State Highway Network Research Articles

Contribution of Network Redundancy to Reducing Criticality of Road Links

Road networks are frequently disrupted by natural hazard events, producing severe consequences for isolated communities as well as increased travel times and significant reconstruction costs. Therefore, identifying which critical links need investment to reduce network impacts has become a priority for road agencies. Road network redundancy contributes to reducing these potential consequences by providing viable alternative routes. Although several metrics have been proposed in the literature to evaluate road criticality, including those based on topological variables and transportation cost increases, a comparison of the contribution of redundancy to reducing expected consequences has not been undertaken using a range of different metrics. This paper proposes a methodology to evaluate road criticality under different metrics and to quantify the contribution of redundancy in reducing expected impacts using the “full scan” method and Monte Carlo simulation. This methodology is then applied to a case study of New Zealand’s South Island to quantify the contribution of secondary and tertiary inter-urban roads to overall network redundancy, and to determine the most critical links under different approaches. The results obtained from the case study demonstrate that the redundancy level provided by secondary and tertiary inter-urban roads, over and above the state highway network, decreases expected transportation cost increases by 94.93% on average, and improves topological metrics, such as network betweenness values, by 73% on average when the road network is disrupted. The proposed methodology has the potential to help decision makers quantify and, therefore, prioritize investments to reduce the consequences of network disruptions.

What can we see from the road? Applications of a cumulative viewshed analysis on a US state highway network

Abstract. In many parts of the world, motorized travel is one of the most common ways that people interact with their regional landscape. This study investigates how travelers' understandings of place might be influenced by what landforms they can see from a vehicle. It uses a cumulative viewshed analysis on the Washington State (United States) highway network to determine which physical landscape features are most frequently visible or obscured from the road. Adapting ideas from Kevin Lynch's The Image of the City, I propose spatial data processing methods to derive landmarks, edges, and districts that could most contribute to the mental maps of travelers and should be prioritized for labeling on print, electronic, and augmented reality maps. Other applications of the cumulative viewshed include deriving scenic byways, siting proposed construction for high or low visibility, and guiding conversations about critical toponymy and perceptions of place.

Characterisation of transport resilience and measures to enhance resilience in the recovery after the 2016 Kaikōura earthquake

The Ward to Cheviot section of State Highway 1 is a key lifeline transport route that runs through the Kaikōura township. It is a strategically important link in the national state highway network, connecting the North Island via the Wellington-Picton ferry to the city of Christchurch in the South Island. Its strategic importance and vulnerable location between the mountainous Kaikōura range and the Pacific Ocean make it a critical transportation route in the national transport network. The route has been a focus for understanding the resilience of transport networks from as far back as 2000, when this section was used as a pilot study in early research into transport resilience. A further resilience assessment of this section was completed as part of a national state highway resilience study in mid-2016. Subsequently, the Mw 7.8 Kaikōura earthquake struck the northeast of the South Island on 14 November 2016, triggering thousands of large landslides and causing severe disruption to the transport network. The damage and disruption caused by the earthquake was comparable to that assessed in pre-earthquake studies of the resilience of the state highway. Landslides and embankment failures caused the most damage and disruption to the transport infrastructure, with the Main North Line railway closed for over 9 months and State Highway 1 closed for over a year. Post-earthquake landslides and debris flows triggered by storms caused additional damage and disruption during the recovery phase. Post-earthquake assessment of the corridor resilience was carried out to identify measures to enhance resilience as part of the recovery works. These measures included realigning the road and rail away from the steep hillsides, engineered works to reduce the potential for slope failure, and engineered works to reduce the potential for inundation of the corridor. The resilience assessments also enabled tactical and operational measures to be put in place to ensure safety while allowing the recovery operations to proceed in the context of enhanced risk associated with storm events and potential aftershocks.

