| 1. |
- Engelson, Leonid
(författare)
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On dynamics of traffic queues in a road network with route choice based on real time traffic information
- 2003
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Ingår i: Transportation Research Part C. - : Elsevier BV. - 0968-090X .- 1879-2359. ; 11:2, s. 161-183
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Tidskriftsartikel (refereegranskat)abstract
- Introducing real time traffic information into transportation network makes it necessary to consider development of queues and traffic flows as a dynamic process. This paper initiates a theoretical study of conditions under which this process is stable. A model is presented that describes within-one-day development of queues when drivers affected by real-time traffic information choose their paths en route. The model is reduced to a system of differential equations with delay. Equilibrium points of the system correspond to constant queue lengths. Stability of the system is investigated using characteristic values of the linearised minimal face flow. A traffic network example illustrating the method is provided.
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| 2. |
- Marell, Agneta, 1964-, et al.
(författare)
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Intelligent transportation system and traffic safety : – drivers perception and acceptance of electronic speed checkers
- 1999
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Ingår i: Transportation Research Part C. - : Elsevier. - 0968-090X .- 1879-2359. ; 7:2-3, s. 131-147
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Tidskriftsartikel (refereegranskat)abstract
- Intelligent Transportation System (ITS) can play an important role in reducing risks and increasing traffic safety. Discussion as to whether a technological approach or a behavioral approach is the right way to achieve a safer traffic environment forms a point of departure for this paper. On the one hand, there are the technicians who emphasize technology as the way towards safer traffic. Behaviorists, on the other hand, view the drivers’ behavior as fundamental and argue that education and incentive-oriented policies are essential in order to influence the driver and therefore increase traffic safety. Independent of the approach advocated a successful outcome of either a technological improvement, or an information campaign, has to be based on a high level of acceptance among potential users. In order to increase traffic safety, it is therefore essential to recognize driver motivation and attitudes. In this paper we focus on drivers’ attitudes towards risk, traffic safety and safety measures. A study of drivers’ attitudes and acceptance of an electronic device for speed checking (which the drivers tested for nine months) indicated a high acceptance level. The drivers perceived that they had both become more aware of traffic regulations and behaved in accordance with safety regulations.
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| 3. |
- Vythoulkas, P. C., et al.
(författare)
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Modeling discrete choice behavior using concepts from fuzzy set theory, approximate reasoning and neural networks
- 2003
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Ingår i: Transportation Research Part C. - 0968-090X .- 1879-2359. ; 11:1, s. 51-73
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Tidskriftsartikel (refereegranskat)abstract
- Models of discrete choice analysis are usually based on the random utility framework. They assume that decision makers make decisions that maximize their utility. Alternative formulations of the problem have also been proposed in the literature. These approaches model the decision makers' perceptions of the attributes of the various alternatives using fuzzy sets and linguistic variables, and the decision process itself, using concepts from approximate reasoning and fuzzy control. The underlying assumption is that decision makers use a few simple rules that relate their vague perceptions of the various attributes to their preferences towards the available alternatives. The paper extends this approach by incorporating rule weights, which capture the importance of a particular rule in the decision process. It also presents an approach for calibrating the weights using concepts from neural networks. A case study, involving mode choice, is used to demonstrate the potential of the approach and compare it to alternative formulations and methodologies.
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| 4. |
- Abrahamsson, Lars, et al.
(författare)
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An electromechanical moving load fixed node position and fixed node number railway power supply systems optimization model
- 2013
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Ingår i: Transportation Research Part C. - : Elsevier BV. - 0968-090X .- 1879-2359. ; 30, s. 23-40
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an optimization model for simulations of railway power supply systems. It includes detailed power systems modeling, train movements in discretized time considering running resistance and other mechanical constraints, and the voltage-drop-induced reduction of possible train tractive forces. The model has a fixed number of stationary power system nodes, which alleviates optimized operation overtime. The proposed model uses SOS2 (Special Ordered Sets of type 2) variables to distribute the train loads to the two most adjacent power system nodes available. The impacts of the number of power system nodes along the contact line and the discretized time step length on model accuracy and computation times are investigated. The program is implemented in GAMS. Experiences from various solver choices are also discussed. The train traveling times are minimized in the example. Other studies could e.g. consider energy consumption minimization. The numerical example is representative for a Swedish decentralized, rotary-converter fed railway power supply system. The proposed concept is however generalizable and could be applied for all kinds of moving load power system studies.
