Journal of Advanced Transportation最新文献

{"title":"Impact of Driver Age and Behavior on the Effectiveness of ADAS in Cyclist Safety on Rural Roads: A Simulator Study","authors":"Nouman Usama,&nbsp;Ahmed M. Al-Wathinani,&nbsp;Krzysztof Goniewicz,&nbsp;Sami Babar","doi":"10.1155/atr/5862995","DOIUrl":"https://doi.org/10.1155/atr/5862995","url":null,"abstract":"<div>\u0000 <p>The increasing use of bicycles highlights the need for enhanced road safety measures, particularly in interactions between vehicles and cyclists on rural mixed-traffic roads. This study investigates the impact of driver age and behavior on the effectiveness of advanced driver assistance systems (ADASs) in improving cyclist safety. Utilizing a driving simulator, the study analyzed the overtaking maneuvers of 300 male participants, categorized by aggressive and passive driving styles, across three age groups: young (20–34), middle-aged (35–49), and older (50–64) drivers. Results showed that younger drivers exhibited more dynamic and erratic behaviors, with significant variations in lateral control (LC) and time to danger (TTD). Specifically, younger driver’s TTD increased by 20% on average, while older drivers maintained consistent caution with a 10% improvement in LC. Aggressive drivers showed a negligible change in behavior, whereas passive drivers demonstrated a 25% improvement in TTD and a 15% enhancement in LC when using ADAS. The findings suggest that tailored ADAS features are necessary to address the diverse responses of different driver demographics. Future ADAS development should incorporate real-world testing, consider psychological factors, and conduct longitudinal studies to optimize safety outcomes. This study provides critical insights for enhancing the design and implementation of ADAS to protect vulnerable road users such as cyclists.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5862995","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Riding Through the Pandemic: Unveiling Motorcycle Crash Trends Amidst Three Years of the COVID-19 Crisis","authors":"Shahrin Islam,&nbsp;Armana Sabiha Huq,&nbsp;Sadab Ishraq Khan,&nbsp;Sabah Hossain Iqra","doi":"10.1155/atr/8853271","DOIUrl":"https://doi.org/10.1155/atr/8853271","url":null,"abstract":"<div>\u0000 <p>Bangladesh has a significant prevalence of motorcycle usage accompanied by a correspondingly high incidence of motorcycle-related fatalities. The COVID-19 crisis has brought additional challenges to road safety in Bangladesh because of containment strategies and restrictions. The impacts of the pandemic on motorcycle-related road traffic crashes, injuries, and fatalities in Bangladesh are investigated in this study using ARIMA time series analysis. Data spanning 86 months (January 2016 to February 2023) were collected from the Accident Research Institute (ARI), which compiles newspaper-based data serving as an alternative source of information on crashes encompassing both pre-COVID (January 2016 to February 2020) and COVID-19 periods (March 2020 to February 2023). Three COVID-19 waves were demonstrated, with the first wave showing a significant decrease in crashes, injuries, and fatalities due to a government-imposed lockdown. During the second wave, crashes and fatalities approached predicted values, while injuries remained lower than anticipated. The third wave witnessed a sudden drop, followed by a sharp rise in all three variables. Box and whisker plot analysis confirmed the disparities between observed and predicted values, with observed data being lower. These results demonstrate the significant impact that COVID-19 containment strategies have had on trends in motorcycle crashes. By understanding these patterns, policymakers and road safety authorities can develop adaptive interventions to mitigate motorcycle-related incidents during pandemics or similar crises. The study provides a data-driven foundation for designing context-specific policies, adjusting law enforcement strategies, and efficiently allocating resources to enhance road safety under varying conditions.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8853271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Safety of Run-Off-the-Road Vehicles on Vertical and Horizontal Curves With the Foreslope Using Multiple Regression Analysis","authors":"Ali Abdi Kordani,&nbsp;Ali Attari,&nbsp;Seyed Mohsen Hosseinian","doi":"10.1155/atr/1239908","DOIUrl":"https://doi.org/10.1155/atr/1239908","url":null,"abstract":"<div>\u0000 <p>The run-off-the-road (ROR) vehicle from the curves, as one of the most accident-prone sections of roads, has always received special attention. Centrifugal force on vehicles and human error are the two main causes of accidents in these areas, which will eventually lead to overturning or sliding of vehicles. Based on previous research, few studies have been conducted on the influence of friction factors over horizontal and