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This paper is designed to evaluate and improve the effectiveness of transportation systems and reduce traffic congestion through the use of simulation models and scenario development. A system dynamics framework is used to test and evaluate the alternatives of future strategies for the city of Surabaya, Indonesia. Some factors affecting the effectiveness of transport systems include operational effectiveness and service effectiveness, as well as uncertainty. To improve the effectiveness of transportation systems, several strategies can be implemented, such as subsidizing public transportation, increasing the cost of private vehicle parking fees, raising taxes on private vehicles, and reducing delays in public transportation through scenario development. Scenario results show that, by pursuing these strategies, effectiveness could be improved by 80% as the impact of the increase in operational and service effectiveness, helping to mitigate traffic congestion. Congestion could be reduced to 70% (on average) due to the decrease in daily traffic. [ABSTRACT FROM AUTHOR]

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts. [ABSTRACT FROM AUTHOR]

This paper investigates the congestion pricing problem in urban traffic networks. A first-best strategy, a second-best strategy for toll leveling in closed cordons and a second-best strategy for determining both toll levels and toll points are considered. The problem is known to be a mixed integer programming model and formulated as a bi-level optimization problem, with an objective of maximizing the social welfare. A method is presented to solve the problem, based on a novel metaheuristic algorithm, namely quantum evolutionary algorithm (QEA). To verify the proposed method, the widely used genetic algorithm (GA) is also applied to solve the problem. The problem is solved for a medium-size urban traffic network and the results of the QEA are compared against the conventional GA. Computational results show that the QEA outperforms the GA in solution quality. [ABSTRACT FROM PUBLISHER]

This case study compares the Auto Restricted Zone Policy (ARZ) with price changes for parking permits in Louisiana State University (LSU). We find that ARZ has a more significant effect on the reduction in purchase of parking permits than price increases, albeit with a lag. We also find that while driving continues to be the primary mode of choice, a significant number of students are willing to adopt alternative means of transportation, if facilities associated with them are improved. Since LSU is fairly representative, we believe that this case study contains lessons for other universities in the country facing traffic congestion issues. [ABSTRACT FROM AUTHOR]

In urbanised areas around the world, road pricing policies are considered more and more frequently, the aim often being to alleviate (some of the) external traffic-related costs. To assess the effects of a proposed road pricing measure, several evaluation measures can be used, coming from different disciplines, including economics, transportation science and transport geography. In this paper, we compare two types of evaluation measure that can be used to assess the effectiveness of road pricing measures: geographical accessibility measures and economic social surplus measures. We explore the possibilities of both types of measure in terms of evaluating road pricing effects from a theoretical perspective, as well as comparing their outcome measures for a research area in the Netherlands. By means of correlation analysis and spatial comparison of outcomes, we find that geographical accessibility measures, being simpler and easier to interpret than economic measures, offer a poor proxy of the outcomes of the economic evaluation measures and vice versa. Therefore, the decision whether to use economic surplus measures or geographical accessibility indicators to a large extent depends on the research goal. If the goal is to gain a thorough insight into the monetary gains/losses resulting from a policy measure, economic measures, such as the rule-of-half or the logsum measure, are preferable. However, if there are concrete questions about the changes in accessibility of certain types of activity locations, geographical indicators, such as the contour and potential measures, are more appropriate. The outcomes of such geographical measures, and especially those of the contour measures, are, however, sensitive to the spatial distribution of activity locations in the area under study and to the selection of the impedance parameter that has to be selected in advance to compute the effects. Therefore, if geographical indicators are to be used, it would be wise to use different sensitivity parameters. It is only then that a thorough insight can be gained into the (sensitivity of) geographical accessibility effects. [ABSTRACT FROM AUTHOR]

Planners, engineers and economists have introduced various demand management methods in an attempt to reduce the fast growing traffic congestion. The basic idea behind various demand management strategies is to force drivers to travel and use transportation facilities more during off-peak hours and less during peak hours, as well as to increase the usage of underutilized routes. In this paper, a new demand management concept - Auction-based Congestion Pricing - is proposed and modeled. [ABSTRACT FROM AUTHOR]