Search Results (264)

Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs. These challenges are compounded by the dynamic nature of vehicular networks and the stringent requirements for real-time data processing and decision-making. Much research is on using novel technologies such as machine learning, blockchain, and cryptography to secure V2X communications. Our survey highlights the security challenges faced by V2X communications and assesses current ML and blockchain-based solutions, revealing significant gaps and opportunities for improvement. Specifically, our survey focuses on studies integrating ML, blockchain, and multi-access edge computing (MEC) for low latency, robust, and dynamic security in V2X networks. Based on our findings, we outline a conceptual framework that synergizes ML, blockchain, and MEC to address some of the identified security challenges. This integrated framework demonstrates the potential for real-time anomaly detection, decentralized data sharing, and enhanced system scalability. The survey concludes by identifying future research directions and outlining the remaining challenges for securing V2X communications in the face of evolving threats. Full article

The growing popularity of Personal Light Electric Vehicles (PLEVs), such as e-scooters, has revolutionized urban mobility by offering compact, cost-effective, and environmentally friendly transportation solutions. However, safety concerns, including inadequate infrastructure, poor protective measures, and high accident rates, remain critical challenges. This paper presents the design and development of an innovative self-balancing microvehicle under the H2020 LEONARDO project, which aims to address these challenges through advanced engineering and user-centric design. The vehicle combines features of monowheels and e-scooters, integrating cutting-edge technologies to enhance safety, stability, and usability. The design adheres to European regulations, including Germany’s eKFV standards, and incorporates user preferences identified through representative online surveys of 1500 PLEV users. These preferences include improved handling on uneven surfaces, enhanced signaling capabilities, and reduced instability during maneuvers. The prototype features a lightweight composite structure reinforced with carbon fibers, a high-torque motorized front wheel, and multiple speed modes tailored to different conditions, such as travel in pedestrian areas, use by novice riders, and advanced users. Braking tests demonstrate deceleration values of up to 3.5 m/s², comparable to PLEV market standards and exceeding regulatory minimums, while smooth acceleration ramps ensure rider stability and safety. Additional features, such as identification plates and weight-dependent motor control, enhance compliance with local traffic rules and prevent misuse. The vehicle’s design also addresses common safety concerns, such as curb navigation and signaling, by incorporating large-diameter wheels, increased ground clearance, and electrically operated direction indicators. Future upgrades include the addition of a second rear wheel for enhanced stability, skateboard-like rear axle modifications for improved maneuverability, and hybrid supercapacitors to minimize fire risks and extend battery life. With its focus on safety, regulatory compliance, and rider-friendly innovations, this microvehicle represents a significant advancement in promoting safe and sustainable urban mobility. Full article

The world is facing a state of “global boiling,” causing damage to various sectors. Developing pedestrian systems is a key to mitigating it, especially in tropical and humid cities where the climate discourages walking and increases the need for shaded walkways. Recent research shows a lack of data and in-depth studies on the built environment promoting walkability in such climates, creating a research gap this study aims to fill. Using Singapore as a case study, four locations—Marina Bay, Orchard Road, Boat Quay, and Chinatown—were surveyed and analyzed through visual decoding and questionnaires. Results show that natural light is the most frequently observed and important element in pedestrian pathway design in tropical and humid areas. Trees and sidewalks are also important in creating a walk-friendly environment. Green spaces significantly influence the desire to walk, though no clear positive outcomes were found. Additionally, “Other Emotions” negatively affect the decision to walk, suggesting these should be avoided in future pedestrian pathway designs to encourage walking. Full article

Walking-friendly cities not only promote health and environmental benefits but also play crucial roles in urban development and local economic revitalization. Typically, pedestrian interviews and surveys are used to evaluate walkability. However, these methods can be costly to implement at scale, as they demand considerable time and resources. To address the limitations in current methods for evaluating pedestrian pathways, we propose a novel approach utilizing wearable sensors and deep learning. This new method provides benefits in terms of efficiency and cost-effectiveness while ensuring a more objective and consistent evaluation of sidewalk surfaces. In the proposed method, we used wearable accelerometers to capture participants’ acceleration along the vertical (V), anterior-posterior ($AP$), and medio-lateral ($ML$) axes. This data is then transformed into the frequency domain using Fast Fourier Transform (FFT), a Kalman filter, a low-pass filter, and a moving average filter. A deep learning model is subsequently utilized to classify the conditions of the sidewalk surfaces using this transformed data. The experimental results indicate that the proposed model achieves a notable accuracy rate of 95.17%. Full article

