Showing papers in "Journal of Transportation Engineering-asce in 2013"

Cumulative Travel-Time Responsive Real-Time Intersection Control Algorithm in the Connected Vehicle Environment

Abstract: This paper presents a cumulative travel-time responsive (CTR) real-time intersection control algorithm that takes full advantage of connected vehicles (CVs). The potential benefits of the proposed CTR algorithm under varying imperfect CV market penetration rates and traffic congestion conditions were investigated. The core of the CTR algorithm is based on a stochastic state estimation technique utilizing Kalman filtering that is used in estimating the cumulative travel times under imperfect market penetration rates at every update interval. Comprehensive simulation experiments covering varying volume-to-capacity ratios and imperfect market penetration rates were performed at a hypothetical isolated intersection with two through lanes and a single left-turn lane at each approach. At 100% market penetration, the CTR algorithm improved the total delay time and average speed of the intersection by 34 and 36%, respectively, compared to an optimized actuated control. It was found that at least 30% market penetration rates are needed to realize the benefits of the CTR algorithm.

Impact of Traffic Overload on Road Pavement Performance

Abstract: Traffic on a road pavement is characterized by a large number of different vehicle types, and these can be considered in pavement design by using truck factors to transform the damage they apply to the pavement to the damage that would be applied by a standard axle. The truck factors to convert trucks into standard axles or the load equivalent factors to convert axles into standard axles are defined by considering the average loads for each axle. This process includes the vehicles that travel with axle loads above the maximum legal limit. There are also a substantial number of overloaded vehicles in terms of total vehicle weight. These axles/vehicles cause significant damage to the pavements, increasing the pavement construction and rehabilitation cost. Thus, this paper investigates the impact of overloaded vehicles on road pavements by studying the truck factors for different vehicle cases applied to a set of pavements composed of five different asphalt layer thicknesses and five different subgrade stiffness moduli. The study revealed that the presence of overloaded vehicles can increase pavement costs by more than 100% compared to the cost of the same vehicles with legal loads.

Robust optimization model of bus transit network design with stochastic travel time

Abstract: The design of urban bus transit systems aims to determine a network configuration with a set of bus lines and associated frequencies that achieve the targeted objective. This paper presents a methodology framework to formulate and solve the bus transit network design problem (TNDP). It first proposes a TNDP taking into account the travel time stochasticity. A robust optimization model is formulated for the proposed problem, which aims to minimize the sum of the expected value of the operator cost and its variability multiplied by a weighting value. A heuristic solution approach, based on k-shortest path algorithm, simulated annealing algorithm, Monte Carlo simulation, and probit-type discrete choice model, is subsequently developed to solve the robust optimization model. Finally, the proposed methodology is applied to a numerical example. (C) 2013 American Society of Civil Engineers.

Large Truck–Involved Crashes: Exploratory Injury Severity Analysis

Abstract: In recent years, a growing concern related to large truck accidents has increased owing to the level of injury severity that can be sustained and to the related potential economic impact. Current studies related to large truck-involved crashes are scarce and do not address the human factors that can greatly influence accident outcomes. This study presents an analysis of data from the fusion of several national data sets addressing injury severity related to large truck-involved crashes. This is accomplished by considering human, road environment, and vehicular factors in large truck-involved crashes on U.S. interstates. A random-parameter ordered-probit model was estimated to predict the likelihood of five injury severity outcomes—fatality, incapacitating, nonincapacitating, possible injury, and no injury. The modeling approach accounts for possible unobserved effects relating to human, vehicular, and road environment factors not present in the data. Estimation findings indicate that the level of injury severity is highly influenced by a number of complex interactions between factors, and the effects of some factors can vary across observations. DOI: 10.1061/(ASCE)TE.1943-5436.0000539. © 2013 American Society of Civil Engineers. CE Database subject headings: Freight transportation; Trucks; Injuries; Parameters; Traffic accidents. Author keywords: Freight movement; Large trucks; Ordered probit; Random parameter; Safety; Injury severity.

