Journal of Advanced Transportation最新文献

{"title":"Application of CNN-LSTM Model for Vehicle Acceleration Prediction Using Car-following Behavior Data","authors":"Shuning Tang,&nbsp;Yajie Zou,&nbsp;Hao Zhang,&nbsp;Yue Zhang,&nbsp;Xiaoqiang Kong","doi":"10.1155/2024/2442427","DOIUrl":"10.1155/2024/2442427","url":null,"abstract":"<p>Accurate vehicle acceleration prediction is useful for developing reliable Advanced Driving Assistance Systems (ADAS) and improving road safety. The existence of driver heterogeneity magnifies the variations in acceleration data, leading to consequential impacts on the precision of vehicle acceleration prediction. However, few studies have fully considered the driver heterogeneity when predicting vehicle acceleration. To model the characteristics of individual drivers, this study first identifies the driving behavior semantics which is defined as the underlying patterns of driving behaviors. The analysis results from the coupled hidden Markov model (CHMM) are used to evaluate the driving behavior differences between different drivers by Wasserstein distance. Then the convolutional neural network (CNN) and long short-term memory (LSTM) network are applied to predict vehicle acceleration. To validate the accuracy of the proposed prediction framework, vehicle acceleration data in car-following conditions is extracted from the safety pilot model deployment (SPMD) dataset. The segmentation results indicate that the CHMM possesses a robust capacity for modeling driving behavior. The prediction results demonstrate that the proposed framework, which incorporates driver clustering before prediction, significantly improves the accuracy of predictions. And the CNN-LSTM outperforms the LSTM in predicting vehicle acceleration during car-following scenarios. The findings from this study can enhance the development of personalized functionalities within ADAS to promote its deployment, thereby improving its acceptance and safety.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Edge AI-Based Smart Intersection and Its Application for Traffic Signal Coordination: A Case Study in Pyeongtaek City, South Korea","authors":"Seongjin Lee,&nbsp;Seungeon Baek,&nbsp;Wang-Hee Woo,&nbsp;Chiwon Ahn,&nbsp;Jinwon Yoon","doi":"10.1155/2024/8999086","DOIUrl":"10.1155/2024/8999086","url":null,"abstract":"<p>Recently, smart intersections have emerged as a novel intelligent transportation system (ITS) solution that integrates traffic monitoring, optimal signal control, and even traffic safety. Although smart intersections have been prevalent in many cities, there are a few drawbacks in their practical operations. First, there are inevitable delays in transmitting and processing the video data. Second, there is still a need to develop a real-time signal control method leveraging the acquired data from smart intersections. Thus, this study aims to construct edge AI-based smart intersections and to provide their application for traffic signal coordination. To this end, we install smart intersections on three consecutive intersections of Route 45 in Pyeongtaek city, South Korea. The real-time traffic data are collected by an edge AI video analysis model which is compressed and optimized for its operation in on-site edge devices. The optimized model maintains a similar level of accuracy (93.64%), even if the size is reduced by 97.8% compared to the original. Next, we utilize the LT2 model to treat the coordination failure problem in nonpeak hours occurring unnecessary delays of the side-streets with relatively high demands. We complement some constraint conditions in order to consider the compatibility with the current legacy system. The experiment is conducted on a virtual environment of which geometry and traffic demand are configured based on the features of the study site. The numerical results conclude that the optimal offsets calculated by the LT2 model effectively manage bandwidths for multidirectional flows based on the real-time traffic demands collected from the edge AI-based smart intersections. This study contributes to serve high-resolution real-time traffic data using edge AI on smart intersections and to provide a case study for signal coordination.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Driver Behavior Pattern in Merging Area under Naturalistic Driving Conditions","authors":"Yan Li,&nbsp;Han Zhang,&nbsp;Qi Wang,&nbsp;Zijian Wang,&nbsp;Xinpeng Yao","doi":"10.1155/2024/7766164","DOIUrl":"10.1155/2024/7766164","url":null,"abstract":"<p>To reduce the risk of traffic conflicts in merging area, driver’s behavior pattern was analyzed to provide a theoretical basis for traffic control and conflict risk warning. The unmanned aerial vehicle (UAV) was used to collect the videos in two different types of merging zones: freeway interchange and service area. A vehicle tracking detection model based on YOLOv5 (the fifth version of You Only Look Once) and Deep SORT was constructed to extract traffic flow, speed, vehicle type, and driving trajectory. Acceleration/deceleration distribution and vehicle lane-changing behavior were analyzed. The influence of different vehicle models on vehicle speed and lane-changing behavior was summarized. Based on this data, the mean and standard deviation of velocity, acceleration, and variable acceleration were selected as the characteristic variables for driving style clustering. To avoid redundant information between features, principal component dimensionality reduction was performed, and the dimensionality reduction data was used for K-means and K-means++ clustering to obtain three driving styles. The results show that there are obvious differences in the driving behaviors of vehicles in different types of merging areas, and the characteristics of different areas should be fully considered when conducting traffic conflict warnings.