Iisakki Kosonen

Multi-Agent Fuzzy Signal Control Based on Real-Time Simulation

In this paper a traffic signal control system based on real-time simulation, multi-agent control scheme and fuzzy inference is presented. This system called HUTSIG is closely related to the microscopic traffic simulator (HUTSIM) and both have been developed by the Helsinki University of Technology. The HUTSIM simulation model is used both for off-line evaluation of the signal control scheme and for on-line modeling of traffic situations during actual control. Indicators are derived from the simulation model as input to the control scheme. In the presented control technique each signal operates individually as an agent, negotiating with other signals about the control strategy. The decision making of the agents is based on fuzzy inference that allows combination of various aspects like fluency, economy, environment and safety.

Map updating and change detection using vehicle-based laser scanning

The vehicle-based laser scanning (VLS, also known as mobile mapping) is a new technology, which is currently under development for creating 3D models of the surrounding environment. VLS is based on the integration of GPS, IMU, laser scanner and preferably digital cameras mounted on top of a moving platform, i.e. a car in most applications. VLS is a logical development after the first operative Airborne Laser Scanner (ALS) in 1994 and Terrestrial Laser Scanners mounted on top of a tripod. The data/image processing of VLS are mainly based on modifications of the methods created for ALS and TLS taking into account the differences of VLS compared to ALS and TLS. Compared to ALS, the geometry of VLS scanning is different and the pulse density varies as function of range. Two main differences between stationary TLS and constantly moving VLS are the evenness of the data and the perspective. In VLS, the point cloud is evenly distributed along the driving direction, and the viewing direction to the target remains constant. In the stop-and-go mode, the data characteristics of the VLS and conventional TLS are similar. A reasonable amount of research has been done to develop methods for single-time VLS processing, but there have not been any attempts to our knowledge of multitemporal processing of VLS data. In this paper, the high potential of change detection based on multitemporal VLS point clouds was demonstrated. Example cases include the change detection of city models and defoliation of city trees. A method to map biomass and biomass change of (city) trees was developed.

Collective dynamics of pedestrians interacting with attractions.

In order to investigate collective effects of interactions between pedestrians and attractions, this study extends the social force model. Such interactions lead pedestrians to form stable clusters around attractions, or even to rush into attractions if the interaction becomes stronger. It is also found that for high pedestrian density and intermediate interaction strength, some pedestrians rush into attractions while others move to neighboring attractions. These collective patterns of pedestrian movements or phases and transitions between them are systematically presented in a phase diagram. The results suggest that safe and efficient use of pedestrian areas can be achieved by moderating the pedestrian density and the strength of attractive interaction, for example, in order to avoid situations involving extreme desire for limited resources.

Effects of switching behavior for the attraction on pedestrian dynamics

Walking is a fundamental activity of our daily life not only for moving to other places but also for interacting with surrounding environment. While walking on the streets, pedestrians can be aware of attractions like shopping windows. They can be influenced by the attractions and some of them might shift their attention towards the attractions, namely switching behavior. As a first step to incorporate the switching behavior, this study investigates collective effects of switching behavior for an attraction by developing a behavioral model. Numerical simulations exhibit different patterns of pedestrian behavior depending on the strength of the social influence and the average length of stay. When the social influence is strong along with a long length of stay, a saturated phase can be defined at which all the pedestrians have visited the attraction. If the social influence is not strong enough, an unsaturated phase appears where one can observe that some pedestrians head for the attraction while others walk in their desired direction. These collective patterns of pedestrian behavior are summarized in a phase diagram by comparing the number of pedestrians who visited the attraction to the number of passersby near the attraction. Measuring the marginal benefits with respect to the strength of the social influence and the average length of stay enables us to identify under what conditions enhancing these variables would be more effective. The findings from this study can be understood in the context of the pedestrian facility management, for instance, for retail stores.

Energy efficient traffic-based street lighting automation

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.

Granular Analysis of Traffic Data for Turning Movements Estimation

The paper discusses the principles and the algorithm of granular analysis of data in a specific context of urban traffic monitoring and control (EIS). The proposed granular information processing enables extraction of information on the pattern of journeys from the detailed traffic counts. This facilitates progression from the local optimisation of traffic on individual crossroads to the more holistic optimisation of traffic in a road network. The proposed EIS makes use of readily available stop-line queue data, which is used for adaptive tuning of traffic signals, and adds a data processing layer referred to as granular analysis. It is argued that granular analysis is preferred to statistical data processing since it does not require any assumptions about statistical characterisation of traffic. The granulation algorithm has two distinctive features: (1) the information granules are formed by means of hierarchical optimisation of information density, and (2) the granules are created as hyperboxes thus being readily interpretable in the pattern space. The granular estimates of turning movements are calibrated using an HUTSIM micro-simulator.

Tutorial: Road Lighting for Efficient and Safe Traffic Environments

ABSTRACT This article discusses various aspects of outdoor lighting energy efficiency by means of new light sources and smart lighting systems. We will also discuss visibility, traffic flow, safety, and environmental and economic aspects. The use of an optimum level of road lighting maximizes the contrast between the background and the object to be seen. This suggests that the combined effect of road lighting and car headlights should be taken into account. Solutions for future measurement need to include 3D modeling of the lighting environment and mesopic photometry. The life cycle environmental impacts of high-pressure sodium (HPS) and light emitting diode (LED) luminaires were found to be on a similar level, but it is expected that LED luminaires will surpass HPS luminaires in environmental friendliness across the whole life cycle in the future. The energy-saving potential is based on new energy-efficient technology, reduced burning hours with smart control, and new lighting dimensioning. The energy saving potential when replacing HPS lamps with LED luminaires is 31% with current technology and 66% with improved technology in the future. Further energy savings are achievable with reduced burning hours enabled with smart lighting. Altogether, the energy-saving potential of the future LED luminaire is 83% compared to current HPS luminaires.

A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation

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.

Three-level perspective for analyzing changes in socio-technical regimes - case electric mobility

When talking about changes caused by new emerging technologies, the focus is often very strongly on technology itself. Depending on the novelty of the technology and its transitions, its effects on the society and the societal functions are taken into minor account. A model of socio-technical change, developed by Frank W. Geels takes into account these socio-technical configurations in a multi-level framework. Electric mobility is a current example of an on-going socio-technical transition. The socio-technical framework well describes the electric mobility as a socio-technical change with multidimensional interactions. This transition will have effects on many societal functions related to personal transportation and the transport of goods. The change is in a very early phase, and that is why it is vitally important to increase the understanding of the phenomenon, dimensions affecting it and mechanisms for controlling the change. This paper describes a three-level perspective for analyzing the changes in case of electric mobility. Because the changes are slow and complex having a lot of uncertainties, new business and collaboration models are needed.

Integration of Geographic Information System for Transportation with Real-Time Traffic Simulation System: Application Framework

Real-time traffic information applications (RTIA) collect real-time traffic data from a wide variety of detectors. The problem with these applications is that they are complex and hard to maintain because of the large number of distributed detectors involved. However, it is well recognized that traffic simulation systems have the ability to improve the efficiency of traffic analysis, prediction, and control. This paper presents an application framework that integrates a real-time traffic simulation system with RTIA. Within this framework, a geographic information system for transportation (GIS-T) architecture, combined with a temporal-spatial database, provides a flexible way to present the real-time traffic information for road users. Several critical system components are introduced as well, including a real-time dynamic traffic data exchange model. The real-time simulation system, a static traffic model in GIS-T, and a Java-based application architecture are also briefly discussed.