Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-24 Cooperative journals: 《计算机应用研究》
Abstract： Based on the optimization problem of site selection and optimal path planning of UAV during traffic network inspection, this paper proposed a method of combining super network with space-time network, and built a model through this method. This paper constructed a super-space-time network by adding virtual take-off and landing points in the space-time network, and requires the virtual take-off and landing point to be connected with the alternative base stations at all times. In this way, the path planning considering the site selection of the base station was transformed into a simple multi-UAV path planning problem. Compared with the path planning without considering the site selection of the base station, considering the base station site selection could reduce the maximum stand-alone flight time and total flight time by 5.71% and 11.59%, respectively. Numerical analysis shows that the integration of base station location and traffic patrol route planning can effectively reduce the UVA patrol costs.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-18 Cooperative journals: 《计算机应用研究》
Abstract： The existing traffic assignment theorem hardly dealt with the congested traffic state of link. To solve the above problem, based on the classic straight line inverse λ fundamental diagram, a static traffic assignment method with given states of links was presented. Firstly, through analyzing the fundamental diagram, the travel time function of link with two stages was obtained. Secondly, by introducing the indicating label of traffic state of link and constructing the flow conservation equations at nodes, the system optimal and user equilibrium traffic assignment models were formulated. At last, to solve the non-convex user equilibrium model, a branch and bound algorithm with relaxed partial objective function was proposed. Numerical examples were used to demonstrate the effectiveness of the new model and algorithm. By extending the one-sided assumption of monotone increasing of link travel time function, the new theory can deal with the congested traffic state of link effectively and improve the practicality of existing theories.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： Highly-informed grid-based city management can supply the real time passenger information and the position information of taxis for taxi operation optimization. On this account, we proposed a grid-based taxi dispatching dynamic control method based on reinforcement learning to solve the problem of the high vacant taxis rate and the low matching rate between taxis and passengers. By providing the optimal cruising routes for the vacant taxis, the new control method aims to improve the service level of taxis and to lower the waiting time of passengers. Firstly, based on the grids of city, we clarified the key problem of taxi dispatching. Secondly, by using the adjustment of vacant taxi route as the control action, we formulated the reinforcement learning model of taxi dispatching. At last, we proposed the corresponding Q learning algorithm to solve the new model. Numerical example demonstrated the effectiveness of the new dispatching method. The results show that the new method can not only increase the match rate between taxis and passengers and the total income of operation of taxi service, but also reduce the average waiting time of passengers and the total travel time of vacant taxis.
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