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vertical Equity Analysis of Parking Reservation Based on the Auction Strategy","authors":"Rong Chen,&nbsp;Ge Gao,&nbsp;Fahui Pan,&nbsp;Shuo Liu,&nbsp;Xinbo Mao","doi":"10.1155/2024/1470562","DOIUrl":"10.1155/2024/1470562","url":null,"abstract":"<p>As an on-demand mobility service, parking reservations can greatly alleviate the issue of parking challenges. There are currently three primary strategies for parking reservation: first-come-first-served, permit reservation, and auction. In contrast to the first-come-first-served and permit-reserved strategies, the auction strategy uses dynamic pricing to allocate parking supplies efficiently based on the auction, which attracts more scholars for the research. However, parking reservations based on the auction process may have an inequity issue because drivers’ age, gender, income level, and location of residence fluctuate. This inequity may limit the growth of reserved parking by influencing parking drivers’ acceptance of reserved parking. But currently, very few scholars focus on the issue of reserved parking equity, and even fewer measure this nebulous and personal issue. In consideration of this, the Lorenz curve of parking reservation and the vertical equity index of parking reservation are proposed in this paper along with the calculation method for the index, which enables the problem of reserved parking vertical equity to be visualized and made concrete. The numerical experimental method is used to analyze the vertical equity of drivers with varying income levels, utilizing the Vickrey–Clarke–Groves (VCG) auction process as an example. According to the research, loss-averse drivers are more than gain-neutral and gain-seeking drivers when the income levels of the drivers using reserved parking are the same. With the increasing number of high-income drivers involved in the parking reservation, medium to low-income drivers would lose their chances of successful reservations because of their uncompetitive bid price which leads to inequity issues when the number is less than the number of parking spaces. In contrast, the vertical equity index changes more for gain-seeking drivers while being generally steady when loss-averse and gain-neutral drivers participate. For instance, when the profit and loss coefficient is 3 and 15% of drivers with high-income levels use the parking reservation platform, the vertical equity index rises from 0.09128 to 0.45434. The reference price has a moderating influence on the vertical equity index when the number of driver participants at high-income levels remains constant. In general, within a reasonable range, the higher the reference price, the more equitable the parking reservation procedure and the lower the vertical equity index.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140362663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Mandatory Lane-Changing Location Planning for CAV Based on Cell Transmission Model","authors":"Gao Gao,&nbsp;Zhengfeng Huang,&nbsp;Wei Ji,&nbsp;Pengjun Zheng","doi":"10.1155/2024/9411726","DOIUrl":"10.1155/2024/9411726","url":null,"abstract":"<p>If dedicate a lane to connected autonomous vehicle (CAV) on a multilane road, the traffic congestion and safety risks remain a major problem but in a different style. Random and disorderly mandatory lane-changing behaviour before approaching the next ramp or intersection would have a disturbing effect on the following vehicles of the traffic flow. This paper mainly establishes the optimal mandatory lane-changing location matching model for each target vehicle in the dedicated CAV lane environment. The aim is to minimizing the total travel time, which could take the disturbing effect into account. This model nests the cell transmission model (CTM) to describe vehicle running. The constraints include the relation between target CAV lane-changing cell and the corresponding behaviour start time, the updating of the flow, and occupancy for varied cells. We use the Ant Colony Optimization (ACO) algorithm to solve the problem. Through the case study of a basic two-lane road scenario in Ningbo, we acquire the convergence results based on the ACO algorithm. Our optimal lane-changing location matching scheme can save 5.9% total travel time when compared to the near-end location lane-changing scheme. We test our model by increasing the total number of upstream input vehicles with 4%, 11%, 15%, and the mandatory lane-changing vehicles with 60%, 200%, respectively. The testing results prove that out optimization method could deal with varied road traffic flow situations. Specifically, when the traffics and mandatory lane-changing vehicles increase, our method could perform better.