Road System Research Articles

Weather event characterization: a catalyst for improved spatial mapping and benefit quantification in winter road maintenance

Monitoring winter road surface conditions (RSC) is essential for optimizing winter road maintenance operations and ensuring public traffic safety and mobility. However, many existing RSC estimation methods focus primarily on local or site-specific conditions, thus lacking effectiveness in comprehensive spatial mapping under varying winter weather events. Additionally, the potential financial benefits these methods could provide to maintenance authorities remain largely unexplored. This study addresses these gaps by introducing a refined methodology that harnesses the K-Means algorithm to characterize various weather events – a significant stride towards improving the generalizability and accuracy of road surface temperature (RST) estimations. The study also incorporates regression kriging (RK), a renowned geostatistical technique, as an integral component of a system for constructing an extensive spatial map of RSC across large highway networks. This strategy maximizes the use of data from existing road weather information systems (RWIS) to bridge their large spatial gaps. This study further quantifies the potential savings derived from optimally placing RWIS stations and reducing traffic collisions. The efficacy of these methods is validated through a real-world case study on two major interstate highways in Iowa, US, with RST estimation discrepancies as low as 0.619 °C. The findings also indicate potential cost savings by conserving up to 10 RWIS stations, which can be further translated into monetary savings of RWIS capital costs, traffic collisions prevention, enhanced traffic mobility and savings in maintenance material usage.

Thermal effects on rheological characteristics and its evolution mechanism of bio-modified rubberized asphalt for sustainable road system: A focus on rubber particle size

Bio-modified rubberized asphalt (BMR) has been acclaimed for its superior pavement performance and eco-friendliness, which can promote the sustainability of road systems. However, its rheological properties, intimately tied to crumb rubber (CR) particle size, display variability during thermal storage. This study probed the effect of CR particle size on BMR's rheological attributes under thermal conditions. BMRs were prepared using varied CR particle sizes, thermally conditioned over a span of up to 10 h, and then tested for rheological properties. Our findings illustrate particle size's pivotal role in CR swelling, degradation, and asphalt aging mechanisms during thermal conditioning, consequently affecting various BMR characteristics. Large CR particles displayed slower swelling rates, with secondary swelling observed. The CR's micro-skeleton within asphalt phase amplified asphalt's elasticity recovery, causing an increased rutting factor and complex viscosity. In contrast, stress concentration due to CR particles curtailed the fatigue life of BMR. With smaller CR particles, both elastic response and viscosity of BMR diminished due to CR's devulcanization and depolymerization during thermal conditioning. However, substances released during CR degradation altered the asphalt composition, bolstering BMR's fatigue resistance. During thermal process, asphalt oxidation resulted in increased stiffness, thereby degrading BMR's rheological properties. It is beneficial for CR of 40 mesh or coarser to extend the breeding time to stabilize its performance, whereas for asphalt prepared with 60 mesh or finer CR, it should be used as soon as possible after preparation to prevent a significant performance degradation. In summary, managing particle size and thermal conditioning time is crucial in preserving BMR's optimal rheological properties.

Construction of street tree risk assessment system and empirical analysis based on non-destructive testing technologies

The traditional visual tree assessment method is subjective in evaluating tree risks and therefore not effective in precisely detecting internal decay in tree trunk and root systems. To improve the accuracy of street tree risk assessment, a new nondestructive testing method was proposed. This new tree risk assessment method combines different non-destructive testing technologies, such as sonic tomography and ground-penetrating radar, which could significantly increase the accuracy of risk assessment in tree trunks and roots. The method was applied to evaluate the risk of 1,001 street trees in Shanghai’s historical feature protection area. The results revealed that despite most street trees having low branch and trunk risk levels, more than one-third had high root risk levels. The risk factors of street trees were mainly in the trunk and root system, with a significant correlation between the street tree risk level and tree cavities, diseases, and insect pests, as well as the depth and range of the root distribution, leaning, and internal decay in trunks. With the help of non-destructive testing and risk assessment analysis, as well as targeted prevention measures, the possibility of street risk damage was largely reduced, including street trees tilting and collapsing during typhoons, etc.

An integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port of Bangladesh

An integrated intermodal freight transportation system is a derived demand to transport shipping containers from/to the seaport to/from the hinterland, instead of undertaking cargo loading and unloading activities in port-protected areas. The concept of the intermodal system is to transfer containers to nearby hinterland nodes, such as dry ports, inland rail, road, and river terminals as a part of port development, as well as increasing port efficiency and productivity. Lloyd’s List ranked Chattogram Port as the 67th busiest container port in the world as per container port throughput in 2022. Chattogram Port has small-scale intermodal facilities for off-docks/ICDs in the port city only. In addition, a pure intermodal system has been developed by one rail ICD in the capital city, Dhaka, and two RICTs nearby Dhaka, but less than 5 % of port throughput. A large-scale intermodal for serving the major cities, SEZs, EPZs, and industrial areas is absent due to planning and policy problems, as well as the unavailability of intermodal infrastructure and network. Due to an improper hinterland intermodal chain, the port faced container supply chain disruptions at the port yard and exceeded port capacity, resulting in container vessel congestion at the outer anchorage of Chattogram Port. By developing rail and road infrastructure, and utilizing natural river connectivity, it is possible to develop road, rail, and river intermodal systems, and shape an integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port. To develop an integrated intermodal system, this research chose a quantitative research methodology for port throughput data analysis and forecasting future throughputs that are advanced to the intermodal model for Chattogram Port. Overall, this paper aims to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness actively. Highlights Intermodal system is a derived demand for managing hinterland and port terminals of a seaport that needs to be implemented in Chattogram Port Container supply chain disruptions to be avoided to increase the port productivity and efficiency Inland intermodal connectivity will help to increase hinterland of a seaport It is necessary to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness globally

Automated pavement marking integrity assessment using a UAV platform – a test case of public parking

ABSTRACT Intact pavement markings organize the utilization of the pavement surface area, increase the road capacity, and improve traffic safety. However, deterioration occurring over the service life will lead to traffic safety hazards. A detailed inspection is regarded as the central tenet of pavement marking management. Conventional manual assessment approaches are time-consuming, qualitative, and argued to be subjective. Thus, cost reduction, quantitative analysis, and automatization have been the focus of research. Unmanned Aerial Vehicle (UAV) platform has been studied wildly in civil tasks due to its low cost and high maneuverability. A UAV-based platform was developed in this research to address the inefficiency, access limitations, and image processing of existing road marking inspection systems. In this research, the resolution of the image is 5472 × 3080 pixels and is captured with a fixed focal length of 8.8 mm. Given intensity differences between pixels of paintings and asphalt backgrounds, the pixels belonging to painting regions are classified using the K-mean clustering algorithm. After detecting all parking lines from images, the Otsu method was employed to determine the threshold of 0.9 as the quantitative indicator of painting quality. The UAV-based platform exhibits expected performance in assessing the pavement markings in a parking area. Future research will explore the deployment in city-scale applications.

Assessing road vulnerability in seismic conditions: a comprehensive study

Road infrastructure is indispensable for societal functionality, yet it is highly susceptible to the devastating impacts of seismic events. This paper focuses on enhancing the resilience of road systems by systematically identifying, quantifying, and assessing factors contributing to their vulnerability during earthquakes. The core objective of this study is to develop and validate a seismic vulnerability index for road sections, which aims to evaluate and classify the susceptibility of road infrastructure to earthquake-induced damage comprehensively. This systematic approach is pivotal for guiding effective mitigation strategies and prioritization efforts. To fulfill this objective, the study employs the Analytic Hierarchy Process (AHP) to introduce a novel methodology for calculating the seismic vulnerability index, incorporating various factors that influence road vulnerability. This method allows for the accurate classification of road sections into distinct levels of susceptibility, providing a solid foundation for implementing targeted interventions and enhancing road resilience. Further, the paper validates the theoretical model through several case studies, demonstrating the practical applicability and effectiveness of the seismic vulnerability index in real-world scenarios. Additionally, the use of Geographic Information System (GIS) technology to simulate earthquake scenarios within an urban road network offers valuable insights into the potential seismic behavior of roads. These simulations are crucial for identifying critical areas that require intervention and for planning resilience-building efforts more effectively. By proposing a comprehensive framework that combines rigorous analysis, empirical validation, and advanced simulation techniques, this paper seeks to make a significant contribution to the field of infrastructure resilience. It aims to advance the understanding of road vulnerability in seismic conditions and supports the development of strategic approaches for enhancing the resilience of road infrastructure against earthquakes. Through the development and validation of a seismic vulnerability index, this study meets its primary objective, providing a valuable resource for researchers, policymakers, and practitioners in disaster management and infrastructure planning.

