A. Nourbakhshrezaei , M. Jadidi , M. R. Delavar , B. Moshiri
{"title":"A novel context-aware system to improve driver’s field of view in urban traffic networks","authors":"A. Nourbakhshrezaei , M. Jadidi , M. R. Delavar , B. Moshiri","doi":"10.1080/15472450.2022.2130290","DOIUrl":"10.1080/15472450.2022.2130290","url":null,"abstract":"<div><p>Principal objectives of the Intelligent Transportation Systems (ITS) are to improve traffic safety, facilitate informed traffic decision making, and enhance quality of life and services in a smart traffic environment. Vehicle crashes at urban traffic intersections are among the rudimentary sources of injuries and fatalities in the cities. According to the report of the World Health Organization (WHO), in every 25 seconds, one vulnerable road-user is being killed by a vehicle crash. Therefore, it is necessary to take a novel and smart approach for improving the safety and reducing vehicle crashes. This leads to a contextual perception and spatial awareness of driver to increase security and safety for the driver, vehicle, and road users. Autonomous vehicles collects the information from the environment through equipped sensors on the vehicle such as camera, laser, radar, and Global Navigation Satellite Systems (GNSS). The main challenge arises when the person or objects are located beyond the driver’s Field of View (FOV) and cannot be detected by embedded sensors on the vehicles. This paper proposes an Advanced Driver Assistance System (ADAS) to increase the safety on road intersections by taking advantage of existing infrastructures (e.g road camera) being used for traffic control. The aim of this research is improving the driver’s FOV using a computer vision approach (e.g background subtraction algorithm) and Location Based Service (LBS). The case study results at Tehran metropolitan demonstrate the reduction in traffic collision risk and improvement of pedestrian safety using the proposed system.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 297-312"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85306183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chunwei Yang , Junfeng Zhang , Xuhao Gui , Zihan Peng , Bin Wang
{"title":"A data-driven method for flight time estimation based on air traffic pattern identification and prediction","authors":"Chunwei Yang , Junfeng Zhang , Xuhao Gui , Zihan Peng , Bin Wang","doi":"10.1080/15472450.2022.2130693","DOIUrl":"10.1080/15472450.2022.2130693","url":null,"abstract":"<div><p>Flight time estimation is expected to play a crucial role in predicting the Estimated Time of Arrival, which could help detect conflicts and manage arrivals. This paper proposes a novel data-driven method for flight time estimation based on arrival pattern identification and prediction. Firstly, a trajectory clustering algorithm is employed to group the arrival trajectories into different arrival patterns. A new trajectory representation technique is presented during the clustering process for better-describing arrival patterns. Secondly, we extract features from radar tracks for data-driven flight time estimation. These features consist of current states related, historical information related, traffic situation related, and environmental conditions related features. Furthermore, the permutation feature importance and recursive feature elimination method are adopted to reduce feature dimensions. Then, we develop three widely used tree-based models to estimate the flight time for each arrival pattern. We also propose an image-based flight patterns prediction method to classify each new arrival aircraft into the corresponding arrival pattern for actual operation. Finally, we take the Guangzhou arrival operation as a case to validate our proposed method. The results indicate that our proposed method could improve flight time estimating accuracy. Besides, through the data-driven strategy, we could also find several significant factors affecting the flight time within the Terminal Maneuvering Area.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 352-371"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85178366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sepehr G. Dehkordi , Grégoire S. Larue , Michael E. Cholette , Andry Rakotonirainy , Sébastien Glaser
{"title":"Including network level safety measures in eco-routing","authors":"Sepehr G. Dehkordi , Grégoire S. Larue , Michael E. Cholette , Andry Rakotonirainy , Sébastien Glaser","doi":"10.1080/15472450.2022.2129022","DOIUrl":"10.1080/15472450.2022.2129022","url":null,"abstract":"<div><p>Following the most energy-efficient route can have a significant impact on reducing energy consumption. While most eco-routing research has focused on reducing energy consumption and travel time, the safety aspect of route choice is currently neglected. In this paper, a multi-objective optimization methodology is formulated to concurrently minimize fuel consumption, travel time and safety risk, which is quantified using a novel methodology based on network-level safety measures. The proposed optimization framework provides a transparent way to intuitively include driver preferences via “budgets” for time, fuel consumption and safety – which represent the driver’s willingness to sacrifice these factors for fuel consumption improvements. The performance of the proposed method was tested on urban road networks in Brisbane-Australia, with a rear-end collision risk model as the safety measure. The results demonstrate that eco-routing with safety considerations has the potential to improve fuel efficiency while simultaneously reducing safety risks.