OzTug mobile robot for manufacturing transportation

Firstly, this paper introduces the OzTug mobile robot developed to autonomously manoeuvre large loads within a manufacturing environment. The mobile robot utilizes differential drive and necessary design criteria includes low-cost, mechanical robustness, and the ability to manoeuvre loads ranging up to 2000kg. The robot is configured to follow a predefined trajectory while maintaining the forward velocity of a user-specified velocity profile. A vision-based fuzzy logic line following controller enables the robot to track the paths on the floor of the manufacturing environment. Secondly, in order to tow large loads along predefined paths three different robot-load configurations are proposed. Simulation within the Webots environment was performed in order to empirically evaluate the three different robot-load configurations. The simulation results demonstrate the cost-performance trade-off of two of the approaches.

Upgrading arc median shortest path problem for an urban transportation network

In this paper, we propose an algorithm for an upgrading arc median shortest path problem for a transportation network. The problem is to identify a set of nondominated paths that minimizes both upgrading cost and overall travel time of the entire network. These two objectives are realistic for transportation network problems, but of a conflicting and noncompensatory nature. In addition, unlike upgrading cost which is the sum of the arc costs on the path, overall travel time of the entire network cannot be expressed as a sum of arc travel times on the path. The proposed solution approach to the problem is based on heuristic labeling and exhaustive search techniques, in criteria space and solution space, respectively. The first approach labels each node in terms of upgrading cost, and deletes cyclic and infeasible paths in criteria space. The latter calculates the overall travel time of the entire network for each feasible path, deletes dominated paths on the basis of the objective vector and identifies a set of Pareto optimal paths in the solution space. The computational study, using two small-scale transportation networks, has demonstrated that the algorithm proposed herein is able to efficiently identify a set of nondominated median shortest paths, based on two conflicting and noncompensatory objectives.

Triploid and diploid rainbow trout do not differ in their stress response to transportation

We examined the neuroendocrine and cellular stress responses of diploid and triploid rainbow trout Oncorhynchus mykiss to transportation. Juvenile diploid and triploid rainbow trout (28 and 26 g/fish average weight, respectively) were stocked at 100 g/L in replicate 70-L tanks and subjected to transportation for an 8-h period. Subsequent levels of plasma cortisol and glucose and of cellular hepatic glutathione (GSH) and heat shock protein 70 (Hsp70) were similar between ploidy groups, indicating that triploid fish respond to transportation in much the same way as diploid fish. A stationary treatment was also included that involved confinement of experimental fish in similar tanks without transport to determine to what extent high-density containment contributed to the stress response in the absence of the noise and vibration of transport. Unexpectedly, fish in the stationary treatment had significantly higher plasma cortisol and glucose levels than the transported fish; however, this might be attributable to a confounding effect of hyperoxia, as oxygen levels fluctuated between 150% and 460% saturation in the stationary tank, while those in the transported tank remained within 100–200% saturation. We suggest that when long stops are necessary while transporting fish, water agitators be used to preclude the additional stress of excessive gas saturation. This may be particularly important for triploid fish, which had lower hepatic GSH levels than diploid fish as well as a low level of mortality in the stationary treatment, unlike the diploid fish.

Solving the median shortest path problem in the planning and design of urban transportation networks using a vector labeling algorithm

This paper proposes an alternative algorithm to solve the median shortest path problem (MSPP) in the planning and design of urban transportation networks. The proposed vector labeling algorithm is based on the labeling of each node in terms of a multiple and conflicting vector of objectives which deletes cyclic, infeasible and extreme-dominated paths in the criteria space imposing cyclic break (CB), path cost constraint (PCC) and access cost parameter (ACP) respectively. The output of the algorithm is a set of Pareto optimal paths (POP) with an objective vector from predetermined origin to destination nodes. Thus, this paper formulates an algorithm to identify a non-inferior solution set of POP based on a non-dominated set of objective vectors that leaves the ultimate decision to decision-makers. A numerical experiment is conducted using an artificial transportation network in order to validate and compare results. Sensitivity analysis has shown that the proposed algorithm is more efficient and advantageous over existing solutions in terms of computing execution time and memory space used.

An algorithm to median shortest path problem (MSPP) in the design of urban transportation networks

This paper proposes an efficient solution algorithm for realistic multi-objective median shortest path problems in the design of urban transportation networks. The proposed problem formulation and solution algorithm to median shortest path problem is based on three realistic objectives via route cost or investment cost, overall travel time of the entire network and total toll revenue. The proposed solution approach to the problem is based on the heuristic labeling and exhaustive search technique in criteria space and solution space of the algorithm respectively. The first labels each node in terms of route cost and deletes cyclic and infeasible paths in criteria space imposing cyclic break and route cost constraint respectively. The latter deletes dominated paths in terms of objectives vector in solution space in order to identify a set of Pareto optimal paths. The approach, thus, proposes a non-inferior solution set of Pareto optimal paths based on non-dominated objective vector and leaves the ultimate decision to decision-makers for purpose specific final decision during applications. A numerical experiment is conducted to test the proposed algorithm using artificial transportation network. Sensitivity analyses have shown that the proposed algorithm is advantageous and efficient over existing algorithms to find a set of Pareto optimal paths to median shortest paths problems.

Time series analysis of air transportation service quality and travel demand in Japan

The evolution of domestic air travel service in Japan is a product of many factors including airline responses to the changing aviation market, government interventions in terms of regulatory/deregulatory policies, infrastructure investments, and changes in market structure. This paper presents an empirical investigation of the changing quality of passenger airline service and its implications in the domestic aviation market in Japan using qualitative review and a time series analysis of the domestic airline markets from 1986 to 2003. The results show that to meet the ultimate aim of deregulation to increase air passengers’ welfare gain, there is a need to instill measures to correct service imbalance and to create innovative airport demand-capacity management measures.

Is park visitation associated with leisure-time and transportation physical activity?

Objective
The aim of this study was to examine whether frequency of park visitation was associated with time spent in various domains of physical activity among adults living in a disadvantaged neighbourhood of Victoria, Australia.

Methods
In 2009, participants (n = 319) self-reported park visitation and physical activity including: walking and cycling for transport, leisure-time walking, leisure-time moderate- to vigorous-intensity physical activity, and total physical activity.

Results
The mean number of park visits per week was 3.3 (SD = 3.8). Park visitation was associated with greater odds of engaging in high (as compared to low) amounts of transportation physical activity, leisure-time walking, leisure-time moderate- to vigorous-intensity physical activity (MVPA) and total physical activity. Each additional park visit per week was associated with 23% greater odds of being in the high category for transportation physical activity, 26% greater odds of engaging in high amounts of leisure-time walking, 11% greater odds of engaging in MVPA, and 40% greater odds of high total physical activity.

Conclusions
Acknowledging the cross-sectional study design, the findings suggest that park visitation may be an important predictor and/or destination for transportation and leisure-time walking and physical activity. Findings highlight the potentially important role of parks for physical activity.