Road Design Research Articles

Enhancing people’s walking preferences in street design through generative artificial intelligence and crowdsourcing surveys: The case of Tokyo

The emerging generative artificial intelligence (generative AI) model, Stable Diffusion, is increasingly recognized as a promising tool for efficiently translating public preferences and ideas into spatial design representations. At the same time, deep learning techniques and crowdsourcing methods have enabled the large-scale collection of public walking preference data. This study introduces an innovative approach that leverages the Stable Diffusion model, combined with extensive public walking preference data, to create a workflow for generating revitalized street scenes aimed at enhancing subjective walking preferences. Compared to existing GAN-based methods, the approach used in this study is more efficient to train and generates more realistic and controllable outputs. The approach was tested and validated using data from Tokyo’s Setagaya ward, confirming its effectiveness. This workflow represents a significant advancement in street design and redevelopment, delivering practical value and innovation by equipping designers and planners with rapid visual insights in the early design stages. Additionally, it fosters democratic urban design by utilizing crowdsourced data as training input for generative AI models.

IoT-Powered Flexible Road Dividers for Accident Impact Reduction

In road safety, accidents involving collisions with road dividers often result in severe injuries and fatalities. To mitigate the impact of such accidents, this study focuses on designing and testing flexible road dividers to reduce collision severity and real-time alerting through IoT Integration. A novel flexible road divider incorporates advanced materials like expanded polystyrene separators and barriers (EPS), and specific engineering principles like design, shape, and flexibility make dividers capable of absorbing and dissipating kinetic energy after impact. The system is engineered to be durable, resilient, and cost-effective, making it a viable solution for enhancing road safety in the Indian transportation system. Detailed measurements of forces, deformation, and energy absorption are recorded to quantify the system's effectiveness in reducing the severity of accidents. The findings of this research have implications for road design and infrastructure and offer valuable insights into the development of safer transportation systems with a real-time collision alert mechanism using vibration sensors. Ultimately, adopting flexible road dividers with enhanced impact-reducing properties could represent a significant step forward in safeguarding the lives of road users and reducing the economic burden associated with road accidents. The new prototype discussed in this is anticipated to enhance the energy-absorbing capacity of concrete barriers and lessen the effect of cars beside concrete barriers – a unit weight of 1650 kg/m3.

Strength and microstructural characteristics of sand soils stabilized with paper sludge Ash-Based geopolymer

Stabilizing and improving weak and poorly graded soils in road construction projects is a widely used and highly interesting technology. This research study utilizes paper sludge ash (PSA) residues as a geopolymer waste material to stabilize loose and poorly graded sands (SP), improve mechanical properties, and support sustainable pavement development. Geotechnical tests using the unconfined compressive strength test (UCS), Young’s modulus (Es), California bearing ratio (CBR), and a direct shear test (DST) assessed the performance and strength development of geopolymer-stabilized soil. The stabilized soil’s microstructure and chemical mineralogy were also examined using SEM and XRD. Additionally, a laboratory testing apparatus was designed and developed to assess the permanent strain behavior of subgrade soil and geopolymer-stabilized soil layers under cyclic loading. The research analysed variables including curing duration (1, 3, and 7 days), PSA concentration (5, 10, and 15%), and the type and concentration of alkaline activators (NaOH or Na₂SiO₃). Soil samples treated with PSA and Na₂SiO₃ geopolymers showed higher UCS, Es, and CBR values, leading to improved strength from increased N-A-S-H and C-A-S-H gel formation among sand soil particles. On the contrary, the NaOH solution enhanced the strength parameter of geopolymer-stabilized soil samples. The results showed that geopolymer-stabilized soil significantly improved its resistance to permanent deformation after applying loads. The mineralogical examination also shows a high concentration of lime and cubic aluminate, which may be active cementitious pozzolanic material. This research reflects that PSA has promising potential to stabilize sandy soil and improve the design and maintenance of roads and infrastructure in areas with weak soils.

