Perceived importance of inclusive street dimensions: a public questionnaire survey from a vision(ing) perspective

Transportation - The increasingly prevalent concept of inclusiveness in the public discourse is gaining a foothold in the paradigm shift of street design from a predominance of vehicular traffic...     

Costs of air pollutants from shipping: a meta-regression analysis

ABSTRACT

This study estimated the external cost of air pollution from shipping by means of a meta-regression analysis, which has not been made before. Three pollutants, which were included in most of the primary studies, were considered: nitrogen oxides (NO_x), sulphur dioxides (SO₂) and particulate matters with a diameter of max 2.5 micrometres (PM_2.5). All primary studies included damages of health and a majority added impacts on agriculture and estimated the cost of air pollutants by transferring cost estimates from studies on costs of air emissions from transports in Europe. Different regression models and estimators were used and robust results were found of statistically significant emission elasticities of below one, i.e. total external costs increase by less than 1% when emissions increase by 1%. There was a small variation between the pollutants, with the highest elasticity for PM_2.5 and lowest for NO_x. Calculations of the marginal external cost of the pollutants showed the same pattern, with this cost being approximately six times higher for PM_2.5 than for the other pollutants. Common to all pollutants was that the marginal external cost decreases when emission increases. Another robust result was a significant increase in the cost of studies published in journals compared with other publication outlets. These findings point out some caution when transferring constant external unit cost of air pollutant from shipping, which is much applied in the literature, and the cost functions estimated in this study could thus provide a complementary transfer mechanism.     

GIS-based identification and visualization of multimodal freight transportation catchment areas

Transportation - To estimate impacts, support cost–benefit analyses, and enable project prioritization, it is necessary to identify the area of influence of a transportation infrastructure...     

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.     

Dynamics of Tracked Vehicles

This paper provides a brief review of the state-of-the-art of tracked vehicle dynamics, including mobility over soft terrain, ride dynamics over rough surfaces and manoeuvrability. It is found that considerable progress has been made in the development of analytical frameworks for evaluating and predicting tracked vehicle mobility over soft terrain, taking into account the characteristics of terrain response to normal and shear loading. Certain computer simulation models for tracked vehicle mobility have been gaining increasingly wide acceptance by industry and governmental agencies in product development and in procurement. It is also found that most of the research on tracked vehicle ride dynamics and manoeuvrability is confined to operations on rigid surfaces. To achieve a realistic evaluation and prediction of the dynamic behaviour of tracked vehicles in the field, the key is to have a better understanding of terrain response to dynamic vehicular loading, including its dynamic stiffness and damping. Challenges that face vehicle dynamicists in this emerging field are identified.     

Active Roll Control for Passenger Cars

The development of a mathematical model of a limited bandwidth hydro-pneumatic suspension that is incorporated into a vehicle handling model is described. The combined model is used to evaluate a suitable control strategy for eliminating body roll during a cornering manoeuvre. The philosophy behind the roll control strategy has been to use feedback measurements of the body motions which do not compromise the ride control. A study of the influence of the position of the body motion feedback transducer on the effectiveness of the system to reduce the body roll is presented. Non-linear modelling of the suspension components for a 0.8g cornering manoeuvre has revealed performance limitations. Conclusions are drawn as to the effectiveness of the control scheme.     

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.     

Estimation of origin‐destination matrices for a multimodal public transit network

This paper presents a procedure for the estimation of origin‐destination (O‐D) matrices for a multimodal public transit network. The system consists of a number of favored public transit modes that are obtained from a modal split process in a traditional four‐step transportation model. The demand of each favored mode is assigned to the multimodal network, which is comprised of a set of connected links of different public transit modes. An entropy maximization procedure is proposed to simultaneously estimate the O‐D demand matrices of all favored modes, which are consistent with target data sets such as the boarding counts and line segment flows that are observed directly in the network. A case study of the Hong Kong multimodal transit network is used to demonstrate the effectiveness of the proposed methodology.     

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.