| 1. |
- Abedin, Sarder, et al.
(författare)
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Data Freshness and Energy-Efficient UAV Navigation Optimization : A Deep Reinforcement Learning Approach
- 2021
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 22:9, s. 5994-6006
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we design a navigation policy for multiple unmanned aerial vehicles (UAVs) where mobile base stations (BSs) are deployed to improve the data freshness and connectivity to the Internet of Things (IoT) devices. First, we formulate an energy-efficient trajectory optimization problem in which the objective is to maximize the energy efficiency by optimizing the UAV-BS trajectory policy. We also incorporate different contextual information such as energy and age of information (AoI) constraints to ensure the data freshness at the ground BS. Second, we propose an agile deep reinforcement learning with experience replay model to solve the formulated problem concerning the contextual constraints for the UAV-BS navigation. Moreover, the proposed approach is well-suited for solving the problem, since the state space of the problem is extremely large and finding the best trajectory policy with useful contextual features is too complex for the UAV-BSs. By applying the proposed trained model, an effective real-time trajectory policy for the UAV-BSs captures the observable network states over time. Finally, the simulation results illustrate the proposed approach is 3.6 % and 3.13 % more energy efficient than those of the greedy and baseline deep Q Network (DQN) approaches.
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| 2. |
- Ahlström, Christer, et al.
(författare)
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A gaze-based driver distraction warning system and its effect on visual behaviour
- 2013
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 14:2, s. 965-973
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Tidskriftsartikel (refereegranskat)abstract
- Driver distraction is a contributing factor to many crashes; therefore, a real-time distraction warning system should have the potential to mitigate or circumvent many of these crashes. The objective of this paper is to investigate the usefulness of a real-time distraction detection algorithm called AttenD. The evaluation is based on data from an extended field study comprising seven drivers who drove on an average of 4351 ± 2181 km in a naturalistic setting.Visual behavior was investigated both on a global scale and on a local scale in the surroundings of each warning. An increase in the percentage of glances at the rear-view mirror and a decrease in the amount of glances at the center console were found. The results also show that visual time sharing decreased in duration from 9.94 to 9.20 s due to the warnings, that the time from fully attentive to warning decreased from 3.20 to 3.03 s, and that the time from warning to full attentiveness decreased from 6.02 to 5.46 s. The limited number of participants does not allow any generalizable conclusions, but a trend toward improved visual behavior could be observed. This is a promising start for further improvements of the algorithm and the warning strategy.
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| 3. |
- Ahlström, Christer, 1977-, et al.
(författare)
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A Generalized Method to Extract Visual Time-Sharing Sequences From Naturalistic Driving Data
- 2017
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 18:11, s. 2929-2938
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Tidskriftsartikel (refereegranskat)abstract
- Indicators based on visual time-sharing have been used to investigate drivers' visual behaviour during additional task execution. However, visual time-sharing analyses have been restricted to additional tasks with well-defined temporal start and end points and a dedicated visual target area. We introduce a method to automatically extract visual time-sharing sequences directly from eye tracking data. This facilitates investigations of systems, providing continuous information without well-defined start and end points. Furthermore, it becomes possible to investigate time-sharing behavior with other types of glance targets such as the mirrors. Time-sharing sequences are here extracted based on between-glance durations. If glances to a particular target are separated by less than a time-based threshold value, we assume that they belong to the same information intake event. Our results indicate that a 4-s threshold is appropriate. Examples derived from 12 drivers (about 100 hours of eye tracking data), collected in an on-road investigation of an in-vehicle information system, are provided to illustrate sequence-based analyses. This includes the possibility to investigate human-machine interface designs based on the number of glances in the extracted sequences, and to increase the legibility of transition matrices by deriving them from time-sharing sequences instead of single glances. More object-oriented glance behavior analyses, based on additional sensor and information fusion, are identified as the next future step. This would enable automated extraction of time-sharing sequences not only for targets fixed in the vehicle's coordinate system, but also for environmental and traffic targets that move independently of the driver's vehicle.
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| 4. |
- Ahlström, Christer, et al.
(författare)
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Processing of Eye/Head-Tracking Data in Large-Scale Naturalistic Driving Data Sets
- 2012
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; vol.13:no.2, s. pp.553-564
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Tidskriftsartikel (refereegranskat)abstract
- Driver distraction and driver inattention are frequently recognized as leading causes of crashes and incidents. Despite this fact, there are few methods available for the automatic detection of driver distraction. Eye tracking has come forward as the most promising detection technology, but the technique suffers from quality issues when used in the field over an extended period of time. Eye-tracking data acquired in the field clearly differs from what is acquired in a laboratory setting or a driving simulator, and algorithms that have been developed in these settings are often unable to operate on noisy field data. The aim of this paper is to develop algorithms for quality handling and signal enhancement of naturalistic eye- and head-tracking data within the setting of visual driver distraction. In particular, practical issues are highlighted. Developed algorithms are evaluated on large-scale field operational test data acquired in the Sweden-Michigan Field Operational Test (SeMiFOT) project, including data from 44 unique drivers and more than 10 000 trips from 13 eye-tracker-equipped vehicles. Results indicate that, by applying advanced data-processing methods, sensitivity and specificity of eyes-off-road glance detection can be increased by about 10%. In conclusion, postenhancement and quality handling is critical when analyzing large databases with naturalistic eye-tracking data. The presented algorithms provide the first holistic approach to accomplish this task.
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| 5. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Real-Time Adaptation of Driving Time and Rest Periods in Automated Long-Haul Trucking : Development of a System Based on Biomathematical Modelling, Fatigue and Relaxation Monitoring
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1524-9050 .- 1558-0016. ; 23:5, s. 4758-4766
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Tidskriftsartikel (refereegranskat)abstract
- Hours of service regulations govern the working hours of commercial motor vehicle drivers, but these regulations may become more flexible as highly automated vehicles have the potential to afford periods of in-cab rest or even sleep while the vehicle is moving. A prerequisite is robust continuous monitoring of when the driver is resting (to account for reduced time on task) or sleeping (to account for the reduced physiological drive to sleep). The overall aims of this paper are to raise a discussion of whether it is possible to obtain successful rest during automated driving, and to present initial work on a hypothetical data driven algorithm aimed to estimate if it is possible to gain driving time after resting under fully automated driving. The presented algorithm consists of four central components, a heart rate-based relaxation detection algorithm, a camera-based sleep detection algorithm, a fatigue modelling component taking time awake, time of day and time on task into account, and a component that estimates gained driving time. Real-time assessment of driver fitness is complicated, especially when it comes to the recuperative value of in-cab sleep and rest, as it depends on sleep quality, time of day, homeostatic sleep pressure and on the activities that are carried out while resting. The monotony that characterizes for long-haul truck driving is clearly interrupted for a while, but the long-term consequences of extended driving times, including user acceptance of the key stakeholders, requires further research.
