In the surveillance of multiple targets by mobile sensor agents (MSAs), system performance relies greatly on the motion-control strategy of the MSAs. This paper investigates the motion-planning problem for a limited resource of M MSAs in an environment of N targets (M<N). The kinematics of the MSA is modeled as a point mass moving at a constant speed with a bounded turning radius. Based on the fact that the track information of each target degrades over time, the motion-planning problem is formulated as an optimization problem whose objective is to minimize the average time duration between two consecutive observations of each target. In the case of a single MSA, the motion-planning problem is further interpreted so as to find a time-optimal loop path to traverse the targets. A gradient-approximation algorithm is then proposed to generate a suboptimal loop path for a mobile agent to traverse a sequence of target points. For the multi-MSA-multitarget case, a cooperative online motion-planning approach is developed.

Motion planning for multitarget surveillance with mobile sensor agents

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Public Transit Planning and Operation

As is well known, bus systems are naturally unstable. Without control, buses on a single line tend to bunch, reducing their punctuality in meeting a schedule. Although conventional schedule-based strategies that hold buses at control points can alleviate this problem these methods require too much slack, which slows buses. This delays on-board passengers and increases operating costs. It is shown that dynamic holding strategies based on headways alone cannot help buses adhere to a schedule. Therefore, a family of dynamic holding strategies that use bus arrival deviations from a virtual schedule at the control points is proposed. The virtual schedule is introduced whether the system is run with a published schedule or not. It is shown that with this approach, buses can both closely adhere to a published schedule and maintain regular headways without too much slack. A one-parameter version of the method can be optimized in closed form. This simple method is shown to be near-optimal. To put it in practice, the only data needed in real time are the arrival times of the current bus and the preceding bus at the control point relative to the virtual schedule. The simple method was found to require about 40% less slack than the conventional schedule-based method. When used only to regulate headways it outperforms headway-based methods.

Dynamic bus holding strategies for schedule reliability: Optimal linear control and performance analysis

This paper describes an analytic model that determines the optimal vehicle holding time at a control stop along a transit route. This model is based on a stochastic transit service model presented by Andersson and Scalia-Tomba (1981) and enhanced by Marguier (1985). The use of a stochastic service model allows greater realism in the analytic modeling. Making use of these results, the paper presents an analytic model that may be used to determine the optimal holding time for a vehicle at a control stop. As it is formulated, the single vehicle holding problem is a convex quadratic program in a single variable, and is easily solved using gradient or line search techniques. The analytic holding model overcomes two noted problems in the literature: it includes stochastic service attributes of vehicle running times and passenger boarding and alighting processes, and the model may be used for real-time control purposes. The use and potential benefits of the model are illustrated in a simple example. This model may be useful in developing a computerized decision support system to enhance the effectiveness of transit operational decision-making.

https://www.jstor.org/stable/pdfplus/25768957.pdf

An Analytic Stochastic Model for the Transit Vehicle Holding Problem

Publisher Summary This chapter reviews a survey on the operations research literature applied to the domain of public transit, with a focus on recent contributions. It highlights a fruitful cooperation between the public transit agencies and the operations research community. Indeed, public transit has provided interesting and challenging problems to operations research, while operations research has been successful at solving efficiently several important public transit problems—for example, network design, timetabling, vehicle scheduling, and crew scheduling. New problems—the integration of vehicle and crew scheduling, bus parking and dispatching, as well as a wide variety of real-time control problems—that presents new challenges to the operations research community have also been studied recently. Research on these problems has already suggested innovative models and solution methodologies, which might be applicable in practice in a near future. The main goal of most transit agencies is to offer to the population a service of good quality that allows passengers to travel easily at a low fare. The agencies, thus, have a social mission that aims at reducing pollution and traffic congestion as well as increasing the mobility of the population.

Chapter 2 Public Transit

In practice punctuality of transit service has been a chronic operational problem mainly due to the random environment and very high complexity of the public transport processes. This challenging problem affects both travellers (reliability of service) as well as operators (productivity and efficiency of resources utilization). The potential of new information and communication technologies and existing hardware possibilities offer great opportunities for the development of effective and flexible management and control tools for public transport. In this paper the simulation decision-support tool for dynamic optimal dispatching control purposes have been developed, with the use of the SIMULINK package with Toolboxes. The following optimal dispatching control problems have been solved: punctuality control (which compensates deviations from schedule), regularity control (which compensates deviations from regular headway) and synchronizing control with linear (LQ, dead-beat) feedback and control and system state constraints; LQG stochastic control with real-time estimation of the model parameters; and bus route zone control for synchronising passenger transfers or the operation of different lines on common segments of the route. The results presented are illustrated by 15 numerical examples.

Simulation support tool for real-time dispatching control in public transport

The paper is focused on NI Compact-RIO configured as a controller for the active magnetic levitation used here as a benchmark for time-critical systems. Three real-time configurations: soft, soft with IRQ and hard FPGA are considered. The quality of the real-time control has been tested for each configuration.

Real-time controller design based on NI Compact-RIO

Variable Control Parameterization for Time-Optimal Problems 1 1This work was supported by Polish State Committee of Scientific Research under Grant 8 TI1A 018 18.

An experiment in practical implementation of simulated time-optimal control in a laboratory cart-pendulum system is described. The simulation results are compared with two types of measured trajectories of the real system: generated by an implementation of the time-optimal control, and generated by a rule-based algorithm. The technologies of rapid prototyping, real-time simulation and hardware-in-the-loop simulation are used for direct synthesis of control algorithms. The feasibility of construction of time-optimal controller in the real system has been pointed out.

Time optimal control for the pendulum-cart system in real-time

Presents an integrated environment which fills a gap between control system design and the real-time implementation of control algorithms. The integrated environment uses a standard hardware platform, a standard operating system and a computer-aided control design system as a design tool. This paper focuses on the application of a rapid-prototyping toolbox which automatically generates real-time code for Windows 95/98/NT operating systems. The code is created from the Simulink model of the controller. The real-time properties of the control system are analysed. The inverted pendulum control example is used to illustrate the efficiency of the proposed solution.

Andrzej Turnau

Papers

Simulation support tool for real-time dispatching control in public transport

Real-time controller design based on NI Compact-RIO

Variable Control Parameterization for Time-Optimal Problems 1 1This work was supported by Polish State Committee of Scientific Research under Grant 8 TI1A 018 18.

Time optimal control for the pendulum-cart system in real-time

Rapid prototyping environment for real-time control education