Spatial Interpolation of Missing Annual Average Daily Traffic Data Using Copula-Based Model

Accurate estimation of traffic counts [(i.e., annual average daily traffic (AADT)] is essential to transportation agencies for traffic demand forecasting, emission evaluation, pavement design, and project prioritization. Traditional AADT estimation methods rely on either temporal data imputation techniques based on historical records or kriging-based spatial interpolation approaches. However, Kriging method utilizes the correlation function as the sole descriptor of spatial dependency, posing limitations to yield accurate interpolation results for unstable AADTs under complex traffic patterns due to diverse road functions or land uses. This study proposed a copula-based model that combines spatial dependency and marginal distribution for missing AADT interpolation to weaken the limitation of Kriging method. Thus, the proposed model not only can describe the spatial dependency but also is robust to outliers. AADT data collected from the California state highway network were used to evaluate the effectiveness of spatial copula models with varying missing data rates. Four road segments with regular and recreational traffic patterns were selected to compare with existing kriging-based approaches. Results suggested that the spatial copulas yielded significantly higher accuracy rates than kriging did for irregular travel patterns with high missing data rates. Spatial copula models hold a great potential to improve the performance of large-scale transportation network-wide data imputation for planning and operational usages.

Incorporating driving range variability in network design for refueling facilities

To stimulate and facilitate the use of alternative-fuel vehicles, it is crucial to have a network of refueling or recharging stations in place that guarantees that vehicles can reach (most of) their destinations without running out of fuel. Because initial investments in these stations are restricted, it is important to choose their locations deliberately. A fast growing stream of literature therefore analyzes the problem of locating refueling or recharging stations. The models proposed in these studies assume that the driving range is fixed, although reality shows that the driving range is highly stochastic. These models thereby misrepresent the actual coverage a network of refueling stations provides to drivers. This paper introduces two problems that do take the stochastic nature of the driving range into account. We first introduce the Expected Flow Refueling Location Problem, which is to maximize the expected number of drivers who can complete their trip without running out of fuel. The Chance Constrained Flow Refueling Location Problem is to maximize the number of drivers for which the probability of running out of fuel is below a certain threshold. We prove the problems to be strongly NP-hard, propose novel mixed-integer programming formulations for these problems, and show how these models can be extended to the case that the driving range varies during a trip. Furthermore, we extensively analyze and compare our models using randomly generated problem instances and a real life case study about the Florida state highway network. Our results show that taking the stochastic nature of the driving range into account can substantially improve network coverage, that optimal solutions are highly robust with respect to data impreciseness, and that the potential gains of stochastic models heavily depend on the driving range distribution. Based on the results, we discuss policy implications.

Model Development, Field Section Characterization, and Model Comparison for Excess Vehicle Fuel Use Attributed to Pavement Structural Response

In this study, consumption of energy attributed to pavement structural response through viscoelastic deformation of asphalt pavement materials under vehicle loading was predicted for 17 field sections in California by using three different models. Calculated dissipated energy values were converted to excess fuel consumption (EFC) to facilitate comparisons under different traffic loads (car, SUV, and truck) and speeds and different temperature conditions. The goal of the study was to compare the different modeling approaches and provide first-level estimates of EFC in preparation for simulations of annual EFC for different traffic and climate scenarios, as well as different types of pavement structures on the California state highway network. Comparison of the predicted EFC for test sections showed that all three models produced different results, which can be attributed to the differences in the three modeling approaches. However, predictions from the three models were generally of the same order of magnitude or an order of magnitude different, indicating that overall these models can be calibrated with data from field measurements, which is the next step in the research program.