vertical curves with foreslopes for ROR vehicles considering various factors such as vehicle type, speed, departure angle, and foreslope slope through the vehicle dynamics simulation. Thus, in this research, the safety of ROR vehicles on curves over the foreslope was investigated from the perspective of the vehicle dynamics simulation. Finally, by simulation outputs for each of the vehicles used (Sedan, SUV, and truck), a multiple regression modeling was presented to examine the side friction factor of horizontal and vertical curves with a foreslope. The results showed that for horizontal curves, the first third of the beginning of the curve was the most dangerous part when vehicles deviated from the curves. Also, in vertical curves, the departure angle of 15 and 25° for vehicles, and foreslopes of 1: 3 and 1: 4, had the greatest effect on the overturning points of the vehicles. In addition, trucks had fewer friction factors at all speeds in comparison with Sedans and SUVs, and consequently, they had lower skidding potential in all specified conditions. On the other hand, an increase in skidding potential was observed in all tests on steeper foreslopes, which was caused by increasing the side friction factors and decreasing the margin of safety of vehicles on these types of foreslopes. Finally, based on the multiple regression analysis, the best model was presented to predict the side friction factor for various vehicles on horizontal and vertical curves with a foreslope, and it was indicated that the obtained models had a good correlation for all the test conditions. The study’s findings can be applied to improve road safety by modifying road geometry, adjusting foreslope angles, enhancing pavement friction, and informing vehicle design and driver education programs.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1239908","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-Layer Dynamic Optimization Model for Carbon-Conscious Transport Mode Allocation","authors":"Jing Gan,&nbsp;Dongmei Yan,&nbsp;Linheng Li","doi":"10.1155/atr/2160394","DOIUrl":"https://doi.org/10.1155/atr/2160394","url":null,"abstract":"<div>\u0000 <p>Within the framework of China’s “Dual Carbon” strategy, numerous cities have articulated visions and objectives for optimizing the travel structure of transport to further urban sustainable development goals. A critical challenge lies in minimizing CO₂ emissions from road networks while meeting diverse transport demands. However, at present the mode shares are set arbitrarily and may not be realistically achievable. When government officials establish travel structure targets, they may not adequately consider the intricate balance between residents’ travel demands and low-carbon development objectives. To address this issue, this paper presents a dual-layer optimal allocation model for transport modes, which simultaneously addresses travel demand management and carbon emission control. The upper-layer model evaluates carbon emissions with the help of speed-dependent emission factors for various transport modes, and the lower-layer model leverages the logit Stochastic User Equilibrium (logitSUE) model to yield the velocities of road segments under a diverse array of travel structures. A sophisticated fusion algorithm, integrating the Dial_MSA algorithm with a genetic algorithm (GA), is developed to solve the model. The proposed model and algorithm are tested on a large-scale real network and show its robustness and scalability. The optimal travel structure derived from this study can provide a theoretical foundation and empirical support for policymakers and urban planners in setting transport infrastructure goals and strategies.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2160394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban Traffic Accident Frequency Modeling: An Improved Spatial Matrix Construction Method","authors":"Jing Gan,&nbsp;Qing Su,&nbsp;Linheng Li,&nbsp;Yanni Ju,&nbsp;Linchao Li","doi":"10.1155/atr/1923889","DOIUrl":"https://doi.org/10.1155/atr/1923889","url":null,"abstract":"<div>\u0000 <p>Spatial correlation is a critical factor in establishing accurate traffic accident analysis models, with the choice of measurement method significantly influencing the results. Despite the central role of roads as the primary conduit for traffic flow and a direct exposure variable in accidents, their impact on spatial correlation in accident analysis has not been fully explored. This study introduces an innovative spatial correlation matrix, termed the road matrix, which incorporates shared road lengths between grids to enhance accident prediction accuracy. The model examines the relationship between traffic accidents and various predictor variables, including land use, road networks, and public transportation facilities. Compared to traditional spatial correlation methods such as the rook and queen matrices, the road matrix provides a more precise characterization of spatial dependencies and significantly improves accident frequency estimation. Notably, the application of the road matrix within a conditional autoregressive (CAR) model uncovers additional significant contributors to traffic accidents, such as the number of interchanges and the length of nonexpress arterial roads. These findings offer new insights and practical recommendations for urban planning and traffic safety management. The study provides a valuable reference for future research on traffic accident frequencies and offers guidance for the design of more effective traffic safety measures.