFs using a full Bayesian method to assess the safety effects of specific risk factors for rear-end, left-turn, right-angle, and sideswipe crash types, and for total crashes. Based on these approach-level SPFs, a systematic method that efficiently integrated the procedures of hotspot identification and countermeasure development was proposed. The method can be used to identify high-risk intersection approaches with specific safety problems and can serve as a useful complement to general hotspot analyses that use expected crash totals. It was found that some variables, including the number of through lanes, median presence, and left-turn protection, could have contrary effects on the occurrence of certain crash types. The proposed method can provide insights to aid in the development of countermeasures aimed at reducing certain crash types and an improved ability to identify deficiencies related to geometric and traffic characteristics for each intersection approach. [ABSTRACT FROM AUTHOR]

As one of the most popular unconventional interchange designs, diverging diamond intersection (DDI) has received increased attention over the past decade. Through a reverse operation of traffic movements between its two crossover intersections, DDI can accommodate more traffic movements within each phase. To design an effective signal plan for DDIs, one needs to address the following two critical issues: (1) how to select the common cycle length and green splits at each crossover intersection under different geometric conditions, and (2) how to coordinate a DDI's two crossover intersections with its adjacent conventional intersections. To contend with these issues, this paper presents an optimization model with the objective of maximizing intersection capacity to yield the optimal green splits and cycle length. Also, in view of the potentially large left-turn traffic volumes from the freeway off-ramps, this study has further modified a model to provide progressions to both left-turn and through traffic paths. Using simulation software as an unbiased tool, this study has conducted extensive simulation comparisons between the optimized signal plans and the results from signal optimization software under various traffic scenarios. The experimental results confirm the promising properties of the proposed signal models for DDI, especially if the traffic progression between two crossover intersections is the major concern. [ABSTRACT FROM AUTHOR]

Heteroscedasticity modeling in transportation engineering is primarily conducted in short-term traffic condition forecasting to generate time varying prediction intervals around the point forecasts through quantitatively predicting the conditional variance of traffic condition series. Until recently, the generalized autoregressive conditional heteroscedasticity (GARCH) model and the stochastic volatility model have been two major approaches adopted from the field of financial time series analysis for traffic heteroscedasticity modeling. In this paper, recognizing the pronounced seasonal pattern in traffic condition data, a simple seasonal adjustment approach is explored for modeling seasonal heteroscedasticity in traffic-flow series, and four types of seasonal adjustment factors are proposed with respect to daily or weekly patterns. Using real-world traffic-flow data collected from highway systems in the United Kingdom and the United States, the proposed seasonal adjustment approach is implemented and validated. Empirical results show that the proposed model can effectively capture and hence model the seasonal heteroscedasticity in traffic-flow series. In addition, through a comparison with the conventional GARCH model, the proposed approach is shown to consistently generate improved performances in terms of prediction interval construction. Potential applications are discussed to explore the value of heteroscedasticity modeling in transportation engineering studies. [ABSTRACT FROM AUTHOR]

Daily congestion on transportation networks is the one of the biggest problems that city authorities face. Different strategies for transportation-demand management have been developed with the aim to decrease existing negative traffic impacts. Available strategies are based on the use of accessible transportation infrastructure and have their own characteristics. In accordance with these specific characteristics, each strategy is more or less suitable for a particular transportation network. In this paper, the writers develop a model for the best strategy selection from transportation and drivers' point-of-view. The model is based on the analytical network process, i.e., on the combination with the benefits, opportunities, costs, and risks (BOCR) merit approach, with consideration of BOCR. The approach addresses problems regarding the network structure, whereby the various criteria are relevant for the considered problem. The proposed model is applied and tested on real data collected in Belgrade, Serbia. [ABSTRACT FROM AUTHOR]

Among the main factors affecting road crash injuries, speed is considered as a leading cause and contributing factor. There are numerous studies linking travel speeds and road crashes. Hence, an essential part of road safety plans and interventions is devoted to speed management. However, to manage speed, actual travel speeds have to be systematically and consistently monitored and analyzed. In this study, a system for the collection and analysis of free-flow travel speeds on the road network is presented, enabling speed monitoring at the nationwide level. The paper focuses on the collection and analysis of travel speeds on different road sections. Using the information gathered through advanced technologies combined with geographical information systems, a comprehensive speed database in space and time is provided allowing visual presentation and comparison of the results. This analysis can identify the road sections with significant excesses of travel speeds relative to the speed limits. It can also serve as a baseline to evaluate the impact of various counter-measures employed to reduce speeds. [ABSTRACT FROM AUTHOR]

