| 1. |
- Andreotti, Eleonora, 1988, et al.
(författare)
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Cooperative merging strategy between connected autonomous vehicles in mixed traffic
- 2022
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Ingår i: IEEE Open Journal of Intelligent Transportation Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2687-7813. ; 3, s. 825-837
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Tidskriftsartikel (refereegranskat)abstract
- In this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy. The new cooperation strategy considers a pair of vehicles approaching an on-ramp. The strategy then makes decisions on the target speeds/accelerations of both vehicles, possible lane changing, and a dynamic decision-making approach in order to reduce the risk during the cut-in manoeuvre. In this work, the CRI was first used to assess the risk during the merging manoeuvre. For this purpose, scenarios with penetration rates of autonomous vehicles from 20% to 100%, with step of 10%, both connected and non-connected autonomous vehicles were evaluated. As a result, on average a 35% reduction of the cut-in risk manoeuvres in connected autonomous vehicles compared to non-connected autonomous vehicles is obtained. It is shown through the analysis of probability density functions characterising the CRI distribution that the reduction is not homogeneous across all indicator values, but depends on the penetration rate and the severity of the manoeuvre.
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| 2. |
- Andreotti, Eleonora, 1988, et al.
(författare)
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Mathematical Definitions of Scene and Scenario for Analysis of Automated Driving Systems in Mixed-Traffic Simulations
- 2021
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Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 6:2, s. 366-375
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a unified mathematical definition for describing commonly used terms encountered in systematical analysis of automated driving systems in mixed-traffic simulations. The most significant contribution of this work is in translating the terms that are clarified previously in literature into a mathematical set and function based format. Our work can be seen as an incremental step towards further formalisation of Domain-Specific-Language (DSL) for scenario representation. We also extended the previous work in the literature to allow more complex scenarios by expanding the model-incompliant information using set-theory to represent the perception capacity of the road-user agents. With this dynamic perception definition, we also support interactive scenarios and are not limited to reactive and pre-defined agent behavior. Our main focus is to give a framework to represent realistic road-user behavior to be used in simulation or computational tool to examine interaction patterns in mixed-traffic conditions. We believe that, by formalising the verbose definitions and extending the previous work in DSL, we can support automatic scenario generation and dynamic/evolving agent behavior models for simulating mixed traffic situations and scenarios. In addition, we can obtain scenarios that are realistic but also can represent rare-conditions that are difficult to extract from field-tests and real driving data repositories.
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| 3. |
- Andreotti, Eleonora, 1988, et al.
(författare)
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Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow
- 2023
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Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 6:1, s. 1-15
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Tidskriftsartikel (refereegranskat)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.
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| 4. |
- Andreotti, Eleonora, 1988, et al.
(författare)
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Safety-centred analysis of transition stages to traffic with fully autonomous vehicles
- 2020
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC.
-
Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to highlight and investigate the effects of increasing presence rate of autonomous vehicles (AVs) in terms of traffic safety and traffic flow characteristics. For this purpose, using existing driver models in traffic simulator software SUMO we identify and analyze those parameters that characterize and distinguish AVs' driving from manual driving in a heterogeneous traffic context. While it is essential to identify the parameters for traffic flow characteristics of heterogeneous fleets compared to homogeneous ones comprising manually driven vehicles (MV) only (i.e. current status), the safety aspects must be also accounted for. In order to combine these two fundamental aspects of heterogeneous traffic, we used a complete description of a highway driving scenario. The scenario integrates the perceptions of different type of vehicles (i.e. AV and MV) involved and the reaction times of human drivers and decision-making units of autonomous vehicles, to explore the impact of both the rate of AV presence and the perturbation in perception capabilities in highway scenarios.
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| 5. |
- Andreotti, Eleonora, 1988, et al.