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| 6. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Technologies for Risk Mitigation and Support of Impaired Drivers
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:5, s. 4736-4738
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This editorial serves as an extended introduction to the Special Issue on Technologies for Risk Mitigation and Support of Impaired Drivers. It gives the context to recent advances in assisted and automated driving and the new challenges that arise when modern technology meets human users. The Special Issue focuses on the development of robust sensors and detection algorithms for driver state monitoring of fatigue, stress, and inattention, and on the development of personalized multimodal, user-oriented, and adaptive information, warning, actuation, and handover strategies. A summary of more recent developments serves as a motivation for each article that follows.
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| 7. |
- Ahlström, Christer, 1977-, et al.
(författare)
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Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1524-9050 .- 1558-0016. ; 23:5, s. 4778-4790
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents initial work on a context-dependent driver distraction detection algorithm called AttenD2.0, which extends the original AttenD algorithm with elements from the Minimum Required Attention (MiRA) theory. Central to the original AttenD algorithm is a time buffer which keeps track of how often and for how long the driver looks away from the forward roadway. When the driver looks away the buffer is depleted and when looking back the buffer fills up. If the buffer runs empty the driver is classified as distracted. AttenD2.0 extends this concept by adding multiple buffers, thus integrating situation dependence and visual time-sharing behaviour in a transparent manner. Also, the increment and decrement of the buffers are now controlled by both static requirements (e.g. the presence of an on-ramp increases the need to monitor the sides and the mirrors) as well as dynamic requirements (e.g., reduced speed lowers the need to monitor the speedometer). The algorithm description is generic, but a real-time implementation with concrete values for different parameters is showcased in a driving simulator experiment with 16 bus drivers, where AttenD2.0 was used to ensure that drivers are attentive before taking back control after an automated bus stop docking and depot procedure. The scalability of AttenD2.0 relative to available data sources and the level of vehicle automation is demonstrated. Future work includes expanding the concept to real-world environments by automatically integrating situational information from the vehicles environmental sensing and from digital maps.
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| 8. |
- Ali, Mohammad, 1982, et al.
(författare)
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Predictive Prevention of Loss of Vehicle Control for Roadway Departure Avoidance
- 2013
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 14:1, s. 56-68
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate predictive approaches to the problem of roadway departure prevention via automated steering and braking. We assume a sensing infrastructure detecting road geometry and consider a two-layer accident avoidance framework consisting of a threat assessment and an intervention layer. A novel active safety function for prevention of loss of vehicle control is proposed and implemented using the considered accident avoidance framework. Simulation and experimental results are presented, showing that the proposed approach effectively exploits road preview information to prevent the vehicle from operating in regions of the state space where standard electronic stability control systems are normally activated.
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| 9. |
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| 10. |
- Antoniou, Constantinos, et al.
(författare)
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Non–linear Kalman Filtering Algorithms for On–line Calibration of Dynamic Traffic Assignment Models
- 2007
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 8:4, s. 661-670
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Tidskriftsartikel (refereegranskat)abstract
- An online calibration approach that jointly estimates demand and supply parameters of dynamic traffic assignment (DTA) systems is presented and empirically validated through an extensive application. The problem can be formulated as a nonlinear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman filter, and therefore, nonlinear extensions need to be considered. The following three extensions to the Kalman filtering algorithm are presented: 1) the extended Kalman filter (EKF); 2) the limiting EKF (LimEKF); and 3) the unscented Kalman filter. The solution algorithms are applied to the on-line calibration of the state-of-the-art DynaMIT DTA model, and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy that is comparable to that of the best algorithm but with vastly superior computational performance. The robustness of the approach to varying weather conditions is demonstrated, and practical aspects are discussed.
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| 11. |
- Aramrattana, Maytheewat, et al.
(författare)
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A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations
- 2021
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, NJ : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016.
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Tidskriftsartikel (refereegranskat)abstract
- Platooning refers to a group of vehicles that--enabled by wireless vehicle-to-vehicle (V2V) communication and vehicle automation--drives with short inter-vehicular distances. Before its deployment on public roads, several challenging traffic situations need to be handled. Among the challenges are cut-in situations, where a conventional vehicle--a vehicle that has no automation or V2V communication--changes lane and ends up between vehicles in a platoon. This paper presents results from a simulation study of a scenario, where a conventional vehicle, approaching from an on-ramp, merges into a platoon of five cars on a highway. We created the scenario with four platooning gaps: 15, 22.5, 30, and 42.5 meters. During the study, the conventional vehicle was driven by 37 test persons, who experienced all the platooning gaps using a driving simulator. The participants' opinions towards safety, comfort, and ease of driving between the platoon in each gap setting were also collected through a questionnaire. The results suggest that a 15-meter gap prevents most participants from cutting in, while causing potentially dangerous maneuvers and collisions when cut-in occurs. A platooning gap of at least 30 meters yield positive opinions from the participants, and facilitating more smooth cut-in maneuvers while less collisions were observed.
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| 12. |
- Aramrattana, Maytheewat, 1988-, et al.
(författare)
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Team Halmstad Approach to Cooperative Driving in the Grand Cooperative Driving Challenge 2016
- 2018
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, N.J. : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; 19:4, s. 1248-1261
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Tidskriftsartikel (refereegranskat)abstract
- This paper is an experience report of team Halmstad from the participation in a competition organised by the i-GAME project, the Grand Cooperative Driving Challenge 2016. The competition was held in Helmond, The Netherlands, during the last weekend of May 2016. We give an overview of our car’s control and communication system that was developed for the competition following the requirements and specifications of the i-GAME project. In particular, we describe our implementation of cooperative adaptive cruise control, our solution to the communication and logging requirements, as well as the high level decision making support. For the actual competition we did not manage to completely reach all of the goals set out by the organizers as well as ourselves. However, this did not prevent us from outperforming the competition. Moreover, the competition allowed us to collect data for further evaluation of our solutions to cooperative driving. Thus, we discuss what we believe were the strong points of our system, and discuss post-competition evaluation of the developments that were not fully integrated into our system during competition time. © 2000-2011 IEEE.
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| 13. |
- Ashraf, Nouman, et al.