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140363659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modification of the Clarke and Wright Algorithm with a Dynamic Savings Matrix","authors":"Jan Fikejz,&nbsp;Markéta Brázdová,&nbsp;Ľudmila Jánošíková","doi":"10.1155/2024/8753106","DOIUrl":"10.1155/2024/8753106","url":null,"abstract":"<p>The goods collection and delivery process often relates to distribution logistics problems. The task is to deliver goods from warehouses to customers under specific circumstances. Efforts to optimize the process are largely aimed at reducing overall costs of goods transportation. Among the prominent algorithms for solving the basic type of the delivery (or collection) problem, which includes a single depot and a homogeneous vehicle fleet, is the algorithm developed by Clarke and Wright in 1964. This algorithm minimizes transportation costs by maximizing the savings achieved through merging multiple routes into one. This paper primarily aims to solve the pickup and delivery problem where the goods must be delivered and empty packaging collected in a single process. The request of a customer can be routed from the depot or from another customer. Similarly, the destination of the request may be the depot or another customer. Unlike the original version of the Clarke and Wright algorithm, the initial routes are created to satisfy delivery orders, and therefore, the same customer can occur in multiple routes. Consequently, a situation may arise in which two routes containing one or more common vertices must be combined during the calculation. Furthermore, these vertices need not be the outermost vertices of the routes. This situation cannot be addressed by using the original version of the Clarke and Wright algorithm, and that is why we propose its modification. Merging routes through inner vertices means that the cost savings depend on the configurations of the routes, and therefore, they cannot be calculated a priori. Instead, the dynamic savings matrix must be used.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140323551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Impact of Automated Vehicles on the Safety and Operation of Low-Speed Urban Networks","authors":"Amir Hossein Karbasi,&nbsp;Nan Zheng,&nbsp;Steve O’Hern","doi":"10.1155/2024/3835831","DOIUrl":"10.1155/2024/3835831","url":null,"abstract":"<p>Automated vehicles (AVs) will appear on the road soon and will influence the properties of road traffic networks such as capacity and safety. While the impact of AV on traffic operations has been discussed extensively, most existing literature in this direction focuses on microscopic and mesoscopic levels. This study examines the effect of AVs on traffic flow operations and crash risks at a network scale. In addition, this study discusses the implications for designing and operating safe, low-speed urban road networks. Simulation experiments were carried out in a grid road network with AVs and human-driven vehicles operating in mixed flow conditions. To assess traffic performance, the macroscopic fundamental diagram (MFD) relationships were estimated, specifically focusing on speed-density correlations. From this analysis, it was possible to extract key traffic performance indices such as capacity and critical speed. Using time-to-collision surrogate safety measures, macroscopic safety diagrams were generated which associate the level of congestion with the potential crash conflicts among vehicles at an aggregated spatial scale. Utilizing this knowledge, a novel multiobjective optimization based on the NSGA-II algorithm was applied to identify the optimal trade-off between efficiency and safety. The presence of AVs was found to have a positive impact on the capacity, critical density, and average speed on a system level, even in low-speed scenarios. Moreover, AVs can result in increased critical density in the network, which suggests that the road system can serve more vehicles at its capacity, thus improving efficiency, while decreasing the number of conflicts. These findings are useful for both traffic planners and operators.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140315039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Factors Affecting the Severity of Injuries in Electric Two-Wheeled Vehicle Crashes with or without Violation: A Random Parametric Logit Model considering Heterogeneity of Means and Variances","authors":"Fulu Wei,&nbsp;Yuxin Han,&nbsp;Yanyong Guo,&nbsp;Yongqing Guo","doi":"10.1155/2024/7861707","DOIUrl":"10.1155/2024/7861707","url":null,"abstract":"<p>Electric two-wheeled vehicle is one of the main commuting tools in China, but they are also more likely to have violations of the road group. In order to study the effect of the presence of violation on the severity of road traffic crashes among electric two-wheeler riders, in this study, the effects of rider characteristics, road characteristics, collision characteristics, and environmental characteristics on the severity of injuries of electric two-wheeled vehicle riders were considered