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1923889","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Simulation-Based Multiple-Objective Optimization for Designing K-Stacks Autonomous Valet Parking Lots","authors":"Chu Zhang,&nbsp;Shaopei Xue,&nbsp;Jiayi Chen,&nbsp;Jun Chen","doi":"10.1155/atr/9322602","DOIUrl":"https://doi.org/10.1155/atr/9322602","url":null,"abstract":"<div>\u0000 <p>Autonomous valet parking has drawn wide attention these years. The k-stacks layout, known for its ability to increase parking capacity by stacking vehicles more compactly, is of great practicality among all possible layout patterns. Although this layout can increase the capacity of a parking lot, it generates relocations, which let vehicles move additional distances and influence the lot’s peak hour service ability. For the sake of optimizing them all simultaneously, we propose a simulation-based multiple-objective optimization (SMOO) and use NSGA II to solve the problem, obtaining candidate solutions. Then, a nondominated sorting based on cumulative advantages (NSCA) method is put forward to select the most robust solution from all candidates, considering different demand scenarios. K-stacks parking lots optimized by the SMOO can provide 36%–59% more parking spaces than a traditional parking lot while keeping other evaluations fine. In addition, we specify high-demand and low-demand scenarios and discuss the impact of different aspect ratios. It is recommended to use k-stacks layouts when a lot’s length is close to its width.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9322602","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reinforcement Learning–Based Ramp Metering Strategy Considering Queue Management","authors":"Yang Yang,&nbsp;Shixuan Yu,&nbsp;Fan Ding,&nbsp;Yu Han","doi":"10.1155/atr/2838943","DOIUrl":"https://doi.org/10.1155/atr/2838943","url":null,"abstract":"<div>\u0000 <p>This paper introduces an action replacement module for reinforcement learning (RL)–based ramp metering to address the issue of ramp queue spillback during the training process. Ramp queue spillback leads to significant impacts on the traffic efficiency of adjacent road networks, making it a critical concern in ramp control. Existing RL approaches often employ ramp states as reward functions to encourage agents to learn strategies that avoid queue overflow. However, due to the trial-and-error nature of RL, these methods frequently generate actions that cause queue spillback during training, posing challenges for real-time online training in real-world applications. To overcome this limitation, the proposed action replacement module utilizes the store-and-forward model to estimate a lower bound for ramp metering rates. By identifying and replacing actions that fail to meet this constraint, the strategy effectively prevents queue spillback. In addition, penalties are imposed on replaced actions to guide the agent in learning effective and practical control policies. The proposed method is evaluated in both single-ramp and multiramp scenarios. Experimental results demonstrate that the agent can learn the queue spillback prevention strategies, and nearly eliminate ramp queue spillback without compromising control performance.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2838943","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means","authors":"Dengzhong Wang,&nbsp;Jiayu Zhou,&nbsp;Gen Li,&nbsp;Haigen Min,&nbsp;Chenming Jiang,&nbsp;Linjun Lu","doi":"10.1155/atr/5635494","DOIUrl":"https://doi.org/10.1155/atr/5635494","url":null,"abstract":"<div>\u0000 <p>The hit-and-run caused a delay in medical assistance to the victim and posed a significant threat to the safety of drivers in road tunnels. This study investigates the potential factors contributing to drivers’ hit-and-run violations in river-crossing tunnels. This paper built three models (the logit model, the random parameter logit model, and the random parameter logit model with heterogeneity in means) based on a dataset consisting of crashes reported in thirteen river-crossing tunnels in Shanghai, China. Potential contributors from five aspects (offending drivers, vehicle conditions, tunnel characteristics, environmental conditions, and crash information) were explored. Results showed that the random parameter logit model with heterogeneity in means produced the highest fitting accuracy among the three models. Eight important variables (nighttime, single-vehicle, multi-vehicle, two-wheeled vehicle, passenger car, heavy goods vehicle, rear-end, and short tunnel) were found to affect hit-and-run violations significantly. The research has highlighted that nighttime and short tunnel increase the likelihood of hit-and-run and other variables are the opposite. The results of this study could provide useful information for the development of interventions to improve the level of safety in tunnels and reduce the rate of hit-and-run offenses.