In this paper, a criterion for predicting the reliability of freeway traffic flow is presented. The idea is based on an analysis of spot speed time series divided into sequences of events of random and homogeneous traffic processes. For each process, the flow rate and density were calculated; then the relationships between parameters of spot speed processes and vehicular density were obtained. Using these relationships and a simulation procedure for the spot speed process, a formulation for predicting the reliability of traffic flow moving along the offside lane on the freeway roadway was derived. Through this formulation and the measurements of flow rate and speed, the probability of instability of the roadway under examination was calculated. Furthermore, with an inverse procedure, the capacity of a lane was estimated: setting the reliability value close to 1 and considering a 15 min interval, the resulting flow rate represented the capacity. Thus, the simulation procedure was used to provide, in real time, the incoming instability conditions on the roadway and to estimate roadway capacity for the A22 Brenner Freeway, Italy. [ABSTRACT FROM AUTHOR]

Despite the increasing use of continuous-flow intersections (CFIs) to contend with the congestion caused by heavy through and left-turn traffic flows, a reliable and convenient tool for the traffic community to identify potential deficiencies of a CFI's design is not yet available. This is due to the unique geometric feature of CFI, which comprises one primary intersection and several crossover intersections. The interdependent relationship between traffic delays and queues at a CFI with five closely spaced intersections cannot be fully captured with the existing analysis models, which were developed primarily for conventional intersections. In response to such a need, this study presents a comprehensive analysis for the overall CFI delay, identifies the potential queue spillback locations, and develops a set of planning-stage models for the CFI design geometry. To facilitate the application of these proposed models, this paper also includes a case study of a CFI at the intersection of MD 4 and MD 235 constructed by the Maryland State Highway Administration. [ABSTRACT FROM AUTHOR]

This paper presents a Bayesian inference-based dynamic linear model (DLM) with switching based on three-phase traffic flow theory to predict online short-term travel time with plate recognition data. The proposed method combines the DLM model with a Hidden Markov Model (HMM) to capture the probability of flow breakdown and delays associated with congestion. By viewing travel time fluctuations as a time-varying stochastic process due to unforeseen events (e.g., incidents, accidents, or bad weather), the proposed dynamic linear model with Markov switching (SDLM) employs the HMM to determine the optimal traffic state sequence corresponding to a given travel time and flow rate observation sequence. The experimental results based on automatic license plate recognition data of a Jingtong Expressway stretch in Beijing City suggest that the proposed method can provide accurate and reliable travel time prediction under various traffic conditions. [ABSTRACT FROM AUTHOR]

This paper quantitatively assesses the performance of manual traffic-signal control by comparing its performance with two optimized traffic-signal controls during oversaturated conditions. To simulate manual traffic-signal control, the VisSim-based hardware-in-the-loop simulation (HILS), which provides similar manual controls at a field traffic-signal, was implemented. Whereas the normal-day traffic signal-timing plan was obtained from the city of Charlottesville, optimized signal-timing plans were obtained from Synchro. The results obtained from the VisSim-based simulation indicate that benefits can be achieved by utilizing manual traffic-signal control and optimized signal-controls relative to normal-day traffic-signal control during oversaturated conditions. In particular, manual traffic-signal control reduced delays to a greater extent than the two optimized signal-timing plans. Although the reduction in delays achieved by the manual signal-controls was not statistically significant when compared with the performance of the two optimized signal-controls, the results of the third and fourth manual signal-control attempts by the same operators reflecting the performance of trained manual controls showed statistically significant improvements in reducing delays. [ABSTRACT FROM AUTHOR]

Transportation professionals in China have started using an unconventional left-turn waiting area design as an innovative approach to mitigate traffic congestion at signalized intersections. The waiting area is set up beyond the stop bar at single or dual left-turn lanes at signalized intersections with lagging protected left-turn phases. This paper evaluated the effects of left-turn waiting areas on capacity and level of service of exclusive left-turn lanes at signalized intersections using empirical data. Capacity and delay models were developed by analyzing the arrival and discharge patterns of left-turning vehicles at single and dual left-turn lanes with differently sized left-turn waiting areas. The saturation headway, start-up lost time, and clearance time for left-turning passenger cars were estimated with field data measured from 22 sites. The capacity and delay models were calibrated and validated against both field-measured and simulated data. The results of sensitivity analyses showed that left-turn waiting areas increase the capacity of left-turn lanes at signalized intersections, and the capacity gains will increase with an increase in the storage capacity of the left-turn waiting areas. A procedure was proposed to determine the level of service of left-turn lanes with left-turn waiting areas at signalized intersections. [ABSTRACT FROM AUTHOR]

