Perceptions of safety on a shared road: Driving,cycling, or walking near an autonomous vehicle

Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.     

Impacts of converting from leaded to unleaded gasoline on ambient lead concentrations in Jakarta metropolitan area

Total suspended particulate mater （TSP） concentrations were monitored for one year from July 2000 and for one year from April 2003 in Jakarta City. Thirteen elemental TSP components, aluminum （Al）, sodium （Na）, iron （Fe）, lead （Pb）, potassium （K）, zinc （Zn）, titanium （Ti）, manganese （Mn）, bromine （Br）, copper （Cu）, chromium （Cr）, nickel （Ni）, and vanadium （V） were analyzed by a sequential X-ray fluorescence spectrometer. Al, Na, Fe, K, and Pb were major components at most of the sampling locations in 2000. However, only Pb in 2003 dramatically decreased to one tenth. The phase-out of leaded gasoline began on July 1, 2001 in Jakarta City and lead content in gasoline decreased to one tenth, too. The decrease in Pb concentration was a result of the phase-out of leaded gasoline, as lead emissions mainly are exhaust gas from vehicles.     

Passenger distractions among adolescent drivers

PROBLEM: Adolescents who drive with peers are known to have a higher risk of crashes. While passengers may distract drivers, little is known about the circumstances of these distractions among teen drivers. METHOD: This study used survey data on driving among 2,144 California high school seniors to examine distractions caused by passengers. RESULTS: Overall, 38.4% of youths who drove reported having been distracted by a passenger. Distractions were more commonly reported among girls and students attending moderate- to high-income schools. Talking or yelling was the most commonly reported type of distraction. About 7.5% of distractions reported were deliberate, such as hitting or tickling the driver or attempting to use the vehicle's controls. Driving after alcohol use and having had a crash as a driver were both significant predictors of reporting passenger-related distraction. CONCLUSION: Adolescents often experience distractions related to passengers, and in some cases these distractions are intentional. IMPACT ON INDUSTRY: These results provide information about teenage drivers who are distracted by passenger behaviors. In some cases, passengers attempted to use vehicle controls; however, it seems unlikely that this behavior is common enough to warrant redesign of controls to make them less accessible to passengers.     

北京市某高层建筑高空电磁辐射环境影响分析

选取北京市某代表性高层居民楼顶平台作为高空电磁辐射环境水平监测点进行综合场强和选频监测,评价总体电磁辐射环境水平,并分析监测区域电磁辐射能量的来源。结果表明：该高空监测区域的电磁辐射环境总体水平低于国家规定的公众照射导出限值,但高于地面水平。监测区域主要受30 km 外的中波台影响,其次是9 km 外的中央电视塔。影响最大的是639 kHz频率的中波信号,占100 kHz～300 MHz总场强的95％以上,其次是1．28 MHz频率的中波信号。提出,开展敏感建筑物规划建设时,应考虑中波的传播特性和对环境的影响。     

Comparative analysis of air pollution emissions by electric utilities: Public policy implications

One of the objectives of US environmental regulations was to reduce industrial air pollution emissions, especially from the electric utility industry, the major industrial air polluter. In this study, a comparative analysis of air pollution emissions from fossil-fuel-burning electric utility plants is conducted. The analysis focuses on a 12-yr period from 1975 to 1987 for three air pollutants: particulates, surfur dioxide, and nitrogen oxides. The results indicate that particulate emissions have been significantly reduced but that sulfur dioxide and nitrogen oxides are still major problems for a number of plants. Furthermore, the disparity in the performance by plants indicates that by using current technology, the industry as a whole could greatly reduce these emissions. These results have policy implication for future environmental legislation.     

CFD Prediction of Air Quality in the Area between Two City Vehicular Tunnels Considering Moving Cars

Concentration fields of different pollutants that spread outside two roadtunnels predicted with a CFD code will be presented. The solution domain represents the city area located between two tunnel outlets – tunnel Strahov and tunnel Mrazovka in Prague. The vicinity of both tunnels is a heavily built up area with tall buildings forming typical street canyons. The CFD modelling predicts the situation after the tunnel Mrazovka will be finished and traffic will increase considerably between both tunnels. Namely, an interest was given to the prediction of dispersion of emissions leaving both tunnel and the area touched by the traffic. For the CFD predictions, a method previously developed for moving vehicles was used. The method uses combination of Eulerian and Lagrangian approaches to moving objects and is capable of modeling different speeds and traffic rates of cars as well as traffic-induced turbulence. Influence of several meteorological parameters was studied, namely wind speed and direction and traffic parameters, like traffic rates and speed of cars. The method separates contributions from different sources to the total concentration field, namely from background, tunnel outlet and roadway. Results are presented in the form of horizontal and vertical concentration fields of NO_x.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Effectiveness of primary enforcement safety belt laws and enhanced enforcement of safety belt laws: a summary of the Guide to Community Preventive Services systematic reviews

BACKGROUND: The use of safety belts is the single most effective means of reducing fatal and nonfatal injuries in motor-vehicle crashes. This paper summarizes the systematic reviews of two interventions to increase safety belt use: primary enforcement safety belt laws and enhanced enforcement of safety belt laws. The reviews were previously published in the American Journal of Preventive Medicine. METHODS: We conducted the systematic reviews using the methodology developed for the Guide to Community Preventive Services. RESULTS: These reviews provide strong evidence that primary laws are more effective than secondary laws in increasing safety belt use and decreasing fatalities and that enhanced enforcement is effective in increasing safety belt use. Increases in belt use are generally highest in states with low baseline rates of belt use. DISCUSSION: Primary safety belt laws and enhanced enforcement programs tend to result in greater increases in usage rates for target groups with lower baseline rates. Concerns regarding public opposition to these interventions may impede their implementation in some jurisdictions. However, surveys indicate that a substantial majority of the public supports implementation of both primary laws and enhanced enforcement programs. CONCLUSION: Based on the strong evidence for effectiveness of primary safety belt laws and enhanced enforcement programs, the Task Force on Community Preventive Services recommended that all states enact primary safety belt laws and that communities implement enhanced enforcement programs.     

The connecticut indirect source review: A methodology and model for evaluating CO concentrations

The body of information presented in this paper is directed to air pollution engineers who are concerned with the effect of indirect sources on ambient concentrations of carbon monoxide (CO). Data taken under controlled conditions are used to empirically derive and calibrate a model for predicting CO concentrations in the vicinity of roadway intersections and other points of possible vehicular congestion. Since the predicted free flow CO contribution of vehicles traveling at normal road speeds is relatively low, it is concluded that idling vehicles at points of congestion are the major cause of CO violations, and that state and federal programs should place more emphasis on relieving congestion and reducing idling emission rates in new vehicles.