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 283-296"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78027022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 multi-state merging based analytical model for an operation design domain of autonomous vehicles in work zones on two-lane highways","authors":"Qing Tang , Xianbiao Hu","doi":"10.1080/15472450.2022.2130697","DOIUrl":"10.1080/15472450.2022.2130697","url":null,"abstract":"<div><p>As a special application of connected and automated vehicles (CAVs), the Autonomous Truck Mounted Attenuator (ATMA) vehicle system is promoted to reduce fatalities in work zone locations. In this manuscript, we focus on the Operational Design Domain (ODD) problem of two-lane highways, i.e., under what traffic conditions should an ATMA be deployed. Due to the dramatic speed difference between ATMA vehicles and general vehicles, a queue will be formed, leading to a percent-time-spent-following (PTSF) increase during maintenance. General vehicles in the queue will assess a gap on the opposite lane to perform a passing maneuver, which is broken down into multi-stage merging behavior. As such, an analytical model is first made, based on queuing theory in which the arrival rate and service rate are analyzed to estimate the PTSF. In this way, the linkage between annual average daily traffic (AADT) and level of service (LOS) is analytically established. Then, the proposed model is validated by comparing the estimated PTSF with that of the Highway Capacity Manual (HCM) values. The comparison results show that the mean error is 9.58%, and the mean absolute error is 12.36%, which demonstrate that the developed model is able to generate satisfactory results when compared with the HCM model. Numeric analysis also shows that roadway performance is sensitive to the K factor and D factor, as well as the operating speed of an ATMA. If LOS = C is a desirable design objective, a good AADT threshold to use would be around 11,000 vehicles per day.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 372-385"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78862430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 stochastic microscopic based freeway traffic state and spatial-temporal pattern prediction in a connected vehicle environment","authors":"Seiran Heshami , Lina Kattan","doi":"10.1080/15472450.2022.2130291","DOIUrl":"10.1080/15472450.2022.2130291","url":null,"abstract":"<div><p>Traffic state prediction forms the basis for effective and efficient traffic control and management strategies. A model-based traffic state prediction approach based on a stochastic microscopic three-phase model is developed to predict traffic flow, speed, and travel time in short prediction horizons consisting of multiple time steps ahead. The proposed model utilizes connected vehicles’ trajectory data including location and speed information and fuses this information with detector measurements using an Adaptive Kalman filter. Stochastic driver behaviors in merging, lane-changing, and over-acceleration are considered in the three-phase microscopic model, which allows for a precise prediction of macroscopic parameters for a relatively long stretch of freeway. Traffic flow and speed predictions are conducted for each lane individually and, for a whole segment. Per-lane predictions provide valuable information regarding different speed fluctuations in each lane for identifying congestion and applying proactive freeway controls. Predicted traffic parameters are used for tracking and predicting the spatial-temporal traffic patterns in real-time. The accuracy of the proposed model is examined and validated for various penetration rates of connected vehicles and prediction horizons and outperforms the baseline prediction methods.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 313-339"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74454901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparative analysis of drowsiness and performance in conditionally automated driving and manual driving considering the effect of circadian rhythm","authors":"Qi Zhang , Chaozhong Wu , Hui Zhang , Sara Ferreira","doi":"10.1080/15472450.2022.2130292","DOIUrl":"10.1080/15472450.2022.2130292","url":null,"abstract":"<div><p>Drowsiness in manual driving (MD) is influenced by circadian rhythms. Conditionally automated driving (CAD) affects drivers’ drowsiness. We conducted a simulator study with 30 participants (every ten subjects in morning group, afternoon group, and evening group) to investigate the effect of circadian rhythm on the changes in drivers’ drowsiness and performance in different driving modes. Each subject was required to complete CAD experiment first and MD experiment later, and experienced 8 risk scenarios in each experiment. The self-reported Karolinska Sleepiness Scale (KSS) was recorded by an investigator every time when the subject drove past the scenario as the drowsiness measurement. The speed, acceleration, time-related metrics, and vehicle lane position were collected as the performance measurements. KSS data were statistically analyzed, and the Spearman’s Rho test was used to confirm the correlation among performance measurements, KSS, and scenarios. The result of the KSS statistical analysis showed that the effect of circadian rhythm on fatigue in MD groups is consistent with the previous studies, but the existence of CAD changes the effect of the circadian rhythm. Compared with the MD, CAD slowed down the drowsiness growth rate in the morning group and promoted the drowsiness growth rate in the evening group. The brake input rate, mean longitude acceleration, max Standard Deviation of Lane Position (SDLP), and the time to pass (TTP) were significantly related to the driver´s drowsiness in both driving modes.