Minimizing Illegal Overweight Truck Frequencies through Strategically Planned Truck Inspection Operations
Keywords:Weigh-in-motion (WIM) data;Overweight trucks;Permit trucks;Truck weight enforcement;Optimum truck inspections
Abstracts:Over the past two decades, heavy truck traffic volumes and cargo weights have been steadily increasing due to economic growth and improved transportation system efficiency. These changes are producing an exponential increase in the damage caused to highway pavements and bridges. A disproportionate amount of highway damage is caused by extremely heavy trucks, many of which are illegally exceeding existing truck weight limits. To control the number of illegal overweight trucks, many states have installed fixed truck weighing stations on main highways and have deployed specially trained state police units that perform random roadside inspections to verify the safe operation of trucks and their compliance with the applicable legal weight limits. However, a preliminary study of police roadside inspections shows no correlation between the regions of high enforcement operations and those where overweight trucks are most frequent. Such random deployment of enforcement teams reduces the efficiency of the effort at a time when resources for such activities are in short supply. To help optimize the efficiency of the enforcement process, this paper investigates the possibility of developing a tool that utilizes available weigh-in-motion (WIM) data to plan truck traffic enforcement operations in a manner that minimizes the number of illegal overweight vehicles around a state. The proposed approach is consistent with the concept well known to sociologists and criminologists as the broken windows principle. The principle has been extensively used in many large U.S. cities to help reduce the level of crime. The implementation of the proposed methodology is demonstrated using a large truck database collected in New York State. The examples provided in this paper demonstrate that the implementation of the proposed approach will help reduce the numbers of illegal overweight trucks, which can result in a reduction of New York State’s expenditures on pavement and bridge repair and maintenance by an amount ranging from $16.0 to $53.2 million per year excluding the amount collected as fines.
Dynamic Forces at Square and Inclined Rail Joints: Field Experiments
Keywords:Insulated rail joints;Displacement;Vibration;Noise;Field experiments
Abstracts:Insulated rail joints (IRJs) are widely used in signaling and broken rail identification systems. Track deterioration adjacent to IRJ is frequent due to excessive dynamic forces generated at IRJs by the repetitive passage of the ongoing traffic. Hence, they exhibit low service life and are considered high-risk elements and maintained through high standards. With a view to increase operational speed and the annual operational throughput, many improved structural designs have been proposed, of which inclined IRJs are the focus of this paper. To compare noise, vibration, and adjacent sleepers’ vertical displacement of square and 30° and 45° cut joints, a series of field tests have been carried out in the Tehran-Karaj urban metro track. Results show that sleepers in the vicinity of 45° cut joint have less vertical displacements compared to that of 30° and square cut joints. Peak root-mean square (RMS) values of acceleration signatures of 30 and 45° cut joints are almost half the value for square joints. Noise test results show that sound level of 30° cut IRJ is less than that of 45° and square cut IRJs by 2 and 6 dBs, respectively. Also, the noise level of 30° cut IRJs is less than that of 45° and square cut joints by 1 and 3 dBA, respectively.
Development of Emission Factors for an Urban Road Network Based on Speed Distributions
Abstracts:To investigate the feasibility of incorporating speed distributions instead of average speeds to develop emission factors for emission estimations, this research collects large amounts of emission and traffic activity data. First, the relationship between emission factors and average speeds is developed. Second, speed distributions during daytime hours for classified roads are analyzed to find the speed distribution on the expressway followed the bimodal distribution; speed distributions on arterials and collectors followed the same distribution pattern, but with a single peak. Third, the research develops emission factors for the road network based on speed distributions, then compared these with those found using the traditional average-speed-based method. A comparative analysis shows even though both emission factors for these two distinct methods presented a similar variation trend, the results from the average-speed-based method were lower. The research identifies two reasons for those differences. First, speed distributions are flatter during peak hours, and secondly, the relationship between average speeds and emission factors is nonlinear in nature; thus, the relative differences in the low-speed fraction increased more significantly during peak hours.
Exploring Different Alert Limit Strategies in the Maintenance of Railway Track Geometry
Keywords:Railways;Maintenance strategy;Markov policies;Planned and unplanned costs;Railway track geometry
Abstracts:This paper explores a quantitative model with different maintenance strategies to control railway track geometry degradation in Portugal. The alert limits put forward by the international standards are assessed regarding the planned and unplanned impacts associated with those limits, namely preventive maintenance and renewal costs, corrective maintenance costs, planned infrastructure delays due to changes in the maximum permissible speed, and unplanned infrastructure delays due to temporary speed restrictions. The effects of different choices for the alert limits of the main quality indicators for railway track geometry are assessed, considering a cost penalty due to delays set by the regulatory entity. Finally, a sensitivity analysis is conducted on the effect of this delay cost penalty on the optimized choice of the alert limits for both quality indicators.
