Avijit Maji

Reliability considerations of bituminous pavement design by mechanistic–empirical approach

The reliability issues in bituminous pavement design, based on mechanistic–empirical approach, have been discussed in this paper. Variabilities of pavement design input parameters are considered and reliability, for various proposed failure definitions, of a given pavement is estimated by simulation as well as by analytical (first order second moment) method. A methodology has been suggested for designing a bituminous pavement for a given level of overall reliability by mechanistic–empirical pavement design approach.

Modeling Highway Infrastructure Maintenance Schedules with Budget Constraints

Highway infrastructure elements, such as signs, guardrails, structures, and pavements, deteriorate over time because of weather, accidents, daily wear and tear, and other factors. To keep them functional and operational, the elements require periodic maintenance. In the absence of an optimization model that can optimally allocate the annual maintenance budget for needed maintenance, it is often difficult to secure adequate funding for such activities. A mathematical model is developed; it evaluates the condition of elements, considers a budget constraint, and suggests the optimal maintenance schedule over a specified period of time. A genetic algorithm has been used to solve the model. The model considers a parabolic function over time to represent deterioration of the elements as well as rehabilitation expenses. The extent of rehabilitation at a given time is considered as dependent on the present condition and amount of deterioration. Also, threshold values for level of deterioration are considered as a check for the minimum condition before rehabilitation is warranted. With inputs such as deterioration levels, rehabilitation costs, threshold deterioration levels, and annual budget, the model can give the optimum maintenance schedule of the elements over a specified time period as an output. The approach is illustrated through a numerical example.

Cross-Sectional Study of Road Accidents and Related Law Enforcement Efficiency for 10 Countries: A Gap Coherence Analysis

ABSTRACT Objective: Road crashes are considered as the eighth leading causes of death. There is a wide disparity in crash severity and law enforcement efficiency among low-, medium-, and high-income countries. It would be helpful to review the crash severity trends in these countries, identify the vulnerable road users, and understand the law enforcement effectiveness in devising efficient road safety improvement strategies. Method: The crash severity, fatality rate among various age groups, and law enforcement strategies of 10 countries representing low-income (i.e., India and Morocco), medium-income (i.e. Argentina, South Korea, and Greece), and high-income (i.e., Australia, Canada, France, the UK, and the United States) are studied and compared for a period of 5 years (i.e., 2008 to 2012). The critical parameters affecting road safety are identified and correlated with education, culture, and basic compliance with traffic safety laws. In the process, possible road safety improvement strategies are identified for low-income countries. Results: The number of registered vehicles shows an increasing trend for low-income countries as do the crash rate and crash severity. Compliance related to seat belt and helmet laws is high in high-income countries. In addition, recent seat belt– and helmet-related safety programs in middle-income countries helped to curb fatalities. Noncompliance with safety laws in low-income countries is attributed to education, culture, and inefficient law enforcement. Conclusion: Efficient law enforcement and effective safety education taking into account cultural diversity are the key aspects to reduce traffic-related injuries and fatalities in low-income countries like India.

A Multi-Objective Genetic Algorithm for Optimizing Highway Alignments

We develop a multi-objective approach to optimize 3-dimensional (3D) highway alignments using a genetic algorithm. Multi-objective genetic algorithms have been very popular for handling trade-offs among various objectives. The concept of Pareto optimally has been introduced in works and multi-objective genetic algorithms have been developed for this purpose. What we have found is that every problem is unique and there is no black box approach to implement multi-objective genetic algorithms in all problems. We implement the Pareto-optimality concept to develop a multi-objective genetic algorithm for the 3D highway alignment optimization problem on which we have worked for the last 10 years. We apply the multi-objective optimization approach to an example problem on which we had previously worked. The results suggest that the multi-objective approach has great promise for obtaining the best trade-off among various objectives to reach an optimal solution