(författare)
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Intelligent Beam Steering for Wireless Communication Using Programmable Metasurfaces
- 2023
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, N.J. : IEEE. - 1524-9050 .- 1558-0016. ; 24:5, s. 4848-4861
-
Tidskriftsartikel (refereegranskat)abstract
- Reconfigurable Intelligent Surfaces (RIS) are well established as a promising solution to the blockage problem in millimeter-wave (mm-wave) and terahertz (THz) communications, envisioned to serve demanding networking applications, such as 6G and vehicular. HyperSurfaces (HSF) is a revolutionary enabling technology for RIS, complementing Software Defined Metasurfaces (SDM) with an embedded network of controllers to enhance intelligence and autonomous operation in wireless networks. In this work, we consider feedback-based autonomous reconfiguration of the HSF controller states to establish a reliable communication channel between a transmitter and a receiver via programmable reflection on the HSF when Line-of-sight (LoS) between them is absent. The problem is to regulate the angle of reflection on the metasurface such that the power at the receiver is maximized. Extremum Seeking Control (ESC) is employed with the control signals generated mapped into appropriate metasurface coding signals which are communicated to the controllers via the embedded controller network (CN). This information dissemination process incurs delays which can compromise the stability of the feedback system and are thus accounted for in the performance evaluation. Extensive simulation results demonstrate the effectiveness of the proposed method to maximize the power at the receiver within a reasonable time even when the latter is mobile. The spatiotemporal nature of the traffic for different sampling periods is also characterized. Author
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| 14. |
- Autili, Marco, et al.
(författare)
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Cooperative Intelligent Transport Systems : Choreography-Based Urban Traffic Coordination
- 2021
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; 22:4, s. 2088-2099
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Tidskriftsartikel (refereegranskat)abstract
- With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each other for improving the overall transport performance such as safety, efficiency and sustainability. Massive information on road and traffic is already available and provided through standard services with different protocols. By reusing and composing the available heterogeneous services, novel value-added applications can be developed. This paper introduces a choreography-based service composition platform, i.e. the CHOReVOLUTION Integrated Development and Runtime Environment (IDRE), and it reports on how the IDRE has been successfully exploited to accelerate the reuse-based development of a choreography-based Urban Traffic Coordination (UTC) application. The UTC application takes the shape of eco-driving services that through real-time eco-route evaluation assist the drivers for the most eco-friendly and comfortable driving experience. The eco-driving services are realized through choreography and they are exploited through a mobile app for online navigation. From specification to deployment to execution, the CHOReVOLUTION IDRE has been exploited to support the realization of the UTC application by automatizing the generation of the distributed logic to properly bind, coordinate and adapt the interactions of the involved parties. The benefits brought by CHOReVOLUTION IDRE have been assessed through the evaluation of a set of Key Performance Indicators (KPIs).
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| 15. |
- Axelsson, Jakob
(författare)
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Safety in Vehicle Platooning: A Systematic Literature Review
- 2017
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 18, s. 1033-1045
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Tidskriftsartikel (refereegranskat)abstract
- Vehicle platooning has been studied for several decades, with objectives such as improved traffic throughput on existing infrastructure or reduced energy consumption. All the time, it has been apparent that safety is an important issue. However, there are no comprehensive analyses of what is needed to achieve safety in platooning, but only scattered pieces of information. This paper investigates, through a systematic literature review, what is known about safety for platooning, including what analysis methods have been used, what hazards and failures have been identified, and solution elements that have been proposed to improve safety. Based on this, a gap analysis is performed to identify outstanding questions that need to be addressed in future research. These include dealing with a business ecosystem of actors that cooperate and compete around platooning, refining safety analysis methods to make them suitable for systems-of-systems, dealing with variability in vehicles, and finding solutions to various human factors issues.
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| 16. |
- Aydin, N., et al.
(författare)
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Heuristics Based Optimization for Multidepot Drone Location and Routing Problem to Detect Post-Earthquake Damages
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; , s. 1-9
-
Tidskriftsartikel (refereegranskat)abstract
- The aim of this research is to detect the post-disaster damage by drones as soon as possible so that decision makers can assign search and rescue teams effectively and efficiently. The main differences of this research from the others, which use drones in literature, are as: First, the regions are divided into grids and different importance values are assigned according to the number of buildings that are likely to be damaged and are vital for the response stage, such as hospitals, schools, and fire stations. Second, these importance levels are updated based on the day and time, which helps ordering the grids in a more realistic manner. Third, the depots are selected among the pre-determined candidate locations in accordance with the purpose of objective function. Fourth, detection times at grids are considered as uncertain. Fifth, two versions of Ant Colony Optimization (ACO) are developed as alternatives to exact solution tools. Last, sensitivity analyzes are performed by reducing the number of sorties, reducing the number of drones, and comparing day and night importance values for each instance. According to the results, only for very small-scale instances, exact solution tool was able to reach the optimal while both versions of ACO reached to similar results within a very less CPU times. Additionally, these ACO algorithms also found good results for the larger scaled problems. Then the performance of these ACO algorithms and the exact solution method are compared based on the CPU time and solution quality. IEEE
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| 17. |
- Aydogdu, Canan, 1978, et al.
(författare)
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RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation
- 2021
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 22:1, s. 416-429
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Tidskriftsartikel (refereegranskat)abstract
- In the automotive sector, both radars and wireless communication are susceptible to interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate interference in both systems. This article analyses the mutual interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of interference among FMCW based automotive radars, including self-interference, using radar and communication cooperation. The results show that RadChat can significantly reduce radar mutual interference in single-hop vehicular networks in less than 80 ms.
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| 18. |
- Bae, Sangjun, 1986, et al.
(författare)
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A Game Approach for Charging Station Placement Based on User Preferences and Crowdedness
- 2022
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:4, s. 3654-3669
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Tidskriftsartikel (refereegranskat)abstract
- The placement of electric vehicle charging stations (EVCSs), which encourages the rapid development of electric vehicles (EVs), should be considered from not only operational perspective such as minimizing installation costs, but also user perspective so that their strategic and competitive charging behaviors can be reflected. This paper proposes a methodological framework to consider crowdedness and individual preferences of electric vehicle users (EVUs) in the selection of locations for fast-charging stations. The electric vehicle charging station placement problem (EVCSPP) is solved via a decentralized game theoretical decision-making algorithm and k-means clustering algorithm. The proposed algorithm, referred to as k-GRAPE, determines the locations of charging stations to maximize the sum of utilities of EVUs. In particular, we analytically present that 50% of suboptimality of the solution can be at least guaranteed, which is about 17% better than the existing game theoretical based framework. We show a few variants to describe the utility functions that may capture the difference in preferences of EVUs. Finally, we demonstrate the viability of the decision framework via three real-world data-based experiments. The results of the experiments, including a comparison with a baseline method are then discussed.
