Journal of Intelligent and Connected Vehicles最新文献

{"title":"Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow","authors":"Eleonora Andreotti;Selpi;Pinar Boyraz","doi":"10.26599/JICV.2023.9210001","DOIUrl":"https://doi.org/10.26599/JICV.2023.9210001","url":null,"abstract":"This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility (SUMO) with real traffic flow. Specifically, real traffic flow and speed data collected in 2002 and 2019 in Gothenburg were used to simulate daily flow variation in SUMO. In order to predict the most likely drawbacks during the transition from a traffic consisting only manually driven vehicles to a traffic consisting only fully-autonomous vehicles, this study focuses on mixed traffic with different percentages of autonomous and manually driven vehicles. To realize this aim, several parameters of the car following and lane change models of autonomous vehicles are investigated in this paper. Along with the fundamental diagram, the number of lane changes and the number of conflicts are analyzed and studied as measures for improving road safety and efficiency. The study highlights that the autonomous vehicles' features that improve safety and efficiency in 100% autonomous and mixed traffic are different, and the ability of autonomous vehicles to switch between mixed and autonomous driving styles, and vice versa depending on the scenario, is necessary.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"6 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10175392/10175393.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67858195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ERTMS/ETCS Level 3: Development, assumptions, and what it means for the future","authors":"Daniel Knutsen;Nils O.E. Olsson;Jiali Fu","doi":"10.26599/JICV.2023.9210003","DOIUrl":"https://doi.org/10.26599/JICV.2023.9210003","url":null,"abstract":"The purpose of this paper is to categorize the research on Level 3 and Hybrid Level 3; map how the research focus on ERTMS Level 3 has developed over time; summarize key assumptions in research on Level 3 and Hybrid Level 3. This study uses a scoping review approach. This review method provides a comprehensive overview of the literature in a selected field. The literature searches in this study were primarily conducted in Scopus and Web of Science and were complemented with a follow-up search in Google Scholar. The topics are divided into two thematic areas: Effects on the Railway System and Technical Requirements. The thematic area Technical Requirements is further divided into the following subcategories: train, trackside, and communication. The effects on the railway system are measured using performance indicators: capacity, stability/robustness, and safety. ERTMS Level 3 has developed from a pure Level 3 to Hybrid Level 3. Hybrid Level 3 represents a pragmatic solution, but it may emerge as a threat to the long-term objective of the Level 3 moving block. Studies of Level 3 are based on a moving block solution, while studies of Hybrid Level 3 are mainly based on virtual sub-sections. Both Level 3 and Hybrid Level 3 studies tend to make assumptions that risk missing wider aspects of the railway system. There is also a need to correctly represent different ERTMS Level 3 configurations to ensure expected capacity gains. For a better understanding of the development and future path of ERTMS Level 3, it is interesting to study the following aspects: the historical development of ERTMS Level 3 research, the assumptions made about ERTMS Level 3, and the conditions and restrictions under which ERTMS Level 3 will be implemented. Assumptions and simplifications are necessary for modeling work, but there is also a need to highlight underlying assumptions in analyses of different ERTMS Level 3 configurations.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"6 1","pages":"34-45"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10175392/10124376.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68021348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-like lane-changing trajectory planning algorithm for human-machine conflict mitigation","authors":"Changhua Dai;Changfu Zong;Dong Zhang;Gang Li;Kaku Chuyo;Hongyu Zheng;Fei Gao","doi":"10.26599/JICV.2023.9210004","DOIUrl":"https://doi.org/10.26599/JICV.2023.9210004","url":null,"abstract":"The purpose of this paper is to alleviate the potential safety problems associated with the human driver and the automatic system competing for the right of way due to different objectives by mitigating the human-machine conflict phenomenon in human-machine shared driving (HMSD) technology from the automation system. Firstly, a basic lane-changing trajectory algorithm based on the quintic polynomial in the Frenet coordinate system is developed. Then, in order to make the planned trajectory close to human behavior, naturalistic driving data is collected, based on which some lane-changing performance features are selected and analyzed. There are three aspects have been taken into consideration for the human-like lane-changing trajectory: vehicle dynamic stability performance, driving cost optimization, and collision avoidance. Finally, the HMSD experiments are conducted with the driving simulator to test the potential of the human-like lane-changing trajectory planning algorithm. The results demonstrate that the lane-changing trajectory planning algorithm with the highest degree of personalization is highly consistent with human driver behavior and consequently would potentially mitigate the human-machine conflict with the HMSD application. Furthermore, it could be further employed as an empirical trajectory prediction result. The algorithm employs the distribution state of the historical trajectory for human-like processing, simplifying the operational process and ensuring the credibility, integrity, and interpretability of the results. Moreover, in terms of optimization processing, the form of optimization search followed by collision avoidance detection is adopted to in principle reduce the calculation difficulty. Additionally, a new convex polygon collision detection method, namely the vertex embedding method, is proposed for collision avoidance detection.