More Than Smart Pavements: Connected Infrastructure for Enhanced Winter Safety and Resilience on Highways

Currently, there is an urgent demand for more cost-effective, resource-ecient and reliable solutions to address safety, mobility, and resilience challenges on highways enduring snowy winter weather. To address this pressing issue, this commentary proposes that the physical and digital infrastructures should be upgraded to take advantage of emerging technologies and facilitate the vehicle-infrastructure integration (VII), to better inform decision-makers at various levels. Driven by the paradigm shift towards more automation and more intelligent transportation, it is time to reimagine the vehicle-infrastructure ecosystem with the cold-climate issues in mind, and to enhance communications and coordination among various highway users and stakeholders. This commentary envisages the deployment of vehicle-to-everything (V2X) technologies to bring about transformative changes and substantial benets in terms of enhanced winter safety and resilience on highways. At the center of the commentary is a conceptualized design of next-generation highways in cold climates, including the existing infrastructure entities that are appropriate for possible upgrade to connected infrastructure (CI) applications, to leverage the immensely expanded data availability fueled by better spatial and temporal coverage. The commentary also advances the idea that CI solutions can augment the sensing capabilities and condence level of connected or autonomous vehicles. We then briey explore the application scenarios of VII system, and conclude with some discussion of the paradigm shift towards V2X applications and a look to the future in terms of identied research needs in the arena of CI. We hope to inspire dialogues and synergistic collaborations among various stakeholders of the VII revolution, because the specic challenges call for systematic, holistic, and multidisciplinary approaches accompanied by concerted efforts in the research, development, pilot testing, and deployment of CI technologies.