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| 19. |
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| 20. |
- Bai, Ting, et al.
(författare)
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Large-Scale Multi-Fleet Platoon Coordination : A Dynamic Programming Approach
- 2023
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 24:12, s. 14427-14442
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Tidskriftsartikel (refereegranskat)abstract
- Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dispatching strategies that facilitate the platoon formations across fleets are required. This paper presents a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs. The waiting time scheduling problem of individual trucks is formulated as a distributed optimal control problem with continuous decision space and a reward function that takes non-zero values only at discrete points. By suitably discretizing the decision and state spaces, we show that the problem can be solved exactly by dynamic programming, without loss of optimality. Finally, a realistic simulation study is conducted over the Swedish road network with 5,000 trucks to evaluate the profit and efficiency of the approach. The simulation study shows that, compared to single-fleet platooning, multi-fleet platooning provided by our method achieves around 15 times higher monetary profit and increases the CO2 emission reductions from 0.4% to 5.5%. In addition, it shows that the developed approach can be carried out in real-time and thus is suitable for platoon coordination in large transportation systems.
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| 21. |
- Bakker, Bram, et al.
(författare)
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A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:5, s. 4791-4800
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Tidskriftsartikel (refereegranskat)abstract
- Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1-9 or a binary decision as alert (defined as KSS 1-6) or sleepy (defined as KSS 7-9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.
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| 22. |
- Bellone, Mauro, 1982, et al.
(författare)
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Learning Traversability from Point Clouds in Challenging Scenarios
- 2018
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 4:1, s. 296-305
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims at evaluating the capabilities to detect road traversability in urban and extra-urban scenarios ofsupport vector machine-based classifiers that use local descriptors extracted from point cloud data. The evaluation of the proposed classifiers is carried out by using four different kernels and comparing five point descriptors obtained from geometric and appearance-based features. A comparison among the performance of descriptors individually has demonstrated that the normal vector-based descriptor achieves an accuracy of 88%, outperforming by about 6%–15% all the other considered ones. To further improve the interpretation capabilities, the space of features is augmented by merging the components of each point descriptor, reaching 92% classification accuracy. A set of test scenarios have been acquired during an extensive experimental campaign using an all-terrain vehicle. Tests on real data show high classification performance for road scenarios and rural environments; the generality of the method makes it applicable for different types of mobile robots including, but not limited to, autonomous vehicles.
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| 23. |
- Belyaev, Evgeny, et al.
(författare)
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The Use of Automotive Radars in Video-Based Overtaking Assistance Applications
- 2013
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, NJ : IEEE Press. - 1524-9050 .- 1558-0016. ; 14:3, s. 1035-1042
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Tidskriftsartikel (refereegranskat)abstract
- Overtaking on rural roads may cause severe accidents when oncoming traffic is detected by a driver too late, or its speed is underestimated. Recently proposed cooperative overtaking assistance systems are based on real-time video transmission, where a video stream captured with a camera installed at the windshield of a vehicle is compressed, broadcast through the wireless channel, and displayed to the drivers of vehicles driving behind. In such a system, it is of ultimate importance to deliver video information about the opposite lane with low end-to-end latency and good visual quality. In this paper, we propose reallocating the wireless channel resources in favor of the part of the captured video frame containing the image of the oncoming vehicle. To achieve this goal, we apply automotive radar for oncoming vehicle detection, and we use the image of this vehicle as a region-of-interest (ROI) for the video rate control. We present the theoretical framework, which describes the basics of such an approach and can serve as a useful guideline for the future practical implementation of the overtaking assistance systems. The benefits of our proposal are demonstrated in relation to the practical scenario of H.264/Advance Video Coding (AVC), IEEE 802.11p/Wireless Access for Vehicular Environments (WAVE) intervehicle communication standards, and currently used automotive radars.
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| 24. |
- Bencheikh Lehocine, Chouaib, 1993, et al.
(författare)
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Antenna Combiner for Periodic Broadcast V2V Communication Under Relaxed Worst-Case Propagation
- 2023
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:9, s. 9817-9834
-
Tidskriftsartikel (refereegranskat)abstract
- The performance of a previously developed analog combining network (ACN) of phase shifters for periodic broadcast vehicle-to-vehicle (V2V) communication is investigated. The original ACN was designed to maximize the sum of signal-to-noise ratios (SNRs) for $K$ consecutive cooperative awareness messages (CAMs). The design was based on the assumption of a dominant propagation path with an angle of arrival (AOA) that is constant for $K$ messages. In this work, we relax this assumption by allowing the AOA and path-loss (PL) of the dominant path to be time-variant. Assuming a highway scenario with a line of sight (LOS) propagation between vehicles, we use affine approximations to model the time variation of different path quantities, including the PL, the relative distance-dependent phase shift between antennas, and the AOA-dependent far-field function of the antennas. By leveraging these approximations, we analytically derive the ACN sum-SNR as each one of these quantities varies over $K$ CAMs. Moreover, we suggest a design rule for a phase slope that is robust against time variation of the dominant path and optimal under time-invariant conditions. Finally, we validate this design rule using numerical computations and an example of vehicular communication antenna elements.
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| 25. |
- Bencheikh Lehocine, Chouaib, 1993, et al.
(författare)
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Hybrid Combining of Directional Antennas for Periodic Broadcast V2V Communication
- 2022
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:4, s. 3226-3243
-
Tidskriftsartikel (refereegranskat)abstract
- A hybrid analog-digital combiner for broadcast vehicular communication is proposed. It has an analog part that does not require any channel state information or feedback from the receiver, and a digital part that uses maximal ratio combining (MRC). We focus on designing the analog part of the combiner to optimize the received signal strength along all azimuth angles for robust periodic vehicle-to-vehicle (V2V) communication, in a scenario of one dominant component between the communicating vehicles (e.g., highway scenario). We show that the parameters of a previously suggested fully analog combiner solves the optimization problem of the analog part of the proposed hybrid combiner. Assuming L directional antennas with uniform angular separation together with the special case of a two-port receiver, we show that it is optimal to combine groups of ⌈L/2⌉ and ⌊L/2⌋ antennas in analog domain and feed the output of each group to one digital port. This is shown to be optimal under a sufficient condition on the sidelobes level of the directional antennas. Moreover, we derive a performance bound for the hybrid combiner to guide the choice of antennas needed to meet the reliability requirements of the V2V communication links.