Evaluation of coseismic landslide hazard on the proposed Haast-Hollyford Highway, South Island, New Zealand

ABSTRACTCoseismic landsliding presents a major hazard to infrastructure in mountains during large earthquakes. This is particularly true for road networks, as historically coseismic landsliding has resulted in road losses larger than those due to ground shaking. Assessing the exposure of current and planned highway links to coseismic landsliding for future earthquake scenarios is therefore vital for disaster risk reduction. This study presents a method to evaluate the exposure of critical infrastructure to landsliding from scenario earthquakes from an underlying quantitative landslide hazard assessment. The method is applied to a proposed new highway link in South Island, New Zealand, for a scenario Alpine Fault earthquake and compared to the current network. Exposure (the likelihood of a network being affected by one or more landslides) is evaluated from a regional-scale coseismic landslide hazard model and assessed on a relative basis from 0 to 1. The results show that the proposed Haast-Hollyford Highway (HHH) would be highly exposed to coseismic landsliding with at least 30–40 km likely to be badly affected (the Simonin Pass route being the worse affected of the two routes). In the current South Island State Highway network, the HHH would be the link most exposed to landsliding and would increase the total network exposure by 50–70% despite increasing the total road length by just 3%. The present work is intended to provide an effective method to assess coseismic landslide hazard of infrastructure in mountains with seismic hazard, and potentially identify mitigation options and critical network segments.

Reducing greenhouse gas emissions through strategic management of highway pavement roughness

On-road vehicle use is responsible for about a quarter of US annual greenhouse gas (GHG) emissions. Changes in vehicles, travel behavior and fuel are likely required to meet long-term climate change mitigation goals, but may require a long time horizon to deploy. This research examines a near-term opportunity: management of pavement network roughness. Maintenance and rehabilitation treatments can make pavements smoother and reduce vehicle rolling resistance. However, these treatments require material production and equipment operation, thus requiring a life cycle perspective for benefits analysis. They must also be considered in terms of their cost-effectiveness in comparison with other alternatives for affecting climate change. This letter describes a life cycle approach to assess changes in total GHG (measured in CO2-e) emissions from strategic management of highway pavement roughness. Roughness values for triggering treatments are developed to minimize GHG considering both treatment and use phase vehicle emission. With optimal triggering for GHG minimization, annualized reductions on the California state highway network over a 10-year analysis period are calculated to be 0.82, 0.57 and 1.38 million metric tons compared with historical trigger values, recently implemented values and no strategic intervention (reactive maintenance), respectively. Abatement costs calculated using $/metric-ton CO2-e are higher than those reported for other transportation sector abatement measures, however, without considering all benefits associated with pavement smoothness, such as vehicle life and maintenance, or the time needed for deployment.

Pavement-Dependent Load Limits

South Dakota statutes limit the weight of nonsteering axles to 500 lb/in. of tire width. The load allowance for single axles or spread tandem axles with wide-base tires is less than the axle load limit for dual tires. The objective of this research is to assess the potential impact of policy change if the load limit on wide-base tires is increased to be the same as the load limit on dual tires. First, a comprehensive literature review was conducted. Results indicated that the impact of wide-base tires on pavement damage varied, depending on pavement structure and damage mechanism. Pavement response and performance data were obtained from previous studies to calculate damage ratios between wide-base tires and dual tires with the same load. Different pavement failure mechanisms (fatigue cracking, top-down cracking, primary rutting, and subgrade rutting) were applied. Cost functions were then developed by relating the life-cycle cost of four typical asphalt pavement structures used in South Dakota to design traffic levels. The impact of the policy change on the cost of pavement damage was estimated by using detailed traffic data for each road segment in the state highway network. It was found that the cost of pavement damage increased because of wide-base tires on thin asphalt pavements commonly used in secondary roads. However, the impact of wide-base tires on Interstate highways was minimal. In addition, the environmental benefits brought about by the use of wide-base tires were equally significant, especially when the reduction in fuel consumption and air pollution was considered.

Comparative Testing of Lasers for Ride Quality Measurement on Hot-Mix Asphalt Pavements

The Texas Department of Transportation (DOT) is implementing a smoothness specification based on inertial profile measurements. For quality assurance testing, this smoothness specification includes pay adjustment schedules that are tied to the average international roughness index. The acceptance criteria used in this specification are based on surface profile measurements collected with the traditional single-point lasers, which the department has been using to monitor pavement smoothness on the state highway network. Since the Texas DOT implemented its smoothness specification, developments in sensor technology have included multipoint and wide-footprint lasers for noncontact height measurements. There is a need to verify ride quality measurements from these newer lasers to assess their impact on quality assurance tests conducted under the Texas DOT's existing ride specification. This paper presents a comparison of ride quality measurements from tests conducted with various lasers on hot-mix asphalt concrete pavements. Of particular importance to this comparison is the verification of ride quality measurements determined from the lasers tested with corresponding reference profile measurements.

