Trajectory planning for traffic safety with dynamic ethical risk adjustment.

Skid resistance is crucial for the safety of road users; however, it has received little consideration during the asphalt mixture design stage. This study focuses on improving the frictional performance of asphalt mixtures comprising low-friction (e.g., limestone) aggregates. The main objective of this study is to identify the mix parameters that primarily control asphalt mixtures’ frictional performance. To achieve this objective, an experimental plan was devised and executed to quantify various material-related (binder grade and aggregate type), mix design-related (binder content, aggregate gradation, asphalt mixture type, and aggregate types in gradation portions), and construction-related (e.g., compaction effort) parameters on the frictional performance of mixtures. The mixture’s frictional performance was evaluated using a three-wheel polishing device (TWPD) and a dynamic friction tester (DFT) by varying the material, mix design, and construction parameters. The influence of binder grade, binder content, aggregate gradation, asphalt mixture type, and air void percentage on the mixture’s frictional performance was found to be negligible, while the aggregate type showed a profound effect on the mixture’s frictional performance. A more detailed study on the portion of the gradation contributing the most to frictional performance revealed that the aggregate passing through the 4.75 mm sieve and retained on the 2.36 mm sieve is the principal controlling parameter, due to its higher surface area compared to coarser aggregates. Although aggregates smaller than 2.36 mm sieve size have a higher surface area, their effect on frictional performance is less significant due to their loss during the polishing process, their relatively small proportion in the mix, and their embedment into the binder matrix.

P-AEB performance and limiting factors for superior-rated P-AEB systems based on simulations of real-world pedestrian crashes: A simulation study on the VIPA database.

Road safety is a critical public health and economic concern in India, leading to a significant loss of human lives and a decline in economic productivity. Rapid urbanization, increased vehicle usage, and inadequate adherence to traffic regulations have further intensified the problem. This conceptual paper explores how road safety challenges can be transformed into opportunities for economic growth, with a specific focus on Gandhinagar city. The study examines existing road safety conditions, including behavioural issues such as negligence and non-compliance with traffic rules, infrastructural limitations like inadequate pedestrian facilities, and gaps in policy implementation. The paper emphasizes the crucial role of education and awareness programmes in shaping responsible road user behaviour. It also highlights the importance of effective governance, enforcement of traffic laws, and community participation in improving road safety outcomes. By adopting an integrated approach that combines enforcement, education, engineering, and emergency care, the study suggests that road accidents can be significantly reduced. Furthermore, the paper argues that improved road safety contributes to economic growth by reducing healthcare costs, enhancing workforce productivity, and promoting efficient transportation systems. Safer roads not only save lives but also support sustainable urban development and attract investment. The study concludes with practical recommendations for policymakers, educational institutions, and communities to strengthen road safety measures and create a safer, more economically sustainable urban environment.

INTRODUCTION: As cities gradually begin integrating autonomous vehicles into existing transport systems, it becomes essential to assess their potential impacts on traffic dynamics and safety in a comprehensive and systematic manner — particularly through tools that can anticipate impacts before actual on-road deployment. OBJECTIVES: This paper aims to develop a data-driven and modular framework to evaluate the integration of autonomous mobility solutions in mixed traffic conditions. METHODS: A data-driven approach combining sensor data collected during autonomous shuttle trials with video-based behavioural analysis of road users and calibrated traffic microsimulation is employed to perform ex-ante assessment of different deployment scenarios. RESULTS: The framework enables the evaluation of the impacts of autonomous mobility solutions on traffic performance and safety, providing insights across multiple scenarios. CONCLUSION: The framework supports informed decision-making and enhances the understanding of how autonomous mobility can be effectively integrated into urban environments.

ABSTRACT The rapid development of Vehicle-to-Vehicle (V2V) communication raises concerns about potential health risks regarding radiofrequency electromagnetic fields (RF-EMF). This study evaluates thermal effects in a 5.9 GHz V2V exposure scenario using COMSOL Multiphysics® to construct a novel numerical model that encompasses a vehicle with a V2V antenna and road users at different positions. Through quantitative analysis of the specific absorption rate averaged over 10 g tissue (SAR10 g), under worst-case exposure scenarios for road users in closest proximity to the antenna, we observed temperature increases in both superficial sensitive organs and deep tissues. The results reveal that when the antenna operates at 1 W input power for 30 minutes, superficial tissues exhibit the highest thermal sensitivity, with skin tissue showing a maximum temperature rise of 0.047°C, followed by ocular tissues (0.025°C). Deeper tissues display progressively reduced thermal effects, including the central nervous system (gray matter: 0.02°C, white matter: 0.018°C) and visceral organs (gastrointestinal: 0.013°C). All computed temperature rises are significantly below the safety limits set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), confirming no thermal health risk in this V2V scenario. This work also provides a methodological foundation for electromagnetic safety assessments in connected transportation environments.