A Study on the Effect of Conductive Particles on the Performance of Road-Suitable Barium Titanate/Polyvinylidene Fluoride Composite Materials.

The design of piezoelectric roads is one of the future directions of smart roads. In order to ensure the environmentally friendly and long-lasting use of piezoelectric road materials, lead-free piezoelectric ceramics (barium titanate), polymer piezoelectric materials (polyvinylidene fluoride), and conductive particles (conductive carbon black and graphene) were used to prepare composite piezoelectric materials. The electrical performance was studied by the conductivity, dielectric properties, and piezoelectric properties of the composite materials. Then, the mechanical properties of the composite material were investigated by load compression tests. Finally, the microstructure of the composite materials was studied. The results showed that as the amount of conductive particles increased, the electrical performance was improved. However, further addition of conductive particles led to a decline in the electrical performance. The addition of conductive particles had a minimal effect on the mechanical properties of composite materials. The composite material met road use requirements. The overall structure of the composite materials was compact, with a clear wrapping effect of the polymer, and good interface compatibility. The addition of conductive carbon black and graphene had no significant impact on the structure of the composite materials.

Biomechanically driven street environment design for urban regeneration

This paper proposes a biomechanics-based street environment optimization scheme for urban regeneration, integrating biomechanical principles into urban street designs to enhance pedestrian comfort, safety, and overall health. The approach optimizes sidewalks, barrier-free facilities, public seating, and traffic flow lines, focusing on the biomechanical needs of pedestrians, including gait stability, joint stress, and muscle load. To further validate the effectiveness of the proposed approach, additional empirical studies were conducted in diverse urban settings with varying pedestrian densities, surface types, and weather conditions. Simulations were also carried out to predict the scalability and robustness of the design strategies under real-world conditions, ensuring their applicability for future large-scale urban regeneration projects. This practical assessment provides a foundational framework for future urban regeneration projects, particularly in enhancing accessibility and safety for vulnerable groups such as the elderly and people with mobility impairments. Furthermore, these findings contribute to the development of smart cities by integrating biomechanics into urban planning, fostering more sustainable and health-conscious public spaces.

Does road environment aesthetics influence risky driving behavior of autonomous vehicles? An evaluation on road readiness using explainable machine learning and random parameters multinomial logit with heterogeneity

Does road environment aesthetics influence risky driving behavior of autonomous vehicles? An evaluation on road readiness using explainable machine learning and random parameters multinomial logit with heterogeneity

Examining non-linear relationships between campus layout, street design, and walking activity

Examining non-linear relationships between campus layout, street design, and walking activity

Roughness prediction of asphalt pavement using FGM(1,1-sin) model optimized by swarm intelligence and Markov chain.

Roughness prediction of asphalt pavement using FGM(1,1-sin) model optimized by swarm intelligence and Markov chain.

Investigating the safety influence path of right-turn configurations on vehicle-pedestrian conflict risk at signalized intersections.

Investigating the safety influence path of right-turn configurations on vehicle-pedestrian conflict risk at signalized intersections.

Research on Teaching Reform of Road Survey and Design Course under Digital Background

Research on Teaching Reform of Road Survey and Design Course under Digital Background

Settlement Calculation Method of Lakeside Soft Soil Foundations Based on the Statistical Analysis of Physical and Mechanical Indexes