(författare)
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Simulation-based impact projection of autonomous vehicle deployment using real traffic flow
- 2021
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this work we focus on future projected impacts of the autonomous vehicles in a realistic condition representing mixed traffic. By using real flow and speed data collected in 2002 and 2019 in the city of Gothenburg, we replicated and simulated the daily flow variation in SUMO. The expansion of the city in recent years was reflected in an increase in road users, and it is reasonable to expect it will increase further. Through simulations, it was possible to project this increase and to predict how this will impact the traffic in future. Furthermore, the composition of vehicle types in the future traffic can be expected to change through the introduction of autonomous vehicles. 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, we focus 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.
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| 6. |
- Aramrattana, Maytheewat, 1988-, et al.
(författare)
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Behavioral adaptation of drivers when driving among automated vehicles
- 2022
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Ingår i: Journal of Intelligent and Connected Vehicles. - : Emerald Publishing. - 2399-9802. ; 5:3, s. 309-315
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Tidskriftsartikel (refereegranskat)abstract
- Purpose This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles (AVs) compared to driving among manually driven vehicles (MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic situations. Here, mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional MVs. Design/methodology/approach A driving simulator study is designed to explore whether such behavioral adaptations exist. Two different driving scenarios were explored on a three-lane highway: driving on the main highway and merging from an on-ramp. For this study, 18 research participants were recruited. Findings Behavioral adaptation can be observed in terms of car-following speed, car-following time gap, number of lane change and overall driving speed. The adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or MVs. Although significant differences in behavior were found in more than 90% of the research participants, they adapted their behavior differently, and thus, magnitude of the behavioral adaptation remains unclear. Originality/value The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding vehicles. This finding differs from previous studies, which have shown that drivers tend to adapt their behaviors with respect to the surrounding vehicles. Furthermore, the surrounding vehicles in this study are more “free flow'” compared to previous studies with a fixed formation such as platoons. Nevertheless, long-term observations are required to further support this claim.
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| 7. |
- Bärgman, Jonas, 1972, et al.
(författare)
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On data security and analysis platforms for analysis of naturalistic driving data
- 2011
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Ingår i: Proceedings of the 8th European Congress and Exhibition on Intelligent Transport Systems and Services, June 2011, Lyon.
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Konferensbidrag (refereegranskat)abstract
- Studies involving naturalistic driving data, of which Naturalistic Field Operational Tests (N-FOTs) are a subset, are becoming increasingly important for understanding the factors influencing accident causation as well as for the development and evaluation of active safety systems. The methodology project FESTA developed a handbook on how to plan and implement FOTs. This handbook has been extensively used as a guideline in the euroFOT project. However, “the devil is in the details” when implementing e.g. the platforms for data security and analysis in projects which deal with analysis of large amounts of sensitive naturalistic driving data, such as euroFOT. That is, although a guideline such as FESTA is used, how the details are implemented is what makes the implementation a success or not. This paper is a case description of the implementation of the data security and analysis platform used for euroFOT (and other naturalistic data projects) at the SAFER Vehicle and Traffic Safety Centre. The paper covers aspects ranging from physical access to analysis rooms and corresponding digital access, via the platforms for pre-processing of data, to the platforms for information extraction for hypothesis analysis and statistics. The considerations in the design and choice of these platforms include subjects (drivers) privacy concerns, industry commercial concerns, as well as the needs and requirements from the analysis.
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| 8. |
- Dahlman, Anna Sjörs, et al.