Efficiency of urban greening systems with maximized latent heat effect in urban heat island and climate change mitigation

Street, wall, and rooftop greening systems are essential for urban heat reduction and carbon neutrality. In this study, we compared the temperature-reducing effect of current and developed technologies that maximize the latent heat of evaporation through such greening systems. A research site with the maximum urban heat island effect was selected by analyzing the vulnerability of Suwon City, Korea. The latent heat of evaporation for each method was determined by conducting actual measurements and verified by performing computational fluid dynamics simulations. Based on the results of statistical techniques, the validated model was highly reliable. When developed technologies were applied, the temperature of the entire city was reduced by approximately 2 °C. Compared with the existing street greening system, the developed technology achieved a temperature reduction effect even at a distance of 5 m. Current wall greening systems only have a temperature reduction effect at 1 m, but that of the developed technology was approximately 1 °C even at a distance of 2 m. The existing rooftop greening system had a temperature reduction effect only at the height of 1.2 m, whereas that of the developed technology was effective even at 6 m, contributing to a reduction in the temperature of the entire city.

METHODOLOGY APPLIED IN THE CONSTRUCTION OF STRUCTURES USING NATURAL AND ALTERNATIVE MATERIALS FOR STABILIZATION WORKS IN ROAD CONSTRUCTION

The analysis of the current state of applications and the results of studies carried out at international level have led to the approach of an eco-efficient methodology for the recovery of waste generated from construction activities, demolition, and the addition of alternative stabilising materials to obtain optimized structures capable of providing a higher quality of the works carried out. Three types of stabilising slurry agents were selected for the experimental programme: the water-based polymer product AggreBind (AGB-BT), the Terra 3000 solution based on the Power binder, and the Earthzyme polysemantic product. Experimental studies on the use of these types of products in earthworks for stabilizing embankments, building and repairing road systems and industrial platforms have shown significant increases in strength and bearing capacity. The use of these environmentally beneficial alternative materials has led to significant reductions in construction time, decreasing total construction and maintenance costs in the short and long term.

IOT based smart street light fault detection management system

In the contemporary landscape of urbanization and technological progress, efficient resource management, particularly in energy consumption, is paramount. Street lighting stands out as a significant energy consumer in urban environments. This paper proposes a Smart Street Light Fault Detection System utilizing Internet of Things (IoT) technology, a NodeMCU microcontroller, Light Dependent Resistor (LDR), street lights, and the ThingSpeak. The system employs the NodeMCU microcontroller to monitor ambient light conditions through the LDR sensor, enabling automatic control of street lights to optimize energy usage. Furthermore, it integrates fault detection mechanisms to identify abnormalities in street light operations, such as constant light levels amidst changing environmental conditions, indicative of potential faults. Through the ThingSpeak, users can remotely monitor real-time LDR readings, receive notifications about detected faults, and take necessary actions, empowering city authorities or maintenance personnel with timely information for addressing issues and ensuring smooth infrastructure operation. This smart system offers advantages like energy efficiency, automated control, and proactive fault detection, facilitating significant energy savings, reduced maintenance costs, and enhanced sustainability in urban environments, thereby showcasing a practical implementation of IoT technology for smarter and more sustainable cities.

Модель информационно-телекоммуникационного взаимодействия между автоматизированными транспортными средствами в условиях неполного покрытия мобильными сетями

Objective: in order to improve safety, as well as optimize the path of movement in everyday life to reduce the time on the road, there are now more and more prerequisites for the introduction of highly automated and fully automated vehicles into various spheres of human life. This will optimize and improve the road system of the country as a whole, and most importantly — reduce accidents and, consequently, improve road safety. When implementing these vehicles, it is necessary to develop an algorithm for communication between different road users under different conditions and distances between objects. Methods: this study uses simulation modeling methods, the method of tabular and graphical data display, the method of factor analysis, methods of model experiment, as well as the method of expert assessments. Results: within the framework of the work, an algorithm has been developed for transmitting messages with different content and priority information between two highly automated / fully automated vehicles or a vehicle with an automated state infrastructure using various communication channels, as well as a simulation model based on it, which was created in the AnyLogic modeling environment. The use of different priorities allows you to guarantee the minimum delivery time of the most important messages containing information for vehicle management. As a result of the simulation, histograms of the probabilistic-temporal characteristics of the transmission of messages of various priorities and messages confirming their delivery were obtained using various communication channels. Practical significance: the simulation results make it possible to assess the quality and time of message delivery under specified conditions and to ensure effective transmission of information by changing the intensity and size of messages, the use of various communication channels and their speeds, and so on.