The understanding of the settlement deformation law of lakeside soft soil foundations and the definition of a reasonable settlement calculation formula are essential when setting the basis for road design and construction. The present study focuses on the application of a statistical analysis of physical and mechanical indexes to study the settlement law of the lakeside soft soil foundations, with the Jinan-Weishan expressway in China as the study case. With this aim, a correlation among the natural void ratio, compressive modulus, natural water content, density, and liquid index of the lakeside soft soil layer was performed. An improved method for settlement calculation was proposed by combining the calculation formula for predicting settlement for soft soil foundations in the lakeside area with the layer-wise summation method. Laboratory tests were performed to verify its validity. The results evidence a positive correlation of the natural void ratio with the water content and the liquid index, as well as the compressive modulus with the density. The natural void ratio reveals a negative correlation with the density, as well as the compressive modulus with the natural water content and the liquid index. Both the theoretical calculations and the experimental results illustrate that the settlement initially increases rapidly with time, then increases slowly until eventually reaching a stable state after about the 190th day. The settlement deviation between experimental findings and theoretical calculations after 190 days was less than 10%. This supports the suitability of the improved method of determining e–p curves based on density.

Improving Road Safety: Assessing Curve Geometry of Road Network in Rivers State University Main Campus, Port Harcourt, Nigeria

The insertion of curves in road designs is of utmost importance for the safety of the driver and commuters. It provides a smooth transition when the roadway changes direction and also ensures that proper and safe sight distances are maintained for the speed which the road will accommodate. Road curves can be horizontal or vertical, each serving a crucial role in safe navigation. The study investigate the curve parameters of selected road network within the main campus of Rivers State University, Nkpolu Oroworukwo, Port Harcourt, Rivers State. The study utilizes the quantitative data collection approach which is based on ground survey data acquisition. Field data were acquired with the use of the Total Station (Kolida KTS 440L) instrument. The Field data were reduced to obtain horizontal and vertical angles and further processing and map production were carried out using specialized surveying and mapping software. Accuracies of approximately 1:16,000 and 0.008 were achieved for traversing and levelling operations respectively and it is within the degree of allowable minimum accuracy of 1:5000 for traversing as stipulated by the Surveyors Council of Nigeria. Findings from the study revealed that the sections of the road network under study covers a total length and width of approximately 2.93km and 7.00m respectively. The parameters for 5 horizontal curves and 6 vertical curves were determined and will be useful to the University Estate and Works Department in ascertaining if the curves parameters noted were in line with the design prior to construction works.

Walkable Street Design for Congested Urban Areas: Pedestrian's Perception and Attitude

Many people concerned with pedestrian safety and "walkability" cares about these issues because they feel that walking is good exercise or that walkable places are more attractive or that walking is better for the environment than driving. These are all valid arguments and may convince some of those reading this article that walkability is important. But from user point of view, that is, streets where walking is safe and enjoyable, that people are drawn to visit on foot, and where fast and extensive car traffic is not the #1 priority. Streets where walking is safe and easy are streets where businesses usually thrive. Streetscape enhancements add value to an area and are associated with higher rents and the attraction of new businesses. In addition there is good evidence to show that improving walking and cycling environments raises private property values by significant amounts. So the current study focuses on the design of walkable streets for congested areas. While doing so, the focus is also kept on user’s perception and attitude towards walkable streets.

Urban street canyon morphology and its effect on climate-responsive outdoor thermal environment in severe cold regions: a case study of Hohhot, China.

Climate-responsive urban design requires a thorough understanding of how street canyon morphology affects the thermal environment, especially for the severe cold regions in Northern China. Individual geometric parameters often overlook other geometric characteristics of real street canyons, making it impossible to establish precise correlations between morphological parameters and thermal environments. This study investigates the influence of six key geometric parameters on thermal conditions in Hohhot, China. Mobile measurements revealed a significant quadratic relationship between the asymmetrical aspect ratio and mean air temperature at 12:00 (R2 = 0.91654). We also found that the aspect ratio, the complementary index closing ratio, and the smoothness rate were negatively correlated with mean air temperature at various times, while height variation positively influenced air temperature (R2 = 0.67946). Furthermore, the building coverage ratio in adjacent areas significantly impacted mean radiant intensity (R2 = 0.700 and 0.679 at 11:00 and 12:00, respectively, p < 0.05). Multiple regression analyses underscored the collective impact of these parameters on thermal conditions. These findings provide valuable insights for optimizing street canyon design to improve thermal comfort, thereby contributing to more effective climate-responsive urban planning.

