During oblique vehicular impacts with longitudinal barriers, an occupant’s head is often ejected out of a side window. When this occurs, the occupant’s head can contact the barrier or an object attached thereto. This impact event, often termed head slap, normally produces a serious injury or fatality. Roadside barriers and any attached hardware should be designed with sufficient offset at the top to preclude head slap for most impact conditions. The goal of this study was to identify the extent of head ejection that can be expected during high-speed crashes with longitudinal barriers. High-speed videos of full-scale vehicle crash tests were analyzed to determine the occupant head trajectories. Videos of 11 full-scale crash tests with both small cars and pickup trucks were analyzed to produce a head ejection envelope to encompass all head trajectories observed in the tests. Adjustments were made to the envelope to account for varying vehicle heights, seated passenger heights, and vehicle movements during impact. Two head ejection envelopes were created; one to encompass ejections from occupants at or below the 50th percentile male seated height and the other to encompass ejections from occupants at or below the 95th percentile male seated height. The final head ejection envelopes were constructed as a template for designing future barrier systems and for determining the safe placement of fixed objects on top of or behind rigid parapets.

Accurate prediction of bus arrival time at the stop line is a vital element to the bus signal priority system, but most previous approaches focused on predicting bus arrival times at next bus stops only. This paper develops a travel time prediction model to predict bus arrival time on the basis of global positioning system (GPS) data. Bus travel time from the detected location to stop line is divided into three parts: travel time from present point to the end of anterior queue, waiting time for the green light, and time for discharging anterior queue vehicles. Case studies were conducted in real-life signalized intersections to evaluate the performance of the model. Results showed that the presented model provided acceptable prediction accuracy. In addition, by considering the log interval of GPS data and prediction error, a determination method of the optimal decision-making zone when using sequential GPS data was developed.

This paper studies the effect of bicycles on intersection operations for those intersections where bicycle traffic causes the most disturbances to vehicular traffic. By studying different states of bicycles crossing a signalized intersection, this paper divides the conflicts between bicycles and turning vehicles into multiple stages and models the saturation flow rate of turning vehicles under the bicycles’ influence for each stage. For right-turn vehicles, in the first stage, previously queued turning vehicles and bicycles are released at the onset of green, and right-turn vehicles are blocked by through bicycles; in the second stage, bicycles arriving at the intersection randomly after initial queues are discharged, and gap acceptance consideration is used to analyze the conflict between the right-turn vehicles and bicycles to obtain the saturation flow reduction factor for right-turn vehicles. In the first stage, left-turn vehicles wait while the opposing through vehicles discharge from the queue; in the second-stage, the left-turn vehicles cross opposing randomly arriving vehicular flow and may be blocked by the bicycles in queue discharge mode and in the third stage, left-turn vehicles cross randomly arriving opposing through bicycles. The saturation flow rates of right-turn and left-turn vehicles under the bicycles’ influence are modeled considering differences in these stages. The model results are compared with real-world observations and show a better match than those from the Highway Capacity Manual (HCM) model. The results of this study can supplement the content of the signalized intersection capacity analysis method in the HCM and provide the basis for design of intersection signal timing and capacity calculation under mixed traffic conditions at signalized intersections.

This paper presents the analysis results of driver responses during a yellow phase, based on field observations of 1,123 drivers collected with a specially designed system from six signalized intersections of high crash frequency in Maryland. By classifying drivers into aggressive, conservative, and normal groups based on their responses (i.e., stop or pass) and the distances to the stop line when the signal turns yellow, the statistical tests with the ordered probit model clearly indicate some critical variables and their impacts on a driver’s decision at intersections. Such variables include average traffic flow speeds, traffic volume rate, the green split, the number of through and crossing lanes in the target approach, signal coordination, the difference between a vehicle’s approaching speed and the average traffic flow speeds, a driver’s gender and age, talking over a cell phone or not, a vehicle’s type and model, and so on. The research findings for this study offer the basis for responsible agencies to identify underlying factors contributing to aggressive maneuvers at signalized intersections which often cause traffic crashes, and to develop improvement strategies, such as customized driver education and intelligent safety protection systems.

