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The vehicle routing problem is an important problem in logistics. And it has taken as the NP hard problem. Most of the researchers want to get the best resources by many kinds of ways. But the real-world problem is much more difficult than the VRP. In order to make the model and get the solving strategy for the real-world VRP, the paper analysis the customers' demands and divides the problem into...
Features of traffic flow, such as travel time, traffic volume, road choice, etc., are always important information for traffic planning and management. Conventional methods of collecting traffic flow features include loop detectors, closed-circuit televisions, field investigation, etc. They record vehicles' mobility in an indirect and infrastructure-based manner, and have difficulties in producing...
In this work, we apply the iterative learning method to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The macroscopic model to describe the evolution of freeway traffic flow is firstly established. Then traffic density is selected as the control variable in place of traffic occupancy, and the control objective is determined. In conjunction...
The paper studies the coordinated path following problem, namely, steering a group of unicycles to a given path while achieving an inter-vehicle formation pattern. A novel hybrid control approach is proposed in the paper to solve the problem despite that the neighbors of each vehicle may change over time due to limited sensing capabilities. The state space of each vehicle is partitioned into several...
Recent progress in grid computing concept and its allied application technologies has helped us to device an efficient tool for heavy workload management. Concept of this middleware technology supports to build more and more complex application which can process large real time data set. Mobilization of under utilized resources among the needy processes can easily be carried out with distributed grid...
In this paper we present the integration of a linear-time-varying model-predictive-control (LTV-MPC), designed to stabilize a vehicle during sudden lane change or excessive speed-entry in curve, with a slip controller that converts the desired longitudinal tire force variation in pressure variation in the brake system. The lateral controller is designed using a three-degrees-of-freedom vehicle model...
We present novel exploration algorithms and a control law that enable the construction of Voronoi diagrams over unknown areas using a single autonomous vehicle equipped with range sensors. Our control law and exploration algorithms are provably complete. The control law uses range measurements to enable tracking Voronoi edges between two obstacles. Exploration algorithms make decisions at vertices...
In this paper, the safety control problem for a class of hybrid systems with disturbance inputs and imperfect continuous state information is considered. Under the assumption that the system has order preserving dynamics, we provide an algorithmic procedure for computing the control map, which has linear complexity in the number of continuous variables. The structure of the control map with imperfect...
Precise path tracking control of autonomous vehicles is an area which is beginning to benefit from an increased awareness of its importance and its challenge. One of the challenges comes about due to the need for increased accuracy and robustness. Kinematic models are primarily used for path tracking control due to their generic and more simplistic nature when compared to dynamic models. However,...
Assigning targets to multiple flight vehicles which perform a cooperative mission becomes more involved considering the complex environments. In this paper, an coordinated target assignment scheme is proposed based on a finite-time gain measure. The target assignment problem is formulated as multiple Linear Time Varying (LTV) systems. A finite-time generalized H2 measure and its performance criterion...
A new modeling methodology that enables represent the urban traffic system (UTS) dynamic entities using a multi-agent event oriented approach is presented. The methodology uses an enhanced n-Level net system (n-LNS) formalism of Petri nets. The first level describes the traffic network and UTS static and dynamic information objects; the second level describes the general entity behavior (activity...
Most existing dynamic traffic assignment models assume that drivers have sufficient knowledge on roadway networks. However, past experiments have shown that drivers' familiarity with the network layout is an essential component in route selections. In this paper, the concept of recognition level is defined to categorize drivers based on their unfamiliarity of the network and of the alternative routes...
This paper describes the full automated advanced demand signals II (FA-ADS-II) scheme and its performance evaluations. Firstly, the FA-ADS-II scheme is proposed. This is scheme that the ADS-II scheme is extended to automatically decide appropriate system parameters' values according to traffic conditions based on estimated costs without any database; The ADS-II scheme is a traffic signal control scheme...
MATSim-T (multi-agent traffic simulation toolkit) is a simulation platform for large-scale agent-based traffic. Each agent plans its day and performs its activities based on that plan. Then it chooses appropriate routes to reach its destinations. To avoid conflicts in intersections, signal control need to be added into MATSim-T. Phase modeling and a dynamic window signal timing algorithm are proposed...
Estimation of travel time in the analysis of network performance has been suffering from low accuracy due to errors of vehicle speed evaluation, which is affected by the way that intersection areas in the network are delineated. In this paper, two methods, the density-based and the deceleration point-based, were proposed for the purpose of dynamically delineating the intersection based on Floating...
Recently, the authors proposed a distributed dynamic route guidance system called UTOSPF (Urban Traffic Open Shortest Path First) based on Wireless Sensor Networks (WSNs) and Open Shortest Path First (OSPF) protocol. In UTOSPF, the routes will be found only based on Estimated Street Travel Times (ESTTs) which will be needed to pass the streets and regardless of Waiting Times for Green Light (WTGLs)...
Bus signal priority at signalized intersections has demonstrated as an efficient and realizable approach to reduce bus delays. However the impact on passenger delays still needs to be analyzed after bus signal priority. This paper proposes a passenger delays reduction model by using the delay triangle. Taking a two-phase signalized intersection for example, it is found that the passenger delays reduction...
Developing architectural support for self-adaptive systems, i.e. systems that are able to autonomously adapt to changes in their operating conditions, is a key challenge for software engineers. Multi-agent systems are a class of decentralized systems that are known for realizing qualities such as adaptability and scalability. In this paper, we present a pattern language for multi-agent systems. The...
This paper reports a recent effort at GM to develop a remote vehicle diagnostics service under a previously proposed framework of connected vehicle diagnostics and prognostics. An algorithm development methodology combining the physics-based approach and the data-driven approach is presented to identify, select, and calibrate failure precursors to predict vehicle no-start due to battery failures....
This work treats the topic of solving dynamic pickup and delivery problems, also known as dial-a-ride problems. A simulation model is introduced that describes how an agent is able to satisfy the transportation requests. The agent behavior is given in form of a complex dispatching rule, which is optimized by metaheuristic approaches. For this purpose, a fitness function is described which is used...
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