North American heavy haul railroads are experiencing growth in traffic demand and increases in capacity constraints. An appropriate service-design process is thus crucial to allow for more effective network capacity planning and efficient rail operations. Existing approaches to freight train routing usually ignore the congestion-induced delay and fail to consider the dynamics in link and node delay in response to traffic volume. Furthermore, different train types can have substantially different operating characteristics, including maximum speed, power-to-ton ratio, and dispatching priority. This heterogeneity causes conflicts between trains that can increase delays and reduce capacity. Therefore, traffic volume and heterogeneity should both be incorporated into the decision process for service design. In this research, the authors proposed to add an additional traffic routing process in service design and developed a novel optimization framework to route trains by considering link and node delay, directional traffic, heterogeneity, and various delay costs according to train types. To improve the solution efficiency, a solution algorithm using Lagrangian relaxation (LR) techniques is also presented. Numerical results show that the optimal strategy has the potential to substantially reduce operational costs. Using this tool can help design better traffic routing, more efficient capacity utilization, and reliable services.

The current method for the analysis of sight distance for left-turn vehicles at signalized intersections assumes that all component variables are deterministic. This paper presents a probabilistic approach based on such random variables as major-road speed, time gap required for left-turn vehicle, vehicle width, lateral position of left-turn vehicle, distance between driver eye of left-turn vehicle and its front, and lateral and longitudinal positions of positioned opposing left-turn vehicle. A safety margin is defined as the difference between available and required sight distances. Relationships for the mean and standard deviation of the safety margin were developed using the first-order second-moment (FOSM) method. This method identifies the offset (distance between left edge of the left-turn lane and right edge of the opposing left-turn lane) at signalized intersections for a desired probability of noncompliance based on intersection and traffic characteristics. The proposed reliability method was validated using Monte Carlo simulation, and design graphs were established. The results show that the deterministic method provides very conservative offsets and that the offset is most sensitive to vehicle width and lateral distance-related variables and less sensitive to longitudinal distance-related variables.

Passing zones are designed to provide sufficient sight distance for fast vehicles to pass safely slow vehicles and contribute to operational efficiency of two-lane highways. However, lack of suitable models to predict passing rate and capacity has made it difficult to quantify operational benefits of passing zones. In this paper, a model is proposed to predict passing rate in the subject direction at passing zones using traffic and geometric factors. The model is developed based on speed and passing data collected at 19 passing zones in Uganda using pneumatic tube classifiers and video recordings. Findings show that passing rates depend on the length of the passing zone, absolute vertical grade, traffic volume in two travel directions, directional split, 85th percentile speed of free-flow vehicles and percent heavy vehicles in the subject direction. The peak passing rate also referred to as the passing capacity occurs at 200, 220, and 240 vehicles/h in the subject direction for $50/50$, $55/45$, and $60/40$ directional splits, respectively. The model could potentially be applicable in planning, design, and safety evaluation of two-lane rural highways.

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 speed-specific 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.

Automated counting technologies are one of the fastest growing sources of data in the non-motorized transportation field. Although automated counts make it possible to collect data for longer time periods and to document temporal variations in volumes more effectively than manual counts, all of the technologies being used are subject to systematic miscount rates that must be accounted for to generate accurate volume estimates. In this paper, accuracy and precision rates are tested for six automated pedestrian and bicycle counting technologies: passive infrared, active infrared, radio beam, pneumatic tubes, inductive loops, and piezoelectric strips. For some technologies, multiple products are tested. Counting devices were installed at 13 sites in seven cities to introduce variation in environmental (weather) conditions and volume levels, and manual validation counts were conducted based on video footage taken at each of the test sites. Correction functions are developed for each technology to increase accuracy of volume estimates. Various environmental conditions including temperature, rain, and lighting are tested in the development of the correction functions. For most technologies, a net undercount effect was observed that appears to worsen at higher volumes. Average error rates (average percentage deviation) for the tested technologies range from 0.55% for inductive loops to $-17.38\%$ for pneumatic tubes. However, after applying correction functions accuracy improves for nearly all technologies.

Optimization of wagon flow organization in heavy-haul loading areas is meaningful to develop a heavy-haul railway network and to improve transportation capacity. This paper proposes a multiobjective optimization of the wagon flow organization for heavy-haul railway (MWFHR) to improve the transportation efficiency and the economic performance of a railway network. A bi-level algorithm is constructed to solve this model, where the lower level of the algorithm collects wagon flows for organization through the ant colony optimization algorithm, and the upper level screens for the best solution set that can minimize total cost under various constraints using the traversal search algorithm. The model is numerically examined in a real case study. Comprehensive practical testing results show that the newly proposed multiobjective optimization approach is promising in establishing an efficient railway network.

Traffic-speed deflectometers (TSD) are used in several countries to evaluate the pavement structural condition at the network level. Fatigue and rutting strains are commonly used as pavement critical responses in mechanistic-empirical design procedures to predict pavement structural performance. For successful pavement management system (PMS) application, robust indices that can be readily computed from TSD measurements and best related to the pavement critical responses should be identified. In this study, a comprehensive sensitivity analysis on deflection basin indices and their correlations with fatigue and rutting strains is performed using a range of pavement structures. A commercially available program was used in the first part of the study to compute dynamic deflection basins and evaluate the effects of material properties and vehicle speed on the indices. The indices that best relate to critical responses were identified from the software analyses and subsequently evaluated with a wider range of pavement structures analyzed using a layered linear-elastic program. Results from the TSD accuracy field evaluation were then used to further identify the robust indices in light of measurement accuracy. The study found that classifying pavement structures based on asphalt concrete (AC) thickness would be an appropriate selection for network-level PMS applications. Evaluation of 67 deflection basin indices showed that deflection slope indices ${\mathrm{DSI}}_{200–300}$ ($D_{200}–D_{300}$) and ${\mathrm{DSI}}_{300–900}$ ($D_{300}–D_{900}$) were well related indices with fatigue and rutting strains, respectively, and were selected to establish relationships with critical pavement responses for pavement categories based on AC layer thickness.

This paper proposes a novel concept, stop-line setback (SLSB), aimed at enhancing the capacity of signalized roundabouts and solving the problem of unbalanced flow patterns. This method is believed to avoid wasting acceptable time gaps and therefore increase the capacity of the approach with SLSB. However, to the best of the authors’ knowledge, no analytical work and little empirical work has yet explored the impact of SLSB. To bridge this gap, the phasing scheme and an adaptive control algorithm are developed for the roundabout with SLSB. Case studies are conducted under different traffic demands to evaluate the method. The findings show that (1) in peak hours the SLSB method is useful to improve the operational performance of the signalized roundabout and solve the problem of unbalanced flow patterns; (2) the right-turning vehicle volume is the critical factor that influences the benefits of the SLSB method; and (3) the phasing scheme and adaptive signal control algorithm developed in this paper are suitable to signalized roundabouts with distances of SLSB. Based on the aforementioned findings, it is recommended that the SLSB method be applied to one or two approaches with heavier traffic loads but not all approaches, which is believed to increase the capacity and reduce the average vehicle delay of the roundabout.