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| 26. |
- Bencheikh Lehocine, Chouaib, 1993, et al.
(författare)
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Robust Analog Beamforming for Periodic Broadcast V2V Communication
- 2022
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:10, s. 18404-18422
-
Tidskriftsartikel (refereegranskat)abstract
- We generalize an existing low-cost analog signal processing concept that takes advantage of the periodicity of vehicle-to-vehicle broadcast service to the transmitter side. In particular, we propose to process multiple antennas using either an analog beamforming network (ABN) of phase shifters, or an antenna switching network (ASN) that periodically alternates between the available antennas, to transmit periodic messages to receivers that have an analog combining network (ACN) of phase shifters, which has been proposed in earlier work. To guarantee robustness, we aim to minimize the burst error probability for the worst receiving vehicular user, in a scenario of bad propagation condition that is modeled by a single dominant path between the communicating vehicles. In absence of any form of channel knowledge, we analytically derive the optimal parameters of both ABN and ASN. The ABN beamforming vector is found to be optimal for all users and not only for the worst receiving user. Further, we demonstrate that Alamouti scheme for the special case of two transmit antennas yields similar performance to ABN and ASN. At last, we show that the derived parameters of the two proposed transmission strategies are also optimal when hybrid ACN-maximal ratio combining is used at the receiver.
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| 27. |
- Benderius, Ola, 1985, et al.
(författare)
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The Best Rated Human-Machine Interface Design for Autonomous Vehicles in the 2016 Grand Cooperative Driving Challenge
- 2018
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 19:4, s. 1302-1307
-
Tidskriftsartikel (refereegranskat)abstract
- This paper provides an in-depth description of the best rated human-machine interface that was presented during the 2016 Grand Cooperative Driving Challenge. It was demonstrated by the Chalmers Truck Team as the envisioned interface to their open source software framework OpenDLV, which is used to power Chalmers' fleet of self-driving vehicles. The design originates from the postulate that the vehicle is fully autonomous to handle even complex traffic scenarios. Thus, by including external and internal interfaces, and introducing a show, don't tell principle, it aims at fulfilling the needs of the vehicle occupants as well as other participants in the traffic environment. The design also attempts to comply with, and slightly extend, the current traffic rules and legislation for the purpose of being realistic for full-scale implementation.
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| 28. |
- Berger, Christian, 1980, et al.
(författare)
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Simulations on Consumer Tests: A Systematic Evaluation Approach in an Industrial Case Study (Extended Version)
- 2015
-
Ingår i: IEEE Intelligent Transportation Systems Transactions and Magazine. - 1524-9050 .- 1558-0016. ; 7:4, s. 24-36
-
Tidskriftsartikel (refereegranskat)abstract
- Context: Consumer tests which assess safety features of modern vehicles have a tradition in Europe. Recently, such test protocols have been substantially extended to also cover active safety systems like Volkswagen's Front Assist. Objective: Simulations for passive safety systems are already a widely adopted approach during vehicle development and internal assessments. As active safety systems are becoming an increasingly important element in a vehicle's safety concept and a differentiating feature, a systematic validation and assessment of such systems is necessary to successfully pass consumer tests and complimentarily identified, relevant traffic scenarios. Method: With this work, we extend our previous conference publication about EuroNCAP CCRs tests by additionally investigating US NCAP scenarios for an AEB system. Therefore, we systematically modeled the allowed variations with a graph where the paths represent concrete test scenarios. These paths are used in a virtual test environment to assess the AEB system. In our previous publication, we illustrated our method of test case generation and simulating consumer test scenarios by showing results of 27 specific test cases. In this work, we focused on integrating a test automatization routine as well as evaluating a set of test cases with a factor of 100 compared to our previous paper. Results: We demonstrate the approach for both EuroNCAP's and US NCAP's CCRs scenarios with a total quantity of more than 2,700 test cases including re-runs to systematically evaluate an AEB algorithm. Our results unveiled varying action points in time for the same initial values for a given consumer test scenario while applying different allowed variations. Conclusion: We foresee the importance of complementary virtual testing for real-world tests on proving grounds especially during the design phase. Our study shows that already small variations that yet accord with the test procedure specification influence the behavior of an active safety system and need to be investigated during development and vehicle testing.
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| 29. |
- Bernado, Laura, et al.
(författare)
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Time- and Frequency-Varying K -Factor of Non-Stationary Vehicular Channels for Safety-Relevant Scenarios
- 2015
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050. ; 16:2, s. 1007-1017
-
Tidskriftsartikel (refereegranskat)abstract
- Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to fast changes in the environment. We characterize the distribution of the envelope of the first delay bin in vehicle-to-vehicle channels by means of its Rician $K$-factor. We analyze the time–frequency variability of this channel parameter using vehicular channel measurements at 5.6 GHz with a bandwidth of 240 MHz for safety-relevant scenarios in intelligent transportation systems (ITS). This data enables a frequency-variability analysis from an IEEE 802.11p system point of view, which uses 10 MHz channels. We show that the small-scale fading of the envelope of the first delay bin is Rician distributed with a varying K-factor. The later delay bins are Rayleigh distributed. We demonstrate that the K-factor cannot be assumed to be constant in time and frequency. The causes of these variations are the frequency-varying antenna radiation patterns, as well as the time-varying number of active scatterers, and the effects of vegetation. We also present a simple but accurate bimodal Gaussian mixture model, which allows to capture the K-factor variability in time for safety-relevant ITS scenarios.
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| 30. |
- Besinovic, Nikola, et al.
(författare)
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Artificial Intelligence in Railway Transport : Taxonomy, Regulations, and Applications
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:9, s. 14011-14024
-
Tidskriftsartikel (refereegranskat)abstract
- Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway transport is no exception. However, due to the plethora of different new terms and meanings associated with them, there is a risk that railway practitioners, as several other categories, will get lost in those ambiguities and fuzzy boundaries, and hence fail to catch the real opportunities and potential of machine learning, artificial vision, and big data analytics, just to name a few of the most promising approaches connected to AI. The scope of this paper is to introduce the basic concepts and possible applications of AI to railway academics and practitioners. To that aim, this paper presents a structured taxonomy to guide researchers and practitioners to understand AI techniques, research fields, disciplines, and applications, both in general terms and in close connection with railway applications such as autonomous driving, maintenance, and traffic management. The important aspects of ethics and explainability of AI in railways are also introduced. The connection between AI concepts and railway subdomains has been supported by relevant research addressing existing and planned applications in order to provide some pointers to promising directions.