(författare)
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D6.1: Evaluation framework, plans and material. Deliverable of the Horizon-2020 PANACEA project, Grant Agreement No. 953426
- 2022
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This deliverable presents the evaluation framework, plans and material for all data collections of the PANACEA project. It describes the objectives of the studies and how they will be realised. The purpose of the PANACEA evaluation framework is to create a common framework to be used in all studies to make sure the data are collected in a way that makes it possible to consolidate the results at the end and to provide what is needed for impact analysis (WP7). This version of the deliverable has its focus on setting the framework and the work process. An update of this deliverable will be done in M22 (D6.2: ‘Evaluation framework, plans and material - an update’). The key content of D6.1 is structured as follows: Chapter 1 is the introduction to the deliverable, specifying its purpose, the intended audience, and interrelations with other project activities. Chapter 2 introduces the project objectives related to the WP6 data collections. Chapter 3 provides a brief overview of each Use Case and Chapter 4 presents the various studies within the project including descriptions of the main actors, environment, vehicles, PANACEA sensors/technologies, and countermeasures. Chapter 5 describes the process of developing the evaluation framework for the project and presents the PANACEA evaluation framework. Chapters 6-18 then follow the steps defined in the evaluation framework. Chapters 6-11 describe the planning phase and present the Use Case Scenarios, Research Questions, Key Performance Indicators, study designs, data gathering tools, and data analysis plan. Chapters 12-14 describe the implementation phase, including pilot site preparations, data collection, and data delivery. Chapters 15-18 describe the data analysis phase and includes chapters about data analysis, results reporting, results consolidation, and impact assessment. Lastly, Chapter 19 provides the conclusions of the deliverable. The deliverable presents both a horizontal perspective of the pilot sites as well as more detailed descriptions of what will be included in the different studies. The general data gathering tools (objective and subjective) are identified and will be further refined in the update of the deliverable. A set of guidelines on practicalities and ethical aspects to take into consideration before and during data collection are presented. The update of the deliverable, planned for M22, will include the detailed evaluation protocols, with ready-made templates for pilot sites, questionnaires to use, performance criteria, indicators, log files to use, crucial timelines, etc. In addition, the final pilot and experimental plans will be defined and described per pilot site and type of evaluation activity.
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| 9. |
- Dahlman, Anna Sjörs, et al.
(författare)
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D6.2: Evaluation framework, plans and material - an update. Deliverable of the Horizon-2020 PANACEA project, Grant Agreement No. 953426
- 2023
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This deliverable presents the evaluation framework, plans and material for all data collections connected to work package 6 (WP6) of the PANACEA project. It describes the objectives of the studies and how they will be realised. The purpose of the PANACEA evaluation framework is to create a common framework to be used in all studies to make sure the data are collected in a way that makes it possible to consolidate the results at the end and to provide what is needed for impact analysis (WP7). The first version of the deliverable (D6.1: ‘Evaluation framework, plans and material´) had its focus on setting the framework and the work process. In this updated version, the focus is on the evaluation protocols for all studies, including templates for the pilot sites, questionnaires to use, key performance indicators (KPI), log files to use, crucial timelines, etc. The experimental plans are described per pilot site and type of evaluation activity. The key content of D6.2 is structured as follows: Chapter 1 is the introduction to the deliverable, specifying its purpose, the intended audience, and interrelations with other project activities. Chapter 2 introduces the project objectives related to the WP6 data collections. Chapter 3 provides a brief overview of each Use Case and Chapter 4 presents the various studies within the project including descriptions of the main actors, environment, vehicles, PANACEA sensors/technologies, and countermeasures. Chapter 5 describes the PANACEA evaluation framework. Chapters 6-15 then describe the steps defined in the evaluation framework. Chapters 6-11 include the planning phase and present the Use Case Scenarios, Research Questions, Key Performance Indicators, study designs, data gathering tools, and data analysis plan. Chapters 12-13 describe the implementation phase, including pilot site preparations, and data collection. Chapters 13-15 describe the data analysis phase and includes chapters about data delivery, data analysis, results reporting, results consolidation, and impact assessment. Lastly, Chapter 16 provides the conclusions of the deliverable. The deliverable presents both a horizontal perspective of the pilot sites as well as more detailed descriptions of what will be included in the different studies. The main text of the deliverable provides an overview of all studies and evaluations within PANACEA. Research questions and KPIs are defined for each study (Appendix III). The general data gathering tools (objective and subjective) are identified. The questionnaires used for the evaluations are included in Appendix IV. A set of guidelines on practicalities and ethical aspects to take into consideration before and during data collection are presented. Experimental plans for all WP6 data collections are included as appendices to the deliverable (Appendix II).
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| 10. |
- Flannagan, Carol A., et al.