transportation system (ITS) solutions such as smart snowplows equipped with automatic vehicle location (AVL), road weather information systems (RWIS), xed automated spray technology (FAST), maintenance decision support system (MDSS), dynamic message signs (DMS), and traveler information systems. For tra c management, it is noteworthy that current ITS technologies (loop detectors, video/camera detectors, and radar sensors) are generally limited to obtaining tra c information at the macroscopic level [Wu 2018]. The advent of technologies in connected and autonomous vehicles (CAVs), Internet of Things (IoT), and advanced driver assistance (ADAS) systems, along with advances in information and communications technology (ICT), is envisaged to bring fundamental changes to the current practices.
The physical and digital infrastructures should be upgraded to take advantage of CVs/AVs and facilitate the cooperation between roadway infrastructure and CVs/AVs, i.e., vehicle-infrastructure integration (VII).
In the near future, we expect to see mixed tra c ows of connected vehicles (CVs), autonomous vehicles (AVs), and conventional vehicles on highways, which presents new opportunities for better system performance and higher level of service, along with new infrastructure requirements. For instance, connected infrastructure (CI) solutions are desirable for bridging the communication gap between unconnected vehicles and CVs/AVs. CVs equipped with sensors could enhance mobile road weather data collection [Dey et al., 2015] and supplement or compliment current roadway sensing entities, raising the effectiveness of the system operations to react to changing conditions. The 360° awareness by vehicle operators and increased system reliability will help reduce the risk of vehicle crashes and enhance the e ciency of system operations. The Connected Vehicle Reference Implementation Architecture (CVRIA) developed by the U.S. Federal Highway Administration (FHWA) has de ned how CVs will contribute to the road weather management data collection and information dissemination [FHWA, 2014]. Speci cally, CV technologies will enable tra c managers to deliver real-time, localized road weather advisories and forecasts directly to the vehicle onboard unit as a visual display to drivers. Moreover, collected real-time raw data can be shared with commercial application developers to build value-added services [Chapman and Drobot 2012]. AVs tend to be CVs at the same time and can offer a multitude of bene ts including alleviated congestion, reduced energy use and emissions, and improved tra c safety [Shladover 2013, Sobanjo 2019].
Recent years have seen substantial progress in the development and pilot testing of technologies that enable CVs to transmit data to and receive data from other CVs (vehicle-to-vehicle, V2V), to and from infrastructure (vehicle-to-infrastructure, V2I), and to and from bicyclists or pedestrians. These can be collectively termed as vehicle-to-everything (V2X) communication, for which use cases, requirements, and design considerations of roadways have been discussed by Boban et al. [2018]. The transmission of microlevel road weather data by vehicles through V2X communication has been demonstrated in the European WiSafeCar project [Sukuvaara and Nurmi, 2012], which is anticipated to bene t the e ciency of road weather management [Ma et al., 2012]. In addition, the USDOT has estimated that combined V2V and V2I systems may potentially address about 81% of all-vehicle target crashes, 83% of all light-vehicle target crashes, and 72% of all heavy-truck target crashes [Naja et al. 2016]. Such safety bene ts of CV are likely to be more signi cant during adverse weather conditions, by enhancing all levels of decision-making by stakeholders. For example, the enriched road weather condition information can be communicated to the general public in a timely fashion, such that they can slow down, choose a different route, or stay home in light of inclement weather.
In addition to safety bene ts, the deployment of V2X technologies and advances in VII are likely to produce resilience bene ts on winter highways, by better informing all the stakeholders and enabling location-speci c and timelier detection of and response to disruptions. By de nition, resilience is "the ability of a system to resume normal function at a performance level equal that which existed before a disruptive event", and can be characterized by metrics such as robustness, adaptability, agility, redundancy, response time, recovery time, level of recovery, and performance loss [Muller 2012]. It is interesting to note that winter weather may induce vulnerabilities in vehicles on highways as well as in physical and digital infrastructures. For instance, the performance and reliability of CVs/AVs (and other sensors) and communications could be destabilized by extremely cold temperatures and heavy snowfall conditions, and such risks should be considered in the design of the VII system to operate in cold climates.
In the context of upcoming VII revolution and increased road user expectations, this commentary aims to inspire dialogues and synergistic collaborations among various stakeholders. The commentary is organized in four main sections. Following this introduction is a discussion of conceptual design of nextgeneration highways in cold climates, including the existing infrastructure entities that are appropriate for possible upgrade to CI applications. Subsequently, the application scenarios of VII system (or V2I technologies) are brie y discussed, with a focus on coordinated truck platooning, safety applications, mobility applications, and road weather applications. The nal section provides concluding remarks regarding the paradigm shift towards V2X applications and a look to the future in terms of identi ed research needs in the arena of CI.
Conceptual Design Of Next-generation Highways In Cold Climates Fig. 1 presents a conceptual design of next-generation highways in cold climates, where a number of CI entities are envisioned. These, along with V2X and ICT capabilities, are expected to greatly enhance the spatial and temporal resolutions of road weather data and thus better inform stakeholders such as highway operators, emergency responders, truck drivers and other highway users. They can also augment the sensing capabilities and con dence level of CVs/AVs, reduce the cost and uncertainties of sensing, enrich the sources of information for both CVs/AVs and unconnected vehicles, and improve the response time. The following sections will further discuss some entities, including: energy-harvesting, connected roadways and roadside infrastructure assets (RIAs); self-sensing or anti-icing pavement; connected Environmental Sensing Stations (ESS) and connected FAST system, followed by ICT capabilities. Other CI entities will not be discussed in detail, including: weather-responsive tra c signals, smart work zone equipment, and non-contact static charging for vehicles. In this work, we also do not discuss AV-enabling infrastructure components, such as smart signage for automatic driving, standardized pavement markings for machine vision, and magnetic nails and re ective striping for lane-keeping.

Energy-harvesting, connected roadways and RIAs
The massive number of roadway mileages and vast amount of lands in the right-of-way present a great opportunity to capture and utilize the energy dissipated from the ambient roadway system, such as mechanical energy from vehicle or wind loadings and thermal energy from the sun or earth. Such energy harvesting is particularly bene cial for roadways in remote, off-grid areas where the lifeline of CI applications is endangered by the lack of access to power. In the U.S. alone, there are 2.6 million miles of paved roads and highways, of which approximately 93 percent has an asphalt surface [Mohamed Jaafar 2019] and 3,000 (linear) miles are equipped with noise barrier [Poe et al. 2017]. The "(unpaved) land cover in close proximity to the National Highway System" in the U.S. has been estimated to be "roughly 68 percent, or 3.4 acres" [Earsom et al. 2010]. A suite of energy-harvesting technologies are available, as illustrated in Fig. 2 [Wang et al. 2018]. These technologies entail the use of piezoelectric materials, micro wind turbines, photovoltaic panels or solar cell roads, geothermal heat pumps, or pipe-pavement thermoelectric generator (PP-TEG) system. They could be potentially incorporated into either the connected roadways such as pavements and tra c signals, or RIAs such as noise barriers and structural snow fences, featuring a wide variety of cost, energy output and e ciency, service life, dimensions, maintenance requirements, recyclability, and other characteristics.
The last ve years have seen increased interest and promising progress in demonstrating the use of piezoelectric materials to harvest deformation energy from asphalt pavement. Yet, the amount of energy harvested is limited but suitable for applications such as "powering wireless sensors embedded into pavement structure" [Roshani et al. 2017] and other microelectronics, "heating road surface on bridge deck for anti-icing, lighting, or powering tra c devices" [Wang et al. 2018]. A few representative advances in the development of piezoelectric energy harvester (PEH) technology is summarized in Table 1.