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| 31. |
- Borkar, Amol, et al.
(författare)
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A Novel Lane Detection System With Efficient Ground Truth Generation
- 2012
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 13:1, s. 365-374
-
Tidskriftsartikel (refereegranskat)abstract
- A new night-time lane detection system and its accompanying framework are presented in this paper. The accompanying framework consists of an automated ground truth process and systematic storage of captured videos that will be used for training and testing. The proposed Advanced Lane Detector 2.0 (ALD 2.0) is an improvement over the ALD 1.0 or Layered Approach with integration of pixel remapping, outlier removal, and prediction with tracking. Additionally, a novel procedure to generate the ground truth data for lane marker locations is also proposed. The procedure consists of an original process called time slicing, which provides the user with unique visualization of the captured video and enables quick generation of ground truth information. Finally, the setup and implementation of a database hosting lane detection videos and standardized data sets for testing are also described. The ALD 2.0 is evaluated by means of the user-created annotations accompanying the videos. Finally, the planned improvements and remaining work are addressed.
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| 32. |
- Brännström, Mattias, 1980, et al.
(författare)
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A Probabilistic Framework for Decision-Making in Collision Avoidance Systems
- 2013
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 14:2, s. 637-648
-
Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with the problem of decision-making in systems that assist drivers in avoiding collisions. An important aspect of these systems is not only assisting the driver when needed but also not disturbing the driver with unnecessary interventions. Aimed at improving both of these properties, a probabilistic framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid a collision. The intervention acceptance is modeled as high if it estimated that the driver judges the situation as critical, based on the driver's observations and predictions of the traffic situation. One advantage with the proposed framework is that interventions can be initiated at an earlier stage when the estimated driver acceptance is high. Using a simplified driver model, the framework is applied to a few different types of collision scenarios. The results show that the framework has appealing properties, both with respect to increasing the system benefit and to decreasing the risk of unnecessary interventions.
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| 33. |
- Brännström, Mattias, 1980, et al.
(författare)
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Model-Based Threat Assessment for Avoiding Arbitrary Vehicle Collisions
- 2010
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 11:3, s. 658-669
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a model-based algorithm that estimates how the driver of a vehicle can either steer, brake, or accelerate to avoid colliding with an arbitrary object. In this algorithm, the motion of the vehicle is described by a linear bicycle model, and the perimeter of the vehicle is represented by a rectangle. The estimated perimeter of the object is described by a polygon that is allowed to change size, shape, position, and orientation at sampled time instances. Potential evasive maneuvers are modeled, parameterized, and approximated such that an analytical expression can be derived to estimate the set ofmaneuvers that the driver can use to avoid a collision. This set of maneuvers is then assessed to determine if the driver needs immediate assistance to avoid or mitigate an accident. The proposed threat-assessment algorithm is evaluated using authentic data from both real traffic conditions and collision situations on a test track and by using simulations with a detailed vehicle model. The evaluations show that the algorithm outperforms conventional threat-assessment algorithms at rear-end collisions in terms of the timing of autonomous brake activation. This is crucial for increasing the performance of collisionavoidance systems and for decreasing the risk of unnecessary braking. Moreover, the algorithm is computationally efficient and can be used to assist the driver in avoiding or mitigating collisions with all types of road users in all kinds of traffic scenarios.
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| 34. |
- Cheema, M. A., et al.
(författare)
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A Drone-Aided Blockchain-Based Smart Vehicular Network
- 2021
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; 22:7, s. 4160-4170
-
Tidskriftsartikel (refereegranskat)abstract
- The staggering growth of the number of vehicles worldwide has become a critical challenge resulting in tragic incidents, environment pollution, congestion, etc. Therefore, one of the promising approaches is to design a smart vehicular system as it is beneficial to drive safely. Present vehicular system lacks data reliability, security, and easy deployment. Motivated by these issues, this paper addresses a drone-enabled intelligent vehicular system, which is secure, easy to deploy and reliable in quality. Nevertheless, an increase in the number of operating drones in the communication networks makes them more vulnerable towards the cyber-attacks, which can completely sabotage the communication infrastructure. To tackle these problems, we propose a blockchain-based registration and authentication system for the entities such as drones, smart vehicles (SVs) and roadside units (RSUs). This paper is mainly focused on the blockchain-based secure system design and the optimal placement of drones to improve the spectral efficiency of the overall network. In particular, we investigate the association of RSUs with the drones by considering multiple communication-related factors such as available bandwidth, maximum number of links a drone can support, and backhaul limitations. We show that the proposed model can easily be overlaid on the current vehicular network reaping benefits of secure and reliable communications. © 2000-2011 IEEE.
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| 35. |
- Chen, Dongliang, et al.
(författare)
-
The Scanner of Heterogeneous Traffic Flow in Smart Cities by an Updating Model of Connected and Automated Vehicles
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:12, s. 25361-25370
-
Tidskriftsartikel (refereegranskat)abstract
- The problems of traditional traffic flow detection and calculation methods include limited traffic scenes, high system costs, and lower efficiency over detecting and calculating. Therefore, in this paper, we presented the updating Connected and Automated Vehicles (CAVs) model as the scanner of heterogeneous traffic flow, which uses various sensors to detect the characteristics of traffic flow in several traffic scenes on the roads. The model contains the hardware platform, software algorithm of CAV, and the analysis of traffic flow detection and simulation by Flow Project, where the driving of vehicles is mainly controlled by Reinforcement Learning (RL). Finally, the effectiveness of the proposed model and the corresponding swarm intelligence strategy is evaluated through simulation experiments. The results showed that the traffic flow scanning, tracking, and data recording performed continuously by CAVs are effective. The increase in the penetration rate of CAVs in the overall traffic flow has a significant effect on vehicle detection and identification. In addition, the vehicle occlusion rate is independent of the CAV lane position in all cases. The complete street scanner is a new technology that realizes the perception of the human settlement environment with the help of the Internet of Vehicles based on 5G communications and sensors. Although there are some shortcomings in the experiment, it still provides an experimental reference for the development of smart vehicles.
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| 36. |
- Chen, Guang, et al.