Urban sustainability is closely linked to walkability, as it impacts social interaction, public health, and economic development. In megacities like Riyadh, where automobiles dominate mobility, the development of pedestrian infrastructure remains inadequate. An online survey was conducted through public sampling to evaluate walking conditions in central Riyadh’s commercial districts. The 302 participants evaluated 49 critical walkability indicators to determine their significance and satisfaction with the current conditions. Gap analysis and a displeasure measurement framework identified pedestrian challenges. Participants acknowledged the importance of walkability aspects but expressed strong dissatisfaction with existing conditions. Key barriers to pedestrian comfort included inadequate facilities, environmental discomfort, weak safety measures, and cultural driving preferences. The study highlighted crucial walkability issues requiring improvement, such as public toilets, shaded pathways, air quality, and pedestrian-friendly infrastructure. The findings emphasize the need for targeted policy interventions in Riyadh’s commercial districts to enhance pedestrian accessibility and comfort, to promote urban sustainability through improved walkability. This study offers a methodological advancement by combining Relative Importance Index, gap analysis, and a novel disgruntlement measurement framework to assess walkability. The use of 49 Delphi-derived indicators contextualized within a GCC megacity adds a unique perspective to urban sustainability research. The findings inform both local policy and global urban studies by demonstrating how culturally and climatically adaptive walkability metrics can guide equitable, data-driven interventions. Full article

Ancient fairs in China were designated as commercial zones with fixed stalls that had emerged from commodity exchange demands and socio-cultural factors such as clan systems and gentry intervention, exhibiting dual commercial–communal characteristics. Several ancient fairs in Shenzhen have been retained, including Gongming Ancient Fair, which maintains its original spatial configuration adjacent to industrial zones and urban villages, attracting a high concentration of migrant workers. Survey results show that 85% of Gongming residents demand public space renovations, citing inadequacy of the spaces to support public activities. Given the intrinsic link between public spaces and public activities, fostering their positive interaction is crucial for enhancing urban vitality. However, existing studies predominantly focus on the physical environment and neglect activity-driven optimization perspectives. This study first employed social network analysis (SNA) to construct two networks of Gongming Ancient Fair, using the software Ucinet 6.755, including a public space network based on spatial connectivity and a public activity network based on pedestrian flow. Second, the networks’ structural characteristics were analyzed using seven metrics: node degree, density, betweenness centrality, betweenness centralization, clustering coefficient, average path length, and small-world property. Discrepancies between the networks were quantified through betweenness centrality comparisons, with field surveys and interviews identifying causal factors including seasonal product limitations, spatial constraints, inadequate supporting facilities, and substandard management. Based on the survey data and analytical results, the key renovation nodes were categorized into three types: high-control-capacity nodes, high-expectation nodes, and culturally distinctive nodes. Finally, three optimization strategies are proposed. This study integrates sociological perspectives into ancient fair revitalization, addressing gaps in activity-driven spatial research. Full article

Decades of migration and refugee influxes have driven Amman’s rapid urban growth, yet newer neighborhoods increasingly grapple with fragmented social cohesion. This study examines whether walkable design can strengthen community bonds, focusing on Deir Ghbar, a car-centric district in West Amman. Using GIS and mixed-methods analysis, we assess how walkability metrics (residential density, street connectivity, land-use mix, and retail density) correlate with sense of community. The results reveal that street connectivity and residential density enhance social cohesion, while land-use mix exhibits no significant effect. High-density, compact neighborhoods foster neighborly interactions, but major roads disrupt these connections. A critical mismatch emerges between quantitative land-use metrics and resident experiences, highlighting the need to integrate spatial data with community insights. Amman’s zoning policies, particularly the stark contrast between affluent low-density Zones A/B and underserved high-density Zones C/D, perpetuate socio-spatial segregation—a central critique of this study. We urge the Greater Amman Municipality’s 2025 Master Plan to prioritize mixed-density zoning, pedestrian retrofits (e.g., traffic calming and sidewalk upgrades), and equitable access to amenities. This study provides a replicable GIS and survey-based framework to address urban socio-spatial divides, aligning with SDG 11 for inclusive cities. It advocates for mixed-density zoning and pedestrian-first interventions in Amman’s Master Plan. By integrating a GIS with social surveys, this study offers a replicable model for addressing socio-spatial divides in cities facing displacement and inequality. Full article