CITY TRAFFIC SIMULATION ON MICROSERVICES

Population growth and urbanization in Kazakhstan have led to significant traffic management problems in large urban areas. Initiatives such as intelligent road systems, real-time traffic information, and traffic management have been implemented to address these issues. However, congestion and delays remain as major problems. Effective traffic modeling is necessary to understand traffic patterns, identify bottlenecks, and implement effective solutions for reducing congestion. Microservice architecture has recently become a trend owing to its advantages, and the authors of this paper propose the use of microservices for urban traffic modeling to solve these problems. In this study, any moving object between two points: a car, a bicyclist, or a pedestrian – was presented as an actor. Each actor is represented as a microservice. They communicate their movements through city microservice. After sending their movements, a red line is displayed on the map, indicating their travel paths. This solution helps to simulate movement more realistically because each microservice is independent and can move randomly.

Investigating the Impact of Automated Vehicles on the Safety and Operation of Low-Speed Urban Networks

Automated vehicles (AVs) will appear on the road soon and will influence the properties of road traffic networks such as capacity and safety. While the impact of AV on traffic operations has been discussed extensively, most existing literature in this direction focuses on microscopic and mesoscopic levels. This study examines the effect of AVs on traffic flow operations and crash risks at a network scale. In addition, this study discusses the implications for designing and operating safe, low-speed urban road networks. Simulation experiments were carried out in a grid road network with AVs and human-driven vehicles operating in mixed flow conditions. To assess traffic performance, the macroscopic fundamental diagram (MFD) relationships were estimated, specifically focusing on speed-density correlations. From this analysis, it was possible to extract key traffic performance indices such as capacity and critical speed. Using time-to-collision surrogate safety measures, macroscopic safety diagrams were generated which associate the level of congestion with the potential crash conflicts among vehicles at an aggregated spatial scale. Utilizing this knowledge, a novel multiobjective optimization based on the NSGA-II algorithm was applied to identify the optimal trade-off between efficiency and safety. The presence of AVs was found to have a positive impact on the capacity, critical density, and average speed on a system level, even in low-speed scenarios. Moreover, AVs can result in increased critical density in the network, which suggests that the road system can serve more vehicles at its capacity, thus improving efficiency, while decreasing the number of conflicts. These findings are useful for both traffic planners and operators.

Evaluation of Recreational Facilities in Guandu section of Baoxiang River Basin Under the Background of Big Data: Based on POI

As the most important place for residents' daily leisure, the planning, layout and service level of urban recreational facilities are closely related to the quality of urban life. Taking national leisure as the benchmark and big data as the background, through the integration of POI data, vector building contour data and OSM road system data, combined with field survey, Tyson polygon is introduced to partition the urban recreational facilities in Guandu section of Baoxiang River Basin, build the urban recreational facilities system, and carry out the evaluation dimension from three aspects: quality, accessibility and coverage of urban recreational facilities, According to the main problems existing in this area, optimization suggestions are put forward, including improving the type of recreational facilities, adding the number of recreational facilities, paying attention to the fairness of recreational facilities and so on. This study has some limitations in the research scope, service scope and service population, but in view of the complex construction of the research scope, rich cultural types and certain representativeness, it can provide some reference for the evaluation and optimization of recreational facilities in similar regions.

CONSERVE CONVENTIONAL ENERGY RESOURCES BY SMART CITY LIGHTS

Our conventional energy resources are being rigorously used day by day. If the same practice goes on there will be no time that it will get extinct and probably, it will be all history to our future generation. Proposed methodology “CONSERVE CONVENTIONAL ENERGY RESOURCES BY SMART CITY LIGHTS”. This proposed system will consume very less electricity as the lighting of the area will be such a way that, it will work productively efficient throughout. In any city, street light is one of the major power consuming factors, most of times we see street light are on even after sunrise thus wasting lot of energy. To avoid this problem of energy wastage, this proposed methodology has automatic street light control base system with the super combination of IoT. This is less power consuming and security base system. The main perspective of this proposed system is to save the electricity. Key Words - Conventional Energy, MTBF, MTTR, Odd-Even, Display Reader, Regenerative Speed Breaker

A New Surrogate Safety Measure Considering Temporal–Spatial Proximity and Severity of Potential Collisions

