# Eco-Efficient Mobility in Smart City Scenarios
## 1 Introduction  
While transport emissions start decelerating worldwide, they are still responsible for 24% of CO\({}_{2}\) emissions from fuel combustion [1]. There are a multitude of works in the literature dealing with this issue in maritime [2, 3] and air transport [4]. However, it is the road segment, including heavy and light vehicles, the one that accumulates 3/4 of transport emissions [1]. These values are extremely high under a global warming far from being solved. Electric vehicles appear as a potential solution to gradually alleviate this problem. Their sales have increased exponentially last years, involving not only cars, but also two-wheelers. As indicated in [5], about 20% of these vehicles are electric right now, with special mention given to electric micro-mobility, including bikes and scooters. This opens a new research niche in which to apply new information and communication technologies to improve traffic efficiency and assure safety, at the time that emissions are reduced in urban areas, above all. During the last twenty years, we have witnessed prominent advances in the vehicular industry. A clear example is the field of autonomous driving that, by the use of state-of-the-art on-board sensing and electronic systems, has become a reality today. Autonomous navigation systems have been refined by the integration of connectivity solutions, which also provide vehicles withnovel services supported by new-generation communication networks [6]. From the perspective of Cooperative-Intelligent Transportation Systems (C-ITS), vehicles are able to communicate among each other (Vehicle-to-Vehicle, V2V) and with the infrastructure (Vehicle-to-Infrastructure, V2I), as shown in Figure 1. This allows for widening the surroundings perception of each vehicle and has fueled the development of new productivity, safety, and entertainment applications, which are the pillars of the future C-ITS ecosystem [7]. However, it is a fact that these advances have been devoted to traditional vehicles, therefore ignoring the previously cited emergent personal mobility options that are transforming the landscape of urban scenarios. Many citizens are currently making use of personal vehicles such as bicycles, scooters, or electric motorcycles, due to their attractive eco-efficient features and the promotion of sustainable and healthy lifestyles. In this particular vehicular segment, and focusing on new-age personal mobility devices, there are special issues to be tackled in both hardware and software planes. Firstly, On-Board Units (OBUs) should be designed considering stringent restrictions in terms of power consumption and hardware integration in a constrained vehicle body. Secondly, the software plane calls for adapted interfaces, safety-aware designs, and the integration of digital maps addressing the unique mobility characteristics of these vehicles. In general, new on-board solutions are needed to support a new range of applications in the frame of sustainable mobility. For those reasons, novel hardware and software platforms should be adapted for personal vehicles (usually two-wheelers) that will permit the integration of connectedopods, bikes, segways, and equivalents into C-ITS and smart city scenarios. In this line, connectivity technologies coming from the Internet of Things (IoT), which have not been deeply investigated for vehicular scenarios yet, are suitable alternatives for this type of vehicles, given their aforementioned constraints. One clear example is the Low Power Wide Area Network (LPWAN) technology, which is  
Figure 1: Urban fully-connected vehicular scenario. White/red arrows: V2V/V2I links. being extensively adopted in smart city deployments, as it provides long range and energy efficient transmissions [8]. In this article, we provide a wide overview of the opportunities and challenges that the new wave of eco-efficient vehicles brings. We discuss about the specific needs of these elements as well as the potential services to be enabled for this market segment.