Wang et al. [2018] reviewed the energy-harvesting technologies in roadway and bridge applications.
Technologies other than PEHs also have their own strengths and limitations. For instance, photovoltaic systems can produce high energy output but their use in roadways may complicate vehicle operations or pose a risk to tra c safety, and more research is needed to address such concerns. Geothermal heat pumps are considered a mature technology, which is "geologically and geographically limited" and most appropriate for safety-critical areas. PP-TEG produces a low energy output at high cost, and more research is needed to improve the system e ciency. One challenge was "only 14.43% of the applied loading was transmitted to the piezoelectric materials" and the electrical productivity of PEHs highly depends on "the axle con guration and magnitude of passing vehicles".

Xiong and Wang [2016]
One layer of "piezoelectric elements with a higher piezoelectric stress constant" and two layers of "more exible conductive asphalt mixtures" Output power: ranging from 1.2 mW to 300 mW at 30 Hz The cost of electricity produced by this PEH can be as low as "$19.15/kWh at a high-volume roadway within a 15-year service life".

Guo and Lu [2017]
In addition to smart pavements, there are a number of conceptual scenarios that energy-harvesting technologies may be incorporated into the roadway infrastructure. For instance, portable micro wind turbines could be mounted on structural snow fences, tra c signals, and so on. Being a cost-effective technology to prevent blowing and drifting snow, snow fences can improve road safety and provide additional bene ts, if designed and sited properly [Du et al. 2017]. Nabavi and Zhang [2016] reported three groups of portable wind energy harvesters, i.e., piezoelectric-, electromagnetic-, and electrostaticbased generators, with different wind-ow-trapping mechanisms and varying dimensions and energy conversion e ciencies. Photovoltaic panels can be strategically installed either in the right-of-way providing su cient space for such a "distributed solar power plant" [Asanov et al. 2019], or integrated with noise barriers to produce a considerable amount of renewable energy [Poe et al. 2017]. Qiao et al.
[2011] proposed the concept of a "smart microgrid that optimally utilizes the public right-of-way and roadway infrastructure to provide cost-effective, highly e cient, and reliable wind/solar electric power production, distribution, storage, and utilization". The design entails a "grid-connected wind/solar hybrid generation system installed on the pole of a roadway/tra c signal light". Considering the great temperature difference between the air and the relatively warm soil beneath pavement, another potential technology to explore is thermoelectric generators. With the thermal gradient in the opposite direction, this concept was demonstrated in south Texas [Datta et al. 2017] where a TEG prototype produced "an average of 10 mW of electric power continuously over a period of 8 h".
Self-sensing or anti-icing pavement Self-sensing pavements can serve as an integral part of connected roadway infrastructure or VII System, and the related research is still in the burgeoning stage. Han et al. [2013] reported the tra c detection performance of a self-sensing pavement being tested at the Minnesota Road Research Facility, USA, both in winter and in summer. This smart pavement was enabled by the admixed carbon nanotubes in concrete, and was able to "accurately detect the passing of different vehicles under different vehicular speeds and test environments". Relative to conventional strain gauges, this self-sensing concrete exhibited advantages in its ease of installation and maintenance, compatibility with pavement structures, and durability. Liu et al. [2014] reported an exploratory study that suggests the potential use of conductive asphalt materials for self-sensing applications, because the different stages of damage evolution corresponded to certain change patterns in their electrical resistivity.
Anti-icing pavements are often not designed for CI applications, but they can contribute to the resilience of surface transportation system during snowy weather. A variety of technologies have been explored to enable anti-icing pavements, ranging from "anti-freezing pavements that rely on physical action, to highfriction in situ anti-icing polymer overlays, to asphalt pavements containing anti-icing additives, to heated pavements using energy transfer systems" [Shi et al. 2018]. All of them aim to "prevent or reduce the bond of ice or compacted snow to pavement or to prevent or treat winter precipitation". Pan et al. [2015] and Zhang et al.
[2020] presented a comprehensive review on the use of conductive and salt-releasing asphalt mixtures as anti-icing pavements, respectively. Note that none of these technologies have been widely adopted by transportation agencies, and this is mainly due to concerns over their long-term performance.

