Transit assignment under crowded conditions

This paper presents a transit assignment algorithm for crowded networks. Both congestion in vehicles and queuing at stations are explicitly taken into account in predicting passenger flows for a fixed pattern of origin-destination trip demands. The overflow effects due to insufficient capacity of transit lines are considered to be concentrated at transit stations, while the in-vehicle congestion effects (or discomforts) are considered to be dependent on in-vehicle passenger volume. Overflow delay at a transit station is dependent on the number of excess passengers required to wait for the next transit car. We use a logit model to determine the split between passengers that chose to wait for the next transit car and passengers that chose to board on the alternative transit lines. The proposed algorithm predicts how passenger will choose their optimal routes under both queuing and crowded conditions.     

A study of passenger discomfort measures at the Hong Kong mass transit railway system

This note investigates the important attributes relating to the crowding effects at the Mass Transit Railway (MTR) stations in Hong Kong. Data was collected at two sets of three MTR stations to study the responses of the passengers due to the discomfort at crowded vehicles and platforms. Stated preference surveys were used to study the effects of passenger discomfort measures.     

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.     

Optimization of transport investment and pricing policies: the role of transport pricing in network design

This paper investigates the role of transport pricing in network design and describes two facts about flow pattern in a transportation system. The first, illustrated by an example of Braess paradox, is that adding a new link to the network does not necessarily minimize the total travel time. The second is that introducing of appropriate toll pricing may reduce not only the total network time but also the travel time for each individual traveller. It follows with the investigations of different system objectives and different pricing policies (only toll pricing and distance‐based pricing are considered), and shows how they affect the system performance and flow pattern. Lastly, a systematic optimization process is proposed for integrated planning of transport network and pricing policies.     

Modeling the interactions between car and bicycle in heterogeneous traffic

In this paper, a new cellular automata model is proposed to simulate the car and bicycle heterogeneous traffic on urban road. To capture the complex interactions between these two types of vehicles, a novel occupancy rule is adopted in the proposed model to consider the variable lateral distances of mixed vehicular traffic. Based on massive simulations, microscopic fundamental diagrams under different bicycle densities are devised. With these, the bicycle's spilling behavior is then investigated and discussed. In order to reflect the interference of a bicycle on a car, the interference transformation from friction state to block state is modeled explicitly. Finally, different simulation results under different occupancy rules indicate that the constant and fixed occupancy rule adopted in the previous studies might lead to overestimation of car flux in the heterogeneous traffic flows with different bicycle densities. Copyright © 2013 John Wiley & Sons, Ltd.     

Public/private-sector cooperation in urban transportation: Lessons from ridesharing experiences in Connecticut

An important characteristic of urban transportation policy and planning today is the increasing role that the private sector is playing in identifying and implementing transportation projects. For example, a recent examination of the possible forms of such involvement found that there were four major categories of action that could be used to classify recent private-sector efforts in urban transportation: (1) aid to and/or provision of transportation services; (2) formation of advocacy or advisory groups whose purpose is to influence public policy; (3) sponsorship of transportation studies; and (4) provision of management assistance to public agencies (Gordon, 1982). In many of these efforts, the successful implementation of a project or program required close cooperation between public and private-sector officials. The purpose of this paper is to examine the characteristics of this interaction and explore the implications for transportation planning and policy.Examples of public/private-sector interaction in two Connecticut cities, Hartford and Stamford, are used to illustrate the characteristics of successful transportation program implementation. Although the examples are limited to two cities, and are mainly concerned with one major category of action (ridesharing), the characteristics of the process used and of the results can be applied to other situations where public/privatesector interaction is desired.     

Short-term Hourly Traffic Forecasts using Hong Kong Annual Traffic Census

The need for acquiring the current-year traffic data is a problem for transport planners since such data may not be available for on-going transport studies. A method is proposed in this paper to predict hourly traffic flows up to and into the near future, using historical data collected from the Hong Kong Annual Traffic Census (ATC). Two parametric and two non-parametric models have been employed and evaluated in this study. The results show that the non-parametric models (Non-Parametric Regression (NPR) and Gaussian Maximum Likelihood (GML)) were more promising for predicting hourly traffic flows at the selected ATC station. Further analysis encompassing 87 ATC stations revealed that the NPR is likely to react to unexpected changes more effectively than the GML method, while the GML model performs better under steady traffic flows. Taking into consideration the dynamic nature of the common traffic patterns in Hong Kong and the advantages/disadvantages of the various models, the NPR model is recommended for predicting the hourly traffic flows in that region.     

A traffic flow simulator for short‐term travel time forecasting

This paper presents an off‐line forecasting system for short‐term travel time forecasting. These forecasts are based on the historical traffic count data provided by detectors installed on Annual Traffic Census (ATC) stations in Hong Kong. A traffic flow simulator (TFS) is developed for short‐term travel time forecasting (in terms of offline forecasting), in which the variation of perceived travel time error and the fluctuations of origin‐destination (O‐D) demand are considered explicitly. On the basis of prior O‐D demand and partial updated detector data, the TFS can estimate the link travel times and flows for the whole network together with their variances and covariances. The short‐term travel time forecasting by O‐D pair can also be assessed and the O‐D matrix can be updated simultaneously. The application of the proposed off‐line forecasting system is illustrated by a numerical example in Hong Kong.     

Special issue: Importance of public transport

The transport demand in most major cities around the world can only be met with a high‐quality public transport system. The requirements on bus, rail, underground and tram systems are manifold with reliability and efficiency as the key factors. The service operating hours and the size of the network are often extended in order to serve the needs better. Further, most metropolitan areas are trying to provide more incentives for citizens to leave the car at home and use the local transit systems instead. The reasons are well known. Not only does a public transport system only make economical sense if it is well used, but most urban areas with a high car‐dependency face at least three major problems; safety, congestion, and pollution (noise and air pollution, land separation, etc.). It is generally recognised that to decrease car usage and to increase public transport usage a stick & carrot approach is needed. The London congestion‐charging scheme is an example since all revenues collected by the scheme are put into the improvement of bus and underground services.     

Risk assessment framework for exposure of cargo and ports to natural hazards and climate extremes

There is an increase in risks and catastrophic losses in maritime transport including ports and cargo. Significant losses have been associated with large scale natural hazards, such as earthquakes, tsunami, cyclones, and other extreme weather events. This paper identifies the main gaps in understanding maritime risks in transportation research. The gaps are attributed to insufficient empirical work available from the maritime transport and logistics research community to guide multi-risk and natural hazards impact assessment on seaport and cargo. In addition, disaster studies communities have barely made adequate efforts to understand and assess port and cargo risks arising from multi-hazards and disaster events. This paper examines existing conceptual frameworks concerning exposure and risk assessments of natural catastrophe’s impacts. Furthermore, the paper identifies trends and gaps in risk assessment frameworks in the field of disaster studies that can be beneficial for maritime risk research. The authors propose a new risk assessment framework that can guide future research and multi-hazard risk assessment processes at different scales of maritime risks.