Real-Time Bus Arrival Time Prediction: Case Study for Jinan, China

Abstract: Providing real-time bus arrival information can help to improve the service quality of a transit system and enhance its competitiveness among other transportation modes. Taking the city of Jinan, China, as an example, this study proposes two artificial neural network (ANN) models to predict the real-time bus arrivals, based on historical global positioning system (GPS) data and automatic fare collection (AFC) system data. Also, to contend with the difficulty in capturing the traffic fluctuations over different time periods and account for the impact of signalized intersections, this study also subdivides the collected dataset into a bunch of clusters. Sub-ANN models are then developed for each cluster and further integrated into a hierarchical ANN model. To validate the proposed models, six scenarios with respect to different time periods and route lengths are tested. The results reveal that both proposed ANN models can outperform the Kalman filter model. Particularly, with several selected performance indices, it has been found that the hierarchical ANN model clearly outperforms the other two models in most scenarios.

Variable Speed Limit Control Design for Relieving Congestion Caused by Active Bottlenecks

Abstract: Variable speed limit (VSL) can be used on freeways to manage traffic flow with the goal of improving capacity. To achieve this objective, it is necessary that both speed and density dynamics be represented accurately. In this study, to deeply understand the effectiveness of VSL control, an analytical model was developed to represent drivers’ response to updated speed limits and macroscopic speed dynamical change with respect to changeable speed limits. Specifically, to model the freeway links having VSL control, the fundamental diagram (FD) was replaced with the VSL control variable in the relaxation term of the METANET. This modification led to the speed control variable appearing linearly, which is preferable for online computation. The density dynamics are based on the cell transmission model (CTM), which is introduced to estimate the transition flow among successive links with some practical constraints. It also offers flexibility in designing active bottleneck in which there is a capacity dro...

Development of Daily Adjustment Factors for Bicycle Traffic

Abstract: 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.

Mode Choice Behavior of Commuters in Thiruvananthapuram City

Abstract: Travel behavior plays an important role in transportation planning. Mode choice analysis is the process of arriving at a decision about which mode to use under a set of circumstances. Choice of a particular mode by a commuter affects the general efficiency of travel within the city. Various techniques are available in the literature for mode choice modeling. Among these, multinomial logit models are found to be efficient in estimating the different mode shares in a scenario where more than two choices of modes of travel are available for a commuter. The present study used multinomial logistic regression to analyze the mode choice behavior of commuters in Thiruvananthapuram, a typical Indian city. The findings from the study revealed that as age increases preference to car increases and preference to two-wheelers decreases in comparison with public transport. Increase in time per distance and increase in cost per distance cause the commuters to switch to car and two-wheelers from public transport. Identification of such factors and its variations will help city planners to formulate effective transport policies to improve the transport within the city. DOI: 10.1061/(ASCE)TE.1943-5436.0000533. © 2013 American Society of Civil Engineers. CE Database subject headings: Logistics; Urban areas; Commute; Travel patterns; Transportation management; India. Author keywords: Mode choice; Revealed preference technique; Multinomial logistic regression; Odds ratio; Significance level.

Relationship between Pavement Roughness and Distress Parameters for Indian Highways

Abstract: The present study demonstrates the relationships between pavement roughness and distress parameters like potholes, raveling, rut depth, cracked areas, and patch work. The pavement distress data collected on four national highways in India using a network survey vehicle (NSV) are used to develop linear and nonlinear regression models between roughness and distress parameters. Analysis of variance of these models indicated that nonlinear relation is better than a linear model. R2 value, root mean square error (RMSE), and mean absolute relative error (MARE) also supported nonlinear models. An artificial neural network (ANN), which is an advanced technique of modeling, is also used in the present study to model pavement roughness with distress parameters. A network with five input nodes, 15 hidden nodes, and one output node is considered. The network was trained with 90% of the data and tested with remaining 10% data. Results of R2 and MSE showed that the neural network performed highly significantly ...

Pedestrian Behavior at Signalized Pedestrian Crossings

Abstract: The objective of this research was to define eventual differences in models of pedestrian behavior at signalized pedestrian crossings, with and without countdown displays. The outcomes of this work represent a contribution to the harmonization of positions on the effect of a countdown display on pedestrian behavior. Video recordings at two completely similar pedestrian crossings enabled the collection of pedestrian behavior data (crossing at the red light), which included different categories (gender, age, individual/group, and “slow” pedestrians), collected in different conditions (during certain red light intervals and traffic volume). The results of the research showed that a statistically significant larger number of pedestrian offenders occurred at pedestrian crossings without countdown displays rather than at crossings with countdown displays. The presence of a countdown display significantly reduced the number of women offenders in particular. The number of offenders in the first and last f...