Emerging evidence suggests that extreme heat elevates road-traffic injuries, undermining international road safety efforts like Vision Zero as global warming intensifies. However, the mechanisms underlying heat-related crashes remain poorly understood, with limited research linking heat exposure to specific crash types that may be driven by heat-induced unsafe road behaviors. Here, we analyzed temperature data and police-reported crash records-including detailed crash scene information-from 177 California cities (2012-2023) using a time-stratified case-crossover design, examining variations in risk by crash type and contextual factors. We observed that extreme heat was associated with elevated risks of fatal and severe crashes, with risk increasing monotonically at higher temperatures. Associations were more pronounced in high-conflict settings such as intersections; among vulnerable road users, including bicyclists and pedestrians; and in crashes involving driver-related violations common to these contexts, such as improper turning and failure to yield to pedestrians, and instances where pedestrians or bicyclists were themselves the at-fault parties. These patterns are consistent with the possibility that extreme heat may increase crash risk by influencing road behavior, reinforcing behavioral mechanisms as a plausible pathway. They also highlight potential disparities in road safety, particularly affecting individuals who continue to walk or cycle and remain mobile during extreme heat, such as low-income individuals without access to climate-controlled vehicles. Urban planning and transportation policies should integrate climate resilience into road safety strategies, such as shaded intersections, cooling interventions for vulnerable road users, enhanced right-of-way protections during extreme heat, and institutional recognition of heat as a situational risk factor.

Poor visibility contributes to nighttime accidents at highway intersections, especially in developing countries where vehicles mix with vulnerable road users (VRUs) such as pedestrians and cyclists. Unlike downtown intersections with traffic signals and ambient lighting, rural intersections have no signals and minimal ambient light, forcing drivers to rely on roadway lighting for hazard recognition. Improving illumination arrangements can significantly reduce the likelihood of crashes. However, there are significant differences in the effects of illumination on drivers’ visual search ability at different vehicle speeds. Therefore, the collaborative matching of illumination and speed limits can effectively improve traffic efficiency and reduce the probability of nighttime accidents. In this paper, we establish a collaborative optimization model of illumination and speed limits at rural highway intersections that considers drivers’ visual recognition of VRUs. We then design an experiment with illuminance, vehicle speed, and VRU type/location as control variables to collect recognition distances, and finally analyze their effects to calculate speed limits under different illuminances. Results indicate that pedestrians and cyclists appearing from the left side are recognized 24.73% and 15.79% earlier than those from the right, suggesting that VRUs from the right side are more vulnerable. Additionally, the safety benefit of improving illumination on increasing speed limits gradually diminishes as illuminance rises. Therefore, determining the most suitable illumination and speed limit configuration requires a comprehensive evaluation of the cost–benefit relationship between lighting investments and the gains resulting from higher speed limits.

With the continuous increase in urban road usage, various cracks often appear on the road surface, which may pose a threat to traffic safety. Presently, road inspection is still primarily limited to manual methods, which suffer from low efficiency, limited accuracy, and subjective judgment. To enhance the efficiency of road crack detection, the paper designs an innovative detection technology that fuses U-net and ResNeXt networks. The results showed that the proposed method achieved superior detection performance on horizontal and vertical cracks. While its recognition and classification capabilities for other types of cracks and block cracks need improvement, it still demonstrated significant overall classification performance. Compared with numerous detection methods, the performance of the proposed method was notably superior. The peak memory efficiency of the video memory of this method is controlled within 2.1GB. This indicates that in practical applications, the proposed method can provide accurate information on road surface cracks, making it easier for workers to take corresponding remedial measures. In summary, the proposed urban road surface crack detection method can be integrated into intelligent transportation systems, providing technical support for real-time monitoring and predictive maintenance of road conditions.