Street Geometry Factors Influencing Outdoor Pedestrian Thermal Comfort in a Historic District

As China’s urbanization progresses, the urban heat island (UHI) effect has become more pronounced, impacting the health of residents and the activity intentions of visitors within historic urban areas. This study focuses on the historic district of the Three Lanes and Seven Alleys Tourist Area (SFQX) in Fuzhou, where simulations were conducted on four representative streets across various times during a typical summer meteorological day. Typological methods were employed to simplify neighborhood modeling, and Phoenics software was utilized to simulate the neighborhood’s wind environment and the outdoor pedestrian thermal comfort index. Aspect ratio (AR), sky view factor (SVF), air velocity (Va), and universal thermal climate index (UTCI) values at specific locations were collected for statistical analysis. The findings reveal that: (1) the N–S orientation exhibits more significant correlations between Va, the UTCI, and street geometry compared to the E–W orientation; (2) the relationship between SVF and the UTCI fluctuates with time; (3) areas with higher AR values, such as medium and deep canyons, offer better thermal comfort for outdoor pedestrians; and (4) at 8:00, the UTCI and wind speed show minimal correlations with street geometry and direction, being predominantly influenced by objective climatic factors. These insights are expected to significantly inform the geometric design and planning of streets in Fuzhou’s historic districts, aiming to create more comfortable outdoor environments for inhabitants and visitors alike.

Research on Urban Road Design Method in South China Based on Climate Zoning

The urban climate in South China is marked by high complexity and substantial precipitation, posing significant challenges to road performance. This study focuses on the importance of precise climate zoning for urban roads in South China and the application of performance grade (PG) asphalt grading technology to enhance pavement durability. Meteorological data from multiple stations across the region were analyzed to identify key climatic indicators. Using spatial interpolation methods and fuzzy c-means clustering, urban roads were classified into five distinct climate zones. Zone I has the highest temperature; Zone II experiences the lowest temperature, necessitating attention to low-temperature pavement cracking; Zone III exhibits greater temperature variability, requiring consideration of both low-temperature cracking and water stability; Zone IV demonstrates relatively stable climatic conditions; and Zone V receives the highest precipitation, demanding a focus on water stability in pavement design. Trend analysis indicates increasing precipitation across all zones except Zone II and a general rise in minimum temperatures, suggesting a diminishing influence of low-temperature conditions. By integrating the Strategic Highway Research Program temperature conversion method and PG classification technology, this study provides asphalt grade recommendations tailored to each climate zone, addressing diverse environmental challenges and optimizing pavement performance.

An Eye-Tracking Study on Exploring Children’s Visual Attention to Streetscape Elements

Urban street spaces play a crucial role in children’s daily commuting and social activities. Therefore, the design of these spaces must give more consideration to children’s perceptual preferences. Traditional street landscape perception studies often rely on subjective analysis, which lacks objective, data-driven insights. This study overcomes this limitation by using eye-tracking technology to evaluate children’s preferences more scientifically. We collected eye-tracking data from 57 children aged 6–12 as they naturally viewed 30 images depicting school commuting environments. Data analysis revealed that the proportions of landscape elements in different street types influenced the visual perception characteristics of children in this age group. On well-maintained main and secondary roads, elements such as minibikes, people, plants, and grass attracted significant visual attention from children. In contrast, commercial streets and residential streets, characterized by greater diversity in landscape elements, elicited more frequent gazes. Children’s eye-tracking behaviors were particularly influenced by vibrant elements like walls, plants, cars, signboards, minibikes, and trade. Furthermore, due to the developmental immaturity of children’s visual systems, no significant gender differences were observed in visual perception. Understanding children’s visual landscape preferences provides a new perspective for researching the sustainable development of child-friendly cities at the community level. These findings offer valuable insights for optimizing the design of child-friendly streets.