separately analyzed based on the data of 6403 two-wheeled electric vehicle traffic crashes in a region of Shandong Province from 2015 to 2021, and a random parametric logit model considering the heterogeneity of the mean and the variance (RP-HMV logit) was established based on the presence or absence of violation behaviors of riders, respectively, in order to explore unobserved heterogeneity. In order to test the validity of the model for modeling the injury severity of pedestrians riding electric two-wheelers, multinomial logit (MN-logit model), and random parameter logit model (RP-logit) were estimated, and the results showed that the RP-HMV logit model was significantly superior in terms of goodness of fit. The study showed that some of the factors differed somewhat between the two scenarios, such as gender, while the factors that were significant in both scenarios were &gt;60, broken pavement, street lights at night, no street lights at night, mixed motorized and nonmotorized lanes, sidewalks, other angles, no control, severe weather, and visibility &lt;200 m, where the severe weather and visibility &lt;200 m were random parameters obeying normal distributions, there is a significant difference between having street lights and no control at night in both scenarios, and the difference is significant. The results of the study can provide a reference for the development of targeted countermeasures to improve the traffic safety of electric two-wheeled vehicles in China.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140201873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Collaborative Control Framework: Achieving Emergency Vehicle Priority While Minimizing Negative Impact on Ordinary Vehicles at Signalized Intersection","authors":"Ke-jun Long,&nbsp;Zhong-gen Zhang,&nbsp;Zhi-bo Gao,&nbsp;Si-qi Zhong,&nbsp;Jian Gu","doi":"10.1155/2024/9691419","DOIUrl":"10.1155/2024/9691419","url":null,"abstract":"<p>When an emergency vehicle (EV) passes through an isolated signal intersection, it is crucial to ensure the efficient passage of the EV while minimizing the negative impact on ordinary vehicles (OVs), particularly in high-traffic flow scenarios. Given the constraints on temporal and spatial resources within intersection areas, OVs ahead of EV often face challenges in finding safe gaps for giving way, resulting in significant obstructions to OVs. This research introduces a novel collaborative control framework to jointly optimize dynamic emergency lane settings and signal schemes, considering EV priority and OVs benefits for a single signalized intersection. Firstly, we propose a dynamic emergency lane control algorithm to help obstructed EV in roadway segments by extending and reallocating temporal and spatial resources for vehicles. Then, we establish a collaborative control model considering EV priority and OVs benefits. Assigning the highest priority to the emergency priority phase, this model optimizes signal schemes to prevent interphase conflict, taking into account OVs benefits. Finally, our collaborative control framework also employs an Eco-Driving algorithm for the optimization of OV speed to reduce fuel consumption. The case study results reveal that in comparison to other baseline methods, our proposed model significantly reduces EV travel time, simultaneously lowering the travel time and fuel consumption of OVs. Sensitivity analysis of varying traffic flow scenarios reveals that, as vehicle volumes increase, our proposed method demonstrates more pronounced reductions in both EV and OV travel time. In addition, there is a progressive increase in the proportion of dynamic emergency lane utilization, with activation occurring at earlier locations.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Interval Prediction of Inbound Passenger Flow of Subway Station under Failure Events","authors":"Yichao Pu,&nbsp;Xiangdong Xu,&nbsp;Qianqi Fan,&nbsp;Shengyu Zhang,&nbsp;Jilai Chen","doi":"10.1155/2024/6833793","DOIUrl":"10.1155/2024/6833793","url":null,"abstract":"<p>Accurate forecasting of subway passenger flows is considered essential for the development of efficient train schedules. However, transport capacity constraints as well as station congestion can be caused by unexpected concerns with trains or power supply, which endanger passenger safety. Predicting passenger flows at the time of a fault is particularly challenging due to the low probability of failure and the complexity of the factors involved. In addition, deviation from the observed value may be resulted by the point-in-time prediction of passenger flow, thus affecting the efficiency of passenger flow control measures. To address this concern, a three-stage A-LSTM prediction model utilizing an attention mechanism and a double-layer LSTM (Long Short-Term Memory) neural network has been proposed. The model is used to map the impact of fault events on subway transport capacity with respect to delays onto the inbound passenger flow. By analyzing the data from the subway system in a metropolitan city of China, the range of passenger flow fluctuations in 10-minute intervals will be precisely predicted and applied to different subway stations.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}