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 340-351"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85896125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Uncertainty analysis of autonomous delivery robot operations for last-mile logistics in European cities","authors":"Clément Lemardelé, Miquel Estrada, Laia Pagès","doi":"10.1080/15472450.2024.2324388","DOIUrl":"https://doi.org/10.1080/15472450.2024.2324388","url":null,"abstract":"Although autonomous delivery robots (ADRs) are widely anticipated to significantly enhance the efficiency of last-mile logistics operations in dense urban environments in the coming years, their im...","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"4 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140614637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiagent reinforcement learning for autonomous driving in traffic zones with unsignalized intersections","authors":"Christos Spatharis , Konstantinos Blekas","doi":"10.1080/15472450.2022.2109416","DOIUrl":"10.1080/15472450.2022.2109416","url":null,"abstract":"<div><p>In this work we present a multiagent deep reinforcement learning approach for autonomous driving vehicles that is able to operate in traffic networks with unsignalized intersections. The key aspects of the proposed study are the introduction of route-agents as the main building block of the system, as well as a collision term that allows the cooperation among vehicles and the construction of an efficient reward function. These have the advantage of establishing an enhanced collaborative multiagent deep reinforcement learning scheme that manages to control multiple vehicles and navigate them safely and efficiently-economically to their destination. In addition, it provides the beneficial flexibility to lay down a platform for transfer learning and reusing knowledge from the agents’ policies in handling unknown traffic scenarios. We provide several experimental results in simulated road traffic networks of variable complexity and diverse characteristics using the SUMO environment that empirically illustrate the efficiency of the proposed multiagent framework.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 1","pages":"Pages 103-119"},"PeriodicalIF":3.6,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82061008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 ridesharing simulation model that considers dynamic supply-demand interactions","authors":"Rui Yao , Shlomo Bekhor","doi":"10.1080/15472450.2022.2098730","DOIUrl":"10.1080/15472450.2022.2098730","url":null,"abstract":"<div><p>This paper presents a new ridesharing simulation model that accounts for dynamic driver supply and passenger demand, and complex interactions between drivers and passengers. The proposed simulation model explicitly considers driver and passenger acceptance/rejection on the matching options, and cancelation before/after being matched. New simulation events, procedures and modules have been developed to handle these realistic interactions. Ridesharing pricing bounds that result in high matching option accept rate are derived. The capabilities of the simulation model are illustrated using numerical experiments. The experiments confirm the importance of considering supply and demand interactions and provide new insights to ridesharing operations. Results show that higher prices are needed to attract drivers with short trip durations to participate in ridesharing, and larger matching window could have negative impacts on overall ridesharing success rate. Comparison results further illustrate that the proposed simulation model is able to replicate the predefined “true” success rate, in the cases that driver and passenger interactions occur.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 1","pages":"Pages 31-53"},"PeriodicalIF":3.6,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84768756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Glocal map-matching algorithm for high-frequency and large-scale GPS data","authors":"Yuanfang Zhu , Meilan Jiang , Toshiyuki Yamamoto","doi":"10.1080/15472450.2022.2086805","DOIUrl":"10.1080/15472450.2022.2086805","url":null,"abstract":"<div><p>The global positioning system (GPS) trajectory data are extensively utilized in various fields, such as driving behavior analysis, vehicle navigation systems, and traffic management. GPS sensors installed in numerous driving recorders and smartphones facilitate data collection on a large-scale in a high-frequency manner. Therefore, map-matching algorithms are indispensable to identify the GPS trajectories on a road network. Although the local map-matching algorithm reduces computation time, it lacks sufficient accuracy. Conversely, the global map-matching algorithm enhances matching accuracy; however, the computations are time consuming in the case of large-scale data. Therefore, this study proposes a method to improve the accuracy of the local map-matching algorithm without affecting its efficiency. The proposed method first executes the incremental map-matching algorithm. It then identifies the mismatching links in the results based on the connectivity of the links. Finally, the shortest path algorithm and the longest common subsequence are used to correct these error links. An elderly driver’s driving recorder data were used to conduct the experiment to compare the proposed method with four state-of-the-art map-matching algorithms in terms of accuracy and efficiency. The experimental results indicate that the proposed method can significantly increase the accuracy and efficiency of the map-matching process when considering high-frequency and large-scale data. Particularly, compared with the two-benchmark global map-matching algorithms, the proposed method can reduce the error rate of map-matching by nearly half, only consuming 18% and 58% of the computation time of the two global algorithms, respectively.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 1","pages":"Pages 1-15"},"PeriodicalIF":3.6,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90709378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}