Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

Analysis on the Characteristics and Development Trends of the Support Technology of High Ground Stress Tunnels in China北大核心CSCD

Combining the present situation and development trend of different tunnel support technologies at home and abroad, this paper analyzes the problems of rockburst in hard rock tunnels and large deformation in soft rock tunnels caused by high ground stress. It is concluded that: 1) regarding the rockburst problem, the current support technology is mainly influenced by the rock burst mechanism which is dominated by static factors, and so the used support components are generally of smaller deformation performance and "passive support" properties; 2) as the rockburst is the result of dynamic-static stress coupling, and only the anchor bolt has the "active support" attribute in the current "shotcrete+anchor bolt+wire net" support system, so the best support system should have the two functions of active support and energy release in terms of the rockburst problem, and the key focus of the research and development is anchorage members; 3) there are three main support types for large deformation in soft rock tunnels, e.g. the heavy support, layered support and yielding support. Among them, the heavy support system in underground cavern with large deformation is easy to induce excessive surrounding rock pressure, and so the applicable conditions are limited. The layered support system is still not the best choice due to its immature theoretical study, difficult determination of the thickness value and the installation time of each support layer and the interference to construction progress. With the characteristics of timely support and yielding while supporting, the yielding support system can give full play to the performance values of surrounding rocks and supporting materials, and make both of them reach the optimal state, so it is the best choice for supporting the soft rock tunnels with large deformations. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

The impact of planned disruptions on rail passenger demand

Transportation - Disruptions to rail journeys are experienced by rail passengers on a daily basis throughout the world, with the impacts on passengers ranging from minimal to major. Such...     

Socioeconomic and usage characteristics of transportation network company (TNC) riders

Transportation - The widespread adoption of smartphones followed by an emergence of transportation network companies (TNC) have influenced the way individuals travel. The authors use the 2017...     

The role of children’s independent mobility and social media use for face-to-face social interaction with friends

Transportation - Social interaction with friends is an important contributor to children’s well-being, but how transport affects this is rarely studied. For two or more children (not of the...     

The influence of parents’ travel patterns,perceptions and residential self-selectivity to their children travel mode shares

Using the UK National Travel Survey from 2002 to 2006, this paper investigates the influence of households’ residential self-selectivity, parents’ perceptions on accessibilities and their travel patterns on their children daily travel mode share. In doing this, this study introduces a model structure that represents the complex interactions between the parents’ travel patterns, their perceptions on public transport services and their reported residential self-selectivity reasons and the children travel mode shares. This structure is analysed with structural equation modelling. The model estimation results show that parents’ residential self-selectivity, parents’ perceptions and satisfactions on accessibilities and their daily travel patterns significantly influence the children’s daily travel mode shares. However, the effects are not uniform across household members. This study has revealed that households’ residential self-selectivity behaviours have more correlations with the children’s non-motorised mode shares, whilst the parents’ perceptions and satisfactions on transport infrastructure and public transport service qualities have more correlations with parents’ mode shares. The results also confirm that parents’ non-motorised modes use in travelling is highly correlated with the children’s physically active travel mode shares. However, at the same time, the results also show that the effects of mothers’ car use to the children travel mode shares is more apparent than fathers’.     

Effects of task complexity and time pressure on activity-travel choices: heteroscedastic logit model and activity-travel simulator experiment

This paper derives, estimates and applies a discrete choice model of activity-travel behaviour that accommodates potential effects of task complexity and time pressure on decision-making. To the best of our knowledge, this is the first time that both factors (task complexity and time pressure) are jointly captured in a discrete choice model. More specifically, our heteroscedastic logit model captures potential impacts of task complexity and time pressure through the scale of the utility of activity-travel options. We collect data using a novel activity-travel simulator experiment that has been specifically designed with the aim of testing our model. Results are in line with expectations, in that higher levels of task complexity and time pressure are found to result in a smaller scale of utility. In other words, higher levels of task complexity and time pressure lead to more random choice behaviour and as a consequence to less pronounced differences in choice probabilities between alternatives. An empirical illustration suggests that choice probability-differences between models that do and those that do not capture these effects, can be very substantial; this in turn suggests that failing to capture the effects of task complexity and time pressure in discrete choice models of activity travel decision-making might lead to serious bias in forecasts of the effects of transport policies.     

The digital revolution and worthwhile use of travel time: implications for appraisal and forecasting

Savings in travel time and more specifically their monetary value typically constitute the main benefit to justify major investment in transport schemes. However, worthwhile use of travel time is an increasingly prominent phenomenon of the digital age. Accordingly, questions are increasingly being asked regarding whether values of time used by countries around the world based on their appraisal approaches are too high. This paper offers the most comprehensive examination of our theoretical and empirical understandings of international appraisal approaches and how they account for worthwhile use of travel time. It combines the economics perspective with wider social science insight and reaches the conclusion that past revolutions in transport that have made longer and quicker journeys possible are now joined by a digital revolution that is reducing the disutility of travel time. This revolution offers potential economic benefit that comes at a fraction of the cost of major investments in transport that are predicated on saving travel time. The paper highlights the challenges faced in both current and indeed potential alternative future appraisal approaches. Such challenges are rooted in the difficulty of measuring time use and productivity with sufficient accuracy and over time to credibly account for how travel time factors into the economic outcomes from social and working practices in the knowledge economy. There is a need for further research to: establish how improvements in the opportunities for and the quality of worthwhile use of travel time impact on the valuation of travel time savings for non-business travel; improve our understanding of how productive use of time impacts on the valuation of time savings for business travellers; and estimate how these factors have impacted on the demand for different modes of travel.     

A stated preference examination of time of travel choice for a recreational trip: An addendum

A paper was published in the immediately previous issue of this journal describing a stated preference experiment examining how people are influenced in the selection of a departure time for a hypothetical trip to see a movie. The title was ‘A stated preference examination of time of travel choice for a recreational trip’, Volume 30(3):17–44. Numbers were used to indicate references in the text of the paper and in Table 1 accompanying the text, but these numbers were omitted from the list of references at the end of the paper - making it very difficult to identify specific citations. The list of references from the paper is reprinted below with the reference numbers included. This provides a listing that can be used in conjunction with the text of the paper and Table 1 as published to identify specific citations as intended.