Dušan Teodorović

The Highway Space Inventory Control System (HSICS) is a novel travel demand management concept in which all road users have to make reservations in advance to enter a highway. A modeling framework for such a system is proposed and illustrated for a hypothetical highway section. The proposed system allocates highway space temporally and spatially over time so as to optimize highway utilization by maximizing passenger miles traveled. In this paper, a methodology is developed to perform a quantitative comparison of the operational performance of HSICS and two isolated ramp metering techniques: the ALINEA algorithm and fixed pre-timed metering. The methodology involves a combination of microscopic traffic simulation and heuristic optimization. The proposed framework is generic and can be applied to compare other traffic control and demand management techniques. The proposed methodology is tested on a simulated highway section with traffic and geometric characteristics similar to a real congested site. Simulation results show that HSICS produces approximately 35 and 45% more passenger miles than ALINEA and fixed pre-timed metering, respectively. Vehicle miles traveled values for HSICS are comparable to those of ALINEA − 4% lower.

Planners, engineers and economists have introduced various demand management methods in an attempt to reduce the fast growing traffic congestion. The basic idea behind various demand management strategies is to force drivers to travel and use transportation facilities more during off-peak hours and less during peak hours, as well as to increase the usage of underutilized routes. In this paper, a new demand management concept – Auction-based Congestion Pricing – is proposed and modeled.

This paper addresses different aspects of quality of service (QoS) negotiation in next generation networks. The differentiated services (DiffServ) framework is assumed in a multi-domain network core, while access networks may implement other QoS models. QoS negotiation results in service level agreement (SLA), i.e., a contract between the provider and the user, which defines technical, financial and legal aspects related with particular service. Solutions for SLA structure and format are discussed, with respect to mapping algorithms on the network-to-network interface. Considering conditions of contract violation, different traffic conditioning policies have been compared by computer simulation. We further provide a brief overview of the recently proposed next steps in signaling (NSIS) framework. The paper also addresses possibilities to achieve efficient usage based pricing in accordance with negotiated technical parameters from the SLA. Finally, we briefly present the object-oriented design and implementation of the application SLA Manager (SLAM), which is intended for QoS negotiation in DiffServ IP network.

This article presents ongoing research on the initial development of a decision support system (DSS) framework for integrated emergency vehicle preemption and transit priority system investment planning. A conceptual intelligent DSS framework provides a holistic framework to perform analytical assessments of integrated emergency vehicle preemption and transit priority systems. Three analytical tools are presented for incorporation into future DSS design: the first addresses the potential impact of transit travel time reduction on transit operating costs; the second addresses the potential impact of reduced emergency vehicle crashes at signalized intersections on fire and rescue operating costs; and the third integrates fuzzy sets concepts and multiattribute decision-making methods to rank order transit signal priority strategy alternatives at the intersection level.

Trips between nodes in public transit networks may be made with or without making transfers. Transfers usually represent an inconvenience to passengers. Since poorly coordinated transfers can increase waiting times significantly, it is especially important (when constructing timetables) to synchronize schedules carefully in cases of larger headways. Poorly coordinated transfers can also reduce the number of passengers using public transit as a result of switching to competitor modes. When designing synchronized schedules it is necessary to try to minimize the total waiting times of all passengers at transfer nodes in a transit network. Often only approximate numbers of transfer passengers are known. This paper develops a model for schedule synchronization where the number of transfer passengers is only approximately known. The model is based on the Fuzzy Ant System that represents a combination of the Ant Colony System and Fuzzy Logic.

In this article, an "intelligent" airline seat inventory control system is developed. Applications of the system are considered for both nonstop flights and flights with stopovers. The system developed is able to recognize a situation characterized by the number of reservations made by individual passenger classes and the number of canceled reservations at a certain moment in time before departure. The system can also make the appropriate decision without knowing the functional relationships in effect between individual variables. As in other intelligent systems, the "intelligent" airline seat inventory control system proposed here is able to generalize, adapt and learn based on new knowledge and new information. The "intelligent" airline seat inventory control system is based on fuzzy logic. The system makes on-line decisions as to whether to accept or reject any passenger request using established fuzzy rules. The "intelligent" system's results are compared with those of the EMSR model for nonstop flights. The results for flights with stopovers are compared with those obtained using integer programming. The final conclusions are very promising.