Unmanned systems provide significant prospects for improving the efficiency of electromagnetic geophysical exploration in mineral prospecting and geological mapping, as they can significantly increase the productivity of field surveys by accelerating the movement of the measuring system along the site, as well as minimizing problems in cases where the pedestrian walkability of the site is a challenge. Lightweight and cheap UAV systems with a take-off weight in the low tens of kilograms are unable to carry a powerful current source; therefore, semi-airborne systems with a ground transmitter (an ungrounded loop or grounded at the ends of the line) and a measuring system towed on a UAV are becoming more and more widespread. This paper presents the results for a new generation of semi-airborne technology SibGIS UAV-TEMs belonging to the “line-loop” type and capable of realizing the transient/time-domain (TEM) electromagnetics method used for studying a uranium object of the paleovalley type. Objects of this type are characterized by a low resistivity of the ore zone located in relatively high-resistivity host rocks and, from the position of the geoelectric structure, can be considered a good benchmark for assessing the capabilities of different electrical exploration technologies in general. The aeromobile part of the geophysical system created is implemented on the basis of a hexacopter carrying a measuring system with an inductive sensor, an analog of a 50 × 50 m loop, an 18-bit ADC with satellite synchronization, and a transmitter. The ground part consists of a galvanically grounded supply line and a current source with a transmitter creating multipolar pulses of quasi-DC current in the line. The survey is carried out with a terrain drape based on a satellite digital terrain model. The article presents the results obtained from the electromagnetic soundings in comparison with the reference (drilled) profile, convincingly proving the high efficiency of UAV-TEM. This approach to pre-processing UAV–electrospecting data is described with the aim of improving data quality by taking into account the movement and swaying of the measuring system’s sensor. On the basis of the real data obtained, the sensitivity of the created semi-airborne system was modeled by solving a direct problem in the class of 3D models, which allowed us to evaluate the effectiveness of the method in relation to other geological cases. Full article

While campus-built environments constitute critical determinants of educational outcomes, empirical research remains scarce regarding how campus pedestrian-oriented design influences academic performance through underlying psycho-behavioral pathways. To address this research gap, we collected research data through a questionnaire survey conducted at a university in Yantai, China, and applied path analysis within structural equation modeling (SEM) to investigate the linkage of perceived campus walkability with academic performance and untangle the mediating effects of walking activity, social capital, and mental health on this linkage. Key findings revealed that perceived campus walkability exerts a significant total effect on academic performance only through its indirect effect. Social capital and mental health significantly mediate the relationship between perceived campus walkability and academic performance, while walking activity has a marginal impact on this relationship. Moreover, grades significantly promote academic performance, while BMI significantly inhibits academic performance. Targeted interventions to enhance academic performance were proposed when translating findings into design protocols. Full article

As a core application of V2X technology, vehicle–road collaboration enables dynamic coordination among road users (pedestrians, vehicles), infrastructure, and networks through real-time, omnidirectional information exchange. This system represents a pivotal solution for addressing critical transportation challenges, including traffic congestion, safety risks, and environmental sustainability. Its experimental teaching, as the core linkage of theoretical innovation and technical verification, is of vital importance to the cultivation of intelligent transportation talents. Compared with traditional experimental teaching, the V2X semi-physical simulation platform effectively reduces capital investment, completely eliminates the safety risks of actual road tests, and emulates the real traffic environment. To verify the teaching effectiveness of this platform, based on the OBE concept and the BOPPPS teaching method, this study constructed an experimental curriculum framework driven by learning goals and conducted an empirical analysis taking global path planning as an example. Teaching evaluation adopts a combination of subjective and objective methods: Subjective evaluation is conducted through questionnaire surveys, and the proportion of those satisfied with the teaching effect reached more than 80%. The objective evaluation consists of eight performance indicators before class, during class and after class. Through reliability analysis, the performance of students in the observation group was shown to increase by 17.39% compared with that in the control group. The results show that the experimental teaching mode based on the V2X semi-physical simulation platform significantly improves the teaching effectiveness of the vehicle–road collaboration course compared with traditional methods. Full article

Improving the pedestrian environment around metro stations and enhancing walkability are important for the daily travel and life quality of passengers. By reviewing existing studies, we summarized nine walkability elements and eventually refined them into 18 quantifiable research indicators. Walkability elements such as street enclosure, number of lanes, and tree canopy coverage were quantified through field surveys and passenger perception data. A stepwise regression analysis identified key influencing factors for nine walkability dimensions. Based on the correlation coefficients, factor assignments, and constants, a composite walkability index formula was established to evaluate pedestrian routes near four Shanghai metro stations. The results show that the proportion of sidewalks covered by a tree canopy, the number of lanes, street enclosures, and the transparency of the ground-floor building facade are the most important factors affecting the walkability of the pedestrian environment. In this study, we calculated the scores of each road section, compared the walking facilities and walking distance of different stations, and finally proposed relevant strategies for improving the walking environment. Full article