Disabled Pedestrian Level of Service Method for Evaluating and Promoting Inclusive Walking Facilities on Urban Streets

Abstract: Current analytical methods to estimate the pedestrian level of service (PLOS) usually only consider a narrow range of pedestrians and may not be applicable for more diverse pedestrian populations with different characteristics. The aim of this study is to conceptualize the disabled pedestrian level of service (DPLOS) for different street hierarchies not previously addressed to ensure inclusive walking conditions. An analytical point system comparing existing pedestrian facilities to a standard is proposed to estimate the DPLOS. Although this practical model is only used for one case study in Singapore, the use of international standards would make this model universally applicable.

Modeling the effects of rainfall intensity on traffic speed, flow, and density relationships for urban roads

Abstract: 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.

Development of City-Specific Driving Cycles for Transit Buses Based on VSP Distributions: Case of Beijing

Abstract: With the rapid increase of automobile ownership, the city of Beijing, China, faces challenging issues with regard to traffic congestion and vehicle emissions. In seeking solutions to these issues, developing and improving public transportation systems is considered one of the most feasible and promising strategies because these systems have high passenger-carrying capacity and low pollution on a per passenger basis. Driving cycles reflect traffic conditions, and thus vehicle emissions, and form a scientific base to further improve bus operations. This paper is intended to develop city-specific driving cycles for transit buses for Beijing. The operational data of 126 buses were collected by using a portable global positioning system (GPS) for three types of bus routes: the bus rapid transit (BRT) line, express line, and regular line. Through analysis of the operating characteristics, a methodology for developing driving cycles is proposed based on the parameter of vehicle-specific power (VSP) distribution. Then, by applying this methodology, driving cycles for BRT, express, and regular lines are developed accordingly. Finally, the developed driving cycles are evaluated. Based on the analysis, the proposed driving cycles are able to reflect the real-world operating characteristics of transit buses better than other driving cycles. Furthermore, the emission factors generated based on the developed driving cycles are lower on average than those predicted by using the default driving cycles in the motor vehicle emission simulator (MOVES).

Operating Speed of Different Classes of Vehicles at Horizontal Curves on Two-Lane Rural Highways

Abstract: The majority of operating speed models reported in the literature primarily consider passenger cars and only rarely consider heavy vehicles. No study on the influence of geometry on speeds of other classes of vehicles like buses and two-wheelers, which contribute significantly to the mix of traffic in India, has been reported. This study highlights the need to develop operating speed and speed reduction models for different classes of vehicles and develops models for predicting operating speed at tangent and midcurve sections of horizontal alignment of two-lane rural highways. In addition, models for estimating the speed reduction from tangent to curve are also developed. The independent variable used to predict tangent speed is the length of the preceding tangent. The radius and length of a curve emerged as the most important variables for speed at midcurve. Speed reduction can be estimated from the preceding variables along with the approach tangent speed. The models developed in the study can be used in the design and evaluation of rural highways as well as in establishing speed limits and other enforcement measures.

Stress and Deflection Parametric Study of High-Speed Railway CRTS-II Ballastless Track Slab on Elevated Bridge Foundations

Abstract: Ballastless track slab system (BTS) of China Rail Transit Summit type-II (CRTS-II) is primarily used in China’s Beijing-Shanghai high-speed railway As a new structural form, CRTS-II has not been extensively tested, and the design and manufacturing processes of CRTS-II BTS systems is not optimized and mature for its load-carrying capacity, structural integrity, deflection, and durability This study carried out a numerical analysis of stress and deflection responses of the CRTS-II BTS system using SAP 2000 Design parameters include stiffness of the rail fastening, thickness and stiffness of the track slab, the cement emulsified asphalt (CA) mortar cushion, and the concrete supporting layer Deflection, maximum bending stress, and maximum shear stress of different structural components of the CRTS-II BTS system are investigated under varying design parameters, with the aim to explore an improved set of design parameters The rail defection is only significantly impacted by the rail fastening stiffness To reduce the high-speed rail deflection so as to mitigate riding discomfort, higher stiffness of the rail fastening is suggested To reduce the track slab bending stresses to prevent the high-speed rail from structural failure, the following parameter design strategy can be used: higher track slab thickness, lower track slab stiffness, lower rail fastening stiffness, higher CA mortar, and concrete supporting layer stiffness All design parameters of the BTS system have negligible influence on the maximum bending stress and shear stress of the elevated bridges The maximum shear stress of the BTS system is relative low compared with the maximum bending stress of the BTS system, suggesting that the BTS system behaves more like a beam rather than a plate

