The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Extended local labor markets due to high speed trains : Visualization of estimations in the Swedish national travel demand forecasting tool, SAMPERS

Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Real-Time Control Of Floods Along The Demer River, Belgium, By Means Of MPC In Combination With GA And A Fast Conceptual River Model

Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

Are price limits on futures markets that cool? evidence from the brazilian merchantile & futures exchange

This paper investigates the impact of price limits on the Brazil- ian future markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. Our main finding is that price limits drive back prices as they approach the lower limit. There is a strong cool-off effect of the lower limit on the conditional mean, whereas the upper limit seems to entail a weak magnet effect on the conditional variance. We then build a trading strategy that accounts for the cool-off effect so as to demonstrate that the latter has not only statistical, but also economic signifi- cance. The resulting Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider.

Are price limits on futures markets that cool?: evidence from the Brazilian Mercantile and Futures Exchange

This paper investigates the impact of price limits on the Brazilian futures markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the S˜ao Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. The results indicate that the conditional mean features a floor cool-off effect, whereas the conditional variance significantly increases as the price approaches the upper limit. We then build a trading strategy that accounts for the cool-off effect in the conditional mean so as to demonstrate that the latter has not only statistical, but also economic significance. The in-sample Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider, whereas out-of-sample results evince similar performances.

On the limits of cheap talk for public good provision

This article studies a model where, as a consequence of private information, agents do not have incentive to invest in a desired joint project, or a public good, when they are unable to have prior discussion with their partners. As a result, the joint project is never undertaken and inefficiency is observed. Agastya, Menezes and Sengupta (2007) prove that with a prior stage of communication, with a binary message space, it is possible to have some efficiency gain since "all ex-ante and interim efficient equilibria exhibit a simple structure". We show that any finite message space does not provide efficiency gain on the simple structure discussed in that article. We use laboratory experiments to test these results. We find that people do contribute, even without communication, and that any kind of communication increases the probability of project implementation. We also observed that communication reduces the unproductive contribution, and that a large message space cannot provide efficiency gain relative to the binary one.

Public debt and the limits of fiscal policy to increase economic growth

Research that seeks to estimate the effects of fiscal policies on economic growth has ignored the role of public debt in this relationship. This study proposes a theoretical model of endogenous growth, which demonstrates that the level of the public debt-to-gross domestic product (GDP) ratio should negatively impact the effect of fiscal policy on growth. This occurs because government indebtedness extracts part of the savings of the young to pay interest on the debts of the older generation, who are no longer saving. Therefore, the payment of debt interest assumes an allocation exchange role between generations that is similar to a pay-as-you-go pension system, which results in changes in the savings rate of the economy. The major conclusions of the theoretical model were tested using an econometric model to provide evidence for the validity of this conclusion. Our empirical analysis controls for timeinvariant, country-specific heterogeneity in the growth rates. We also address endogeneity issues and allow for heterogeneity across countries in the model parameters and for cross-sectional dependence.

Voice over IP 2.0: an analysis of limits and potential of IP2IP telecommunication

Internet Telephony (VoIP) is changing the telecommunication industry. Oftentimes free, VoIP is becoming more and more popular amongst users. Large software companies have entered the market and heavily invest into it. In 2011, for instance, Microsoft bought Skype for 8.5bn USD. This trend increasingly impacts the incumbent telecommunication operators. They see their main source of revenue – classic telephony – under siege and disappear. The thesis at hand develops a most-likely scenario in order to determine how VoIP is evolving further and it predicts, based on a ten-year forecast, the impact it will have on the players in the telecommunication industry.The paper presents a model combining Rogers’ diffusion and Christensen’s innovation research. The model has the goal of explaining the past evolution of VoIP and to isolate the factors that determine the further diffusion of the innovation. Interviews with industry experts serve to assess how the identified factors are evolving.Two propositions are offered. First, VoIP operators are becoming more important in international, corporate, and mobile telephony. End-to-end VoIP (IP2IP) will exhibit strong growth rates and increasingly cannibalize the telephony revenues of the classic operators. Second, fix-net telephony in SMEs and at home will continue to be dominated by the incumbents. Yet, as prices for telephony fall towards zero also they will implement IP2IP in order to save costs. By 2022, up to 90% of the calls will be IP2IP. The author recommends the incumbents and VoIP operators to proactively face the change, to rethink their business strategies, and to even be open for cooperation.

Enforcing international financial standards in Brazil: limits and possibilities for adoption of IOSCO principles

Foreign capital and institutional investors play a key role in the Brazilian capital and financial markets. Internationally promoted regulatory patterns, especially IOSCO principles, have been increasingly influencing administrative rule making by the Brazilian Securities and Exchange Commission (CVM) as well as the adoption of transnational rules in Brazil by means of self-regulatory activity. Even though there is a certain level of convergence of market regulatory standards at the transnational level, implementation and enforcement of rules remains essentially domestic. We analyze two case studies regarding the transposition of international standards into the Brazilian legal system, which illustrate this tension between the transnational and domestic dimensions of financial markets regulation. The first case concerns a CVM rule on disclosure of executive compensation and the its interpretation by local courts. The second case refers to the adoption of suitability rules.

The impact of property rights and its limits

The empirical evaluation of the effect of land property rights typically suffers from selection problems. The allocation of property rights across households is usually not random but based on wealth, family characteristics, political clientelism, or other mechanisms built on differences between the groups that acquire property rights and the groups that do not. In this paper, we address this selection concern exploiting a natural experiment in the allocation of property rights. Twenty years ago, a homogenous group of squatters occupied a piece of privately owned land in a suburban area of Buenos Aires, Argentina. When the Congress passed an expropriation law transferring the land from the former owners to the squatters, some of the former owners surrendered the land (and received a compensation), while others decide to sue in the slow Argentine courts. These different decisions by the former owners generated an allocation of property rights that is exogenous to the characteristics of the squatters. We take advantage of this natural experiment to evaluate the effect of the allocation of urban land property rights. Our preliminary results show significant effects on housing investment, household size, and school attrition. Contradicting De Soto's hypotheses, we found nonsignificant effects on labor income and access to credit markets.