Abstract Limiting carbon emissions from the transportation sector has become increasingly critical due to the intensification of global climate change. Congestion pricing strategy has received widespread attention as a measure to reduce emissions. However, the pricing affects both traffic conditions and environmental outcomes, which in turn influences the effectiveness of such pricing strategies. To capture these endogenous interactions and derive effective pricing strategy designs, this study proposes a bi-level programming emission reduction congestion pricing model (ERCM), considering the endogenous relationship between pricing strategies, road network operating conditions and vehicle emission factors. The upper-level model represents traffic managers optimizing emission reduction pricing strategies, while the lower-level model represents road users and establishes a congestion-pricing-based user equilibrium model (CSUEM) that incorporates emission reduction charges. In order to distinguish the power sources of different vehicles, gasoline emission factors were calibrated using Motor Vehicle Emission Simulator (MOVES) -based speed bins, while electric vehicle factors were estimated via a power-energy conversion model. A case study conducted in Dongguan, China, evaluated the carbon reduction effects of various congestion pricing strategies. The results indicate that, compared to a no-pricing scenario, the proposed pricing scheme reduced total CO₂ emissions by 3.01% across the city and by 13.06% within the pricing zone, respectively, within the congestion pricing demonstration area. This study provides both a theoretical foundation and empirical evidence for urban traffic managers to formulate effective carbon emission reduction pricing strategies.

Under growing urbanization and environmental challenges, sustainable urban mobility has become a critical priority for cities worldwide. Public Transport (PT) systems play a central role in reducing car dependency, lowering emissions, increasing network capacity, and promoting more equitable and efficient access to urban spaces for all users. Hence, the present paper aims to investigate PT preferences in the city of Larissa, Greece. Larissa is a medium-sized city currently serviced only by buses, and is currently focusing on the potential introduction of a new tram system to operate in parallel with existing bus services. To this end, a SP survey was designed and implemented, resulting in 972 observations that were collected for further statistical analysis. Survey results show a slight preference for trams over buses, with 54.63% selecting the tram and 45.37% favoring the buses. Moreover, a context-based segmentation pipeline was established using PCA, DBSCAN and t-SNE algorithms, aiding the visualization of existing clusters for transport choice approaches. Afterwards, a series of mixed logit models was applied, and statistically significant variables influencing mode choice were determined. The study also examines Value of Time (VoT) metrics and finds that respondents assign lower VoTs to trams than to buses, especially in out-of-vehicle segments of the journey, such as waiting and walking, and therefore consider trams as more pleasant and less burdensome. The findings also indicate that passengers place a high value on the quality of infrastructure related to access and waiting times, underlining the need to improve the overall user experience beyond the vehicle itself. In summary, the present research offers valuable insights into how the introduction of a tram system could possibly reshape PT usage patterns when compared with the legacy existing bus services.

This paper develops a shock-absorbing asphalt mixture for pedestrian pavements that mitigates the impact of normal walking on pedestrians’ bodies by incorporating crumb rubber from recycled tires to produce a soft mixture. This aims to reduce injuries to vulnerable road users, enable the rethinking of urban pavement designs, and address the major challenges facing societies, ultimately achieving more sustainable, resilient, and safer cities. To promote land sustainability, the designed asphalt mixture should be pervious, allowing water to infiltrate into the underlying soil. The development of the asphalt mixture followed an experimental methodology that involved formulating asphalt mixtures with conventional bitumen, polymer-modified bitumen, and bituminous emulsion. The shock-absorbing capability was evaluated by measuring the deformation of the asphalt mixture over time in response to a falling weight from a Light Falling Weight Deflectometer. Permeability capabilities were assessed through the permeability test. Subsequently, the asphalt mixture was characterized according to its macrotexture, friction, air void content, rutting resistance, and stiffness to assess its suitability as a walking surface material. Results indicate that increasing rubber content enhances deformation capacity and improves cushioning but reduces stiffness. Among the solutions, mixtures with polymer-modified bitumen and intermediate rubber content achieved the balance between impact attenuation and mechanical performance.

Transformer-based multi-agent traffic simulation for autonomous vehicle testing in shared urban road segments.