Design of LRT Signal Priority to Improve Arterial Traffic Mobility
Keywords:Transit signal priority;VISSIM;Ring barrier controller;Arterial performance
Abstracts:Transit signal priority (TSP) is a cost-effective strategy for improving the movement of public transit vehicles, such as Light Rail Transit (LRT), buses, and streetcars, through controlled intersections. The application of TSP strategies improves the reliability and quality of service for transit vehicles with less disruption to normal traffic. The City of Edmonton in Alberta, Canada has recently extended its LRT system, which mainly runs through at-grade intersections. Edmonton’s LRT is currently operating under pre-emption, which causes significant delays to other traffic. The problem is especially pronounced during peak hours when the LRT headway is decreased to 5 min in both directions. This has led to dissatisfaction among motorists using the roadway along the LRT corridor. This paper analyzes different TSP strategies for improving the performance of the LRT corridor. A standard microsimulation tool with a ring barrier controller emulator was used to implement the strategies at a major intersection during peak hours. Field data for both morning and evening peak hours were collected at four intersections along the LRT corridor for the calibration of the model. Three strategies were explored in this paper: (1) simple LRT pre-emption, (2) LRT prediction and pre-emption, and (3) LRT prediction and pre-emption together with transit bus priority. A number of performance measures were used to evaluate each strategy. Results revealed that Strategy 2, where LRT arrival time is predicted to provide LRT pre-emption, yields the highest improvement in corridor performance.
Merging Preparation Behavior of Drivers: How They Choose and Approach Their Merge Positions at a Congested Weaving Area
Keywords:Merging behavior;Lane-changing preparation;Merge position
Abstracts:Vehicle merging is a tactical process. In the existing merging models, drivers need to select a target gap and adjust their speed to reach a comfortable merge position to execute lane changing. However, such sequential premerging preparation process has not yet been well-captured on the basis of the field trajectory data. In this study, the authors will focus on analyzing the lane-changing behavior as drivers choose and approach their merge positions at congested merging areas. This study is based on noise-filtered computer-based trajectory data. The authors classify the observed merging vehicles in a congested weaving section into original-gap-targeting (OGT) and forward-gap-targeting (FGT) vehicles. The analysis of the merge-position selection indicates different selection behavior between OGT and FGT merging vehicles. The length of target gap, the speed, and the route plan of vehicles surrounding the merging vehicles have an influence on their merge-position selection. To investigate merge tactics of merging vehicles, their speed synchronization and acceleration behaviors when approaching their merge positions were analyzed. The results illustrate that the acceleration and deceleration behaviors of the FGT merging vehicles in the approaching process should be split into two distinct stages: acceleration to overtake the rejected gap and deceleration to execute speed synchronization. The findings from this study shed light on the complex lane-changing process at merging areas.
An Unsupervised Learning Approach for Analyzing Traffic Impacts under Arterial Road Closures: Case Study of East Liberty in Pittsburgh
Abstracts:This paper adopts an unsupervised learning approach, -means clustering, to analyze the arterial traffic flow data over a high-dimensional spatiotemporal feature space. As part of the adaptive traffic control system deployed around the East Liberty area in Pittsburgh, high-resolution traffic occupancies and counts are available at the lane level in virtually any time resolution. The -means clustering method is used to analyze those data to understand the traffic patterns before and after the closure and reopening of an arterial bridge. The modeling framework also holds great potentials for predicting traffic flow and detect incidents. The main findings are that clustering on high-dimensional spatiotemporal features can effectively distinguish flow patterns before and after road closure and reopening and between weekends and weekdays. On arterial streets, clustering based on 5-min data is sufficient to eliminate potential distortion on measurements caused by signals. Either of the two, count or occupancy, is adequate to serve as a feature for effective pattern clustering. It is plausible to use data from only selected locations and time periods to infer representative flow patterns and detect arterial incidents, which allows applications in large-scale networks with cheap sensing. In addition, for some lanes, there exists a transitional time period (1 week in this case study) immediately following the closure and reopening when traffic flow is transformed to a new type of daily pattern.