(författare)
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Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones
- 2019
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This research project used the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study(NDS) to improve highway safety by using statistical descriptions of normal driving behavior to identify abnormal driving behaviors in work zones. SHRP2 data used in these analyses included 50 safety-critical events (SCEs) from work zones and 444 baseline events selected on a matched case-control design. Principal components analysis (PCA) was used to summarize kinematic data into “normal” and “abnormal”driving. Each second of driving is described by one point in three-dimensional principal component (PC) space;an ellipse containing the bulk of baseline points is considered “normal” driving. Driving segments without-of-ellipse points have a higher probability of being an SCE. Matched case-control analysis indicates that thespecific individual and traffic flow made approximately equal contributions to predicting out-of-ellipse driving. Structural Topics Modeling (STM) was used to analyze complex categorical data obtained from annotated videos.The STM method finds “words” representing categorical data variables that occur together in many events and describes these associations as “topics.” STM then associates topics with either baselines or SCEs. The STM produced 10 topics: 3 associated with SCEs, 5 associated with baselines, and 2 that were neutral. Distractionoccurs in both baselines and SCEs. Both approaches identify the role of individual drivers in producing situations where SCEs might arise. A countermeasure could use the PC calculation to indicate impending issues or specific drivers who may havehigher crash risk, but not to employ significant interventions such as automatically braking a vehicle without-of-ellipse driving patterns. STM results suggest communication to drivers or placing compliant vehicles in thetraffic stream would be effective. Finally, driver distraction in work zones should be discouraged.
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| 11. |
- Flannagan, Carol A.C., et al.
(författare)
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Mutual Recognition Methodology Development
- 2015
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Phase 1 of the Mutual Recognition Methodology Development (MRMD) project developed an approach to statistical modeling and analysis of field data to address the state of evidence relevant to mutual recognition of automotive safety regulations. Specifically, the report describes a methodology that can be used to measure evidence for the hypothesis that vehicles meeting EU safety standards would perform similarly to US-regulated vehicles in the US driving environment, and that vehicles meeting US safety standards would perform similarly to EU-regulated vehicles in the EU driving environment. As part of the project, we assessed the availability and contents of crash datasets from the US and the EU, as well as their collective ability to support the proposed statistical methodology.The report describes a set of three statistical approaches to “triangulate” evidence regarding similarity or differences in crash and injury risk associated with EU- and US-regulated vehicles. Approach 1, Seemingly Unrelated Regression, tests whether the models are identical and will also assess the capability of the data analysis to detect differences in the models, if differences exist.Approach 2, Consequences of Best Models, uses logistic regression to develop two separate models, one for EU risk and one for US risk, as a function of a set of predictors (i.e., crash, vehicle, and occupant conditions). The two models will then be exercised on a standard population for the EU and a standard population for the US. Approach 3, Evidence for Consequences, turns the question aroundto measures the overall evidence for each of a set of possible conclusions. Each conclusion is characterized by a range of relative risk on a single population. Evidence is measured using a weighted average of likelihoods for a large group of models that produce the same outcome. That evidence is then compared using Bayes Factors.
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| 12. |
- Hansson, Anders, et al.
(författare)
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Lane-Level Map Matching based on HMM
- 2021
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Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 6:3, s. 430-439
-
Tidskriftsartikel (refereegranskat)abstract
- Lane-level map matching is essential for autonomous driving. In this paper, we propose a Hidden Markov Model (HMM) for matching a trajectory of noisy GPS measurements to the road lanes in which the vehicle records its positions. To our knowledge, this is the first time that HMM is used for lanelevel map matching. Apart from GPS values, the model is further assisted by yaw rate data (converted to a lane change indicator signal) and visual cues in the form of the left and right lane marking types (dashed, solid, etc.). Having defined expressions for the HMM emission and transition probabilities, we evaluate our model to demonstrate that it achieves 95.1% recall and 3.3% median path length error for motorway trajectories.
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| 13. |
- Imberg, Henrik, 1991, et al.
