| 1. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Cooperative merging strategy between connected autonomous vehicles in mixed traffic
- 2022
-
Ingår i: IEEE Open Journal of Intelligent Transportation Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2687-7813. ; 3, s. 825-837
-
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.
|
|
| 2. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Mathematical Definitions of Scene and Scenario for Analysis of Automated Driving Systems in Mixed-Traffic Simulations
- 2021
-
Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 6:2, s. 366-375
-
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.
|
|
| 3. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow
- 2023
-
Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 6:1, s. 1-15
-
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.
|
|
| 4. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Safety-centred analysis of transition stages to traffic with fully autonomous vehicles
- 2020
-
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.
|
|
| 5. |
- Andreotti, Eleonora, 1988, et al.
(författare)
-
Simulation-based impact projection of autonomous vehicle deployment using real traffic flow
- 2021
-
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.
|
|
| 6. |
- Aramrattana, Maytheewat, 1988-, et al.
(författare)
-
Behavioral adaptation of drivers when driving among automated vehicles
- 2022
-
Ingår i: Journal of Intelligent and Connected Vehicles. - : Emerald Publishing. - 2399-9802. ; 5:3, s. 309-315
-
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.
|
|
| 7. |
- Bärgman, Jonas, 1972, et al.
(författare)
-
On data security and analysis platforms for analysis of naturalistic driving data
- 2011
-
Ingår i: Proceedings of the 8th European Congress and Exhibition on Intelligent Transport Systems and Services, June 2011, Lyon.
-
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.
|
|
| 8. |
- Dahlman, Anna Sjörs, et al.
(författare)
-
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.
|
|
| 9. |
- Dahlman, Anna Sjörs, et al.
(författare)
-
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).
|
|
| 10. |
- Flannagan, Carol A., et al.
(författare)
-
Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones
- 2019
-
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.
|
|