The spatial heterogeneity effects of street environmental factors on the preference for sports and leisure cycling paths across different street types

Current research has not fully explored how streetscape elements in different street spaces affect long-distance, high-speed recreational cycling. As a result, the applicability of existing findings across different street environments is limited, hindering their practical value in urban street design. To address this issue, this study focuses on the core urban area of Hangzhou, China. Streets are functionally categorized based on Point of Interest (POI) data, and Strava crowdsourced data are used to obtain cycling activity trajectories. Streetscape indicators that may influence recreational cycling paths are calculated using streetscape imagery and machine learning techniques. Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models are employed to identify significant streetscape indicators that impact cycling, and spatial heterogeneity in cycling route preferences is analyzed at different scales across street types. The results indicate that: (1) Recreational cyclists prefer mixed-use and scenic streets, particularly those along river corridors or within and around large green spaces. (2) Among the streetscape indicators, safety isolation degree has the most positive impact, followed by facility diversity, motorization level, and green view index, all of which positively influence cycling traffic to varying extents. Interface transparency and disorder negatively affect cycling, with transparency having the strongest influence. (3) In mixed-use, commercial, and life service streets, the effect of streetscape indicators on cycling route preferences varies by spatial location, exhibiting both promoting and inhibiting effects. In scenic streets, streetscape indicators show stronger positive or negative impacts, while in industrial streets, their influence is weaker. Based on these findings, the study proposes strategies for creating cycling-friendly environments tailored to different street types. The results validate and extend existing theories on the interaction between street environments and cycling behavior, offering valuable insights for diagnosing problems and implementing effective interventions to promote cycling-friendly environments, thus contributing to urban health, equity, and sustainable development.

The Role of Autopsy in the Forensic and Clinical Evaluation of Head Trauma and Traumatic Brain Injury in Road Traffic Accidents: A Review of the Literature.

Road traffic accidents (RTAs) are a leading cause of morbidity and mortality worldwide, frequently resulting in traumatic brain injuries (TBIs), skull fractures, and spinal injuries. This manuscript examines the forensic aspects of head trauma caused by RTAs, focusing on the role of autopsy and imaging in diagnosing and characterizing injuries. Through a systematic review of the literature, the study highlights the mechanisms of injury, including high-speed collisions, whiplash, and pedestrian impacts, and explores their pathological consequences, such as subarachnoid hemorrhage, intracranial hemorrhage, and diffuse axonal injury. The differentiation between traumatic and non-traumatic conditions, such as aneurysmal subarachnoid hemorrhage, is emphasized to ensure accurate clinical and forensic assessments. Advances in imaging technologies, particularly virtopsy, are discussed for their potential in non-invasive documentation and analysis of head injuries, while limitations of this approach are acknowledged. Furthermore, the manuscript underscores the importance of preventive measures, including helmet and seatbelt use, vehicle safety innovations, and improved road design, in reducing the incidence and severity of RTAs. By integrating clinical, forensic, and preventive perspectives, this study provides a comprehensive framework for understanding and addressing the burden of head trauma related to RTAs.

Shared dockless e-scooter and metro station built environment: its nonlinear relationship using random forest modeling

ABSTRACT Determinants of varying adoption rates of e-scooters across areas remain unclear, particularly in built environments near metro stations. Methodologically, linear regression modelings have limitations in capturing complex relationships between the built environment of metro stations and e-scooter ridership. This research uses random forest modeling to examine the nonlinear relationship between the built environment, focusing on station area and shared dockless e-scooter trips. By emphasizing metro stations as critical nodes for multimodal connectivity, the research identifies built environment characteristics – such as activity density, population density, compact index score, and job-housing balance – significantly influence higher e-scooter usage. Though less significant, street design variables like road and intersection densities show nonlinear effects. This study confirms that development factors in metro station areas are more substantial than street design factors in promoting e-scooter ridership, highlighting the need to optimize transit-oriented development and multimodal transportation strategies near metro stations.