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5635494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion","authors":"Tursun Mamat,&nbsp;Abdukeram Dolkun,&nbsp;Runchang He,&nbsp;Yonghui Zhang,&nbsp;Zulipapar Nigat,&nbsp;Hanchen Du","doi":"10.1155/atr/7427074","DOIUrl":"https://doi.org/10.1155/atr/7427074","url":null,"abstract":"<div>\u0000 <p>Pavement distress is one of the most serious and prevalent diseases in pavement road detection. However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. Consequently, we propose the shuffle attention for you only look once version eight (SA-YOLOv8) model, which is based on an enhanced framework. Initially, we establish the required dataset and classify images proportionally based on their states. Subsequently, we conduct comparative testing against the results of the original model, analyzing issues such as the oversight of shallow and small cracks, truncation in the recognition of single-instance long cracks, and imprecise detection. We devise an improved detection approach based on YOLOv8. This method incorporates a small target detection layer to optimize the receptive field range, aiming to focus on identifying shallow and small cracks. Simultaneously, the Shuffle Attention mechanism and the transplanted spatial pyramid pooling-fast (SPP-F) reuse structure are introduced in the feature extraction network to enhance the model’s attention to detection targets. This augmentation improves the fusion of features for shallow small targets and overall and partial features of long cracks, thereby alleviating the precision of the model in crack detection. The experimental results demonstrate a stepwise improvement in the model’s mean average precision (mAP) with each enhancement to the original network. Initially, adding a small object detection layer increased the mAP by 3.4 percentage points, raising it to 68.2%. Subsequently, incorporating the spatial attention (SA) module resulted in a more substantial improvement, boosting the mAP by 8.7 percentage points to 73.5%. Finally, the addition of the transplanted SPP-F module further enhanced accuracy, increasing the mAP by 0.7 percentage points from the previous stage, thus achieving a final mAP of 74.2%. Overall, these modifications resulted in a total improvement of 9.4 percentage points in mAP compared to the original model. In conclusion, the proposed SA-YOLOv8s model effectively supports the automated recognition of asphalt road surface cracks, demonstrating applicability in practical scenarios. The recognition performance is notably favorable, demonstrating robustness in complex environments.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7427074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Traffic Signal Setting at Urban Junctions and Fundamental Diagram: A Before–After Study","authors":"Borja Alonso,&nbsp;Salvatore Del Giudice,&nbsp;Giuseppe Musolino,&nbsp;Antonino Vitetta","doi":"10.1155/atr/3475935","DOIUrl":"https://doi.org/10.1155/atr/3475935","url":null,"abstract":"<div>\u0000 <p>The paper analyses the effects of modifying traffic light regulations at urban road junctions, focussing on the ratio between green time and cycle time, as a function of vehicular traffic variables (flows, density and speed) on the links. The analyses are conducted in an urban setting using a before-and-after approach, employing traffic data detected by loop detectors and traffic light control parameters (the ratio between green time and cycle time) that were actually implemented. The data pertain to a central street in the city of Santander (Spain), collected during several significant weeks in different periods corresponding to varying demands for mobility. In the context of existing studies on the flow–density diagram, a function is estimated that considers the ratio between green time and cycle time as the independent variable and link capacity as the dependent variable. The analysis at the link level may be extended in the future to the network level by incorporating the network fundamental diagram into the traffic signal setting design problem.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/3475935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}