Geographical analysis of commercial motor vehicle hazardous materials crashes on the Oregon state highway system

Crashes on highways frequently cause hazardous material exposure to the public and the environment. We evaluated differences in hazardous materials-related crashes vs. non-hazardous-material-related commercial motor vehicle crashes occurring from 2000 to 2006 on the Oregon state highway network. The two groups were compared for crash characteristics by χ2 analysis, and spatial clustering was tested using Ripley's K-function and kernel density estimator analyses. There were 8,622 total commercial motor vehicle crashes, 232 being hazardous-materials related. Hazardous materials-related crashes were not significantly associated with different road surface conditions, weather conditions or cause of crash. Hazardous materials-related crashes were associated more frequently with late evening/early morning hours and under artificial lights or at dusk. The commercial motor vehicle drivers in hazardous materials-related crashes were less frequently at fault than ones in the non-hazardous materials-related crashes. The planar Ripley's K-function indicated non-hazardous materials-related crashes were more clustered than hazardous materials-related ones. Both cohorts clustered at the 12–14 mile range. The kernel density estimator analysis indicated hazardous materials-related clusters are small and discrete along the main highway corridors, non-Hazardous materials-related ones seemed to form elongated confluent clusters along all highways. Since there seem to be few differences between the two cohorts in characteristics of the crashes and the frequency of hazardous materials-related crashes is low compared to the total commercial vehicle crashes, future geographical studies may focus on characteristics of all commercial motor vehicle crashes.

An integrated model to solve the winter asset and road maintenance problem

Winter road maintenance operations require many complex strategic and operational planning decisions. The main problems include locating depots, designing sectors and routes, and configuring and scheduling vehicles. The complexity involved in each of these decisions has generally resulted in research that approaches each of the problems separately, which can lead to isolated and suboptimal solutions. In addition to being integrated, a successful approach to these problems must consider the necessary practical aspects of each problem and include a straightforward, easily executable solution methodology; otherwise, it is unlikely to be implemented. This research proposes a systematic, heuristic-based optimization approach to integrate the winter road maintenance planning decisions. The approach is illustrated using an example of the state highway road network in Boone County, Missouri, which is maintained by the Missouri Department of Transportation.

Geocoding police collision report data from California: a comprehensive approach

BackgroundCollision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record. On California police reports, relative collision location is recorded using a highway postmile marker or a street intersection. The objective of this study was to create a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies.ResultsGeocoding was completed with a multi-step process. First, pre-processing was performed using a scripting language to clean and standardize street name information. A state highway network with postmile values was then created using a custom tool written in Visual Basic for Applications (VBA) in ArcGIS software. Custom VBA functionality was also used to incorporate the offset direction and distance. Intersection and address geocoding was performed using ArcGIS, StreetMap Pro 2003 digital street network, and Google Earth Pro. A total of 142,007 fatal and severe injury collisions were identified in SWITRS. The geocoding match rate was 99.8% for postmile-coded collisions and 86% for intersection-coded collisions. The overall match rate was 91%.ConclusionsThe availability of geocoded collision data will be beneficial to clinicians, researchers, policymakers, and practitioners in the fields of traffic safety and public health. Potential uses of the data include studies of collision clustering on the highway system, examinations of the associations between collision occurrence and a variety of variables on environmental and social characteristics, including housing and personal demographics, alcohol outlets, schools, and parks. The ability to build maps may be useful in research planning and conduct and in the delivery of information to both technical and non-technical audiences.