Mixed traffic flow is often converted to equivalent flow in passenger car units (PCUs) by multiplying the number of each category of vehicles in the traffic stream by their respective PCU factors and then adding them up. PCU is a complex parameter and depends on multitude of factors. This paper presents a methodology to convert a mixed traffic stream into a homogeneous equivalent without making use of PCU factors. Traffic volume and speed data collected on different six-lane urban arterial roads in India are analyzed to determine PCU values of five different categories of vehicles found on these roads. These PCU values are used to convert heterogeneous traffic volume in vehicles per hour to homogeneous volume in PCU per hour. A new term stream equivalency factor (SEF) is introduced in this study and denoted by . It is the ratio of traffic volume in PCU per hour and volume in vehicles per hour. The factor is related to traffic composition and volume on a road through the regression analysis method. A microsimulation program is used to generate the traffic flow data for two, three, four, and five categories of vehicles in the traffic stream, and these data were utilized to present a generalized solution for determining the value of for any combination of traffic composition and volume on a road. The proposed method is simple to use and expected to eliminate the problem of estimation of PCU factors required in many studies. [ABSTRACT FROM AUTHOR]

Daily and monthly adjustment factors have traditionally been used to expand the estimation of daily traffic volumes into average monthly and average annual traffic. However, research efforts that are devoted to developing and evaluating these factors for nonmotorized traffic, especially for cycling, are currently rare. This is attributed mainly to the lack of extensive data that can enable reliable calibration and testing of such factors. This paper explores some issues related to the development and application of daily adjustment factors for bicycle traffic. Examples include the impact of grouping daily factors by weekday/weekend and developing weather-specific factors and factors for different road classes. The analysis made use of a large data set of 500 months of daily bicycle volume data that covered 74 links in the city of Vancouver, Canada, for the years 2010 and 2011. Monthly average daily cycling volumes were estimated using different sets of factors, and the estimation accuracy was assessed and compared. It was found that developing factors for each day of the week provided similar estimation errors to grouping the factors for weekdays and weekends. In general, the best estimation results of the monthly average cycling volumes were achieved when using daily factors that are disaggregated by weather conditions. The temporal transferability of the factors was also evaluated by applying the factors from 2010 and 2011 to data from 2009. Compared to the daily factors from 2011, it was shown that the factors from 2010 provided slightly better estimation accuracies of the monthly average of daily bicycle traffic for different months in 2009. This demonstrates the degradation in the reliability of the daily adjustment factors over time, which calls for an update of these factors every few years. [ABSTRACT FROM AUTHOR]

This paper establishes a mathematical model that can represent the conflicting effects of two pedestrian streams that have an oblique intersecting angle in a large crowd. In a previous paper, a controlled experiment in which two streams of pedestrians were asked to walk in designated directions was used to model the bidirectional pedestrian stream of certain intersecting angles. In this paper, the writers revisit that problem and apply the Bayesian inference method to calibrate an improved model with the controlled experiment data. Pedestrian movement data are also collected from a busy crosswalk by using a video observation approach. The two sets of data are used separately to calibrate the proposed model. With the calibrated model, the relationship between speed, density, and flow is studied in both the reference and conflicting streams, and a prediction is made regarding how these factors affected the interactions of moving pedestrian streams. It is found that the speed of one stream not only decreases with its total density, but also decreases with the ratio of its flow relative to the total flow, i.e., the speed of the pedestrians decreases if their stream changes from the major to minor stream. It is also observed that the maximum disruption that was induced by pedestrian flow from an intersecting angle occurs when the angle is approximately 135°. [ABSTRACT FROM AUTHOR]

The relationships between traffic speed, flow, and density under various rainfall conditions on urban roads in Hong Kong are investigated in this study. The effects of rainfall intensities are examined empirically, particularly their effects on the reduction of key traffic stream parameters such as free-flow speed, speed at capacity, and capacity (or maximum flow) on urban roads. Rainfall intensity has been found to have significant impacts on urban road key traffic stream parameters, but not on traffic jam density. Generalized speed-flow and speed-density functions are also proposed and calibrated, taking into account the effects of varied rainfall intensity. The calibrated generalized functions are validated with an independent data set from the same location. The generalized speed-flow and speed-density functions are useful for assessing the performance of urban roads, particularly in cites with relatively high annual rainfall intensity. It is believed that the findings could provide better insights into the effects of rainfall intensity on urban road traffic environments for modeling their impacts on road users' route choice behaviors. [ABSTRACT FROM AUTHOR]