Connected ESS
RWIS-ESS could be further enhanced so as to serve as integral part of the CI solution and of the larger vehicle-infrastructure ecosystem, with the focus on design improvements and cost reductions. RWIS refers to "networks of ESS that observe the near-surface atmosphere and pavement surface and subsurface" [Albrecht et al. 2018], generally deployed at xed locations to better inform WRM operations. Each ESS consist of various sensors that provide site-speci c, real-time data on the meteorological conditions, RSC, and subsurface temperature, which altogether enables pro-active WRM practices such as anti-icing, improves the roadway level of service and resource allocation, and enhances traveler information, tra c management and emergency response Fay 2007, Kwon et al. 2017]. Kwon et al. [2017] developed a framework to optimize the siting of RWIS stations in a given network to maximize "the coverage of accident-prone areas (while) minimizing the total estimation error", addressing the needs by both WRM operators and the traveling public. Note that the mobile data collection by CVs/AVs will likely bolster the accuracy of road weather forecasting models, which in turn induces advances in the RWIS-ESS technology.

Connected FAST system
FAST has been employed by many roadway agencies to prevent or pro-actively mitigate black ice or bonding of compacted snow and ice to pavement (or bridge deck). Conceptually, the design of FAST system could be further enhanced to improve its connectedness and thus contribute to the vehicleinfrastructure ecosystem. Ye et al. [2013] surveyed the state of the art of FAST systems and con rmed their potential in delivering substantial bene ts, such as less need for mobile operations and WRM materials and reduced crash frequency and tra c delay. This technology "works best for frost and light snow events", but its application has been hindered by challenges in sensor malfunctioning, system maintenance, and training. A study by Veneziano et al. [2015] examined the safety effects of FAST systems operated by the Colorado Department of Transportation and recommended the deployment of such system at "high-tra c, high-crash severity locations". For instance, FAST systems were able to contribute to "an annual reduction of 16-70% on urban Interstates, 31-57% on rural Interstates, and 19-40% on interchange ramps between Interstates", when sited and operated properly.
Arguably, there are a number of roadside or CV solutions other than embedded pavement sensors that can augment the FAST's detection capability and improve its reliability by providing additional information on the road surface condition (RSC). The technologies include non-invasive pavement friction sensors [Ewan et al. 2013

ICT capabilities
This commentary agrees that as part of the transportation cyber-physical system (TCPS), the physical infrastructure of roadways should be "upgraded with digital (ICT) infrastructure that evolves with increasing CV penetration levels (so as to) create an environment suitable for fostering bene cial V2I innovations" [Khan et al. 2019]. This is critical for enabling the timely and reliable sensing, processing and communication of the unprecedented amount of data available in the VII environment. Khan et al.
[2019] summarized the typical roadway digital infrastructure components (as shown in Fig. 3 We are at the dawn of the 5G era, which stands for the 5th generation mobile network and features communication capabilities better meeting the needs of IoT and V2X applications, particularly safetycritical use cases [Boban et al. 2016]), i.e., higher data rates, ultralow latency, ultra-reliability, and increased availability. Boban et al. [2016] proposed an architecture of the 5G V2X network, embodied in a heterogeneous multi-radio V2X network designed to leverage the strengths of "cellular systems in centimeter (cmWave) and millimeter (mmWave) frequency bands, vehicular visible light communication (VVLC)" and DSRC/WAVE. The computing infrastructure, either distributed or centralized, is also a key player in the TCPS to enable smart and seamless mobility, and should be planned, designed, deployed, operated and maintained properly [Khan et al. 2019]. To attain outstanding performance and reliability of V2X applications, innovations are also expected in the eld of information technology in terms of system design, hardware and software, by tapping into recent advances in blockchain and edge computing [Liu et al. 2018 ultralow latency 5G scenario, where networking technologies (cloud computing, mobile edge computing, and software de ned networking) were integrated to provide ubiquitous network connectivity and e cient computing to support V2X communications. Among them, edge computing (a.k.a., fog computing) refers to "the enabling technologies allowing computation to be performance at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services" [Shi et al. 2016], and it brings many advantages in "addressing the concerns of response time requirement, battery life constraint, bandwidth cost savings, and data safety and privacy".

