In this paper we consider a network whose travel demands and road capacities are endogenously considered to be random variables. With stochastic demand and supply the route travel times are also random variables. In this scenario travelers choose their routes under travel time uncertainties. Several evidences suggest that the decision making process under uncertainty is significantly different from that without uncertainty. Therefore, the paper applies the decision framework of cumulative prospect theory (CPT) to capture this difference. We first formulate a stochastic network model whose travel demands and link capacities follow lognormal distributions. The stochastic travel times can then be derived under a given route choice modeling framework. For the route choice, we consider a modeling framework where the perceived value and perceived probabilities of travel time outcomes are obtained via transformations following CPT. We then formulate an equilibrium condition similar to that of User Equilibrium in which travelers choose the routes that maximizes their perceived utility values in the face of transformed stochastic travel times. Conditions are established guaranteeing existence (but not uniqueness) of this equilibrium. The paper then proposes a solution algorithm for the proposed model which is then tested with a test network.
Abstract. In improving road safety, the identification of black spots based on potential saving in accident costs is an attempt to make the selection of black spots to treat out of the identified ones. This selection is based on a new approach in which safety potential is employed as a key parameter which has a dual function of identification and prioritization. With this approach, it is possible to find black spots where safety improvement measures are expected to have the greatest economical effectiveness. Therefore, the approach may be a practically suitable tool for developing countries in road traffic accident reduction effort. This paper intends to introduce the new approach to identify road accident black spots in detail. First, the evolution of criteria for black spot identification is reviewed. What follows is an analytical framework for identifying black spots based on potential saving in accident costs. Finally, a particular case of practical implementation is enclosed in order to illustrate the approach.
This paper proposes a flexible transport network capacity evaluation and design problem (FNDP) under demand variability. The future stochastic demand is assumed to follow a normal distribution. Travellers' path choice behaviour is assumed to follow the Probit Stochastic User Equilibrium (SUE). The network reserve capacity is used to evaluate the performance of the network. Since the future demand is stochastic, the reserve capacity is measured by possible increases in both mean and standard deviation (SD) of the base demand distribution. The proposed model therefore represents the flexibility of the network in its robustness to OD demand variation (i.e. high SD). The proposed model can also determine an optimal network design to maximize the reserve capacity of the network in terms of both the mean and SD of the increased demand distribution. The paper applies the implicit programming approach to solve the FNDP. Sensitivity analysis is adopted to provide all necessary derivatives. The model and algorithm are tested with a hypothetical network to illustrate the merits of the proposed model.
In the road transport network, intersections are among the most critical locations leading to a risk of death and serious injury. The traditional methods to assess the safety of intersections are based on statistical analyses that require crash data. However, such data may be under-reported and omit important crash-related factors. The conventional approaches, therefore, are not easily applied to making comparisons of intersection designs under different road classifications. This study developed a risk-based approach that incorporates video-based traffic conflict analysis to investigate vehicle conflicts under mixed traffic conditions including motorcycles and cars in Thailand. The study applied such conflict data to assess the risk of intersections in terms of time-to-collision and conflict speed. Five functional classes of intersections were investigated, including local-road/local-road, local-road/collector, collector/arterial, collector/collector, and arterial/arterial intersections. The results showed that intersection classes, characteristics, and control affect the behavior of motorists and the safety of intersections. The results found that the low-order intersections with stop/no control are high risks due to the short time-to-collision of motorcycle-related conflicts. They generate frequent conflicts with low chance of injury. The high-order intersections with signal control are high risks due to high conflicting speeds of motorcycle–car conflicts. They generate few conflicts but at a high chance of injury. The study presents the applicability of video-based traffic conflict analysis for systematically estimating the crash risk of intersections. The risk-based approach can be deemed as a supplement indicator in addition to limited crash data to evaluate the safety of intersections. However, future research is needed to explore the potential of other road infrastructure under different circumstances.
ABSTRACT:This study presents the current situation of the land transport of sugar products in Northeastern Thailand. Data collections, field surveys and individual interviews with sugar producers, transporters, warehouse operators, exporters and marketing teams were conducted. It was revealed that most sugar product is currently transported via the road transport because the rail transport system commonly suffers from delays, unreliability, and results in dirty, damaged and lost goods. In addition, there is no direct route for rail transport connecting warehouses near the seaports. Freight transport models were developed to estimate the modal shift of sugar transport between road and rail systems according to the transport infrastructure development plans. It was found that rail infrastructure development would potentially influence sugar product transport systems to shift freight transport from the road system to the rail system. Furthermore, the development of motorways will decrease the amount of sugar product transported by the rail system.
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