Road Grade Measurement Using In-Vehicle, Stand-Alone GPS with Barometric Altimeter

Abstract: Real-world vehicle fuel use and emission rates are sensitive to road grade. There is a need for a practical method for measuring road grade in combination with on-board measurement of vehicle activity, energy use, and emissions using portable emissions measurement systems (PEMS). This paper focuses on quantification of the accuracy and precision of a low-cost method using a stand-alone global positioning system (GPS) receiver with an in-built barometric altimeter. Approximately 100 one-way runs were made on each of several study routes. The sensitivity of average grade estimates to the averaging distance over which grade is estimated is quantified. The repeatability of vehicle location and distance traveled is quantified. The run-to-run variability and confidence intervals for average estimates of grade are quantified. The accuracy of the grade estimates is evaluated in comparison to LIDAR-based estimates. The low-cost method is shown to be accurate, but imprecision in the measurements leads to a need for typically at least 10 or more repeated runs, depending on the desired precision of the average estimate of grade.

System Reliability Analysis of Flexible Pavements

Abstract: The uncertainty in material properties and traffic characterization in the design of flexible pavements has led to significant efforts in recent years to incorporate reliability methods and probabilistic design procedures for the design, rehabilitation, and maintenance of pavements. In the mechanistic-empirical (ME) design of pavements, despite the fact that there are multiple failure modes, the design criteria applied in the majority of analytical pavement design methods guard only against fatigue cracking and subgrade rutting, which are usually considered as independent failure events. This study carries out the reliability analysis for a flexible pavement section for these failure criteria based on the first-order reliability method (FORM) and the second-order reliability method (SORM) techniques and the crude Monte Carlo simulation. Through a sensitivity analysis, the most critical parameter affecting the design reliability for both fatigue and rutting failure criteria was identified as the surface layer thickness. However, reliability analysis in pavement design is most useful if it can be efficiently and accurately applied to components of pavement design and the combination of these components in an overall system analysis. The study shows that for the pavement section considered, there is a high degree of dependence between the two failure modes, and demonstrates that the probability of simultaneous occurrence of failures can be almost as high as the probability of component failures. Thus, the need to consider the system reliability in the pavement analysis is highlighted, and the study indicates that the improvement of pavement performance should be tackled in the light of reducing this undesirable event of simultaneous failure and not merely the consideration of the more critical failure mode. Furthermore, this probability of simultaneous occurrence of failures is seen to increase considerably with small increments in the mean traffic loads, which also results in wider system reliability bounds. The study also advocates the use of narrow bounds to the probability of failure, which provides a better estimate of the probability of failure, as validated from the results obtained from Monte Carlo simulation (MCS).

Concept of Stream Equivalency Factor for Heterogeneous Traffic on Urban Arterial Roads

Abstract: 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 K. It is the ratio of traffic volume in PCU per hour and volume in vehicles per hour. The K factor is related to traffic composition and volume on a road through the regression analysis meth...

Availability Approach to Optimizing Railway Track Renewal Operations

Abstract: This paper proposes a multiobjective optimization approach for planning railway ballast, rail, and sleeper renewal operations. The objective is to support an informed decision that considers not only the railway track life-cycle cost (LCC) but also the track occupation times required to perform interventions. Two objective functions were minimized, as follows: (1) railway track unavailability caused by railway track maintenance and renewal operations, and (2) railway track components’ LCC. Furthermore, to rationalize the renewal strategy, the model considers a multicomponent formulation that assesses, in time and space, the opportunistic combination of railway track renewal activities. A numerical application of the model on a real case study (Lisbon-Oporto line) is developed and discussed. The results show the interest of using this simple multiobjective optimization approach to obtain a decision-making process to support the scheduling of major railway track renewal works with an informed LCC-un...

