考虑用户时间冲突的停车共享方案优化研究

随着机动车保有量的快速增加,大城市中心区用地的有限导致停车位不足,而许多居民区的私人车位在白天处于空闲状态.停车共享策略可以很好地解决不同群体对同一地块停车需求在时间上的互补问题.然而,停车共享的实施必须要解决好一个问题,即,车位提供者与外部使用者之间的冲突.本文主要研究如何实施停车共享,根据需求调节共享终止时刻、泊位供应率,使得在避免冲突的情况下停车管理者收益最大.     

Truck capacity analysis in a cross‐dock transportation network considering direct shipment

In a transportation network, decision making parameters may change and may cause the optimum value of objective function to vary in a specific range. Therefore, managers try to identify the effects of these changes by sensitive analysis to find appropriate solutions. In this paper, first, a model for cross‐dock transportation network considering direct shipment is presented, and then an algorithm based on branch and bound algorithm and dual price concept for sensitive analysis is developed. When managers encounter problems such as budget limit, they may decide to change the capacity of trucks as a procedure to reduce the transportation costs of the network. The algorithm provides a useful lower bound on the solutions of the problems and makes it easy for the managers to eliminate inappropriate options of truck capacities, which cannot lead to cost reduction. To verify the algorithm, an example will be given at the end of the paper. Copyright © 2013 John Wiley & Sons, Ltd.     

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Optimization method of alternate traffic restriction scheme based on elastic demand and mode choice behavior

As a countermeasure to urban traffic congestion, alternate traffic restriction (ATR) involves a certain proportion of automobiles being prohibited from entering pre-determined ATR districts during specific time periods. The present study introduces an optimization method for ATR schemes in terms of both their restriction districts and the proportion of restricted automobiles. As a Stackelberg game between traffic policy makers and road users, the ATR scheme optimization problem is established using a bi-level programming model, with the upper-level examining an ATR scheme aimed at consumers’ surplus maximization under the condition of overload flow minimization, and the lower-level synthetically optimizing elastic demand, mode choice (private car, public transit and park-and-ride) and multi-class user equilibrium assignment. A genetic algorithm based on the graph theory is also proposed to solve the bi-level programming model with a gradient project algorithm for solving the lower-level model. To our knowledge, this study represents the first attempt to theoretically optimize an ATR scheme using a systematic approach with mathematical model specification.     

The optimal dual-pricing policy of mall parking service

In studies of parking policy, the role of parking pricing has been addressed. Most researches have focused on the determination of a proper price for city parking spaces that are open to the public and it is now evident that price is used by authorities as a tool to manage transport demand. However, studies of parking pricing that pertain to privately-owned parking resources are few and in particular, the problem of setting a proper price for physical market parking has rarely been studied, such as a mall’s ‘dual-pricing portfolio’ decision for the simultaneous determination of a parking fee and the consumer spending required for free parking (i.e., the ‘threshold’). This is a common problem for most malls, but the different agents involved (e.g., the visitors, the mall, the marketplace and the parking lot departments) usually have diverse goals, so the decision must take account of a multiplicity of criteria and subtle relationships. In order to systematically support this type of inter-departmental decision process, a decision model that includes an analytical decision-aid process and the relevant programming models is established. A numerical example verifies the proposed model by taking the data for a mall in Taiwan and the implications, in terms of management, are given. This systematic computational model can be generalized to any type of commercial market that requires a (new) parking pricing policy.     

Real-time traffic estimation using data expansion

This paper presents a method for estimating missing real-time traffic volumes on a road network using both historical and real-time traffic data. The method was developed to address urban transportation networks where a non-negligible subset of the network links do not have real-time link volumes, and where that data is needed to populate other real-time traffic analytics. Computation is split between an offline calibration and a real-time estimation phase. The offline phase determines link-to-link splitting probabilities for traffic flow propagation that are subsequently used in real-time estimation. The real-time procedure uses current traffic data and is efficient enough to scale to full city-wide deployments. Simulation results on a medium-sized test network demonstrate the accuracy of the method and its robustness to missing data and variability in the data that is available. For traffic demands with a coefficient of variation as high as 40%, and a real-time feed in which as much as 60% of links lack data, we find the percentage root mean square error of link volume estimates ranges from 3.9% to 18.6%. We observe that the use of real-time data can reduce this error by as much as 20%.     

智能车避障路径规划方法研究

避障路径规划是智能车技术的关键部分,对智能车研究具有重大意义,正确的选择规划方法至关重要。本文首先初步选定人工势场法规划路径,仿真得知传统人工势场法规划出的路径存在局部最优、碰撞及达不到目标点的问题。因此提出改进人工势场法,通过改变势场函数和设定初始条件来解决此问题。最后,为了规划出能够同时避开静态和动态障碍物且能到达目标点的理想路径,在改进人工势场法中加入速度元素,经过仿真,证明了基于速度的改进人工势场法在智能车避障路径规划中的可行性和优越性。     

湘江船闸的过闸调度算法研究

船闸调度主要任务是确定排哪些船舶及其各自在船闸中相对位置,是一个多目标非线性规划问题。为解决此问题,首先建立调度数学模型,通过研究调度算法进行求解,试验证明船闸面积利用率比前期提高,工作效率得到改善。     

军用飞行器低空突防航路规划算法分析

通过分析军用飞行器低空突防航路规划算法应满足的条件及特点,阐述了目前国内外正在研究和应用的几种航路规划算法：动态规划法、启发式A^＋搜索法、遗传算法、蚁群算法等,并分别指出了其优缺点。最后简要总结低空突防航路规划算法的发展方向。     

Fuzzy neural network control of underwater vehicles based on desired state programming

1 Introduction1 With the development of the activities in deep sea, the application of underwater vehicle is widespread. However, owing to the nonlinearity and unpredictable operating environment of underwater vehicles, many factors must be taken into con…