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| 5. |
- Ahlström, Christer, et al.
(författare)
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Fit-for-duty test for estimation of drivers sleepiness level: Eye movements improve the sleep/wake predictor
- 2013
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Ingår i: Transportation Research Part C. - : Elsevier. - 0968-090X .- 1879-2359. ; 26, s. 20-32
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Tidskriftsartikel (refereegranskat)abstract
- Driver sleepiness contributes to a considerable proportion of road accidents, and a fit-for-duty test able to measure a drivers sleepiness level might improve traffic safety. The aim of this study was to develop a fit-for-duty test based on eye movement measurements and on the sleep/wake predictor model (SWP, which predicts the sleepiness level) and evaluate the ability to predict severe sleepiness during real road driving. Twenty-four drivers participated in an experimental study which took place partly in the laboratory, where the fit-for-duty data were acquired, and partly on the road, where the drivers sleepiness was assessed. A series of four measurements were conducted over a 24-h period during different stages of sleepiness. Two separate analyses were performed; a variance analysis and a feature selection followed by classification analysis. In the first analysis it was found that the SWP and several eye movement features involving anti-saccades, pro-saccades, smooth pursuit, pupillometry and fixation stability varied significantly with different stages of sleep deprivation. In the second analysis, a feature set was determined based on floating forward selection. The correlation coefficient between a linear combination of the acquired features and subjective sleepiness (Karolinska sleepiness scale, KSS) was found to be R = 0.73 and the correct classification rate of drivers who reached high levels of sleepiness (KSS andgt;= 8) in the subsequent driving session was 82.4% (sensitivity = 80.0%, specificity = 84.2% and AUC = 0.86). Future improvements of a fit-for-duty test should focus on how to account for individual differences and situational/contextual factors in the test, and whether it is possible to maintain high sensitive/specificity with a shorter test that can be used in a real-life environment, e.g. on professional drivers.
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| 6. |
- Anand, N., et al.
(författare)
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Validation of an agent based model using a participatory simulation gaming approach : The case of city logistics
- 2016
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Ingår i: Transportation Research Part C. - : Elsevier. - 0968-090X .- 1879-2359. ; 71, s. 489-499
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Tidskriftsartikel (refereegranskat)abstract
- Agent-based modeling is used for simulating the actions and interactions of autonomous entities aiming to assessing their effects on the system as a whole. At an abstract level, an agent-based model (ABM) is a representation of the many simple agents and interactions among them. The decision making of the agents is based on the rules given to them. In an ABM, the model output is the result of internal decision-making and may differ with alteration in the decision path. On the contrary, with the set of rules embedded in agents, their behavior is modeled to take a ‘certain action’ in a ‘certain situation’. It suggests that the internal decision making behavior of agents is truly responsible for the model output and thus it cannot be ignored while validating ABMs. This research article focuses on the validating agents’ behavior by evaluating decision-making processes of agents. For this purpose, we propose a validation framework based on a participatory simulation game. Using this framework we engage a human player (i.e. a domain stakeholder) to allow us to collect information about choices and validate the behavior of an individual agent. A proof-of-concept game is developed for a city logistics ABM to test the framework.
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| 7. |
- Antoniou, C., et al.
(författare)
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Dynamic data-driven local traffic state estimation and prediction
- 2013
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Ingår i: Transportation Research Part C. - : Elsevier BV. - 0968-090X .- 1879-2359. ; 34, s. 89-107
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Tidskriftsartikel (refereegranskat)abstract
- Traffic state prediction is a key problem with considerable implications in modern traffic management. Traffic flow theory has provided significant resources, including models based on traffic flow fundamentals that reflect the underlying phenomena, as well as promote their understanding. They also provide the basis for many traffic simulation models. Speed-density relationships, for example, are routinely used in mesoscopic models. In this paper, an approach for local traffic state estimation and prediction is presented, which exploits available (traffic and other) information and uses data-driven computational approaches. An advantage of the method is its flexibility in incorporating additional explanatory variables. It is also believed that the method is more appropriate for use in the context of mesoscopic traffic simulation models, in place of the traditional speed-density relationships. While these general methods and tools are pre-existing, their application into the specific problem and their integration into the proposed framework for the prediction of traffic state is new. The methodology is illustrated using two freeway data sets from Irvine, CA, and Tel Aviv, Israel. As the proposed models are shown to outperform current state-of-the-art models, they could be valuable when integrated into existing traffic estimation and prediction models.