Diverging Diamond Interchange Analysis: Planning Tool

Many traffic simulation software tools have emerged over the last decade and are widely used for analyzing capacity, delay, and level of service at intersections, ramps, and along arterial/freeway segments. Although these tools have shown great promise, they are expensive and the data collection and input setup is time consuming and resource intensive. Traffic engineers predominantly use one of those tools to analyze a diverging diamond interchange (DDI), also known as double crossover diamond interchange. Developing a simulation model and performing required analysis takes considerable time. Because it is not necessary to obtain a detailed traffic operational analysis of a DDI while interchange alternatives are being developed, a quick and easy evaluation procedure is warranted. In this paper, a critical lane volume (CLV)-based DDI analysis methodology is developed, which could be an appropriate tool to bridge the gap. In this methodology, two intersections or nodes of a DDI, where through-traffic movements along the arterial cross each other, are considered crucial. Understanding of the crossover movements, ramp movements, and coordination of traffic movements between the two nodes and lane configuration are used in developing the methodology. Critical movements are analyzed, compared, and logically added to obtain the CLV of the two nodes. The obtained CLV is used in deriving the level of service of the two intersections in a DDI. The paper describes the mathematical formulation and analysis procedure to evaluate a DDI. Two real-world DDIs are analyzed by using the developed method and compared with simulation results for reliability and accuracy.

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as other pre-existing alignments. Constructing a new highway will ease the traffic in the existing road network. Based on Wardrop’s principle, the users will choose a route that will minimize their travel-time. Users will unilaterally shift to the available routes for their benefit and thus, traffic flow will attain equilibrium. Theoretically, the equilibrium of traffic flow between the existing highway and the newly designed highway alternative can be achieved by a user equilibrium model. A new methodology is developed in this paper to optimize a new three-dimensional highway alignment based on the existing highway alignment system information using a cost-benefit analysis approach. The results are quite promising for new road design and bypass construction since benefit maximization and cost minimization is performed simultaneously while attaining user equilibrium.

Hierarchical clustering analysis framework of mutually exclusive crash causation parameters for regional road safety strategies

ABSTRACT Hierarchical clustering analysis framework is developed to identify benchmark and critical regions for effective road safety strategies. The regions are grouped based on agglomeration coefficient of mutually exclusive crash causation parameters. Subsequently, regions from groups with lower than a threshold index value are selected as benchmark for the poorly performing critical counterparts. Euclidean distance-based Wards, median and centroid clustering techniques are explored through a case study of Indian states and Union Territories. As per data between 2006 and 2015, fatal crash percentages of driving under influence of drug and alcohol, excessive speeding, vehicle malfunction and road conditions related crash causation parameters, severity index and its growth rate are assessed based on respective threshold values of 6.35%, 43.28%, 2.42%, 1.79%, 26.7 and 3.1%. These are the national average of respective indices. It demonstrated the unique application of hierarchical clustering analysis in benchmark and critical region identification.

Integrating Highway Alignment Design Capability to the Interactive Highway Safety Design Model (IHSDM): A Two Lane Highway Case Study

Interactive Highway Safety Design Model (IHSDM) is a software analysis and decision-support tool that is widely used to check design consistency in response to required safety and operational performance level along two-lane rural highways. It can only identify the inconsistent sections along a given highway. Therefore, after every check, the inconsistent sections are redesigned and checked again to ensure consistency. This process is manual and is time consuming. The objective of this research is to incorporate the highway alignment design capability to the IHSDM. This will reduce the manual repetitive steps involved in highway design and safety checks. In this study highway geometric design properties are used and integrated with IHSDM such that the inconsistent sections of the highway are replaced with sections having optimal safety and operational performance level. This method first identifies the inconsistent sections from the given highway alignment using IHSDM and then replaces the sections with new, and more appropriate sections. This process continues until all inconsistent sections are replaced. A real-world problem is solved in this paper using the proposed method.

Operating speed prediction models for tangent sections of two-lane rural highways in Oklahoma State

ABSTRACT In this study, geometric features (e.g. road and shoulder width), pavement characteristics (e.g. shoulder type, skid number, and international roughness index), and traffic parameters (e.g. posted speed limit and average daily traffic) were extensively analyzed to identify the significant predictors and develop better-fit 85th percentile speed prediction models for the tangent sections of two-lane rural highways. Three models, representing all highways, lower speed limit highways, and higher speed limit highways, were developed using stepwise multiple linear regression analysis. About 80% data from 251 locations in the State of Oklahoma, United States, was used in model development and 20% for validation. The all highways model is the best-fit among the three. Two most significant parameters of this model are posted speed limit and skid number. Additionally, international roughness index is significant in the higher speed limit highway model. The lower speed limit highway model depends only on the posted speed limit.