(författare)
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Optimization of Two-Phase Sampling Designs With Application to Naturalistic Driving Studies
- 2022
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:4, s. 3575-88
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Tidskriftsartikel (refereegranskat)abstract
- Naturalistic driving studies (NDS) generate tremendous amounts of traffic data and constitute an important component of modern traffic safety research. However, analysis of the entire NDS database is rarely feasible, as it often requires expensive and time-consuming annotations of video sequences. We describe how automatic measurements, readily available in an NDS database, may be utilized for selection of time segments for annotation that are most informative with regards to detection of potential associations between driving behavior and a consecutive safety critical event. The methodology is illustrated and evaluated on data from a large naturalistic driving study, showing that the use of optimized instance selection may reduce the number of segments that need to be annotated by as much as 50%, compared to simple random sampling. IEEE
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| 14. |
- Itkonen, Teemu, 1985, et al.
(författare)
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Characterisation of Motorway Driving Style Using Naturalistic Driving Data
- 2020
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Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour. - : Elsevier BV. - 1369-8478. ; 69, s. 72-79
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Tidskriftsartikel (refereegranskat)abstract
- The study of measurable differences between drivers has ramifications for several subfields in traffic and transportation research. Better understanding of the variability in individual driving styles would be especially useful for understanding driver preferences, psychological mechanisms for vehicle control and for developing more realistic traffic simulations. In our study based on a large naturalistic data set, we investigated the driving style of 76 individuals driving in a motorway setting. We discovered that the majority of between-driver variation in keeping longitudinal and lateral safety margins, lane changing frequency, acceleration and speed preference, can be reduced to two dimensions, which we interpret as habitualised motives centred around mental effort and expediency.
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| 15. |
- Jing, Xiao, et al.
(författare)
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Safety benefit of cooperative control for heterogeneous traffic on-ramp merging
- 2022
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Ingår i: Transportation Safety and Environment. - : Oxford University Press (OUP). - 2631-6765 .- 2631-4428. ; 4:4
-
Tidskriftsartikel (refereegranskat)abstract
- The safety of heterogeneous traffic is a vital topic in the oncoming era of autonomous vehicles (AVs). The cooperative vehicle infrastructure system (CVIS) is considered to improve heterogeneous traffic safety by connecting and controlling AVs cooperatively, and the connected AVs are so-called connected and automated vehicles (CAVs). However, the safety impact of cooperative control strategy on the heterogeneous traffic with CAVs and human-driving vehicles (HVs) has not been well investigated. In this paper, based on the traffic simulator SUMO, we designed a typical highway scenario of on-ramp merging and adopted a cooperative control method for CAVs. We then compared the safety performance for two different heterogeneous traffic systems, i.e. AV and HV, CAV and HV, respectively, to illustrate the safety benefits of the cooperative control strategy. We found that the safety performance of the CAV and HV traffic system does not always outperform that of AV and HV. With random departSpeed and higher arrival rate, the proposed cooperative control method would decrease the conflicts significantly whereas the penetration rate is over 80%. We further investigated the conflicts in terms of the leading and following vehicle types, and found that the risk of a AV/CAV followed by a HV is twice that of a HV followed by another HV. We also considered the safety effect of communication failure, and found that there is no significant impact until the packet loss probability is greater than 30%, while communication delay's impact on safety can be ignored according to our experiments.
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| 16. |
- Johansson, Edvin, et al.
(författare)
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Scenario-based trajectory generation and density estimation towards risk analysis of autonomous vehicles
- 2023
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. ; , s. 1375-1380
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Konferensbidrag (refereegranskat)abstract
- A large amount of testing is needed to determine when autonomous vehicles are sufficiently safe. To achieve this goal, test cases should be representative of real-world driving but also designed to provide sufficient coverage of both frequent and rare events. This is a crucial step in finding potential high consequence events, failure borders of the Autonomous Driving (AD) function and accurate estimation of the corresponding residual risks. In this paper, we propose a new method to adapt generative models to generate vehicle trajectories that are representative of the ones collected from the real world. The method uses Non-Uniform Rational B-Splines (NURBS) combined with normalizing flows to build a statistical scenario model. The method allows us to estimate a joint probability density that can be used to evaluate the likelihood of different trajectory occurrences. We demonstrate the method for statistical modeling on the (smooth and abrupt) cut-in traffic scenario and we give an example of how the estimated joint probability distribution can be used to assess the risk (trajectory occurrence probability and criticality) for different test cases. The results can be used for accelerated testing purposes, where the aim is to sample the rare tests more frequently, but can also be used to calculate the failure probability of AD functions.