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| 8. |
- Börjesson, Maria, 1974-, et al.
(författare)
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The economics of electric roads
- 2021
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Ingår i: Transportation Research Part C. - : Pergamon-Elsevier Science Ltd. - 0968-090X .- 1879-2359. ; 125
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we present a method for evaluating social benefits of electric roads and apply it to the Swedish highway network. Together with estimated investments costs this can be used to produce a cost benefit analysis. An electric road is characterized by high economies of scale (high investment cost and low marginal cost) and considerable economies of scope (the benefit per kilometre electric road depends on the size of the network), implying that the market will produce a smaller network of electric roads, or charge higher prices for its use, than what is welfare optimal. For this reason, it is relevant for governments to consider investing in electric roads, making the cost-benefit analysis a key decision support. We model the behaviour of the carriers using the Swedish national freight model system, SAMGODS, determining the optimal shipment sizes and optimal transport chains, including mode and vehicle type. We find that if the user charge is set as to optimize social welfare, the revenue will not fully cover the investment cost of the electric road. If they are instead set to optimize profit, we find that the revenue will cover the costs if the electric road network is large enough. Electric roads appear to provide a cost-effective means to significantly reduce carbon emissions from heavy trucks. In a scenario where the expansion connects the three biggest cities in Sweden, emissions will be cut by one-third of the overall emissions from heavy trucks in Sweden. The main argument against a commitment to electric roads is that investment and maintenance costs are uncertain and that, in the long run, battery development or hydrogen fuel cells can reduce the benefit of such roads.
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| 9. |
- Carrasco Limeros, Sandra, et al.
(författare)
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Towards explainable motion prediction using heterogeneous graph representations
- 2023
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Ingår i: Transportation Research, Part C: Emerging Technologies. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0968-090X .- 1879-2359. ; 157
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Tidskriftsartikel (refereegranskat)abstract
- Motion prediction systems play a crucial role in enabling autonomous vehicles to navigate safely and efficiently in complex traffic scenarios. Graph Neural Network (GNN)-based approaches have emerged as a promising solution for capturing interactions among dynamic agents and static objects. However, they often lack transparency, interpretability and explainability — qualities that are essential for building trust in autonomous driving systems. In this work, we address this challenge by presenting a comprehensive approach to enhance the explainability of graph-based motion prediction systems. We introduce the Explainable Heterogeneous Graph-based Policy (XHGP) model based on an heterogeneous graph representation of the traffic scene and lane-graph traversals. Distinct from other graph-based models, XHGP leverages object-level and type-level attention mechanisms to learn interaction behaviors, providing information about the importance of agents and interactions in the scene. In addition, capitalizing on XHGP's architecture, we investigate the explanations provided by the GNNExplainer and apply counterfactual reasoning to analyze the sensitivity of the model to modifications of the input data. This includes masking scene elements, altering trajectories, and adding or removing dynamic agents. Our proposal advances towards achieving reliable and explainable motion prediction systems, addressing the concerns of users, developers and regulatory agencies alike. The insights gained from our explainability analysis contribute to a better understanding of the relationships between dynamic and static elements in traffic scenarios, facilitating the interpretation of the results, as well as the correction of possible errors in motion prediction models, and thus contributing to the development of trustworthy motion prediction systems. The code to reproduce this work is publicly available at https://github.com/sancarlim/Explainable-MP/tree/v1.1.
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| 10. |
- Chen, C., et al.
(författare)
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The promises of big data and small data for travel behavior (aka human mobility) analysis
- 2016
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Ingår i: Transportation Research Part C. - : Elsevier. - 0968-090X .- 1879-2359. ; 68, s. 285-299
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Tidskriftsartikel (refereegranskat)abstract
- The last decade has witnessed very active development in two broad, but separate fields, both involving understanding and modeling of how individuals move in time and space (hereafter called "travel behavior analysis" or "human mobility analysis"). One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists. Researchers in these two fields work with different datasets, apply different methodologies, and answer different but overlapping questions. It is our view that there is much, hidden synergy between the two fields that needs to be brought out. It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations between the two. It is our hope that this paper will stimulate many future cross-cutting studies that involve researchers from both fields.
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