| 1. |
- Andersson Granberg, Tobias, 1973-, et al.
(författare)
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Supporting dispatch decisions for the fire and rescue services
- 2015
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Ingår i: 2015 IEEE 18th International Conference on Intelligent Transportation Systems. - : IEEE conference proceedings. - 9781467365956 ; , s. 2562-2567
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Konferensbidrag (refereegranskat)abstract
- Decision support tools for efficient dispatching of fire and rescue resources are developed and evaluated. The tools can give suggestions about which resources to dispatch to new accidents, and help the decision makers in evaluating the current preparedness for handling future accidents. The tools are evaluated using simulation game based experiments, with players from the fire and rescue services. The results indicate that the tools can help the fire and rescue services in identifying the closest resources to new accidents, and to select resources that preserve the preparedness in the area. However, the results also indicate that there is a risk that the tools increase the decision time.
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| 2. |
- Bengtsson, Hoai, et al.
(författare)
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Interaction Protocol for Highway Platoon Merge
- 2015
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Ingår i: 2015 IEEE 18th International Conference on Intelligent Transportation Systems. - Los Alamitos : IEEE. - 9781467365963 - 9781467365956 ; , s. 1971-1976
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Konferensbidrag (refereegranskat)abstract
- An interaction protocol for cooperative platoon merge on highways is proposed. The interaction protocol facilitates a challenge scenario for the Grand Cooperative Driving Challenge (GCDC) 2016, where two platoons running on separate lanes merge into one platoon due to a roadwork in one of the lanes. Detailed interaction procedures, described with state machines of each vehicle are presented. A communication message set is designed to support platoon controllers to perform safe and efficient manoeuvres. © 2015 IEEE.
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| 3. |
- Berger, Christian, 1980, et al.
(författare)
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Large-Scale Evaluation of an Active Safety Algorithm with EuroNCAP and US NCAP Scenarios in a Virtual Test Environment – An Industrial Case Study
- 2015
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Ingår i: Proceedings of 18th IEEE International Conference on Intelligent Transportation Systems. - : IEEE. - 9781467365956
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Konferensbidrag (refereegranskat)abstract
- Context: Recently, test protocols from organizations like European New Car Assessment Programme (EuroNCAP) were extended to also cover active safety systems. Objective: The official EuroNCAP test protocol for Autonomous Emergency Braking (AEB)/Forward Collision Warning (FCW) systems explicitly defines to what extent a Vehicle-Under-Test (VUT) is allowed to vary in its lateral position. In addition, the United States New Car Assessment Programme (US NCAP) test protocol has broader tolerance ranges. The goal for automotive OEMs is to understand the impact of such allowed variations on a the overall vehicle's performance. Method: A simulation-based approach is outlined that allows systematic, large-scale analysis of such influences to effectively plan time-consuming and resource-intense real-world vehicle tests. Our models allow a profound analysis of an AEB algorithm by modeling and conducting more than 3,000 simulation runs with EuroNCAP's dynamic CCRm and CCRb scenarios including those with adopted USNCAP parameters. Results: Our structured analysis of such test procedures involving dynamic actors is the first of its kind in a relevant industrial setting. Several anomalies were unveiled under US NCAP conditions to support real-world test runs. Hence, we could show that the proposed method supports all possible scenarios in AEB consumer tests and scales as we had to timely process approx. 7.7GB of simulation data. Conclusion: To achieve the expected performance and to study a system's behavior in potential misuse cases from a functional point of view, large scale, model-based simulations complement traditional testing on proving ground.
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| 4. |
- Caltagirone, Luca, 1983, et al.
