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| 2. |
- Jin, Junchen, et al.
(författare)
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A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation
- 2017
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Ingår i: Advances in Engineering Software. - : Elsevier. - 0965-9978 .- 1873-5339. ; 114, s. 348-360
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Tidskriftsartikel (refereegranskat)abstract
- Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is a widely used tool to represent traffic system in engineering applications. The increased traffic congestion in urban areas and their impacts require more efficient controls and management. While the effectiveness of control schemes highly depends on accurate traffic model and appropriate control settings, optimization techniques play a central role for determining the control parameters in traffic planning and management applications. However, there is still a lack of research effort on the scientific computing framework for optimizing traffic control and operations and facilitating real planning and management applications. To this end, the present study proposes a model-based optimization framework to integrate essential components for solving road traffic control problems in general. In particular, the framework is based on traffic simulation models, while the solution needs extensive computation during the engineering optimization process. In this work, an advanced genetic algorithm, extended by an external archive for storing globally elite genes, governs the computing framework, and in application it is further enhanced by a sampling approach for initial population and utilizations of adaptive crossover and mutation probabilities. The final algorithm shows superior performance than the ordinary genetic algorithm because of the reduced number of fitness function evaluations in engineering applications. To evaluate the optimization algorithm and validate the whole software framework, this paper illustrates a detailed application for optimization of traffic light controls. The study optimizes a simple road network of two intersections in Stockholm to demonstrate the model-based optimization processes as well as to evaluate the presented algorithm and software performance.
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| 3. |
- Jin, Junchen
(författare)
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Advance Traffic Signal Control Systems with Emerging Technologies
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Nowadays, traffic congestion poses critical problems including the undermined mobility and sustainability efficiencies. Mitigating traffic congestions in urban areas is a crucial task for both research and in practice. With decades of experience in road traffic controls, there is still room for improving traffic control measures; especially with the emerging technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and Big Data. The focus of this thesis lies in the development and implementation of enhanced traffic signal control systems, one of the most ubiquitous and challenging traffic control measures.This thesis makes the following major contributions. Firstly, a simulation-based optimization framework is proposed, which is inherently general in which various signal control types, and different simulation models and optimization methods can be integrated. Requiring heavy computing resources is a common issue of simulation-based optimization approaches, which is addressed by an advanced genetic algorithm and parallel traffic simulation in this study.The second contribution is an investigation of an intelligent local control system. The local signal control operation is formulated as a sequential decision-making process where each controller or control component is modeled as an intelligent agent. The agents make decisions based on traffic conditions and the deployed road infrastructure, as well as the implemented control scheme. A non-parametric state estimation method and an adaptive control scheme by reinforcement learning (RL) are introduced to facilitate such an intelligent system.The local intelligence is expanded to an arterial road using a decentralized design, which is enabled by a hierarchical framework. Then, a network of signalized intersections is operated under the cooperation of agents at different levels of hierarchy. An agent at a lower level is instructed by the agent at the next higher level toward a common operational goal. Agents at the same level can communicate with their neighbors and perform collective behaviors.Additionally, a multi-objective RL approach is in use to handle the potential conflict between agents at different hierarchical levels. Simulation experiments have been carried out, and the results verify the capabilities of the proposed methodologies in traffic signal control applications. Furthermore, this thesis demonstrates an opportunity to employ the systems in practice when the system is programmed on an intermediate hardware device. Such a device can receive streaming detection data from signal controller hardware or the simulation environment and override the controlled traffic lights in real time.
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| 4. |
- Jin, Junchen, et al.
(författare)
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An intelligent control system for traffic lights with simulation-based evaluation
- 2017
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Ingår i: Control Engineering Practice. - : Elsevier. - 0967-0661 .- 1873-6939. ; 58, s. 24-33
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces an intelligent control system for traffic signal applications, called Fuzzy Intelligent Traffic Signal (FITS) control. It provides a convenient and economic approach to improve existing traffic light infrastructure. The control system is programmed on an intermediate hardware device capable of receiving messages from signal controller hardware as well as overriding traffic light indications during real-time operations. Signal control and optimization toolboxes are integrated into the embedded software in the FITS hardware device. A fuzzy logic based control has been implemented in FITS. In order to evaluate the effects of FITS system, this study attempts to develop a computational framework to evaluate FITS system using microscopic traffic simulation. A case study is carried out, comparing different commonly used signal control strategies with the FITS control approach. The simulation results show that the control system has the potential to improve traffic mobility, compared to all of the tested signal control strategies, due to its ability in generating flexible phase structures and making intelligent timing decisions. In addition, the effects of detector malfunction are also investigated in this study. The experiment results show that FITS exhibits superior performance than several other controllers when a few detectors are out-of-order due to its self-diagnostics feature.
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| 5. |
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| 6. |
- Kosonen, Iisakki, et al.
(författare)
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Simulation of freeway driving behaviour
- 2000
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Ingår i: VTI:s och KFB:s forskardagar. - Linköping : Statens väg- och transportforskningsinstitut. ; , s. 181-203
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Kosonen, Iisakki, et al.