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"6 1","pages":"46-63"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10175392/10124377.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67858197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inferring truck activities using privacy-preserving truck trajectories data","authors":"Arnav Choudhry;Sean Qian","doi":"10.26599/JICV.2023.9210002","DOIUrl":"https://doi.org/10.26599/JICV.2023.9210002","url":null,"abstract":"Global Navigation Satellite System (GNSS) data is an inexpensive and ubiquitous source of activity data. Global Positioning System (GPS) is an example of such data. Although there have been several studies about inferring device activity using GPS data from a consumer device, freight GPS data presents unique challenges for example having low and variable frequency, long transmission gaps, and frequent and unpredictable device ID resetting for preserving privacy. This study aims to provide an end-to-end, generic data analytical framework to infer multiple aspects of truck activity such as stops, trips, and tours. We use popular existing methods to construct the data processing pipeline and provide insights into their practical usage. We also propose improved data filters to different aspects of the data processing pipeline to address challenges found in privacy-preserving freight GPS data. We use freight data across four weeks from the greater Philadelphia region with variable transmission frequency ranging from one second to several hours to perform experiments and validate our methods. Our findings indicate that auxiliary information such as land use can be helpful in fine tuning stop inference, but spatio-temporal information contained in timestamped GPS pings is still the most powerful source of false stop identification. We also find that a combination of simple clustering techniques can provide a way to perform fast and reasonable clustering of the same stop.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"6 1","pages":"16-33"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10175392/10175394.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68145417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The status, challenges, and trends: An interpretation of technology roadmap of intelligent and connected vehicles in China (2020)","authors":"Qing Xu;Keqiang Li;Jianqiang Wang;Quan Yuan;Yanding Yang;Wenbo Chu","doi":"10.1108/JICV-07-2021-0010","DOIUrl":"https://doi.org/10.1108/JICV-07-2021-0010","url":null,"abstract":"Purpose - The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied. Design/methodology/approach - This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies. Findings - The technical architecture of ICVs as the \"three rows and two columns\" structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed. Originality/value - This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004514/10004517.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67851797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments","authors":"Ying Li;Li Zhao;Kun Gao;Yisheng An;Jelena Andric","doi":"10.1108/JICV-06-2022-0024","DOIUrl":"https://doi.org/10.1108/JICV-06-2022-0024","url":null,"abstract":"Purpose - The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver's physiological states. Design/methodology/approach - Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure. Findings - This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver's take-over maneuver is needed. Originality/value - The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors' knowledge, this is the first study using psychophysiological measures to quantify a driver's response to an emergency stop during distracted driving.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 3","pages":"270-282"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004521/10004535.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67856073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and testing of an image transformer for explainable autonomous driving systems","authors":"Jiqian Dong;Sikai Chen;Mohammad Miralinaghi;Tiantian Chen;Samuel Labi","doi":"10.1108/JICV-06-2022-0021","DOIUrl":"https://doi.org/10.1108/JICV-06-2022-0021","url":null,"abstract":"Purpose - Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to poor interpretability. These have exacerbated user distrust and further forestalled their widespread deployment in practical usage. This paper aims to develop explainable DL models for autonomous driving by jointly predicting potential driving actions with corresponding explanations. The explainable DL models can not only boost user trust in autonomy but also serve as a diagnostic approach to identify any model deficiencies or limitations during the system development phase. Design/methodology/approach - This paper proposes an explainable end-to-end autonomous driving system based on \"Transformer,\" a state-of-the-art self-attention (SA) based model. The model maps visual features from images collected by onboard cameras to guide potential driving actions with corresponding explanations, and aims to achieve soft attention over the image's global features. Findings - The results demonstrate the efficacy of the proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with much lower computational cost on a public data set (BDD-OIA). From the ablation studies, the proposed SA module also outperforms other attention mechanisms in feature fusion and can generate meaningful representations for downstream prediction. Originality/value - In the contexts of situational awareness and driver assistance, the proposed model can perform as a driving alarm system for both human-driven vehicles and autonomous vehicles because it is capable of quickly understanding/characterizing the environment and identifying any infeasible driving actions. In addition, the extra explanation head of the proposed model provides an extra channel for sanity checks to guarantee that the model learns the ideal causal relationships. This provision is critical in the development of autonomous systems.