Low-volume rural roads (LVRRs) form the backbone of India’s rural mobility network, yet the sustainability of their maintenance remains largely unaddressed in existing rating systems. This study develops SPATRR – a Sustainable Pavement Assessment Tool for Rural Roads – to evaluate the sustainability performance of maintenance activities using a structured, certifiable, and locally contextual approach. A comprehensive indicator set was constructed through literature review, field observations, and stakeholder consultations. Importance rankings were derived using the relative importance index and reliability validated using Cronbach’s alpha (α > 0.90). Category weights were generated through the analytic hierarchy process (AHP) with expert input from agencies, contractors, practitioners, and road users. The final SPATRR tool includes eight sustainability categories and 41 indicators, supported by an AHP-weighted scoring model and a four-tier sustainability certification scheme. A real-world case study demonstrates the applicability of the tool and highlights improvement pathways. SPATRR offers a simple, transparent, and context-specific assessment mechanism that can support decision makers in prioritising sustainable maintenance of LVRRs.

In about one-quarter of low-speed, truck-involved, vulnerable road user fatalities in the U.S., a driver’s direct vision was impaired. A driver has direct vision of an object outside the vehicle when it can be seen without the aid of mirrors or camera displays. Vehicles vary in how near drivers can see outside the vehicle to the front and to the side. This paper reports a first-in-the-U.S. effort with the U.S. Department of Transportation Volpe Center, the Boston Public Health Commission, and the Boston Transportation Department to assess the direct vision for vehicles used for Boston’s Schools, Fire, and Public Works Departments. The research team quantitatively measured direct vision in 21 vehicles using both a manual approach and a camera-based approach. Using these methods, this paper proposes a direct vision rating system that the City of Boston and other fleets can incorporate into procurement. The proposed system includes front and passenger five-star ratings based on the distance at which a child or adult would be visible directly in front of or to the passenger side of the vehicle, calibrated to federally and locally defined intersection geometric standards. A five-star vehicle enables drivers to see children in the crosswalk and children on bicycles in a buffered bicycle lane. In 11 of the 21 vehicles, drivers whose vehicle was stopped at the stop bar before a crosswalk at an intersection could not adequately see a child in the crosswalk in front or an adult on a bicycle on the side.

<div>While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information.</div> <div>Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in awareness provided by the notification and the usefulness of the assistance. After the driving test was completed, we acquired a subjective evaluation on annoyance acceptability and a self-report of participants’ road usage frequency at notified locations in daily life, as well as questionnaires on their driving style and workload sensitivity. We found that the effectiveness of verbal notifications increased by conveying uncertainty risks at visible locations and by using interrogative sentences or expressions of risk target perspective, although it decreased as a function of age. Our model showed strong performance in predicting positive ratings for the notifications, but this was not the case for negative ratings. We identified individual characteristics and the risk factor of uncertainty as important features in our model.</div> <div>In conclusion, the findings provide an important reference for understanding the early notification of predictive risk and constructing a numerical model for the implementation of assistance systems in vehicles and nomadic devices.</div>

Comparative safety evaluation of ADAS-Equipped electric and gasoline vehicles using real-world crash data.

Pedestrian and cyclist perceptions of interactions with fully automated buses.

Problem, research strategy, and findings Pedestrian and bicyclist deaths now account for nearly one in five traffic fatalities in the United States. They continue to rise even as peer nations have reduced deaths dramatically. We examined 222 miles of arterial highways in Florida to understand the nature of the unique risk confronted by vulnerable road users in the United States. We found that land use decisions—particularly the siting of groceries, pharmacies, gas stations, and fast-food outlets—are strongly associated with the death and injury of vulnerable road users. These household-sustaining uses generate exposure in locations fundamentally incompatible with vulnerable road user safety, activating latent hazards embedded into infrastructure design. We discuss in this article how land use practice differs from that of Europe, and how these differences explain the differences in safety outcomes. We conclude by developing tools for estimating the magnitude of this risk during the project development process and by outlining strategies for enhancing land use and transportation practices to better account for the land use–road safety connection. Takeaway for practice Meaningful progress toward Vision Zero in the United States requires acknowledging that land use decisions—not just street design—are a primary driver of the elevated risk faced by vulnerable road users. Development codes that encourage household-sustaining uses to locate along arterial corridors create predictable and preventable exposure in environments where safety is structurally unattainable without simultaneous changes to the street’s design and function. Addressing this risk demands a shift in planning practice: revising zoning and site-planning standards to explicitly account for safety, redirecting high-risk uses away from arterial corridors, and applying analytic tools that identify and mitigate latent land use hazards during the planning and project development process.

Exploring novel surrogate safety indicators measuring conflict riskiness and severity: a case study in Sacramento, United States.