(författare)
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The potential of microscopic simulation in traffic safety and conflict studies
- 2001
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Ingår i: Road Safety on Three Continents in Pretoria, South Africa, 20-22 September 2000. - Linköping : Statens väg- och transportforskningsinstitut. ; , s. 786-795
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Microscopic traffic simulation has been successfully used in evaluation of traffic efficiency and emissions, but not yet widely in studies of traffic safety aspects. This paper will discuss the potential of traffic safety simulation based on experiences from simulation studies in two research laboratories that were using very different types of traffic simulators. TRANSIMS (Transportation Analysis and Simulation System) is a high-speed parallel micro simulator that allows simulation of large metropolitan areas on microscopic level. It utilises synthetic populations to create the traffic demand and cellular automata for high-speed parallel simulation of traffic flows. HUTSIM is a very different kind of microscopic simulator. The object-oriented HUTSIM model is built for very high precision simulation of interactions between vehicles, pedestrians, traffic environment and traffic control. Because the high fidelity of modelling requires lot of computing power, very large networks cannot be simulated. The paper explains the difficulties in introducing safety and behavioural aspects into existing traffic simulation programs. The use of HUTSIM in conflict studies is presented together with the development work carried out. TRANSIMS has been used in the estimate of accidents in large networks and the paper presents this work.
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| 8. |
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| 9. |
- Nefedov, Evgeny, et al.
(författare)
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Energy efficient traffic-based street lighting automation
- 2014
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Ingår i: 2014 IEEE International Symposium on Industrial Electronics (ISIE 2014). - Piscataway, NJ : IEEE Communications Society. ; , s. 1718-1723
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Konferensbidrag (refereegranskat)abstract
- The emerging LED technology enables intelligent street lighting that is based on sensing individual vehicles and dimming street lights accordingly. The potential energy savings are considerable, exceeding 50% on roads with low traffic. A possible reason why such applications are not yet emerging are financial uncertainties about the size of the savings, which are needed to motivate the investment. Another barrier to adoption are uncertainties about whether proposed approaches meet standards and regulations for traffic safety. In this paper, an energy efficient street lighting design that meets regulations for rural roads is implemented with the IEC 61499 distributed function block architecture. The intelligent lighting is co-simulated against a traffic simulation using cellular automata. Virtual metering in the IEC 61499 application is used to quantify energy savings in simulation scenarios with different traffic volumes. Across a range of traffic volumes representative of rural roads, our simulations indicate that smart dimming can deliver energy savings of 14% to 70%, with savings increasing as traffic density decreases.
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| 10. |
- Wahlstedt, Johan, 1978-
(författare)
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Evaluation of bus priority strategiesin coordinated traffic signal systems
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Increasing congestion and environmental concerns have evoked an interest in promoting urban Public Transport (PT) the last decades. In 2012 the City of Stockholm adopted an “Urban mobility strategy” stating that public transport, cycling and walking should be prioritised over cars in central Stockholm. One of the most important factors influencing the modal choice is the travel time ratio between car and PT travel. According to earlier studies Public Transport Traffic Signal Priority (PTSP) can reduce travel times for public transport with only small negative impacts on other traffic. Conditional PTSP can also help to regulate the PT service. Thus PTSP may support drivers’ decision to change travel mode from car to PT, thus supporting adopted policy goals.Conventional control strategies for coordinated traffic signals have pre-set timings based on traffic surveys. Some traffic adaptation based on real time detector actuations can also take place within the frames of the pre-set cycle time. PTSP changes the signal timings, within pre-set limits, when a PT vehicle is detected. Self-optimising control strategies use a traffic model to predict the traffic flows from traffic counts, and determine the signal changes in real-time by minimising a cost function including delay, number of stops etc. PTSP is included directly in the optimisation by giving PT vehicles a higher weight compared to cars.In this thesis the fundamentals of signal control theory are reviewed as well as unconditional and conditional PTSP criteria and strategies. A simulation based method for evaluation of impacts of different PTSP strategies in coordinated controlled traffic signals is implemented. The simulation setup includes Software-In-the-Loop (SIL) signal controller simulators running the same control logic as used in field. Such simulation models can be useful to test and fine tune PTSP before being implemented in field. Simulations with a SIL setup also enable comparisons of signal control strategies or systems on equal terms, not practically or economically possible in field studies. The implemented SIL simulation model was used to evaluate the impacts on buses and other traffic from the different PTSP functions used in the “PRIBUSS” PTSP method. Short green time extensions showed travel time reductions for buses, with almost no travel time increase for other traffic.Long green time extensions gave somewhat larger benefits for the buses, but more delay to other traffic. Red truncation gave less travel time savings to the prioritised buses and more extra delay for cross street traffic, compared to green extensions. Double red truncation and Extra phase showed some additional travel time savings to the buses, but had the largest negative impact on other traffic. A combination of PRIBUSS functions showed the best results. Depending on the structure of the signal coordination and the location of the bus stops different PTSP functions may be needed.Based on the conclusions from the evaluation of the different PRIBUSS functions a conditional “differential on-time-status” based PTSP strategy was proposed and tested in the SIL simulation environment. The proposed method is focusing on direct travel time savings as well as on reduced bus bunching.The two self-optimising signal control systems Utopia/Spot and ImFlow were tested, and their impacts were compared to conventional control including PTSP with the PRIBUSS method in a SIL simulation environment. The aim was to test if commercially available self-optimising control systems can reduce the overall delay per person by applying more sophisticated PTSP. Both systems reduced the delay for buses, cyclists and pedestrians at a cost of increased delay and increased number of stops compared to the existing conventional control used in field. The total delay for all road users was reduced substantially.
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