铁路旅客旅行换乘方案优选算法

为给铁路旅客选择合理的旅行方案提供参考,以旅行目标值与换乘目标值之和最小作为目标函数值,考虑旅客从起点站出发、最终到达终到站、在中转站进出平衡的约束条件,建立旅客旅行换乘方案选择问题的数学模型。分别给出旅行时间、换乘次数、票价、距离、到发时刻和综合指数6种目标权值的确定方法,提出最短路法和列车匹配法2种求解方法。最短路法是通过构造并简化旅客运输网络,求出网络上若干条次短路,再根据各条次短路上列车的接续,构造列车换乘方案网络图,根据该网络的目标权值确定最短路,得到最优换乘方案。列车匹配法是根据列车运行图信息直接搜索发、到站的接续列车集合,求其两列车对应的重合停车站,根据重合停车站集合的情况选择迭代步数,剔除显然不利方案,构成换乘方案,根据方案的权值进行比选,得到最优换乘方案。对2种算法均用C#编程实现,并用现有的全路客票数据进行检算。计算结果表明:2种算法均能得到最优换乘方案;列车匹配法所用计算时间比最短路法少160 ms。     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.     

Delay Restoration of Single-Track Railway Rescheduling

On the basis of analysis of the principle of delay restoration in a disturbed schedule, a heuristic algorithm for rescheduling trains is developed by restoring the total delay of the disturbed schedule. A discrete event topologic model is derived from the original undisturbed train diagram and a back propagation analysis method is used to label the maximum buffer time of each point in the model. In order to analyze the principle of delay restoration, the concept of critical delay is developed from the labeled maximum buffer time. The critical delay is the critical point of successful delay restoration. All the disturbed trains are classified into the strong-delayed trains and the weak-delayed trains by the criterion of the critical delay. Only the latter, in which actual delay is less than its critical delay, can be adjusted to a normal running state during time horizon considered. The heuristic algorithm is used to restore all the disturbed trains according to their critical details. The cores of the algorithm are the iterative repair technique and two repair methods for the two kinds of trains. The algorithm searches iteratively the space of possible conflicts caused by disturbed trains using an earfiest-delay-first heuristics and always attempts to repair the earliest constraint violation. The algorithm adjusts the weak-delayed trains directly back to the normal running state using the buffer time of the original train diagram. For the strong-delayed trains,the algorithm uses an utility function with some weighted attributes to determine the dynamic priority of the trains, and resolves the conflict according to the calculated dynamic priority. In the end, the experimental results show that the algorithm produces ＂good enough＂ schedules effectively and efficiently in disturbed situations.     

世界银行贷款项目“卫津路拓宽工程”的经济效益计算

本市以天津城市主干道卫津路拓宽改造工程为例，论述城市道路经济效益计算方法。按全天高峰小时、非高峰小时，分别计算机动车和非机动车的运营成本、时间价值及事故费用，采用有、无项目对比法．进行经济效益计算。经济效益中以车辆行程时间延误与路口时间延误的节约作为主要效益。     

Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel

The purpose of this paper is to examine the performance of a new operational system for measuring traffic speeds and travel times which is based on information from a cellular phone service provider. Cellular measurements are compared with those obtained by dual magnetic loop detectors. The comparison uses data for a busy 14 km freeway with 10 interchanges, in both directions, during January–March of 2005. The dataset contains 1 284 587 valid loop detector speed measurements and 440 331 valid measurements from the cellular system, each measurement referring to a 5 min interval. During one week in this period, 25 floating car measurements were conducted as additional comparison observations. The analyses include visual, graphical, and statistical techniques; focusing in particular on comparisons of speed patterns in the time–space domain. The main finding is that there is a good match between the two measurement methods, indicating that the cellular phone-based system can be useful for various practical applications such as advanced traveler information systems and evaluating system performance for modeling and planning.     

Urban form,travel time,and cost relationships with tour complexity and mode choice

The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.

Auto-ignition and micro-explosion behaviors of droplet arrays of water-in-fuel emulsion

The characteristics of auto-ignition and micro-explosion behaviors of one-dimensional arrays of fuel droplets suspended in a chamber with high surrounding temperature were investigated experimentally with various droplet spacings, numbers of droplet and surrounding temperatures. The fuels used were pure n-decane and emulsified n-decane with varied water contents ranging from 10 to 30%. All experiments were performed under atmospheric conditions with high surrounding temperatures. An imaging technique using a high-speed camera was adopted to measure ignition delay, flame lifetime, and flame spread speed. The camera was also used to observe micro-explosion behaviors. As the droplet array spacing increased, the ignition delay also increased, regardless of water content. However, the lifetime of the droplet array decreased as the droplet spacing increased. The micro-explosion starting time remained unchanged regardless of the number of the droplets or the droplet spacing; however, it tended to be delayed slightly as the water percentage and droplet spacing increased.     

Deconstructing development density: Quality, quantity and price effects on household non-work travel

Smart growth and transit-oriented development proponents advocate increasing the density of new land development and infill redevelopment. This is partly in order to reduce auto use, by reducing distances between trip origins and destinations, creating a more enjoyable walking environment, slowing down road travel, and increasing the market for transit. But research investigating how development density influences household travel has typically been inadequate to account for this complex set of hypotheses: it has used theoretically unjustified measures, has not accounted for spatial scale very well, and has not investigated potentially important combinations of measures. Using data from a survey of metropolitan households in California, measures of development density corresponding to the main hypotheses about how density affects travel—activity density affecting distance traveled, network load density affecting the speed of auto travel, and built form density affecting the quality of walking—are tested as independent variables in models of auto trip speed and individual non-work travel. Residential network load density is highly negatively correlated with the speed of driving, and is also highly correlated with non-work travel, both singly and in combination with other measures. Activity density and built form density are not as significantly related, on their own. These results suggest that denser development will not influence travel very much unless road level-of-service standards and parking requirements are reduced or eliminated.     

Passengers’ willingness to pay for airport ground access time savings

There are cases when passengers are willing to pay a premium to reduce the travel time, in particular when the trip has to be made. This paper aims to provide insight into factors that determine passengers’ willingness to pay to reduce travel time for their ground access to an airport. A methodology is developed that comprises two steps: the identification of the passengers with zero willingness to pay and from the rest the estimation of the additional price they are willing to pay to reduce their travel time. For the first step a Probit model was formulated and for the second a linear regression model. To this purpose, data has been collected employing stated preference from passengers at the Athens International Airport. It has been found that a high percentage of passengers have zero willingness to pay, and of the remaining ones those using public transport have a significant willingness to pay to reduce access travel time. The methodology and the models are structured in such a way that their transferability to any airport environment is possible, thus providing a useful tool for decisions relating to airport ground access measures.