Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

Nonlinearities in the real exchange rates: new evidence from developed and developing countries

This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we show that a modified nonlinearity test, which includes additional right-hand-side variables, performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange rate for both developed and developing countries using the modified test for the recent floating period. In general, the results find a greater incidence of nonlinear dynamics for developing country real exchange rates.     

新制度经济学视角下的中国农地制度变迁：回顾与展望

研究目的:分析总结中国农地制度变迁的路径特征、决定条件和影响因素,并展望进一步研究方向。研究方法:文献分析法。研究结果:(1)改革开放以来的中国农地制度变迁呈现出一个较清晰的路径,即改革始终沿着市场取向、明晰产权、稳定地权的方向演进;(2)农地使用权制度改革的成功源于诱致性变迁与强制性变迁的结合,即弹性的中央政策制定、渐进式的地方实施以及具有学习效应的农户认知三者的有机互动,并体现出制度变迁的"共生演化"特征及其蕴含的"适应性效率";(3)新制度经济学是解释中国经济改革和农地制度变迁的有效工具,然而由于经典的新制度经济学本质上的静态性以及国家理论的缺乏,难以对现实世界的各类制度变迁给出一般化的解释。研究结论:基于经典的新制度经济学,进一步整合行为经济学、机制设计理论、演化博弈论等理论工具,超越"强制性—诱致性变迁"二分法,构建一个真正动态的制度变迁模型是一个重要研究方向。     

Macroeconomic adjustment with managed exchange rates and capital controls: Some lessons from China

This paper examines the performance of capital controls and exchange-rate management when the economy finds itself in dark corners. These are times when the real sector experiences a sequence of prolonged negative shocks from world demand, while the central bank faces low world interest rates on its foreign-exchange reserve holdings. We examine two regimes, one of a fixed exchange rate with strong capital controls and another with a more open capital account with a managed exchange rate. We show how this model replicates recent experiences of China as it moved from a relatively fixed exchange rate regime with strong capital controls to a more flexible exchange rate regime with a more open capital account. Our results show that capital-account liberalization should be accompanied by domestic price liberalization to avoid large losses in foreign exchange reserve and jumps in unemployment during dark corners in the more open regime.     

A social-media-based approach to assessing the effectiveness of equitable housing policy in mitigating education accessibility induced social inequalities in Shanghai,China

Social inequalities induced by education accessibility are widespread and concern land use policy makers globally. Yet much of existing research heavily emphasizes on uncovering the spatial patterns of housing price in relation to education resources. This paper aims to renew our understanding of this classical topic by bringing the importance of temporal and institutional dynamics to the fore. Specifically, this research presents a detailed examination of the relationship between school quality and housing rental dynamics under the intervention of equitable housing policy, with special reference to Shanghai, the most developed megacity in China, also one of the first Chinese cities granting equal rights for renters to access schools within the catchment area. Based on time-series housing rental data collected from social media, the t-test discovers that school quality has a significant impact on housing rental prices after the introduction of this new housing policy. Moreover, housing rental prices within high-quality school districts are significantly higher than those within ordinary school districts. The hedonic model and variance partitioning further confirm that school quality is capitalized into housing rental prices, and its relative contribution varies with temporal periods. More specifically, how the relative contribution of school quality changes over time is consistent with the schedule of primary school enrollment and sensitive to policy intervention. The difference in difference model foregrounds that the equitable housing policy does result in rental prices hike in high-quality school districts, i.e., a 13.5 % rental premium of housings within high-quality school districts compared with those within ordinary ones. We conclude that the equitable housing policy fails to achieve the expected goal and propose alternative suggestions for mitigating social inequalities in education accessibility. This study demonstrates a novel methodological framework for evaluating the social consequence of equitable housing policy based on social media data. It unravels how housing rental changes with school district division and the capitalization effect of school quality in housing rental prices.     

Estimating emissions based on the integration of microscopic traffic simulation and vehicle dynamics model

This study proposes an integrated simulation approach, which consists of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section, including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.     