Train Routing Model and Algorithm Combined with Train Scheduling

Abstract: This paper constructs a train routing model combined with a train scheduling problem, which is a 0–1 mixed-integer nonlinear programming problem. Except for train route choice, the model considers a system of complicated constraints on headway, trip time, meeting-crossing and overtaking between trains, capacity of siding, and so on. Based on the delay information of each train, a route adjustment algorithm is designed to obtain satisfactory route schemes of trains. Moreover, a tabu search procedure is designed to further improve the route schemes. The simulation results show that, relative to the optimal solution, the solutions obtained by the current method exhibit small relative error. The tabu search algorithm exhibits unstable performance because of dependence on the initial solution. Combined with the route adjust algorithm, the tabu search technique can improve the quality and stability of solutions. In addition, the departure order of heterogeneous trains exerts important influences on train route choice.

Optimizing Electric Rail Energy Consumption Using the Lagrange Multiplier Technique

Abstract: In the railway sector, one of the sensitive issues to be borne very much in mind is the cost brought about by the energy consumption required to meet schedules, be they local trains, metropolitan systems, or long-distance trains. To reduce energy consumption, considering restrictions like traveling time or speed limits, it is necessary to find a solution for a complex problem in the domain of optimal control theory (OCT). The analytical solution for those problems is not easily carried out. A simpler alternative to that approach is presented in this paper, using a semianalytical solution that leads to a discretization and to the application of the Langrage multipliers method to solve the optimization of n-tuples of speed. With the solution introduced in this work, is possible to include all the details about train operation, such as timetable restrictions or braking types. In the full paper, the detailed solution is presented as well as some real cases to illustrate the method results.

Analysis of Near-Surface Cracking under Critical Loading Conditions Using Uncracked and Cracked Pavement Models

Abstract: In this paper, the mechanism of near-surface cracking under critical loading conditions was investigated using mechanistic modeling approaches. These loading conditions were represented by a combination of nonuniform tire contact stresses in three directions generated during vehicle maneuvers (free rolling, acceleration/braking, and cornering) that were predicted from a tire-pavement interaction model. Three-dimensional finite element models of uncracked and cracked pavements were developed to evaluate the critical factors that are responsible for crack initiation and propagation at the near-surface of a typical full-depth pavement structure. It was found that the near-surface cracks in the proximity of tire edges showed strong mixed-mode (tension and shear) fracture potential. The pavement responses from both uncracked and cracked pavement models indicated that shear mode of fracture in the presence of compression appeared to be the dominant mode of damage for near-surface cracking. Compared to the free rolling condition, tire braking/acceleration and cornering induced high tangential contact stresses on the pavement surface, which could significantly accelerate the development of cracks at the pavement near-surface. The near-surface cracking potential was dependent on the variations of localized tire contact stress distributions. The findings presented in this study shed light on the experimental characterization of the near-surface cracking phenomenon, which appears to be driven by different stress conditions than the classical bottom-up fatigue cracking. This study also highlights the impact of vehicle maneuvering on premature pavement damage that is often neglected in the current pavement design process.

Tangent-to-curve transition on two-lane rural roads based on continuous speed profiles

Abstract: In the road geometric design process, speed variation along the road segment is one of the most popular criteria to evaluate road consistency, hence the importance of estimating operating speed and its variations. Most of the estimation models are based on speed spot data collection, usually assuming some hypotheses like operating speed remains constant at curves and speed variations take place entirely at preceding tangent. This paper presents the results of the study of the deceleration phenomenon using a new methodology based on data collection by global positioning system devices. By means of this new methodology, not only new and more accurate models can be developed, but also the previous hypotheses can be checked and new studies can be carried out. Tangent-to-curve speed variations have been evaluated, comparing the 85th percentile speed differential (Δ85V) and the differential of the 85th percentile operating speed (ΔV85), analyzing the percentage of deceleration length that takes place at...

