Miroslav Vujić

The development of Cooperative multimodal travel guide

Travel and traffic data, due to the rapid development of information and communication technologies are becoming increasingly and more fast accessible to the users. However, the technologies which would facilitate users to find and use such data do not follow such rapid development. For this reason, European regulations and guidelines for the development of sustainable mobility in cities are increasingly emphasizing the importance of the use of multimodal travel guides. The aim of this paper is to describe the concept of cooperative development of multimodal guide based on the optimal use of travel and traffic information. Such systems should provide information about optimal route taking into consideration optimal spatial, cost and time variables. The research reported in this paper is PART OF the FP7 - Collaborative Project: Intelligent Cooperative Sensing for improved traffic Efficiency (FP7-317671 ICSI).

The use of cooperative intelligent transport systems for vehicle emission charging

Emission charging is a new phenomenon in transportation research. Whilst fuel taxation and road tolling are common ways of income raising in many countries, these initiatives are primarily aimed at road infrastructure financing. Worldwide, there has been growing interest in pricing structures designed to manage the growing levels of traffic congestion and, in recent times, an increasing focus on generating reductions in carbon emissions from vehicle ownership and usage. In this research model for vehicle emission charging using cooperative intelligent transport systems (ITS) has been made. With the use of proposed model, traffic management would be more accurate and efficient using the data provided by the Traffic Cooperative Center for Emission Charging. At the end, significant reduction of environmental pollution produced from road traffic would be achieved.

Cooperative Vehicle Actuated Traffic Control in Urban Areas

Rapid increasing in the number of vehicles in urban areas directly affects traffic quality because of the physical limitations of road infrastructure. Frequent congestions in the cities cause the increase of delays, stop-and-go actions and especially travel times. Up-to-date methods of traffic control are focused on advanced intelligent transport systems solutions in order to increase the quality of urban traffic network. This is directly affects improvement of traffic parameters quality such as travel time, delay, etc. Also, defined parameters affect the quality of environmental factors in urban traffic network (emission of pollution from motor vehicles, fuel consumption, noise level, etc.). Higher level of traffic control is enabled by direct real-time communication between vehicles (personal vehicles, public transport vehicles, etc.). This method outperforms traditional fixed cycle management of signalized intersections, which use predetermined signal plans. Benefits of using cooperative actuated control where model with implemented control algorithms is compared with existing traffic model with fixed time signal plans are described. The main goal is to harmonize traffic flow with optimal vehicle speed and to reduce the number of stop-and-go actions which directly affects emission of pollution and fuel consumption.

Cooperative architecture of data acquisition for emission reduction in traffic

Increasing fuel prices, short-term inventories with C02 emission growth worldwide have contributed to the development of technology in auto industry. Many advanced technologies in the auto industry have emerged in the last decade, but with little focus on driver behavior to reduce fuel consumption. With the implementation of cooperative intelligent transport system (C-ITS) architecture for data acquisition from the vehicles it is possible to achieve defined energy and environmental requirements in traffic. In this paper the areas of application of C-ITS in terms of support for eco-driving will be defined and presented. Also, the implementation of presented system can have the influence on traffic flow and other traffic parameters, but defines new requirements for other involved subsystems (driver-vehicle-infrastructure).

Preemptive traffic light control based on vehicle tracking and queue lengths

Today it is possible to implement adaptive traffic light control as part of intelligent transport systems with the goal to reduce the respond times of emergency services. This allows preemptive traffic light control in an effort to reduce travel times of emergency vehicles in urban areas and negative effects on the total travel times of all vehicles in the traffic network. In this paper, a new algorithm for preemptive traffic light control is proposed. It is based on emergency vehicle location and intersection queue length data. Using these data the algorithm dynamically adapts the signal program of a signalized intersection. Proposed algorithm is tested in four different scenarios using a realistically simulated isolated intersection as a use case. The analysis of the obtained results reveals that travel times of emergency vehicles can be reduced up to 13 %. In the same time, the negative effects on the total travel time of all vehicles in the network can be reduced or even compensated.

Upravljanje znanjem u domeni inteligentnih transportnih sustava

Upravljanje znanjem u domeni inteligentnih transportnih sustava ima za cilj postizanje semantičke interoperabilnosti između različitih ITS aplikacija. Time bi se omogućilo predstavljanje podataka i informacija iz nekoga prometnoga konteksta u strojno razumljivom obliku, odnosno ontologijom u informacijskom/računalnom smislu. U radu su opisani osnovni koncepti razmjene znanja u domeni inteligentnih transportnih sustava. Uz značajke semantičkog značenja u prometu, opisana je uloga ontologija u prometu te je predložen model upravljanja znanjem u problemskoj domeni. Također, opisanu su i karakteristični problemi akvizicije činjeničnog znanja iz relacijskih baza prometnih podataka.

Multimodal traveler information systems in maritime environment

Stochastic nature of traffic system creates a need for real time traffic information provision to end-users (travelers) through the whole journey. Modern information and communication technologies (ICT) enable distribution of traffic information, especially with the usage of mobile data transmission. Existing services for distribution of traveler information are limited to one mode of transport (mostly road transport), and there is a need for its extension on all transport modes. The purpose of this research is to define the concept for development of multimodal traveler information systems where end-users can receive needed information for the entire journey. Also, regarding existing services, an extension in maritime environment is proposed, which is based on optimal usage of traveler and traffic data.

Ramp Metering Control Based on the Q-Learning Algorithm

Abstract Modern urban highways are under the influence of increased traffic demand and cannot fulfill the desired level of service anymore. In most of the cases there is no space available for any infrastructure building. Solutions from the domain of intelligent transport systems are used, such as ramp metering. To cope with the significant daily changes of the traffic demand, various approaches with autonomic properties like self-learning are applied for ramp metering. One of these approaches is reinforced learning. In this paper the Q-Learning algorithm is applied to learn the local ramp metering control law in a simulation environment, implemented in a VISSIM microscopic simulator. The approach proposed is tested in simulations with emphasis on the mainstream speed and travel time, using a typical on-ramp configuration.

Shipboard radiation hazards - INMARSAT ship Earth station

The paper analyzes the radiation hazard aniingfiom shipboard Inmarsat ship earth stations (SES) for satellite communications. A review of rued systems is given and the analysis is focused on the Inmarsat A, B, C, F and M SES, especially on the high gain aperture antemas. Power densities around the transmitting antennas are calcirlated by analytical equations and compared to the appropriate permissible exposure limits (PEL} @om relevant documents. ne results show the potential bard of human exposure to the main beam of radiation for all analyzed systems.