The Gobi Wall is a 321 km-long structure made of earth, stone, and wood, located in the Gobi highland desert of Mongolia. It is the least understood section of the medieval wall system that extends from China into Mongolia. This study aims to determine its builders, purpose, and chronology. Additionally, we seek to better understand the ecological implications of constructing such an extensive system of walls, trenches, garrisons, and fortresses in the remote and harsh environment of the Gobi Desert. Our field expedition combined remote sensing, pedestrian surveys, and targeted excavations at key sites. The results indicate that the garrison walls and main long wall were primarily constructed using rammed earth, with wood and stone reinforcements. Excavations of garrisons uncovered evidence of long-term occupation, including artifacts spanning from 2nd c. BCE to 19th c. CE. According to our findings, the main construction and usage phase of the wall and its associated structures occurred throughout the Xi Xia dynasty (1038–1227 CE), a period characterized by advanced frontier defense systems and significant geopolitical shifts. This study challenges the perception of such structures as being purely defensive, revealing the Gobi Wall’s multifunctional role as an imperial tool for demarcating boundaries, managing populations and resources, and consolidating territorial control. Furthermore, our spatial and ecological analysis demonstrates that the distribution of local resources, such as water and wood, was critical in determining the route of the wall and the placement of associated garrisons and forts. Other geographic factors, including the location of mountain passes and the spread of sand dunes, were strategically utilized to enhance the effectiveness of the wall system. The results of this study reshape our understanding of medieval Inner Asian imperial infrastructure and its lasting impact on geopolitical landscapes. By integrating historical and archeological evidence with geographical analysis of the locations of garrisons and fortifications, we underscore the Xi Xia kingdom’s strategic emphasis on regulating trade, securing transportation routes, and monitoring frontier movement. Full article

Currently, within the scope of research on the protection and adaptive reuse of industrial heritage, there is a relative paucity of quantitative studies focusing on pedestrian vitality at the micro-street level. Qingdao Textile Valley, a quintessential example of a creative industrial park, necessitates an in-depth examination of how street vitality influences operational efficacy. This study employs AnyLogic simulation software and spatial syntax Depthmap software, complemented by field survey data, to conduct a comprehensive simulation analysis of pedestrian density and spatial accessibility along the park’s core-periphery roadways. Based on the issues identified through this analysis, several improvement strategies are proposed, particularly increasing the density of the pedestrian network and improving network connectivity. The effectiveness of these strategies was validated through simulation. The research findings indicate that the optimized plan led to an increase in pedestrian traffic on the peripheral streets of the park, mitigated congestion on core roads, and substantially enhanced the overall vitality of the street network. This research offers valuable methodological references and practical insights for developing creative industrial parks and the adaptive reuse of industrial heritage in Qingdao and other regions. Full article

The rapid growth of e-bikes has intensified traffic conflicts on slow-moving shared paths in China. This study analyzed traffic safety of pedestrians and non-motorized vehicles and examined the factors influencing conflict severity utilizing traffic conflict techniques. Video-based surveys were conducted on six shared paths in Shenzhen, and conflict trajectory was extracted by Petrack software (Version 0.8). The minimum Time to Collision and Yaw Rate Ratio were selected as conflict indicators. Fuzzy c-means clustering was employed to classify conflicts into three severity levels: 579 potential conflicts, 435 minor conflicts, and 150 serious conflicts. Nineteen feature variables related to road environment, traffic operation, conflict sample information, and conflict behavior were considered. A SMOTE random forest model was constructed to explore critical influencing factors systematically. The results identified ten key factors affecting conflict severity. The increase in conflict severity is associated with the rise in pedestrian proportion and flow, and the decrease in e-bike proportion and flow. Male participants and pedestrians are more likely to engage in serious conflicts, while illegal lane occupation and wrong-way travel further elevate the severity level. These findings can provide references for traffic engineers and planners to enhance the safety management of shared paths and contribute to sustainable non-motorized transport. Full article

The flock formation of bird species is a crucial behavioral process that enables them to colonize urban areas. However, the factors influencing the structure and composition of ground-feeding bird flocks have not yet been analyzed. This study aimed to relate flock characteristics, including size, number, species richness, and composition, to local and landscape factors in the urban parks of Buenos Aires City, Argentina. Surveys of flocks were conducted in 16 parks during the breeding season, covering both mono-specific and mixed-species flocks. Flock numbers were positively correlated with tree, lawn, and bare ground cover but negatively associated with raptor presence in the parks. Flock species richness declined with increased noise and pedestrian traffic but rose in parks where raptors were present. The composition of species in flocks was linked to tree cover, noise, and the presence of raptors. While the Rock Dove (Columba livia) and the Rufous-bellied Thrush (Turdus rufiventris) were more abundant in parks with greater tree cover, the Eared Dove (Zenaida auriculata) and the Monk Parakeet (Myiopsitta monachus) showed increased abundance in more open parks. Zenaida auriculata and Columba livia experienced a decline in abundance in parks where raptors were present. Our findings indicate that resource availability and predation risk are crucial factors shaping flock formation in urban parks. Full article