Application Scenarios Of Vii System
Coordinated truck platooning Connected and autonomous trucks (CATs) are increasingly introduced into the market, which enables the grouping of densely-spaced trucks to travel together on highways to save on the cost and fuel consumption and improve the e ciency of freight operations. This practice, known as truck platooning, has unintended negative consequences on how the trucks could induce damage in the pavement infrastructure, due to the "channelized truck loading application" [Gungor and Al-Qadi 2020]. To mitigate this detrimental effect, Gungor and Al-Qadi [2020] proposed a framework to optimally randomize the pattern of axel loadings of truck platoons using V2I communication. Such a coordinated truck platooning approach entails cooperative automation among trucks and roadway infrastructure, which uniformly distributes the loadings of truck platoons over the pavement lanes, leading to an overall reduction in damage accumulation in the pavement and a longer service life of the pavement.

Other Application Scenarios
The USDOT V2I research program has developed a computing platform known as V2I hub [Chang 2017], which "interfaces with a variety of ITS (intelligent transportation system) eld equipment such as RSU, tra c signal controllers, and DMS" and the global positioning system (GPS) and TMC. For instance, an RSU can broadcast intersection geometry data (a.k.a., MAP message), signal phase and timing (SPaT) message, GPS correction data, and curve speed warning to incoming vehicles, or receive them from nearby RSUs [Change 2017, NOCoE 2020].
One can expect CI-enabled improvements to be materialized in Safety Applications such as intersection collision warning, emergency vehicle pre-emption, work zone alerts, curve speed warning, railroad crossing violation warning [ Barbaresso and Johnson 2014], in-vehicle signage, oversize vehicle warning, red-light or stop-sign violation warning, reduced speed zone warning/lane closure, restricted lane warning, spot weather impact warning [Iteris 2020], cooperative collision avoidance [Chowdhury et al. 2018], blind spot warning, lane change warning, automated incident spot guidance and alerts, ADAS functionalities, and pedestrian detection and warning. Wu [2018] reported an intriguing CI safety application where multiple roadside LiDAR (Light Detection and Ranging) sensors were deployed to enable real-time, microlevel and high-resolution sensing of road users, with a focus on deer crossing road detection.
One can also expect CI-enabled improvements in Mobility Applications such as advanced traveler information system, corridor management, transit vehicle priority, and multimodal intelligent tra c signal system [Barbaresso and Johnson 2014], tra c queue detection [Chowdhury et al. 2018], incident detection and response, tra c network ow optimization, emergency vehicle priority, adaptive signal control, cooperative adaptive cruise control (CACC), time-to-green-light alert at signalized intersections, smart DMS, and routing support and data-driven apps for freight carriers, transit vehicles and emergency responders. Abbound et al. [2016] summarized a variety of deployment scenarios of V2X applications, including those for vehicle tra c optimization, road safety, passenger infotainment (via in-vehicle Internet access), and car manufacturer services (e.g., point-of-interest noti cation and remote vehicle diagnostics).
Furthermore, Barbaresso and Johnson (2014) summarized some other V2I applications, including Road Weather Applications (motorist advisories and warnings, information for maintenance and eet management systems, and MDSS) and Agency Data Applications (probe-based tra c monitoring, probebased pavement condition monitoring, and performance measures). All of these aim to "provide a safe and e cient transportation system to move people and goods" [Sobanjo 2019].