(författare)
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Truck Platooning Based on Lead Vehicle Speed Profile Optimization and Artificial Physics
- 2015
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC 2015. - 9781467365956 ; 2015 October, s. 394-399
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Konferensbidrag (refereegranskat)abstract
- - Several approaches to truck platooning over varying road topographies are introduced, evaluated, and compared. A simple, stochastic optimization procedure was applied to the lead vehicle speed profiles (covering sections of 10 km), resulting in average lead vehicle fuel savings of around 15.4% relative to standard cruise control. Moreover, several models involving artificial physics were evaluated for the actual platooning, i.e. for the motion of the vehicles following the lead vehicle, with the aim of minimizing the total fuel consumption of the entire platoon. One such model, based on modified artificial gravity, was found to slightly outperform a more standard approach involving adaptive cruise control, while maintaining safety and coherence of the platoon.
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| 5. |
- Eilers, S., et al.
(författare)
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COMPANION-Towards Co-operative Platoon Management of Heavy-Duty Vehicles
- 2015
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. - : IEEE. - 9781467365956 ; , s. 1267-1273
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Konferensbidrag (refereegranskat)abstract
- The objective of the EU project COMPANION is to develop co-operative mobility technologies for supervised vehicle platooning, in order to improve fuel efficiency and safety for goods transport. The potential social and environmental benefits inducted by heavy-duty vehicle platoons have been largely proven. However, until now, the creation, coordination, and operation of such platoons have been mostly neglected. In addition, the regulation and standardization of coordinated platooning, together with its acceptance by the end-users and the society need further attention and research. In this paper we give an overview over the project and present the architecture of the off-board and onboard platforms of the COMPANION cooperative platoon management system. Furthermore, the consortium reports on the first results of the human factors for platooning, legislative analysis of platooning aspects, clustering and optimization of platooning plans and prediction of congestion due to planned special events. Finally, we present the method of validation of the system via simulation and trials.
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| 6. |
- Gundlegård, David, 1978-, et al.
(författare)
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Travel Time and Point Speed Fusion Based on a Macroscopic Traffic Model and Non-linear Filtering
- 2015
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Ingår i: 2015 IEEE 18th International Conference on Intelligent Transportation Systems. - : IEEE conference proceedings. - 9781467365956 ; , s. 2121-2128
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Konferensbidrag (refereegranskat)abstract
- The number and heterogeneity of traffic sensors are steadily increasing. A large part of the emerging sensors are measuring point speeds or travel times and in order to make efficient use of this data, it is important to develop methods and frameworks for fusion of point speed and travel time measurements in real-time. The proposed method combines a macroscopic traffic model and a non-linear filter with a new measurement model for fusion of travel time observations in a system that uses the velocity of cells in the network as state vector. The method aims to improve the fusion efficiency, especially when travel time observations are relatively long compared to the spatial resolution of the estimation framework. The method is implemented using the Cell Transmission Model for velocity (CTM-v) and the Ensemble Kalman Filter (EnKF) and evaluated with promising results in a test site in Stockholm, Sweden, using point speed observations from radar and travel time observations from taxis.
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| 7. |
- Jin, Junchen, et al.
(författare)
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Adaptive Group-Based Signal Control Using Reinforcement Learning with Eligibility Traces
- 2015
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. - : IEEE conference proceedings. - 9781467365956 - 9781467365956 - 9781467365956 - 9781467365956 ; , s. 2412-2417
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Konferensbidrag (refereegranskat)abstract
- Group-based signal controllers are widely deployed on urban networks in the Nordic countries. However, group-based signal controls are usually implemented with rather simple timing logics, e.g. vehicle actuated timing. In addition, group-based signal control systems with pre-defined signal parameter settings show relatively poor performances in a dynamically changed traffic environment. This study, therefore, presents an adaptive group-based signal control system capable of changing control strategies with respect to non-stationary traffic demands. In this study, signal groups are formulated as individual agents. The signal group agent learns from traffic environments and makes intelligent timing decisions according to the perceived system states. Reinforcement learning with multiple-step backups is applied as the learning algorithm. Agents on-line update their knowledge based on a sequence of states during the learning process rather than purely on the basis of single previous state. The proposed signal control system is integrated into a software-in-the-loop simulation (SILS) framework for evaluation purpose. In the testbed experiments, the proposed adaptive group-based control system is compared to a benchmark signal control system, the well-established group-based fixed-time control system. The simulation results demonstrate that learning-based and adaptive group-based signal control system owns its advantage in dealing with dynamic traffic environments in terms of improving traffic mobility efficiency.