The use of Bluetooth technology to determine vehicle travel times offers several benefits over traditional methods—most notably, an increased amount of data points. An understanding of the Bluetooth device discovery procedure provides insight on the impacts of vehicle speed and device effective range on the number of in-range scan intervals, allowing the data collection setup to be modified to improve the probability of device detection. It is determined that the number of in-range scan intervals increases as vehicle speed decreases and that vehicle speed has a greater influence when the device effective range is decreased. Our match probability is defined as the probability that a single vehicle containing a discoverable Bluetooth radio will be detected by two different scanning radios, not a sampling rate produced by the ratio of MAC detections to total number of passing vehicles. The probability of device detection escalates for roadways with lower functional classification, slower posted speed limits, and during periods of congestion. At speeds of 56 $\mathrm{km}/\mathrm{h}$ ( $35\mathrm{mi}/\mathrm{h}$ ) the probability for a match exceeds 30%, whereas at faster speeds [105 $\mathrm{km}/\mathrm{h}$ ( $65\mathrm{mi}/\mathrm{h}$ )], the probability decreases to under 10% because of poor signal strength. Optimizing the data collection setup to increase the effective range between the target radio and roadside scanning radio will result in an improved probability of device detection for faster traffic streams.

As part of the Wisconsin road weather safety initiative, the objective of this study was to microscopically assess the factor effects on the severities of multivehicle-involved crashes on high-speed roadways during rainfall utilizing a sequential logistic regression approach. Research began by considering interstate freeways in Wisconsin. Weather-related factors considered in the research included estimated rainfall intensity, water film depth, temperature, wind speed and direction, and the car-following distance at the time of crash. With each crash observation, weather data were obtained through the three most adjacent weather station locations and the inverse-squared distance method. Nonweather factors such as roadway geometries, traffic conditions, collision manners, vehicle types, and driver and temporal attributes were also considered. Sequential logistic regression was applied to predict multivehicle crash severities in ascending (forward) and descending (backward) orders, respectively. The final model was selected on the basis of a combination of model performance, parameter significance, and prediction accuracies. The backward sequential logistic regression model produced the most desirable results for predicting crash severities in rainy weather in which deficiency of car following, wind speed, the first harmful spot, vehicle types, temporal, and at-fault driver-related actions at the crash moment were found to be statistically significant. These findings can be used to provide quantitative support of road weather safety improvements via weather warning systems, highway infrastructure enhancements, and traffic management.

Bus-arrival-time information service is a key component of an advanced transit information system. Instantaneous and accurate prediction of bus arrival time can help improve the quality of service, and attracts additional ridership. On the bases of analyses of bus running processes, bus arrival time was divided into interzone link travel time and section travel time. A self-adaptive exponential smoothing-based algorithm was proposed for interzone link travel time prediction, whereas link-based and section-based algorithms were proposed for section travel time prediction. With the automatic vehicle location data collected from an actual bus route, an experiment was conducted to measure the performance (accuracy and precision in prediction) of link-based and section-based models with respect to three dominant factors: day of week, time of day, and length of segment. The research results show that: (1) the overall performance of section-based models is superior to that of link-based models on all weekdays but Monday, and few differences exist on weekends between link-based and section-based models; (2) section-based models perform significantly better than link-based models during periods when traffic conditions are relatively better; (3) as the vehicle approaches the target stop, the accuracy of prediction decreases and the precision of prediction increases for both link-based and section-based models. In addition, the performance of section-based models is superior to that of link-based models, but the gap narrows gradually with decreases length of segment.