Road Data Aggregation and Sectioning Considerations for Crash Analysis

Increasingly, road authorities are collecting a variety of data sets related to their networks, including horizontal and vertical alignment, cross section, traffic volumes, crashes, and the location of features such as intersections and passing lanes. These data may be a mixture of point locations, fixed length records, and variable length records. A critical question concerning computational ease and practical usefulness is how best to aggregate or section the available data into appropriate road segments for operational and safety analyses. This issue is becoming more pertinent with the development of tools such as the Interactive Highway Safety Design Model (IHSDM) and the Highway Safety Manual, which require a logical partition of roads based on many different attributes. The guidance on how to do this, however, is rather scant. Analysis of traffic exposure versus crash risk is also affected by the use of fixed or variable length segments. Research is nearing completion in New Zealand to combine road feature, geometry, and crash data on the national rural state highway network. The resulting database will enable better analysis of crash patterns against different types of road elements and will be used to calibrate IHSDM for New Zealand use. This paper outlines the investigation done to determine a rational method for aggregating the available data into logical road segments. The resulting method uses horizontal alignment, significant cross-section changes, and changes in speed limit. It also attempts to minimize the number of very short segments. The resulting data set contains approximately 83,400 segments generated from 20,900 lane km (13,000 lane mi) of highway.

System Risk Curves: Probabilistic Performance Scenarios for Highway Networks Subject to Earthquake Damage

Monte Carlo simulation techniques are used with bridge fragility curves to evaluate bridge damage in terms of a bridge damage index, and highway network link damage in terms of a link damage index. Static, user-equilibrium analysis is used to evaluate total transportation network delay due to seismically induced damage inflicted on the Los Angeles and Orange County State highway and freeway network. A method of regional seismic risk analysis for highway systems is developed based on the definition of scenario earthquakes representing the seismic hazard of the region, and hazard-consistent probabilities are computed for each scenario. The final result of these efforts is a transportation system risk curve.

Performance-Specified Maintenance Contracts

In Australia and New Zealand, there has been a movement toward the private-sector delivery of road maintenance and management by using the performance-specified contract (PSMC) model. These are long-term contracts tendered competitively with a lump sum price. Initially the contracts concentrated on the physical attributes of the network that had to be maintained for the contract period. However, as these contracts matured, a reduction in the crash rates was observed. It was considered that the successful operation of a PSMC contributed to this reduction. By using data and calculation methods developed by Land Transport New Zealand and applying social costs for crashes normally used for justifying capital projects, it can be seen that the social cost of crashes is being reduced at a significantly greater rate on the PSMC 001 network than on the remainder of the state highway network. The value of savings ahead of the national trend has been more than NZ$31 million for a 3-year period. The contractor's performance is measured on the social cost of crashes that occur on the network, regardless of crash causation. To keep the contractor motivated, the contract includes provisions to adjust the contract payments as based on the safety performance. This approach requires a fundamental shift in the attitude of the contractor, moving from a reactive position to a new position of prevention with particular attention on improved safety. Performance data from a 7-year contract and a 3-year contract from New Zealand are presented. Improved safety performance has become a hallmark in these contracts, and safety performance continues to improve through innovations and commitment.

Decision Methodology for Allocating Funds across Transportation Infrastructure Assets

One of the main activities in transportation infrastructure asset management is the allocation of available funds across infrastructure classes (e.g., pavements, bridges, signs) or programs (e.g., maintenance, construction). A methodology for allocating funds across transportation asset classes using multiattribute utility theory has been developed and is provided in this paper. This methodology can be used for performing trade-off analysis among asset classes where it is practical to consider potential shifts in funding from one class to another. The methodology was applied to a sample state highway network in Champaign County, Illinois. The sample highway network consists of pavements, bridges, culverts, signs, and intersections. Four funding allocation alternatives were evaluated using the developed methodology. The case study identified the funding allocation alternative that results in the lowest risk of infrastructure failure or poor performance (i.e., highest utility) from an experienced engineer standpoint. The utility analysis revealed that the decision maker in the case study is risk averse when managing infrastructure classes with the most potential to affect traffic safety and to be noticed by the public, such as bridges and intersections. The case study also revealed that the level of available funding and the level of infrastructure performance affect how the total funding is allocated among asset classes.