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| 8. |
- Kleyko, Denis, et al.
(författare)
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Comparison of Machine Learning Techniques for Vehicle Classification using Road Side Sensors
- 2015
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Ingår i: Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems. - Piscataway, NJ : IEEE Communications Society. - 9781467365956 ; , s. 572-577
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Konferensbidrag (refereegranskat)abstract
- The main contribution of this paper is a comparison of different machine learning algorithms for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard using measurements of road surface vibrations and magnetic field disturbances caused by vehicles. The algorithms considered are logistic regression, neural networks, and support vector machines. They are evaluated on a large dataset, consisting of 3074 samples and hence, a good estimate of the actual classification rate is obtained. The results show that for the considered classification problem logistic regression is the best choice with an overall classification rate of 93.4%.
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| 9. |
- Koller, Julian Phillip Johann, et al.
(författare)
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Fuel-Efficient Control of Merging Maneuvers for Heavy-Duty Vehicle Platooning
- 2015
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. - : IEEE conference proceedings. - 9781467365956 - 9781467365956 - 9781467365956 - 9781467365956 ; , s. 1702-1707
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Konferensbidrag (refereegranskat)abstract
- The formation of groups of closely-spaced heavy-duty vehicles, known as platoons, reduces the overall aerodynamic drag and therefore leads to reduced fuel consumption and reduced greenhouse gas emissions. This paper focuses on the optimal control of merging maneuvers for the formation of a growing platoon. Hereto, the merging problem is formulated as a hybrid optimal control problem and an algorithm for the computation of optimal merging times and corresponding optimal vehicle trajectories is developed by exploiting an extension of Pontryagin's maximum principle. Moreover, a model predictive control approach on the basis of this algorithm is presented that makes the merging maneuvers robust to modelling uncertainties and external disturbances. The results are illustrated by evaluating a scenario involving three vehicles, which indicates fuel savings of up to 13% with respect to the vehicles driving alone.
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| 10. |
- Li, G., et al.
(författare)
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Driving Maneuvers Analysis Using Naturalistic Highway Driving Data
- 2015
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Ingår i: IEEE 18th International Conference on Intelligent Transportation Systems (ITSC), 2015. - 2153-0009. - 9781467365956 ; 2015-October, s. 1761-1766
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Konferensbidrag (refereegranskat)abstract
- - Accounting about 70% of vehicle miles on roadways, highway driving is a critical issue in traffic safety deployment. Of the various maneuvers that comprise the highly complex driving task, each one requires understanding on the connections between driving states, vehicle performance and drivers' actions. This paper attempts to flesh out a complete picture of driving maneuvers on highways. Eighteen drivers participated in this study. They drove an instrumented vehicle on highways to accumulate 2,600 km naturalistic driving data. The data were segmented and classified into 11 maneuver groups manually. Analysis on the maneuvers revealed that: 1) A maneuver transition probabilities model was proposed. According to this model, 7 typical driving patterns were drawn based on the transition probabilities. Transition events pertaining to approaching/following/lane changing accounted for 95% of all the highway transition events. 2) The durations were 7.6/6.6 s and 7.1/7.0 s for free left/right lane changes and overtake from left/right lane changes, respectively. The numbers were 22.5, 21.4 and 16.3 s for far, middle and near following maneuvers, respectively. Statistical significances were found within both groups. 3) How drivers behave in each maneuver was analyzed. Drivers drove faster in free lane changes than did in overtake lane changes. For overtake lane changes, two driving patterns were observed: accelerate to change lane and decelerate to change lane.
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