Open-graded friction course (OGFC), which consists of an open gradation mostly of coarse size aggregate with little fines, is a special purpose mixture that is increasingly used in pavement surfacing around the world. The typical benefits of an OGFC mixture are increased surface permeability, noise reduction, and enhanced surface friction, especially in wet conditions. This paper presents results of a study focusing on the use and properties of OGFC mixtures containing reclaimed polyethylene modified binder (RPEB), crumb rubber modified binder (CRMB), and neat $60/70$ -grade binder with cellulose fibers. The relative performance of mixtures and an aspect relating to the design of such mixtures, based on the laboratory study, have been presented in detail. Several laboratory tests were carried out in this study to evaluate open-graded friction course mixture properties by adopting two different types of Marshall compaction. A draindown test, a Cantabro stone loss test, a permeability test, an indirect tensile strength test, a resilient modulus test, a rutting test, and a skid resistance test were used to evaluate the performance of OGFC mixtures. The addition of fiber stabilizers and polymerized asphalt significantly reduced the potential for draindown in OGFC mixtures. Mixtures compacted by 50 blows on one face by a Marshall hammer were found to give improved results with respect to abrasion and other related mixture properties of the OGFC mixtures. The test results indicated that polymer modification of the binder enhances the relevant engineering properties of the OGFC mixtures. Tensile strength ratio (TSR) values were found to be less for mixtures with modified binders than the mixtures with unmodified binders and fibers.

A test protocol and a data analysis method are developed in this paper on the basis of linear viscoelastic theory to characterize the anisotropic viscoelastic properties of undamaged asphalt mixtures. The test protocol includes three nondestructive tests: (1) uniaxial compressive creep test, (2) indirect tensile creep test, and (3) the uniaxial tensile creep test. All three tests are conducted on asphalt mixture specimens at three temperatures (10, 20, and 30°C) to determine the tensile and compressive properties at each temperature and then to construct the master curve of each property. The determined properties include magnitude and phase angle of the compressive complex modulus in the vertical direction, magnitude and phase angle of the tensile complex modulus, and the magnitude and phase angle of the compressive complex modulus in the horizontal plane. The test results indicate that all tested asphalt mixtures have significantly different tensile properties from compressive properties. The peak value of the master curve of the tensile complex modulus phase angle is within a range from 65 to 85°, whereas the peak value of the compressive moduli phase angle in both directions ranges from 35 to 55°. In addition, the undamaged asphalt mixtures exhibit distinctively anisotropic properties in compression. The magnitude of the compressive modulus in the vertical direction is approximately 1.2 to $\sim 2\mathrm{times}$ of the magnitude of the compressive modulus in the horizontal plane. Dynamic modulus tests are performed to verify the results of the proposed test protocol. The test results from the proposed test protocol match well with those from the dynamic tests.

The objectives of this paper are (1) to characterize the mechanical properties of porous asphalt pavement mixtures containing reclaimed asphalt pavement (RAP) and a WMA additive (Advera® WMA) using Superpave™ gyratory compactor and dynamic modulus testing. Four types of porous asphalt mixtures were evaluated in this study. They are 1) control mixture, a conventional porous asphalt mixture; (2) porous asphalt mixture with WMA additive (Advera® WMA in this case); (3) porous asphalt mixture containing 15% reclaimed asphalt pavement (RAP); and (4) porous asphalt mixture containing 15% RAP and additional WMA additive. This study evaluated compaction energy index (CEI), permeability, indirect tensile strength, and dynamic modulus ( $E^{*}$ ) for all types of porous asphalt mixtures. All of the porous asphalt mixtures meet the typical minimum coefficient of permeability in this study. Compaction energy required for the WMA containing 0.25% Advera® WMA was found to be lower compared with the control mixture (HMA). The results from the dynamic modulus test show that WMA made with 0.25% Advera® WMA had significantly lower values than the control HMA mixture. In addition, only a slight decrease in $E^{*}$ was found when WMA additive was added to the porous asphalt mixture containing RAP. For indirect tensile strength testing, WMA containing RAP was found to have the highest tensile strength among all of the mixtures tested.