A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region

Bogotá and the 17 neighboring municipalities make up one of the biggest metropolitan areas in Latin America. However, despite strong functional interactions within the area, there is no official government body at this level in charge of coordinating authorities and providing solutions to the wide variety of issues arising in the regional urban land system. Aiming at providing an insight on future land-use developments linked to new transport infrastructures and at offering a tool to support territorial decision-making, this paper presents a cellular automata-based (CA) model based in Metronamica® software, that allows testing different scenarios based on potential land-use policies, environmental suitability and transport alternatives.There has not been, so far, an urban planning tool that accounts for the complexities of this region. CA-based land-use simulations constitute a useful approach to understanding the impacts of urban planning policies and regulations. This tool can help to improve inter-territorial and inter-institutional coordination, which through planning and management policies seek a spatially integrated development, with a long-term perspective.The CA-based model proposed was calibrated to reproduce land-use changes between 2007 and 2016 using different methods and indicators. The model was used to simulate and analyze eight scenarios with different policy directions of transport infrastructure in the future of the region. The results of the simulations reflect the dynamics of territorial occupation. The calibration indices in the experiment indicate a high degree of suitability for the CA Bogotá model, proving its effectiveness and potential as a useful tool for decision-making. The results show that occupation scenarios with restricted developable zones within the city, tend to have the greater dispersion rate in the study area, compared to scenarios where land development plans are promoted in Bogotá, which representing a more compact development.     

Oil price shocks and economic growth: The volatility link

This paper shows that oil shocks impact economic growth primarily through the conditional variance of growth. Our comparison of models focuses on density forecasts. Over a range of dynamic models, oil shock measures and data, we find a robust link between oil shocks and the volatility of economic growth. We then develop a new measure of oil shocks and show that it is superior to existing measures; it indicates that the conditional variance of growth increases in response to an indicator of the local maximum oil price exceedance. The empirical results uncover a large pronounced asymmetric response of the growth volatility to oil price changes. The uncertainty about future growth is considerably lower than with a benchmark AR(1) model when no oil shocks are present.     

Is the environment‐friendly factor attractive to customers when purchasing electric vehicles? Evidence from South Korea

In a bid to reduce greenhouse gas emissions, several countries worldwide are implementing policies to promote electric vehicles (EVs). However, contrary to expectations, the diffusion speed of EVs has been rather slow in South Korea. This study analyzes consumer preferences for the technological and environmental attributes of EVs and derives policy and environmental implications to promote market diffusion of EVs in South Korea. We conduct a choice‐based conjoint survey of 1,008 consumers in South Korea and estimate the consumer utility function using a mixed logit model considering consumer heterogeneity. Based on the consumer utility function, we analyze consumers' willingness‐to‐pay (WTP) for EV attributes such as driving range, charging method, charging time, autonomous driving function, carbon dioxide (CO₂) reduction rate, and purchase price. The results indicate that the current low acceptance of EVs is due to their relatively high price and lack of a battery charging technology that satisfies consumers' expectations of the charging method and time. One interesting finding is that Korean consumers have a relatively higher WTP for the CO₂ reduction rate of EVs than consumers in other countries; however, they do not consider CO₂ reduction over other technological attributes when choosing EVs. This implies that the rate of CO₂ reduction of EVs is not an important factor for South Korean consumers when buying EVs. We also calculate the effect of CO₂ reduction with the market penetration of EVs and find that CO₂ reduction through the diffusion of EVs depends on the country's electricity generation mix.     

基于车辆数据的k近邻联合概率数据关联算法

在交通场景中采用一些预警措施能够有效地减少交通事故发生。例如，对车辆轨迹进行跟踪并预测车辆的驾驶行为，就是一个常用的预警方法。在对车辆进行跟踪的过程中，数据关联是很重要的部分，它可以对车辆的观测点和轨迹进行关联，从而更新车辆的轨迹，完成跟踪过程。在此背景下，提出了一种新的数据关联算法，即k近邻联合概率数据关联算法(k Nearest Neighbor-Joint Probability Data Association,kNN-JPDA)。实验结果表明，该算法能够较好地解决在交通场景下车辆数据的数据关联问题，在精度以及运行效率方面都有所提高。