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 3","pages":"235-249"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004521/10004532.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67857755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal control of automated left-turn platoon at contraflow left-turn lane intersections","authors":"Hanyu Yang;Jing Zhao;Meng Wang","doi":"10.1108/JICV-03-2022-0007","DOIUrl":"https://doi.org/10.1108/JICV-03-2022-0007","url":null,"abstract":"Purpose - This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections. Design/methodology/approach - The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique. Findings - The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal. Originality/value - This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 3","pages":"206-214"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004521/10004530.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67857756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social relation and physical lane aggregator: Integrating social and physical features for multimodal motion prediction","authors":"Qiyuan Chen;Zebing Wei;Xiao Wang;Lingxi Li;Yisheng Lv","doi":"10.1108/JICV-07-2022-0028","DOIUrl":"https://doi.org/10.1108/JICV-07-2022-0028","url":null,"abstract":"Purpose - The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic agents' trajectories are influenced by physical lane rules and agents' social interactions. Design/methodology/approach - In this paper, the authors propose the social relation and physical lane aggregator for multimodal motion prediction, where the social relations of agents are mainly captured with graph convolutional networks and self-attention mechanism and then fused with the physical lane via the self-attention mechanism. Findings - The proposed methods are evaluated on the Waymo Open Motion Dataset, and the results show the effectiveness of the proposed two feature aggregation modules for trajectory prediction. Originality/value - This paper proposes a new design method to extract traffic interactions, and the attention mechanism is used in each part of the model to extract and fuse different relational features, which is different from other methods and improves the accuracy of the LSTM-based trajectory prediction method.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 3","pages":"302-308"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004521/10004537.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67857757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Less workplace parking with fully autonomous vehicles?","authors":"Stefan Tscharaktschiew;Felix Reimann","doi":"10.1108/JICV-07-2022-0029","DOIUrl":"https://doi.org/10.1108/JICV-07-2022-0029","url":null,"abstract":"Purpose - Recent studies on commuter parking in an age of fully autonomous vehicles (FAVs) suggest, that the number of parking spaces close to the workplace demanded by commuters will decline because of the capability of FAVs to return home, to seek out (free) parking elsewhere or just cruise. This would be good news because, as of today, parking is one of the largest consumers of urban land and is associated with substantial costs to society. None of the studies, however, is concerned with the special case of employer-provided parking, although workplace parking is a widespread phenomenon and, in many instances, the dominant form of commuter parking. The purpose of this paper is to analyze whether commuter parking will decline with the advent of self-driving cars when parking is provided by the employer. Design/methodology/approach - This study looks at commuter parking from the perspective of both the employer and the employee because in the case of employer-provided parking, the firm's decision to offer a parking space and the incentive of employees to accept that offer are closely interrelated because of the fringe benefit character of workplace parking. This study develops an economic equilibrium model that explicitly maps the employer-employee relationship, considering the treatment of parking provision and parking policy in the income tax code and accounting for adverse effects from commuting, parking and public transit. This study determines the market level of employer-provided parking in the absence and presence of FAVs and identifies the factors that drive the difference. This study then approximates the magnitude of each factor, relying on recent (first) empirical evidence on the impacts of FAVs. Findings - This paper's analysis suggests that as long as distortive (tax) policy favors employer-provided parking, FAVs are no guarantee to end up with less commuter parking. Originality/value - This study's findings imply that in a world of self-driving cars, policy intervention related to work commuting (e.g. fringe benefit taxation or transport pricing) might be even more warranted than today.","PeriodicalId":100793,"journal":{"name":"Journal of Intelligent and Connected Vehicles","volume":"5 3","pages":"283-301"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9944931/10004521/10004536.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67857759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}