Accurate identification and analysis of traffic conflicts through surrogate safety measures (SSMs) are crucial for safety evaluation in road systems. Existing SSMs for conflict identification and analysis mostly consider the temporal–spatial proximity of conflicts without taking into account the severity of potential collisions. This makes SSMs unsuitable for traffic safety evaluation in complex road environments. In order to address the shortcomings above, this study first introduces a new SSM called the Potential Conflict Risk Index (PCRI). To validate the effectiveness of PCRI, the inD dataset is adopted for conflict identification comparison between time-to-collision (TTC) and PCRI. Using PCRI, this study conducts a conflict analysis in the freeway merging areas based on the data from the Outer Ring Expressway Dataset (ORED), accounting for differences between cars and trucks. The comparative results between TTC and PCRI show that PCRI can provide a more comprehensive identification of conflicts and a more accurate identification of the moment with the highest conflict risk. The results of conflict analysis suggest that conflicts occur more frequently in situations involving trucks, and these conflicts commonly occur in closer proximity to the on-ramp at freeway merging areas. The findings from this study can improve the accuracy of conflict identification under different conflict patterns, enhancing the specificity of traffic safety measures and ultimately ensuring the safety of road systems.

Abstract 4787: Preference for multi-target stool DNA for colorectal cancer screening among Alaska Native people in rural/remote communities

Abstract Background: The Alaska Tribal Health System is working on increasing colorectal cancer (CRC) screening rates among Alaska Native people, who have the highest CRC rates in the world. Most remote Alaska Native communities are not connected to the road system, which severely limits access to screening colonoscopy. As part of a clinical trial, Alaska Native patients were offered either colonoscopy or the at-home multi-target stool DNA test (mt-sDNA; Cologuard®). Patients had never been offered mt-sDNA before and it was unknown what they would think about the new test option. Both tests were provided at no cost to patients. Methods: From April 2022 to July 2023, 194 patients who chose mt-sDNA for screening received a follow-up phone survey asking whether they were aware that they could have had colonoscopy instead, their reasons for choosing mt-sDNA, and the factors influencing their choice of mt-sDNA over colonoscopy. Patients answered the survey before receiving results of their mt-sDNA test in order to capture initial screening test preferences. Results: A total of 115 (59%) Alaska Native patients participated in the survey; 56% men and 44% women. About 70% were ages 45 to 60 years while the remaining 30% were 61 to 75 years old. The majority (80%) were aware that they had the option to undergo colonoscopy for CRC screening instead of mt-sDNA. Key themes for mt-sDNA preference included not having to travel, less time commitment, and greater convenience. Many patients expressed financial concerns arising from the costs of air travel and accommodation required to access screening colonoscopy even though the procedure itself was covered. Additionally, patients highlighted existing obligations such as childcare and work responsibilities which made the use of mt-sDNA at home more appealing. Many respondents also shared negative perceptions of colonoscopy procedure including fear, embarrassment, and discomfort as reasons why they preferred mt-sDNA instead. Conclusions: These findings demonstrate the multifaceted factors influencing the preference for at-home mt-sDNA CRC screening among Alaska Native individuals. Challenges such as limited access to medical facilities, financial burdens, and personal commitments have significant bearing on the screening decision-making process. Moreover, the emotional aspect of fear and discomfort associated with colonoscopy plays a role in shaping these preferences. CRC screening programs need to be aware of patient needs and preferences when deciding which screening methods to offer to increase screening rates and result in improved colorectal health outcomes. Citation Format: Diana Redwood. Preference for multi-target stool DNA for colorectal cancer screening among Alaska Native people in rural/remote communities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4787.

Evaluating the Impact of V2V Warning Information on Driving Behavior Modification Using Empirical Connected Vehicle Data

A connected vehicle (CV) enables vehicles to communicate not only with other vehicles but also the road infrastructure based on wireless communication technologies. A road system with CVs, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides drivers with road and traffic condition information using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed while increasing the spacing or changing lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behavior from a traffic safety point of view. This study seeks to quantitatively evaluate the effect of in-vehicle warning information using per-vehicle data (PVD) collected from freeway C-ITSs. The PVD are reproduced to extract the speed–spacing relationship and are evaluated to determine whether the warning information induces drivers to drive in a conservative way. This study reveals that the in-vehicle warning prompts drivers to increase the spacing while decreasing their speed in the majority of samples. The rate of conservative driving behavior tends to increase during the initial operation period, but no significant changes were observed after this period; that is, the reliability of in-vehicle warning information is not constant in the CV environment.