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| 17. |
- Kemp, Graham, 1965, et al.
(författare)
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Pathway and Protein Interaction Data: from XML to FDM Database
- 2004
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 3540213007 ; 2994, s. 212-219
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes our experience with the first steps towards integrating pathway and protein interaction data with other data sets within the framework of a federated database system based on the functional data model. We have made use of DTD and XML files produced by the BIND project. The DTD provides a specification for information about biomolecular interactions, complexes and pathways, and can be translated semi-automatically to a database schema. The load utility uses metadata derived from this schema to help identify data items of interest when recursively traversing a Prolog tree structure representing the XML data. We also show how derived functions can be used to make explicit those relationships that are present in data sets but which are not fully described in DTD files.
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| 18. |
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| 19. |
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| 20. |
- Lin, Amanda Yan, et al.
(författare)
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Combining Support Vector Regression with Scaling Methods for Highway Tollgates Travel Time and Volume Predictions
- 2017
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Ingår i: Proceedings of International Work-Conference on Time Series Analysis (ITISE 2017), Granada, 18-20 September 2017. - 9788417293017 ; 1, s. 411-421
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Konferensbidrag (refereegranskat)abstract
- Toll roads or controlled-access roads are very commonly used, e.g. in Asia. Drivers expect to drive smoother and faster on the toll roads compared to on regular roads. However, long queues on toll roads, particularly at the tollgates, often happen and create many problems. Beingable to accurately predict travel time and volume of the tollgates would allow appropriate measures to improve traffic flow and safety to be taken. This paper describes a novel investigation on the use of scaling methods with Support Vector Regression (SVR) for highway tollgates travel time and volume prediction tasks as well as an investigation of the most important features for these tasks. Experiments were done as part of the Knowledge Discovery and Data Mining (KDD) Cup 2017. Suitability of certain scaling methods for dfferent types of time series and reasoning why certain features are important for these tasks are also discussed.
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| 21. |
- Lin, Amanda Yan, et al.
(författare)
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Using Scaling Methods to Improve Support Vector Regression’s Performance for Travel Time and Volume Predictions
- 2018
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Ingår i: Time Series Analysis and Forecasting, Contributions to Statistics. - Cham : Springer International Publishing. - 9783319969435 ; , s. 115-127
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Konferensbidrag (refereegranskat)abstract
- Long queues often happen on toll roads, especially at the tollgates. These create many problems, including having an impact on the regular roads nearby. If travel time and traffic volume at the tollgates can be predicted accurately in advance, this would allow traffic authorities to take appropriate measures to improve traffic flow and the safety of road users. This paper describes a novel combination of scaling methods with Support Vector Machines for Regression (SVR) for travel time and tollgate volume prediction tasks, as part of the Knowledge Discovery and Data Mining (KDD) Cup 2017. A new method is introduced to handle missing data by utilising the structure of the road network. Moreover, experiments with reduced data were conducted to evaluate whether conclusions from combining scaling methods with SVR could be generalised.
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| 22. |
- Lind, Henrik, et al.