A new highway sign minimum retroreflectivity standard issued by the Federal Highway Administration (FHWA) is compelling agencies to evaluate how to comply while remaining within their budgets. This paper presents the results from a unique microscopic sign system simulation developed to quantitatively evaluate the effectiveness of various sign management practices. The analysis focused on three management methods-nighttime visual inspection, blanket replacement, and expected sign life-and two key sign maintenance functions, sign damage and replacement. The analysis found that sign managers should make prompt replacement of damaged signs a priority. The blanket replacement method was less cost-effective than the nighttime visual inspection method. The expected sign life method was competitive on costs with the visual inspection method while maintaining similar sign conditions. Training inspectors to be more accurate can realize further savings. Skipping inspection or replacement one year, or having an insufficient sign budget, can lead to degraded sign condition levels. The authors offer five best practices that agencies can consider when making sign management decisions. [ABSTRACT FROM AUTHOR]

Traffic-calming measures have been widely used in urban areas, aiming sometimes to reduce vehicle flow rates but primarily to reduce speed and, hence, the number and severity of traffic accidents. The one-way priority working road narrowing (throttle) is a widely used traffic-calming technique. However, installation of such a measure close to a junction can severely affect the operation and level of service, especially for the major road movements. There is a lack of research, guidance, and design standards to inform the effective deployment of such a measure. This paper starts by providing a summary of the terms and standards used in practice for traffic-calming measures, primarily focusing on the use of throttles. The paper aims to investigate the relationship between throttle spacing () from a priority junction and the 'major-to-major movement' driver's delay for different flow levels using the S-Paramics microsimulation model. The model was calibrated and validated with field data collected from a selected site within Greater Manchester for two separate days by using camcorders. Cooperative behavior between drivers (i.e., those with priority who gave way to others) was noticed and analyzed accordingly. Different scenarios were used to test the effects on delays and queues for various parameters including throttle spacing (), major-arms flow level, and reversing the direction of priority. The findings show that there is a direct relationship between throttle spacing () and the level of delay for traffic on the major arms of the junction. It is also shown that for a minor arm with two-way flow level of up to 500 vehicles per hour (), the throttle spacing should be at least 30 m. Once the flow level reaches , the spacing should be at least 50 m, whereas for flow levels of , the spacing should be at least 100 meters. Alternatively, consideration should be given to reversing the priority given to traffic by using MJTP (major-arm traffic has priority) operation rather than MNTP (minor-arm traffic has priority) when less throttle spacing () is required, to minimize delays to traffic on the major arms. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of the principle of demographic gravitation to estimate link-level annual average daily traffic (AADT) based on land-use characteristics. According to the principle, the effect of a variable on AADT of a link decreases with an increase in distance from the link. The spatial variations in land-use characteristics were captured and integrated for each study link using the principle of demographic gravitation. The captured land-use characteristics and on-network characteristics were used as independent variables. Traffic count data available from the permanent count stations in the city of Charlotte, North Carolina, were used as the dependent variable to develop statistical and neural network models. Negative binomial count statistical models (with log-link) were developed as data were observed to be over-dispersed while neural network models were developed based on a multilayered, feed-forward, back-propagation design for supervised learning. The results obtained indicate that statistical and neural network models ensured significantly lower errors when compared to outputs from traditional four-step method used by regional modelers. Overall, the neural network model yielded better results in estimating AADT than any other approach considered in this research. The neural network approach can be particularly suitable for their better predictive capability, whereas the statistical models could be used for mathematical formulation or understanding the role of explanatory variables in estimating AADT. [ABSTRACT FROM AUTHOR]

Freeway interchanges accommodate large traffic volumes within a constrained area. When their design is complex and includes unexpected features, it may increase drivers' workloads and lead to driving errors, thus increasing the likelihood of a crash. The study's goal is to provide a tool for assessing the safety impacts of interchange complexity, promoting a simpler and safer design. This paper presents an interchange complexity model (ICM) that is based on estimations of aggregated drivers' workload in interchanges. A database of 25 interchanges from the New Jersey interstate road system was used to examine the ICM and construct a resulting crash prediction model by comparing their interchange complexity index (ICI) with three years of crash data. Further on, nine additional interchanges were analyzed similarly in order to validate both the use of the ICM and the resulting crash prediction models. Actual observations of the validation data were relatively close to average model predictions. It is proposed that highway planners could use the ICM for estimating the complexity of interchange design alternatives and the implications for road safety to minimize driver errors and thus reduce crash occurrences. [ABSTRACT FROM AUTHOR]