A time‐staged multi‐objective network‐design model

A multi‐objective, time‐staged network‐design problem is formulated. Through transformation, the problem is decomposed into a set of single‐period, single‐objective problems. Lexicographic ordering is instrumental in effecting this transformation; it also allows a backward‐recursion algorithm to be applied using strong pruning criteria. Furthermore, monotonicity properties enable us to solve the problem using the familiar tree‐search algorithms. The solution method has several desirable properties — as shown by an example and a case study of Tripoli Province, Libya. First, the algorithm ensures continuity of project implementation over the multi time‐periods and provides optimality in later computational stages irrespective of the decision at an interim stage. Second, the algorithm tends to provide accessibility to unconnected regions in the study area at low user‐cost without employing weights to the two objective functions of accessibility and user‐cost efficiency. Such a property is deemed advantageous for suggesting transportation investments based purely on purchasing the greatest benefit for each dollar, with political neutrality strictly maintained.     

Modelling parking choices considering user heterogeneity

We examine car driver’s behaviour when choosing a parking place; the alternatives available are free on-street parking, paid on-street parking and parking in an underground multi-storey car park. A mixed logit model, allowing for correlation between random taste parameters and estimated using stated choice data, is used to infer values of time, both when looking for a parking space and for accessing the final destination. Apart from the cost of parking, we found that vehicle age was a key variable when choosing where to park in Spain. We also found that the perception of the parking charge was fairly heterogeneous, depending both on the drivers’ income levels and whether or not they were local residents. Our results can be generalised for personalised policy making related with parking demand management.     

基于分形插值方法的城市轨道交通车站客流拟合与仿真

城市轨道交通车站客流量的变化具有复杂的非线性特点,通过对某些车站一天的客流量时间序列的分析,发现其客流量的变化具有自相似性,并且满足某种拟周期性。本文采用迭代函数系统模型描述城市轨道交通车站客流量的变化特征,用计算机自动求解该迭代函数系统的相关参数,在此基础上采用分形插值的方法模拟产生动态的客流。通过与实际客流调查数据的对比分析可以看出,该方法模拟产生的客流不仅与实际客流较好地吻合,而且能更好地描述客流的非线性特征。     

Liner ship route schedule design with port time windows

This paper examines a practical tactical liner ship route schedule design problem, which is the determination of the arrival and departure time at each port of call on the ship route. When designing the schedule, the availability of each port in a week, i.e., port time window, is incorporated. As a result, the designed schedule can be applied in practice without or with only minimum revisions. This problem is formulated as a mixed-integer nonlinear nonconvex optimization model. In view of the problem structure, an efficient holistic solution approach is proposed to obtain global optimal solution. The proposed solution method is applied to a trans-Atlantic ship route. The results demonstrate that the port time windows, port handling efficiency, bunker price and unit inventory cost all affect the total cost of a ship route, the optimal number of ships to deploy, and the optimal schedule.     

Passenger waiting time and information acquisition using automatic vehicle location for verification

Bus riders utilize a variety of information media to learn how to travel to their destinations and to learn when they should arrive at bus stops. As part of the OCTA (Orange County Transit Authority) Transit Probe evaluation, 1199 passengers were surveyed to measure relationships between information acquisition and waiting time. A unique aspect of the survey was that some of the data could be correlated with automatic‐vehicle‐location (AVL) measurements of bus lateness at stops. Insights are provided as to the types of information riders acquire based on the nature of the trip and demographic characteristics. Insights are also provided as to factors affecting perceived waiting time. We found age group, whether a person needs to arrive at a destination by a specific time, primary language, and whether the person is a first‐time user of the bus line to be significant causal factors.     

Measuring community reaction to urban transportation impacts using Von Neumann‐Morgenstern utility theory

This paper attempts to measure the impacts of urban transportation system improvements or changes on the community. The community's perceptions of the impacts are represented by its utilities (or disutilities) over various ranges of values of the multiple attributes representing these impacts. The utility technique used in the evaluation is based upon von Neumann‐Morgenstern (vN‐M, 1947) Utility Theory, and is applied using Raiffa's (1970) Fractile Method.

The paper specifically applies the technique to model the perceptions of five subgroups within a community to the impact of a new light rail transit system that is being incorporated in the transportation system of the City of Calgary.

Results of the modeling indicate explicitly how the community changes its perception over ranges of values of the attributes evaluated. Biases of various subgroups within the community over these attributes are also shown. Statistical tests indicate that aggregated utility perceptions can represent the utility perceptions of the individual subgroups quite reasonably.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.