Parking Preferences of Tourists in Sun Moon Lake National Scenic Area, Taiwan

Sun Moon Lake is a famous tourist attraction in Taiwan and abroad. However, as Sun Moon Lake is surrounded by mountains and has limited land to develop, traffic congestion around the lake area is commonplace during peak holiday hours. This study focusses on the parking choices of visitors to Sun Moon Lake and develops a stated preference (SP) instrument with multiple scenarios to evaluate parking preferences under various financial and service level scenarios. We estimate Multinomial Logit (MNL) and Mixed Logit (ML) models, accounting for the panel nature of the data (PDML)to identify preferences for parking choices of visitors to Sun Moon Lake. The focus is on understanding how parking price, travel time, walking time, scenery, and transfers between public transport affect visitors' parking choices. Unlike the findings of studies in metropolitan areas, which often find that parking price was the deciding factor, visitors' parking decisions in the tourist area were more concerned with time factors, such as the time to search for places to park and traffic congestion, possibly due to the less frequent use of tourist venues. Although raising parking price can suppress parking demand in the scenic area, other parking management mechanisms work better, such as the construction of new and suitable outer parking lots with transfer buses to relieve the heavily congested traffic in the scenic area. In addition we find that using the parking space in the area can be improved by beautifying the landscaping between the parking lots and the tourist spots, enhancing the pleasure of traveling along the routes, introducing multiple transfer modes, and providing real-time traffic information to tourists

Network Equilibrium under Cumulative Prospect Theory and Endogenous Stochastic Demand and Supply

The 18th International Symposium on Transportation and Traffic Theory (ISTTT), held at the The Hong Kong Polytechnic University in Hong Kong, China on 16-18 July 2009In 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.Department of Civil and Environmental Engineerin

Decision analysis for the exploration of gas reserves: merging todim and thor

This article approaches the problem of selecting the non-dominated alternative for the destination of the natural gas reserves in the Mexilhão field in the Santos Basin, Brazil. Major aims of the case study reported here were to create a mechanism for assisting in the process of analyzing and selecting the best options for the destination of natural gas, and to enable the decision agent to choose the investment options best aligned to the expectations and objectives observed in the company strategies. The decision analysis employed in the study made use of the TODIM method and the THOR multicriteria decision support system. The application of both demonstrated that a decision analytic framework can be extremely useful when recommending options for upstream projects, owing to the fact that it can clearly identify the most important alternatives in the face of the scenarios tested and in relation to the criteria expressed

Equilibrium Trip Scheduling in Congested Traffic under Uncertainty

Whilst traditional modeling and research efforts put emphasis on the effect of congestion on travel choices, recently more and more studies examine the notion of travel time uncertainty on travel decision. In particular, travel time reliability forms an important component in modeling route choice and trip scheduling. This paper considers equilibrium trip scheduling under random travel delay in a single bottleneck. Travelers form a heterogeneous population with distinctive requirements on the probability of punctual arrival and each with a different valuation toward earliness and lateness. The analysis shows that random delay plays a significant role in travel costs and introduces substantial differences in the queuing pattern, departure and arrival times, as compared with the traditional deterministic model