(författare)
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NeuroIV : Neuromorphic Vision Meets Intelligent Vehicle Towards Safe Driving With a New Database and Baseline Evaluations
- 2022
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 23:2, s. 1171-1183
-
Tidskriftsartikel (refereegranskat)abstract
- Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS) using silicon retina are inspired by biological vision, they generate streams of asynchronous events to indicate local log-intensity brightness changes. Their properties of high temporal resolution, low-bandwidth, lightweight computation, and low-latency make them a good fit for many applications of motion perception in the intelligent vehicle. However, as a younger and smaller research field compared to classical computer vision, neuromorphic vision is rarely connected with the intelligent vehicle. For this purpose, we present three novel datasets recorded with DAVIS sensors and depth sensor for the distracted driving research and focus on driver drowsiness detection, driver gaze-zone recognition, and driver hand-gesture recognition. To facilitate the comparison with classical computer vision, we record the RGB, depth and infrared data with a depth sensor simultaneously. The total volume of this dataset has 27360 samples. To unlock the potential of neuromorphic vision on the intelligent vehicle, we utilize three popular event-encoding methods to convert asynchronous event slices to event-frames and adapt state-of-the-art convolutional architectures to extensively evaluate their performances on this dataset. Together with qualitative and quantitative results, this work provides a new database and baseline evaluations named NeuroIV in cross-cutting areas of neuromorphic vision and intelligent vehicle.
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| 37. |
- Chen, Lei, et al.
(författare)
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Cooperative Intersection Management : A Survey
- 2016
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, NJ : IEEE Press. - 1524-9050 .- 1558-0016. ; 17:2, s. 570-586
-
Tidskriftsartikel (refereegranskat)abstract
- Intersection management is one of the most challenging problems within the transport system. Traffic light-based methods have been efficient but are not able to deal with the growing mobility and social challenges. On the other hand, the advancements of automation and communications have enabled cooperative intersection management, where road users, infrastructure, and traffic control centers are able to communicate and coordinate the traffic safely and efficiently. Major techniques and solutions for cooperative intersections are surveyed in this paper for both signalized and nonsignalized intersections, whereas focuses are put on the latter. Cooperative methods, including time slots and space reservation, trajectory planning, and virtual traffic lights, are discussed in detail. Vehicle collision warning and avoidance methods are discussed to deal with uncertainties. Concerning vulnerable road users, pedestrian collision avoidance methods are discussed. In addition, an introduction to major projects related to cooperative intersection management is presented. A further discussion of the presented works is given with highlights of future research topics. This paper serves as a comprehensive survey of the field, aiming at stimulating new methods and accelerating the advancement of automated and cooperative intersections.
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| 38. |
- Chen, Yuhan, 1995, et al.
(författare)
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An Isochrone-Based Predictive Optimization for Efficient Ship Voyage Planning and Execution
- 2024
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; In press
-
Tidskriftsartikel (refereegranskat)abstract
- A voyage optimization algorithm is an essential component in a ship’s routing concerning safety, energy efficiency, arrival punctuality, etc. In this study, predictive optimization is integrated with an Isochrone-based voyage optimization algorithm for energy-efficient sailing. Different waypoints generation and grid partition strategies in search spaces are proposed to achieve smooth convergence toward the destination, and costs ahead of the current sailing time stages are estimated in the cost function to avoid the local suboptimization. Based on these measures, this paper introduces the Isochrone-based predictive optimization (IPO) method that can achieve enhanced and robust performance in real-time multi-objective voyage optimization. The unrealistic routes with abrupt turns that occur in the traditional Isochrone and graph search methods are avoided. The IPO method can suggest energy-efficient routes in diverse sailing environments, while complying with punctuality requirements in voyage planning. Meanwhile, it requires a few computational resources that enable online and real-time adjustment during voyage execution, adapting to dynamic sailing environments. Its efficiency and effectiveness are demonstrated by six case study voyages from a chemical tanker with full-scale measurements, and further compared with other widely used voyage optimization methods. The results show that the proposed method can provide smooth routes with subtle turns with 5% fuel reduction on average for all case voyages, with around 40 seconds runtime.
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| 39. |
- Čičić, Mladen, 1991-, et al.
(författare)
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Coordinating Vehicle Platoons for Highway Bottleneck Decongestion and Throughput Improvement
- 2021
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; , s. 1-13
-
Tidskriftsartikel (refereegranskat)abstract
- Truck platooning is a technology that is expected to become widespread in the coming years. Apart from the numerous benefits that it brings, its potential effects on the overall traffic situation need to be studied further, especially at bottlenecks and ramps. Assuming we can control the platoons from the infrastructure, they can be used as controlled moving bottlenecks, actuating control actions on the rest of the traffic, and potentially improving the throughput of the whole system. In this work, we use a tandem queueing model with moving bottlenecks as a prediction model to calculate control actions for the platoons. We use platoon speeds and formations as control inputs, and design a control law for throughput improvement of a highway section with a stationary bottleneck. By postponing and shaping the inflow to the bottleneck, we are able to avoid capacity drop, which significantly reduces the total time spent of all vehicles. We derived the estimated improvement in throughput that is achieved by applying the proposed control law, and tested it in a simulation study, with multi-class cell transmission model with platoons used as the simulation model, finding that the median delay of all vehicles is reduced by 75.6% compared to the uncontrolled case. Notably, although they are slowed down while actuating control actions, platooned vehicles experience less delay compared to the uncontrolled case, since they avoid going through congestion at the bottleneck.
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| 40. |
- Claes, Rutger, et al.
(författare)
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A Decentralized Approach for Anticipatory Vehicle Routing Using Delegate Multiagent Systems
- 2011
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 12:2, s. 364-373
-
Tidskriftsartikel (refereegranskat)abstract
- Advanced vehicle guidance systems use real-time traffic information to route traffic and to avoid congestion. Unfortunately, these systems can only react upon the presence of traffic jams and not to prevent the creation of unnecessary congestion. Anticipatory vehicle routing is promising in that respect, because this approach allows directing vehicle routing by accounting for traffic forecast information. This paper presents a decentralized approach for anticipatory vehicle routing that is particularly useful in large-scale dynamic environments. The approach is based on delegate multiagent systems, i.e., an environment-centric coordination mechanism that is, in part, inspired by ant behavior. Antlike agents explore the environment on behalf of vehicles and detect a congestion forecast, allowing vehicles to reroute. The approach is explained in depth and is evaluated by comparison with three alternative routing strategies. The experiments are done in simulation of a real-world traffic environment. The experiments indicate a considerable performance gain compared with the most advanced strategy under test, i.e., a traffic-message-channel-based routing strategy.
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| 41. |
- Cui, Shaohua, et al.
