Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

“空巴联运”需求预测模型与实证分析:以湖北地区为例

以非集计离散选择模型理论为依据,建立基于Logit的城际旅客交通方式选择行为模型.根据武汉周边4个城市(孝感、随州、襄阳和十堰)经武汉到上海的旅客出行方式意向选择(Stated Preference,SP)调查数据,研究了影响旅客选择"空巴联运"(即航空与巴士接驳)方式的重要因素,并对影响因素进行灵敏度分析,估计3种交通方式("空巴联运"、动车—高铁、大巴—高铁)的客流分担率.基于调查数据,对模型参数进行了标定.结果表明,城市内出行时间(程前程后出行时间)和总出行货币费用对旅客出行方式选择影响显著.     

An activity-based approach for scheduling multimodal transit services

This paper proposes a new activity-based transit assignment model for investigating the scheduling (or timetabling) problem of transit services in multi-modal transit networks. The proposed model can be used to generate the short-term and long-term timetables of multimodal transit lines for transit operations and service planning purposes. The interaction between transit timetables and passenger activity-travel scheduling behaviors is captured by the proposed model, as the activity and travel choices of transit passengers are considered explicitly in terms of departure time choice, activity/trip chain choices, activity duration choice, transit line and mode choices. A heuristic solution algorithm which combines the Hooke–Jeeves method and an iterative supply–demand equilibrium approach is developed to solve the proposed model. Two numerical examples are presented to illustrate the differences between the activity-based approach and the traditional trip-based method, together with comparison on the effects of optimal timetables with even and uneven headways. It is shown that the passenger travel scheduling pattern derived from the activity-based approach is significantly different from that obtained by the trip-based method, and that a demand-sensitive (with uneven headway) timetable is more efficient than an even-headway timetable.     

Optimal deployment of emergency rescue stations in an urban transportation corridor

This paper addresses the deployment issue of emergency rescue stations in an urban transportation corridor, with an aim to effectively reduce the casualties in traffic accidents. On the basis of urban population density, an accident rate distribution function for a corridor is first presented and calibrated, and a damage cost function is proposed to capture the correlation between rescue time and deteriorating health condition of injured passengers. A continuum model is then developed for determining the optimal number and locations of the rescue stations along the corridor and the medical service resource distribution at rescue stations subject to a capital budget constraint. The solution properties of the proposed model are explored analytically. Numerical examples are provided to show the effects of population density, urban form and different deployment schemes (even and uneven) on the rescue station locations. A case study of Wuhan China is employed to illustrate the effectiveness of the proposed methodology in improving the performance of the emergency rescue system.

     

Modeling intermodal equilibrium for bimodal transportation system design problems in a linear monocentric city

This paper investigates the intermodal equilibrium, road toll pricing, and bus system design issues in a congested highway corridor with two alternative modes - auto and bus - which share the same roadway along this corridor. On the basis of an in-depth analysis of the demand and supply sides of the bimodal transportation system, the mode choice equilibrium of travelers along the continuum corridor is first presented and formulated as an equivalent variational inequality problem. The solution properties of the bimodal continuum equilibrium formulation are analytically explored. Two models, which account for different infrastructure/system regulatory regimes (public and private), are then proposed. In the public regulatory model, the road toll location and charge level are simultaneously optimized together with the bus service fare and frequency. In the private regulatory model, the fare and frequency of bus services, which are operated by a profit-driven private operator, are optimized for exogenously given toll pricing schemes. Finally, an illustrative example is given to demonstrate the application of the proposed models. Sensitivity analysis of residential/household distribution along the corridor is carried out together with a comparison of four different toll pricing schemes (no toll, first best, distance based, and location based). Insightful findings are reported on the interrelationships among modal competition, market regulatory regimes, toll pricing schemes, and urban configurations as well as their implications in practice.