There are a variety of strategies that are now being considered to reduce fuel consumption and carbon dioxide (CO 2 ) emissions from the transportation sector. One strategy that is gaining interest worldwide is known as "eco-driving". Eco-driving typically consists of changing a person's driving behavior based on general (static) advice to the driver, such as accelerating slowly, driving smoothly, reducing high speeds, etc. Taking this one-step further, it is possible to provide realtime advice to drivers based on changing traffic and infrastructure conditions for even greater fuel and emission savings. This concept of dynamic eco-driving takes advantage of real-time traffic sensing and infrastructure information, which can then be communicated to a vehicle with a goal of reducing fuel consumption and emissions. In this paper, we consider dynamic eco-driving in an arterial corridor with traffic signals, where signal phase and timing information of a traffic light is provided to the vehicle. The vehicle can then adjust its velocity while traveling through a signalized corridor with the goal of minimizing fuel consumption and emissions. A dynamic ecodriving velocity planning algorithm has been developed and is described herein. This algorithm has then been tested in simulation, showing initial fuel economy and CO 2 improvements of around 12%.

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In this study, fragrant rosewood (Dalbergia odorifera T.C. Chen) seedlings were cultured with conventional and exponential fertilization treatments at rates of 2 and 4 g plant −1 (15-9-12), and an unfertilized control under the natural photoperiod and extended photoperiods with supplementary lighting for 3 and 6 h. Seedlings under the extended photoperiods had greater height but less root-collar diameter than those under the natural photoperiod. The extended photoperiod with supplementary lighting for 3 h resulted in the greatest biomass in stem and root. Apparent nutrient dilution was found from October 2015 to January 2016 in most fertilization treatments, which, however, was counted by the treatment of exponential fertilization at 4 g plant −1. Vector analysis indicated that the treatment of extended photoperiod with supplementary lighting for 3 h induced nutrition depletion for nitrogen (N) and phosphorus (P) relative to the natural photoperiod, while the exponential fertilization treatment induced luxury consumption for all elements of N, P and potassium (K) relative to the control. In conclusion, the extended photoperiod of supplementary lighting for 3 h was recommended for the culture of fragrant rosewood seedlings, and the exponential fertilization resulted in better nutritional status by counting nutrient dilution relative to the conventional fertilization.

One of the objectives of the U.S. Department of Transportation's connected vehicle (CV) research program is to develop innovative applications that take advantage of communications between vehicles and roadside infrastructure as well as between the vehicles themselves to improve safety, mobility, and the environmental performance of multimodal transportation systems. Many of the energy- and environment-focused CV applications involve the prescription of optimal speed profiles for vehicles that travel within the transportation network. These recommended speed profiles can then be provided to the drivers through human–machine interfaces (HMIs). However, the drivers may not be able to follow the recommended speed profiles closely. In that case, the effectiveness of the applications might be degraded. These HMIs may even be distracting and detrimental to safety. Partial vehicle automation can be used to follow a recommended speed profile and play an important role to ensure that the benefits of these CV applications are realized fully. This paper presents an evaluation of the supplementary benefits from partial vehicle automation in CV applications with the use of an ecoapproach and departure application at signalized inter sections in a case study. This application provides recommended speeds for vehicles as they approach and travel through a signalized intersection so that they pass through the intersection on green or decelerate to a stop in the most ecofriendly manner. The evaluation was based on real-world HMI manual driving data and in simulated partial automation data. The results showed different levels of supplementary benefits, which depended on the ability of the drivers to follow the recommended speeds, compared with the actual target speed profiles that would have been achieved through partial vehicle automation.