(författare)
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Adaptive Collision-Free Trajectory Tracking Control for String Stable Bidirectional Platoons
- 2023
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:11, s. 12141-12153
-
Tidskriftsartikel (refereegranskat)abstract
- Autonomous vehicle (AV) platoons, especially those with the bidirectional communication topology, have significant practical value, as they not only increase link capacity and reduce vehicle energy consumption, but also reduce the consumption of communication resources. Small gaps between AVs in a platoon easily lead to emergency braking or even collisions between consecutive AVs. This paper applies barrier Lyapunov functions to collision avoidance between AVs in a bidirectional platoon during trajectory tracking. Based on backstepping technique, an adaptive collision-free platoon trajectory tracking control algorithm is developed to distributedly design control laws for each AV in the platoon. The control algorithm does not need to introduce additional car-following models to simulate AV driving, and only needs to integrate the position trajectories of consecutive AVs to avoid inter-vehicle collisions. Two sign functions are introduced into the control laws of each AV to ensure strong string stability for bidirectional AV platoons. Moreover, uncertainties and external disturbances in vehicle motion are effectively compensated by introducing adaptation laws. Strong string stability is rigorously proved. CarSIM-based comparison simulations verify the effectiveness of the proposed control algorithm in avoiding inter-vehicle collisions, compensating for uncertainties in vehicle motion, and suppressing the amplification of spacing errors along the platoon.
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| 42. |
- Dabiri, Azita, 1984, et al.
(författare)
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Distributed ramp metering - a constrained discharge flow maximisation approach
- 2017
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 18:9, s. 2525-2538
-
Tidskriftsartikel (refereegranskat)abstract
- Considered in this note is a novel model-based, coordinated ramp metering strategy. It aims at maximising the discharge flow in motorway networks by minimising the divergence of the traffic density from its critical value caused by unknown demand flow. The suggested synthesis algorithm casts the traffic control objective into the form of an induced $\mathcal{L}_2$ norm minimisation problem. Hence, we purport rejecting the effect of disturbance on the overall network performance output while the ramp input flow is subjected to constraints. With such a problem formulation, it is not required to know the disturbance input in order to find the proper control input. Without any central decision unit (traffic control centre), ramp meters coordinate by sharing their local variables with solely their neighbour units (upstream and downstream) to achieve the global performance goal. Under some network symmetry conditions, a compositionally inexpensive distributed flow control method is suggested to address scalability issues. The method is implemented in simulation environment and compared to other control algorithms in two comprehensive case studies.
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| 43. |
- Dahl, John, 1986, et al.
(författare)
-
Performance and Efficiency Analysis of a Linear Learning-Based Prediction Model Used for Unintended Lane-Departure Detection
- 2022
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:7, s. 9115 -9125
-
Tidskriftsartikel (refereegranskat)abstract
- Advanced driver assistance systems have been an active research topic for decades, for which many approaches have been developed not only to reduce the number of traffic accidents but also to increase the driver's comfort. Among the many different solutions proposed, learning-based prediction approaches have gained considerable attention in recent years. Within this scope, this work focuses on the implementation aspects of a linear learning-based regression model for detecting unintended lane-departures, where the goal is to achieve a prediction model with good predictive performance while keeping the computational complexity as low as possible. Aspects under consideration include input signal selection and down-sampling. The linear prediction model is analyzed using a real world data set, and benchmarked against a kinematic constant velocity model and a non-linear regression model. The results show that the linear regression model has a significantly higher prediction performance when compared to a kinematic model. It is also shown that the predictive performance remains comparable to the more complex nonlinear regression model, even though the computational complexity of the linear model is significantly lower.
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| 44. |
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| 45. |
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| 46. |
- Deng, Qichen
(författare)
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A General Simulation Framework for Modeling and Analysis of Heavy-Duty Vehicle Platooning
- 2016
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 17:11, s. 3252-3262
-
Tidskriftsartikel (refereegranskat)abstract
- Platooning heavy-duty vehicles (HDVs) on a highway is a method for improving energy and transport efficiency. On one hand, HDV platoon driving in small intervehicle distances could increase highway capacity; on the other hand, HDVs traveling in small intervehicle distances experience significant air-drag reduction and, therefore, improve fuel efficiency. However, although the majority of research has been conducted on the development of platoon systems, very few studies have focused on quantification of the impacts of HDV platooning on traffic flow. This paper initializes a simulation framework to facilitate the study of HDV platooning and establishes the corresponding concept and operations. The longitudinal driving behaviors of HDV platoons are modeled in detail, considering the acceleration capability of an HDV. The proposed framework is applied on three experimental cases: the first case is to study the impacts of HDV platooning on traffic flow and the second and third cases are about the influence of traffic on HDV platoon formation. In the first case, simulation outcomes show that the increasing percentage of HDV platooning in traffic flow generally results in more dramatic improvements on traffic efficiency, while preserving traffic safety for passenger vehicles. In the second and third cases, for the HDV platoon formation, deceleration of the first HDV to a low speed during platoon formation will increase the formation time to a large extent in medium and heavy traffic.
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| 47. |
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| 48. |
- Díez Rodríguez, Victor, 1992-, et al.
(författare)
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An Approach for Receiver-Side Awareness Control in Vehicular Ad Hoc Networks
- 2018
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 19:4, s. 1227-1236
-
Tidskriftsartikel (refereegranskat)abstract
- Vehicular Ad hoc networks (VANET) are a key element of cooperative intelligent transport systems. One of the challenges in VANETs is dealing with awareness and congestion due to the high amount of messages received from the vehicles in communication range. As VANETs are used in critical applications, congestion on the receiver side caused by the buffering of the packets is a safety hazard. In this paper, we propose a streamwise queuing system on the receiver side and show how it improves the timeliness of the messages received and maintains the awareness of the system in a congestion situation. © Copyright 2017 IEEE
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| 49. |
- Ding, Feng, et al.
(författare)
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Perceptual Enhancement for Autonomous Vehicles : Restoring Visually Degraded Images for Context Prediction via Adversarial Training
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:7, s. 9430-9441
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Tidskriftsartikel (refereegranskat)abstract
- Realizing autonomous vehicles is one of the ultimate dreams for humans. However, perceptual information collected by sensors in dynamic and complicated environments, in particular, vision information, may exhibit various types of degradation. This may lead to mispredictions of context followed by more severe consequences. Thus, it is necessary to improve degraded images before employing them for context prediction. To this end, we propose a generative adversarial network to restore images from common types of degradation. The proposed model features a novel architecture with an inverse and a reverse module to address additional attributes between image styles. With the supplementary information, the decoding for restoration can be more precise. In addition, we develop a loss function to stabilize the adversarial training with better training efficiency for the proposed model. Compared with several state-of-the-art methods, the proposed method can achieve better restoration performance with high efficiency. It is highly reliable for assisting in context prediction in autonomous vehicles.
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