(författare)
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Investigating visually distracted driver reactions in rear-end crashes and near crashes based on 100-car study data
- 2012
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Ingår i: In D. de Waard, N. Merat, A.H. Jamson, Y. Barnard, and O.M.J. Carsten (Eds.) (2012). Human Factors of Systems and Technology. - 9789042304161 ; , s. 201-211
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Konferensbidrag (refereegranskat)abstract
- Rear-end crashes are common accident scenarios and account for approximately 30% of all police-reported accidents in the United States. Previous studies have shown that driver inattention just before the rear-end crashes or near crashes is a major contributing factor. To improve the development of active safety systems, which take into account driver inattention, it is important to understand when and how the driver reacts; from the moment the driver shifts state from being distracted to attentive and becomes aware of the potential threat. This paper investigates the reaction (braking, steering) selection that visually distracted drivers make in a critical rear-end crash situation using the 100-car naturalistic driving study data. A simple model describing the driver’s perception reaction time (PRT) based on headway distance to the forward vehicle is presented. The results presented in this paper can assist further studies where more data will be available and help elucidate how people react to critical near crashes and crashes on road.
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| 23. |
- Liu, Tong, et al.
(författare)
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Comparison of Car-Following Behavior in Terms of Safety Indicators Between China and Sweden
- 2020
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 21:9, s. 3696-3705
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Tidskriftsartikel (refereegranskat)abstract
- Understanding car-following behavior in different countries is essential for the design and development of autonomous driving and further development of active safety systems that can function well worldwide, in particular, in mixed traffic conditions. However, very few studies exist that compare car-following behaviors in different countries based on real driving data. This paper analyses the similarities and differences of drivers’ car-following behavior, in terms of time gap, gap distance, and time to collision (TTC), using both China and Sweden datasets from real road driving studies, in a bid to identify how these indicators affect drivers’ speed control in car-following situations. The results indicate that the highest frequency of gap distance is observed in the same value range in both datasets, while the highest frequency of time gap in the Sweden dataset is found at a lower value range than the corresponding value range in the China dataset. For both datasets, time gap is observed to be a more reliable indicator for car-following analysis than gap distance since it is less sensitive to speed variations. Furthermore, TTC in the low travel speed ranges (v < 50 km/h) tends to be steady in comparison with the TTC at other speed ranges, so the time gap in the high-speed ranges is (v > 90 km/h). Therefore, time gap is recommended as the safety indicator for car-following analysis in high-speed conditions, while a combination of time gap and TTC is recommended for low-speed conditions, especially on urban roads.
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| 24. |
- Liu, Tong, et al.
(författare)
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The Relationship between Different Safety Indicators in Car-following Situations
- 2018
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Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. ; , s. 1515-1520
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Konferensbidrag (refereegranskat)abstract
- Studying different aspects of car-following behavior is still of strong interests for many researchers, due to its usefulness in many applications, such as for further development of traffic simulators and active safety systems (e.g., Adaptive Cruise Control and Autonomous Emergency Braking). This paper investigates the relationships between several safety indicators (e.g., time gap, gap distance, time to collision) in car-following situations, and analyzes which of these indicators affect driver’s behavior in car-following situations and how. All analyses are done using real driving data collected in China. The paper also suggests parameters that can be used for defining, identifying, and extracting car-following events from real driving data. Results indicate that time gap is less sensitive to the variations in speed and road condition compared with gap distance in this test. TTC in the low speed range of subject-vehicle is found to be steady compared with other speed ranges, so is the time gap in the high speed range. Therefore, time gap is more suitable to be the safety indicator compared with gap distance in the future car-following research. Time gap is found to be more appropriate for the analysis of car following behavior in the high speed ranges, but both TTC and time gap should be used as part of the safety indicator for the low speed ranges.
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| 25. |
- Lu, Yichen, et al.
(författare)
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Analytical Method of Traffic Conflict at Urban Road Intersections Based on Risk Region
- 2021
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Ingår i: Tongji Daxue Xuebao/Journal of Tongji University. - 0253-374X. ; 49:7, s. 941-948
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Tidskriftsartikel (refereegranskat)abstract
- A two-stage method of traffic conflict analysis was proposed based on risk region. By using the inD dataset, traffic conflicts were recognized with the calculation of time to risk region(tTTR), and then the degree of traffic conflict risk was judged by risk region duration. Compared with the method based on time-to-collision(tTTC), the proposed method can not only identify rear-end conflicts and crossing conflicts more effectively, but also characterize the degree of traffic conflict risk at different times.
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