Using Truck Probe GPS Data to Identify and Rank Roadway Bottlenecks

Abstract: This paper describes the development of a systematic methodology for identifying and ranking bottlenecks using probe data collected by commercial global positioning system fleet management devices mounted on trucks. These data are processed in a geographic information system and assigned to a roadway network to provide performance measures for individual segments. The authors hypothesized that truck speed distributions on these segments can be represented by either a unimodal or bimodal probability density function and proposed a new reliability measure for evaluating roadway performance. Travel performance was classified into three categories: unreliable, reliably fast, and reliably slow. A mixture of two Gaussian distributions was identified as the best fit for the overall distribution of truck speed data. Roadway bottlenecks were ranked on the basis of both the reliability and congestion measurements. The method was used to evaluate the performance of Washington state roadway segments, and proved efficient at identifying and ranking truck bottlenecks.

Optimal Routing Design of a Community Shuttle for Metro Stations

Abstract: The optimization of a community shuttle route plays an important role in the efficient operation of public transit microcirculation. This paper develops a solution for the optimal routing design problem with the objective of minimizing the total cost, including user and supplier costs, considering passenger traffic demand and budget constraints. The optimization variables include route and headway. To calculate the user cost, a heuristic algorithm for locating stops is presented. Then the optimized headway corresponding to a given bus route is confirmed by minimizing the total cost function. In solving the problem, a depth-first search algorithm (DFS) and a genetic algorithm (GA) are both presented. By comparing the results and the CPU time of the two algorithms, this paper demonstrated that GA is reliable and more efficient than DFS. The impacts of route length and the maximum tolerable walking distance on the cost and headway are also analyzed.

Development and Evaluation of Methods for Constructing Breakdown Probability Models

Abstract: The term breakdown of flow at a freeway bottleneck location has been used to describe the transition from relatively free-flowing traffic to congestion, often called stop-and-go traffic, but more generally experienced as slow-and-go The focus of the research presented in this paper was to develop probabilistic models to predict breakdown of flow by using data from five freeway-ramp merging segments The development of the probabilistic models allows exploration of several issues: the identification of breakdown, the performance measures for the identification of the breakdown, and the breakdown location The breakdown probability model (BPM) is based on lifetime data analysis statistics The breakdown probability models can be very useful tools in establishing capacity values, which in turn can be part of the freeway traffic management process

Numerical Modeling of High-Speed Train/Track System to Assess Track Vibrations and Settlement Prediction

Abstract: The circulation of trains at very high speeds (higher than 300 km/h) leads to important vibrations in the track and its environment. Concerning the track behavior, this dynamic cyclic load...

Principle of Demographic Gravitation to Estimate Annual Average Daily Traffic: Comparison of Statistical and Neural Network Models

Abstract: 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.

Calibration of Platoon Dispersion Parameter Considering the Impact of the Number of Lanes

Abstract: Microscopic vehicle behaviors, such as car following, overtaking, and lane changing, may occur differently on links with different numbers of lanes. Thus, this paper addresses the impact of the number of lanes on the platoon dispersion of traffic flow in low-friction conditions. A well-adopted dispersion model is used to reflect the platoon dispersion. The platoon dispersion factor of the model is then recalibrated using data on road segments with different numbers of lanes. The data are obtained from a comprehensive survey taken at several locations on the arterial streets of Changchun and Hangzhou city, China, where each direction of road segment has two, three, four, or five lanes. The statistical results verify that the number of lanes does have an evident effect on the platoon dispersion factor α: when the number of lanes grows from two to five, the value of α decreases significantly; meanwhile, the slope of the function curve between α and the normalized flow becomes larger.

Accounting for Network Effects in Railway Asset Management

Abstract: System-level infrastructure management involves determining optimal maintenance, rehabilitation, and reconstruction activities for a system of facilities over a planning horizon to maximize the level of service subject to system constraints. In railway networks, different types of facilities (such as tracks, and bridges) comprise the system, and maintenance of one facility may affect the maintenance of other facilities, both economically and functionally. Therefore, when developing an asset management system for railway networks, it is essential to take into account heterogeneity and interdependency in the network. In this paper, a two-stage, bottom-up methodology is formulated to capture these interdependencies and heterogeneities in railroad infrastructure management. Numerical experiments are presented to examine the effects of economic and functional interdependencies on network optimization and to demonstrate the validity of the proposed model. The results show that accounting for heterogenei...