The economic performance of transportation infrastructure: an empirical study on the recent development of China

It has been widely recognised that infrastructure systems highly affect the economic development of a country or region. In particular, the quality and quantity of transportation infrastructure have a direct bearing on economic growth in developing countries. Therefore, it is challenging to allocate the infrastructure construction budget across a country so that economic growth as a whole will not be hampered by the lack of infrastructure construction in any local area. In this research, the authors focus on simulating the correlations between economic growth, capital investment and transportation infrastructure construction in China historically and comparing the production and investment indicators at the cross-region based on the statistical data reported from government agencies in China. These computed correlations and indicators are crucial for making financial decisions and investment policies on transportation infrastructure construction at a national level.

Promoting transportation cycling for women : the role of bicycle infrastructure

Objective.
Females are substantially less likely than males to cycle for transport in countries with low bicycle transport mode share. We investigated whether female commuter cyclists were more likely to use bicycle routes that provide separation from motor vehicle traffic.
Methods.
Census of cyclists observed at 15 locations (including off-road bicycle paths, on-road lanes and roads with no bicycle facilities) within a 7.4 km radius of the central business district (CBD) of Melbourne, Australia, during peak commuting times in February 2004.
Results.
6589 cyclists were observed, comprising 5229 males (79.4%) and 1360 females (20.6%). After adjustment for distance of the bicycle facility from the CBD, females showed a preference for using off-road paths rather than roads with no bicycle facilities (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.12, 1.83), or roads with on-road bicycle lanes (OR = 1.34, 95% CI: 1.03, 1.75).
Conclusions.
Consistent with gender differences in risk aversion, female commuter cyclists preferred to use routes with maximum separation from motorized traffic. Improved cycling infrastructure in the form of bicycle paths and lanes that provide a high degree of separation from motor traffic is likely to be important for increasing transportation cycling amongst under-represented population groups such as women.

Endogenous transportation technology in a cournot differential game with intraindustry trade

We investigate a dynamic Cournot duopoly with intraindustry trade, where firms invest in R&D to reduce the level of iceberg transportation costs. We adopt both open-loop and closed-loop equilibrium concepts, showing that a unique (saddle point) steady state exists in both cases. In the open-loop model, optimal investments and the resulting efficiency of transportation technology are independent of the relative size of the two countries. On the contrary, in the closed-loop case firms’ R&D incentives are driven by the relative size of the two countries. Policy implications are also evaluated.

An optimal transportation routing approach using GIS-based dynamic traffic flows

This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively.

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.