Enhanced Bridge Replacement Cost Models for Indiana's Bridge Management System

Bridge managers have a duty to monitor and update the costs of bridge preservation activities and to implement cost-effective actions that are in the best interests of taxpayers. This paper presents details of replacement cost modeling for each bridge component (superstructure, substructure, approach, and other costs) for bridges with concrete slab, concrete beam, or steel superstructures. This was done with recent bridge construction data on the Indiana state highway network. It was determined that costs other than substructure and superstructure costs accounted for more than one-half of total replacement cost. The present study supports earlier studies by asserting that basic bridge characteristics such as type, length, and deck area may generally be used to derive reliable estimates of bridge replacement costs. The study also shows that economies of scale can play a significant role in reliable bridge cost estimation. It was determined that the average overall unit cost of replacement for steel superstructure bridges was generally lower than that for concrete superstructure bridges. It was seen that differences in replacement costs across bridge types are attributable not necessarily to cost differences in material and construction procedure only but also to economy-of-scale effects. Cost models can be used to predict total costs of future bridge replacements and are therefore useful for vital bridge management functions such as needs assessments, budgeting, and programming.

Enhanced Bridge Replacement Cost Models for Indiana's Bridge Management System

Bridge managers have a duty to monitor and update the costs of bridge preservation activities and to implement cost-effective actions that are in the best interests of taxpayers. This paper presents details of replacement cost modeling for each bridge component (superstructure, substructure, approach, and other costs) for bridges with concrete slab, concrete beam, or steel superstructures. This was done with recent bridge construction data on the Indiana state highway network. It was determined that costs other than substructure and superstructure costs accounted for more than one-half of total replacement cost. The present study supports earlier studies by asserting that basic bridge characteristics such as type, length, and deck area may generally be used to derive reliable estimates of bridge replacement costs. The study also shows that economies of scale can play a significant role in reliable bridge cost estimation. It was determined that the average overall unit cost of replacement for steel superstructure bridges was generally lower than that for concrete superstructure bridges. It was seen that differences in replacement costs across bridge types are attributable not necessarily to cost differences in material and construction procedure only but also to economy-of-scale effects. Cost models can be used to predict total costs of future bridge replacements and are therefore useful for vital bridge management functions such as needs assessments, budgeting, and programming.

Knowledge-Based Scheduling Analysis Software for Highway Rehabilitation and Reconstruction Projects

Most of California's highway infrastructure was built between 1955 and 1970. These pavements had 20-year design lives, and many now require frequent maintenance. In 1998, the California Department of Transportation (Caltrans) launched the Long-Life Pavement Rehabilitation Strategies (LLPRS) program to rebuild approximately 2,800 lane kilometers of high-traffic-volume urban freeway in the 78,000-lane kilometer state highway network over a 10-year period. Priorities identified for the successful implementation of LLPRS projects are the selection of construction schedules and the development of traffic management plans that minimize road user and agency costs. This paper presents a construction simulation program called CA4PRS (Construction Analysis for Pavement Rehabilitation Strategies). The program was developed as a scheduling and production analysis tool for LLPRS projects for use during the planning and design stages. CA4PRS estimates the optimized distance and duration of highway rehabilitation projects. It takes into account the constraints of scheduling interfaces, pavement design, lane closure tactics, and contractor logistics. As a knowledge-based computer system on a Microsoft Access database, it uses Monte Carlo simulation, critical path method analysis, and linear scheduling. CA4PRS is designed to help highway agencies and paving contractors make construction schedule decisions that balance rehabilitation productivity, traffic inconvenience, and agency cost. Application of the CA4PRS model to urban freeway rehabilitation projects in California, including the I-10 Pomona, I-710 Long Beach, and I-15 Devore projects, has demonstrated its value in saving millions of dollars for both Caltrans and road users.