基于GIS的城市公交出行时间链研究

分析城市公交网络的各种空间实体数据和属性数据,建立了基于GIS的公交网络信息数据库。利用GIS空间分析与决策功能,分析研究乘客公交出行时间链,采用Logit反推模型,结合苏州市公交规划调查数据,回归计算出公交出行时间链各部分权重值。公交出行时间链的研究是公交网络配流及网络优化的理论基础,其权重值的分析计算具有重要的实用意义。     

Application of Auction Algorithm for Shortest Paths to Traffic Assignment

Auction algorithm is a new and simple algorithm for finding shortest paths in a directed graph proposed by Prof. Bertsekas, whose application has been extended to solve a variety of linear network flow problems. In this paper, auction algorithm for shortest paths is introduced and its characteristics are analyzed. The paper compares the auction algorithm with other algorithms widely used such as label-setting algorithm and label-correcting algorithm. The auction algorithm is particularly applicable to parallel computation and to the solution of a large-scale sparse network, which precisely meets the requirements of the traffic assignment. The algorithm is easy to program. Through a variety of measures the basic algorithm can be improved and speeded up and the computation speed can be increased by several times. The auction algorithm can be adopted in various traffic assignment methods. It can be used efficiently in the case of multiple origins and a single destination, and a single origin and multiple destinations. Different origin sets and destination sets are determined in accordance with the requirement of the traffic assignment. It is not required any more to find the shortest paths connecting any node pairs, so a lot of computation can be avoided and the computing time can be reduced by the use of the auction algorithm in the traffic assignment. Auction algorithms can thus be broadly applied in the transportation fields.     

生产管理中一类排序问题的扩展模型及通用算法

讨论了生产管理中将n个零件安排给m台机器加工的一类排序问题。取消了m≤n的限制，允许机制空闲并引入负荷（最大加工零件数）的思想，得出了此类排序问题的扩展模型以及通用求解算法。算便结果表明该扩展模型和求解算法的有效性。     

用遗传算法解决固定需求交通平衡分配问题

为了提高交通量预测模型的可靠性,利用遗传算法的结构并行性将其用于求解固定需求交通平衡分配问题中。算法设计中采用多维并行交叉、变化的交叉率与变异率、优先策略及目标函数加惩罚项等改进措施,从而大大提高计算速度,减少了交通分配的时间,降低了分配的复杂性,为交通分配问题开创了一条新的途径,同时显示出遗传算法在交通规划中潜在的实用前景。     

基于D—S证据理论的复合制导目标识别技术

根据主动雷达／红外复合制导反舰导弹各传感器所提供的信息构建基本概率赋值函数;依据基于准贝叶斯结构的D-S证据理论合成BPA、进行目标识别、提出算法流程。仿真实验表明：这种基于D-S证据理论的复合制导目标识别技术能有效降低目标识别的不确定性概率,提高正确识别率。     

Dynamic stochastic transit assignment with explicit seat allocation model

This paper proposes a stochastic dynamic transit assignment model with an explicit seat allocation process. The model is applicable to a general transit network. A seat allocation model is proposed to estimate the probability of a passenger waiting at a station or on-board to get a seat. The explicit seating model allows a better differentiation of in-vehicle discomfort experienced by sitting and standing passengers. The paper proposes simulation procedures for calculating the sitting probability of each type of passengers. A heuristic solution algorithm for finding an equilibrium solution of the proposed model is developed and tested. The numerical tests show significant influences of the seat allocation model on equilibrium departure time and route choices of passengers. The proposed model is also applied to evaluate the effects of an advanced public transport information system (APTIS) on travellers’ decision-making.     

A bi-objective cyclist route choice model

It is widely acknowledged that cyclists choose their route differently to drivers of private vehicles. The route choice decision of commuter drivers is often modelled with one objective, to reduce their generalised travel cost, which is a monetary value representing the combined travel time and vehicle operating cost. Commuter cyclists, on the other hand, usually have multiple incommensurable objectives when choosing their route: the travel time and the suitability of a route. By suitability we mean non-subjective factors that characterise the suitability of a route for cycling, including safety, traffic volumes, traffic speeds, presence of bicycle lanes, whether the terrain is flat or hilly, etc. While these incommensurable objectives are difficult to be combined into a single objective, it is also important to take into account that each individual cyclist may prioritise differently between travel time and suitability when they choose a route.This paper proposes a novel model to determine the route choice set of commuter cyclists by formulating a bi-objective routing problem. The two objectives considered are travel time and suitability of a route for cycling. Rather than determining a single route for a cyclist, we determine a choice set of optimal alternative routes (efficient routes) from which a cyclist may select one according to their personal preference depending on their perception of travel time versus other route choice criteria considered in the suitability index. This method is then implemented in a case study in Auckland, New Zealand.The study provides a starting point for the trip assignment of cyclists, and with further research, the bi-objective routing model developed can be applied to create a complete travel demand forecast model for cycle trips. We also suggest the application of the developed methodology as an algorithm in an interactive route finder to suggest efficient route choices at different levels of suitability to cyclists and potential cyclists.     

Network impacts of a road capacity reduction: Empirical analysis and model predictions

In spite of their widespread use in policy design and evaluation, relatively little evidence has been reported on how well traffic equilibrium models predict real network impacts. Here we present what we believe to be the first paper that together analyses the explicit impacts on observed route choice of an actual network intervention and compares this with the before-and-after predictions of a network equilibrium model. The analysis is based on the findings of an empirical study of the travel time and route choice impacts of a road capacity reduction. Time-stamped, partial licence plates were recorded across a series of locations, over a period of days both with and without the capacity reduction, and the data were ‘matched’ between locations using special-purpose statistical methods. Hypothesis tests were used to identify statistically significant changes in travel times and route choice, between the periods of days with and without the capacity reduction. A traffic network equilibrium model was then independently applied to the same scenarios, and its predictions compared with the empirical findings. From a comparison of route choice patterns, a particularly influential spatial effect was revealed of the parameter specifying the relative values of distance and travel time assumed in the generalised cost equations. When this parameter was ‘fitted’ to the data without the capacity reduction, the network model broadly predicted the route choice impacts of the capacity reduction, but with other values it was seen to perform poorly. The paper concludes by discussing the wider practical and research implications of the study’s findings.     

负指数网络配流模型在长三角集装箱运输分流预测中的应用

为更好地分析长三角区域内主要港口对腹地外贸集装箱箱源的竞争情况,对于港口腹地存在重合的情况,以负指数网络配流模型为基础,引入港口导向因数修正负指数网络配流模型,得出更适应长三角地区港口发展特征的集装箱配流模式,为长三角地区主要港口外贸集装箱吞吐量预测提供更加有效的方法。