Epidemiologic analysis and mortality outcome of firearm injuries in French Guiana (2016–2019)

BackgroundFrench Guiana (FG) is a French territory located in South America with the highest rate of armed assaults. FG presents a poorly developed road system and a young and precarious population that makes the geographical and socio-demographic characteristics specific. No data concerning the firearm injury management are available in this country. Studying thesis trauma could permit to improve the management of victims. The objective of this study is to investigate the epidemiology of firearm injuries in FG, to define characteristics of the victims, and to assess factors associated with death. These identified factors could enable target primary prevention and intensification of medical management.MethodsFrom January 2016 to December 2019, we conducted a retrospective study at the Cayenne General Hospital (CGH), including all patients admitted for firearm injuries in the emergency department, the medical emergency and resuscitation service, and the forensic service. A bivariate analysis was performed to assess relevant clinical data that were entered into a logistic regression model to assess factors associated with death.ResultsA total of 871 files were analyzed concerning 340 patients included after cross-checking. Victims were mainly males (90%) and young (30 ± 11 years old). The injury occurred mainly at night (60%), in a context of assaults (83%) and with long-barreled guns (82%). Among the 290 patients managed at the CGH, 60% were hospitalized including 12% that were in the intensive care unit, 41% that required surgical treatment, and 7% that died in hospital. The overall average length of stay was 10 ± 18 days. Overall mortality (n = 71, 21%) is statistically associated with male gender (p = 0.007) and suicide context (p < 0.001). In multivariate analysis, the sites of wounds (head and neck, thorax; p < 0.001) as well as induced organ injuries (neurological, respiratory, and vascular; p < 0.005) were independent factors associated to mortality.ConclusionsThis work underlines the high incidence of ballistic trauma in FG. This mainly involves a young and male population linked to the use of long arms and assaults. Despite the geographical difficulties of the territory and the technical platform deficits (no neurosurgery, no cardiothoracic surgery, no interventional radiology), the mortality is comparable to other studies, but remains more than twice as high as in mainland France. Finally, despite a change in legislation restricting access to firearms, our results show that gunshot firearm injuries remain a major public health concern requiring greater political actions.

A comparative review study on the electrified road structures: Performances, sustainability, and prospects

The electrified road (eRoad) technology, which allows for delivering electrical power to electric vehicles (EVs) in motion, has been under active development as a novel charging solution, with a great potential to eliminate EV’s range anxiety and to reduce the battery dependency. Three promising eRoad technologies, including pantograph, conductive rail, and the inductive power transfer (IPT), have gained momentum. In this review, the following studies are performed: (1) a comparative analysis of the three eRoad technologies is made by focusing on the working principles, performances as well as technology readiness levels (TRLs). (2) From the perspective of road infrastructure, the potential structural compatibility issues are extensively discussed; the recommendations and emerging research needs, which could improve the eRoads’ service lifetime, are further presented. (3) Life cycle sustainability potential for the three eRoad solutions are comparably analyzed, emphasizing as well the importance of integrating eRoad infrastructure into the full life cycle assessment on the use of EVs for clean transport. (4) In the context of the drastic development of smart road systems, potential synergistic development of eRoad with other novel technologies is envisioned.

Exploring the relationship of transport network and land use patterns: an approach through weighted centrality assessment

ABSTRACT This study investigates the relationship between transport networks and land use patterns in the Delhi Metropolitan Area by employing a weighted centrality assessment approach. Recognizing the limitations of traditional monocentric and accessibility-based urban models, this study introduces a multimodal perspective that integrates both road and rail systems. Land use patterns are scrutinized in terms of spatial distribution of Residential, commercial, Public semipublic (PSP)/institutional, industrial and other landuse. Weighted centrality measures are assessed in terms of closeness, betweenness, and straightness, applied within a weighted framework to reflect the multimodal transport characteristics. This study introduces a path evaluation function (PEF) that incorporates transport network capacity and travel time and is calibrated with a turning parameter (α). Through multinomial logistic regression, we explore the complex relationship between weighted centrality of transport network and land use patterns. Results reveal a significant relationship, underscoring that higher centrality tends to favor commercial and public-semi-public/institutional uses, whereas centrality at lower spectrum favors the development of residential areas. This research not only advances the theoretical understanding of urban planning but also offers practical insights for policymakers, emphasizing the importance of multimodal transport considerations in urban development.