To expand the applications of pervious concrete, additional research and testing must be conducted as to its structural performance. Distress surveys were performed on two field installations of pervious concrete subjected to equivalent traffic stresses as some collector streets in use for 20 years. The results of the distress survey were then used to calculate the pavement condition index (PCI) using the procedure from ASTM D6433. The PCI rating was considered to be a quantification of structural performance. The high PCI ratings of the thicker pervious concrete sections indicated that pervious concrete, when properly designed, is capable of being used for most residential streets and many collector streets for typical design life durations (20–30 years) while exhibiting satisfactory structural performance.

Moisture damage is the degradation of the mechanical properties of the material attributable to the presence of moisture in its microstructure. To enhance the life of bituminous pavements, it is necessary to understand moisture’s damage on pavements and to evaluate the effects of hydrated lime as moisture damage resisting agents. The basis of laboratory work was AASHTO T 283 test and it was performed on two types of dense graded bituminous mixes that included dense bituminous macadam and bituminous concrete mix. The study was carried out for mixes prepared without lime, and the same process was repeated with addition of 2% quantity of hydrated lime. The addition of hydrated lime in the asphalt mix improves the tensile strength ratio. However, a well-controlled lime treatment is required to maximize distribution and dispersion of lime particles on aggregate surfaces. This study also presents various causes of moisture damage and their mechanisms. Attention is also given to the chemical and mineralogical composition of aggregates and effect of some important minerals on moisture susceptibility of aggregates.

In this article a new method of designing railway track geometry is introduced. This method is adapted to the technique of global positioning system (GPS) surveying. In the presented method, the basic data necessary to project railway line modernization (the arterial directions of routes and their intersection angles as well as the coordinates of the existing rail-track axis) are obtained through continuous rail-track satellite measurements using antennas installed on mobile rail vehicle. Because the shaping of straight-line track with satellite measurements does not cause any difficulty, attention was given to designing bending sections. It has been assumed that the geometric track layout will be designed on the basis of an appropriate working system of coordinates. Then, some transformation of the acquired solution will be conveyed to the global system. The whole analysis together with the included theoretical equations is aimed at developing a concept of the rail-track system that will be as friendly in practice as possible. Therefore, it has been illustrated with a calculation example, taking advantage of data obtained from a railway line in use.

In the area with railway engineering, scheduling preventive maintenance actions is an important issue for engineers and railway administrations because the optimization of maintenance actions at a preventive level allows maintenance costs to be reduced during the life cycle of the track, with the guarantee of its geometrical quality. This paper describes a model designed to optimize the tamping operations in ballasted tracks as preventive maintenance. The model, formulated as mixed 0–1 linear program, considers real technical aspects as constraints, which is a novel approach in the optimization of track maintenance over time. Global optimization is used to predict and to schedule tamping, taking into account four aspects: the evolution of the track degradation over time; the track layout; the dependency of the track quality recovery on the track quality at the moment of the maintenance operation; the track quality limits that depend on the maximum permissible train speed. Computational experience with two track stretches of the Portuguese Northern Railway Line is included to highlight the efficacy of the proposed methodology.

Transport networks in many cities are generally very seriously congested. Consequently, travel time, number of stops, unexpected delays, transport costs, level of air pollution, noise, and traffic accidents are increased. In addition to daily congestion, there may be congestion and traffic jams as a consequence of reconstruction of the roads’ lanes. During the past decade, different strategies for transport demand management have been developed, with the aim to decrease existing traffic congestion. One of the available strategies is a ride matching (sharing) concept. This strategy means that several participants share only one private car when traveling from origin to destination. A model for grouping drivers into cars for ride matching, according to similarities of a place of living and working, working hours, and type of car license plate, is developed in this paper. The writers apply the ride matching concept on congested traffic during the reconstruction of the main bridge in Belgrade, Serbia, which is the Gazela Bridge. The basis of the proposed model is the $K$ -means method and even-odd concept. To solve the ride matching problem, the writers present improvement of the traditional $K$ -means algorithm, in which the numbers of centers is unknown in advance and the number of clusters may not be the same as the number of centers. This modification of the traditional $K$ -means algorithm, called advanced $K$ -means, for solving a specific ride matching problem is the main contribution of the paper.