Conclusion And Outlook
Currently, there is an urgent demand for more cost-effective, resource-e cient and reliable solutions to address safety, mobility, and resilience challenges on highways enduring snowy winter weather. One can envisage a fundamentally changed landscape for WRM operations, traveler information, and tra c management on winter highways, amid the increasing introduction of innovative concepts (e.g., Smart Cities, Crowdsourcing, and V2X) and more penetration of emerging technologies (e.g., CVs/AVs/CATs, IoT, 5G, Cloud Computing, and Edge Computing) into the transportation sector. These concepts and technologies will catalyze the increasing momentum of VII to enable a signi cantly higher level of service. As such, there is the need to conceptualize and strategically plan for a more connected roadway infrastructure for VII system, even though many of the CI solutions are still in the nascent stages of development.
Driven by the paradigm shift towards more automation and more intelligent transportation, it is time to reimagine the vehicle-infrastructure ecosystem with the cold-climate issues in mind, and to enhance communications and coordination among various highway users and stakeholders. A next step is to promote the synergies among the enabling technologies and unlock their potential for the speci c needs of highway agencies. For instance, CI technologies are currently less mature than CV technologies. Great bene ts can be achieved once we integrate the array of both CI and CV technologies, by providing better, more accurate and timely knowledge of conditions throughout the roadway network (albeit with a focus on critical locations and road segments), in terms of tra c characteristics, RSCs, and environmental conditions. This big data could be processed, archived, and communicated to highway operators and traveling public in a timely fashion. In addition to informing travelers, such information can be fed into agency decision support tools such as the Maintenance Decision Support System (Ye et al. 2009, Rennie and Groeneweg 2017) to greatly bene t the roadway level of service and the overall safety, mobility, and productivity of the surface transportation system.
To inspire dialogues and synergistic collaborations among various stakeholders of the VII revolution, this commentary has underscored the need to plan, design, and engineer a multifunctional, next-generation highway infrastructure that is more intelligent, safer and more resilient and adaptive than the conventional highway infrastructure, fueled by more reliable and rapid collection, processing and communication of big data.
The challenges in achieving better safety and resilience on winter highways may continue to evolve and they must be addressed with systematic, holistic, and multidisciplinary approaches. A next step is to carry out concerted efforts in the research, development, pilot testing, and deployment of CI technologies, which needs to bring together expertise from different disciplines to transform the built highway environment to one that better facilitates the real-time detection of localized conditions and the ow of high-quality road weather data (e.g., V2X). The ultimate goal is to improve the safety and resilience of highways in cold climates, which in turn would translate to a broad array of social, economic and environmental bene ts.
The VII revolution is still in its infancy and there are many unexplored territories and dynamics, unanswered questions, and open challenges. Innovations are much needed to overcome the various technological and institutional barriers to the successful implementation of VII system for highways in cold climates, and to maximize the synergies between the physical and digital infrastructures. It is imperative to note, however, that innovations should be anchored in answering the user requirements, i.e., following a needs-pull (vs. technology-push) approach.
The following presents some of research needs identi ed in the arena of CI: Optimize the materials selection, PEH design (packaging, composite con guration of elements, etc.) and power electronics, as a function of given tra c patterns, in-service environmental conditions, and speci c energy requirements of the CI application. The objective is to achieve balanced performances in energy output and e ciency, cost-effectiveness, reliability and resilience, durability, recyclability, and sustainability over the life cycle of the PEH.
Develop a set of cost-effective, durable asphalt pavement mixtures or surface layers that enable reliable real-time detection of key vehicle ow parameters and other functionalities such as in situ anti-icing, sensing of the surface condition (dry, wet, snowy, icy, etc.) and/or sensing of the overall health condition of the pavement itself.
Tap into recent advances in various V2X and ICT technologies and investigate better compatibility, automation, and integration among them, to provide the best possible road weather information, in terms of spatial and temporal resolutions, reliability, and so on. The efforts may be in the aspects of system design [Li et al. 2019, Muller 2012, hardware, and software and should take into account the given constraints of cost, communications speed and reliability, etc. as well as the speci c performance requirements and functionalities needed by the VII system. The objective is to have a cohesive and affordable VII system that operates e ciently and reliably during disruptive weather of snow and ice.
Address the technical and non-technical challenges vis-à-vis scalability, interoperability, privacy and security, in anticipation of increased number and heterogeneity of smart devices and immense amount of sensor data available, similar to those hindering the implementation of Smart City services and applications [Balakrishna 2012].
Investigate the transformation of physical roadway infrastructure for the needs of VII applications, build resilience into highways, and tap into the opportunities of improving the design, health monitoring and diagnosis, preservation, and utility of roads, bridges, tunnels, culverts, and RIAs, while reducing their life-cycle cost and environmental footprints.