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About 64% of global oil consumption and 23% of the worldwide CO2 emissions are attributed to transportation [1]. [...]every year, congestion accounts for billions of dollars due to wasted time and fuel consumption, and the World Health Organization (WHO) [2] estimated that 1.3 million people died on roads in 2015. Connected and Automated Vehicles (CAVs) hold the potential to improve the current operational safety and efficiency of the transportation system by relieving drivers from some or all the driving tasks and enabling the cooperation among vehicles, between vehicles, and roadway infrastructure or other road users. Simulation results show that the proposed scheme improves both the travel time and fuel economy significantly on a typical urban road with successive signalized intersections. 3. Md Abdus Samad Kamal Mohsen Ramezani Guoyuan Wu Claudio Roncoli Jackeline Rios-Torres Olivier Orfila [1] The World Bank, \"Understanding poverty: transport,\" . https://www.worldbank.org/en/topic/transport [2] WHO, \"Global status report on road safety,\" 2018. https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/ [3] O. Orfila, D. Gruyer, K. Hamdi, S. Glaser, \"Safe and ecological speed profile planning algorithm for autonomous vehicles using a parametric multiobjective optimization procedure,\" International Journal ofAutomotive Engineering, vol. 10 no. 1, pp. 26-33, DOI: 10.20485/jsaeijae.10.1_26, 2019.

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

Camera-based mirror systems (CBMSs) are a relatively new technology in the automotive industry, and much of the United States’ medium- and heavy-duty commercial fleet has been reluctant to convert from standard glass, or “west coast”, mirrors to CBMSs. CBMSs have the potential to reduce the number of truck and passenger vehicle incidents, improving overall fleet safety. CBMSs also have the potential to improve operational efficiency by improving aerodynamics and reducing drag, resulting in better fuel economy, and improving maneuverability. Improvements in overall safety are also possible; the field of view for the driver is potentially 360° with the addition of trailer cameras, allowing for visibility of the rear of the trailer and the front of the truck. These potential improvements seem promising, but the literature on driver surveys clearly shows that there is reluctance to adopt this technology for many reasons. Additionally, more robust testing in the laboratory and in the field is necessary to determine whether CBMSs are adequate to replace standard mirrors on trucks. This analysis provides an overview of key research questions for CBMS testing based on the current literature on the topic (surveys, standards, and previous testing). The purpose of this analysis is to serve as guidance in developing further testing of CBMSs, especially testing involving human subjects.

Environmental concerns along with stronger governmental regulations regarding automotive fuel-economy and greenhouse-gas emissions are contributing to the push for development of more sustainable transportation technologies. Furthermore, the widespread use of the automobile gives rise to other issues such as traffic congestion and increasing traffic accidents. Consequently, two main goals of new technologies are the reduction of vehicle fuel consumption and emissions and the reduction of traffic congestion. While an extensive list of published work addresses the problem of fuel consumption reduction by optimizing the vehicle powertrain operations, particularly in the case of hybrid electric vehicles (HEV), approaches like eco-driving and traffic coordination have been studied more recently as alternative methods that can, in addition, address the problem of traffic congestion and traffic accidents reduction. This dissertation builds on some of those approaches, with particular emphasis on autonomous vehicle coordination control. In this direction, the objective is to derive an optimization approach for energy efficient and safe coordination control of vehicles in merging highways. Through the application of the Pontryagin’s minimum principle, a closed-form solution is obtained which allows the implementation of a real-time optimal control for fleets of conventional vehicles. The results of applying the proposed framework show that the system can reduce the fuel consumption by up to 50% and the travel time by an average of 6.9% with respect to a scenario with not coordination strategy. By integrating the traffic coordination scheme with in-vehicle energy management, a two level optimization system is achieved which allows assessing the benefits of integrating hybrid electric vehicles into the system. Regarding in-vehicle energy optimization, four methods are developed to improve the tuning process of the equivalent consumption optimization strategy (ECMS). First, two model predictive control (MPC)-based strategies are implemented and the results show improvements in the efficiency when compared with those obtained with the standard ECMS implementation. On the other hand, the research efforts focus in performing analysis of the engine and electric motor operating points which can lead to the optimal tuning of the ECMS with reduced iterations. Two approaches are evaluated and even though the results in fuel economy are slightly worse than those for the standard ECMS, they show potential to significantly reduce the tuning time of the ECMS. Additionally, the benefits of having less aggressive driving profiles on different powertrain technologies such as conventional, plug-in hybrid and electric vehicles are studied.

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This paper investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other in roundabouts to achieve a smooth traffic flow. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the proposed approach is validated through simulation and it is shown that fully coordinated vehicles reduce total travel time by 51% and fuel consumption by 35%. Furthermore, we study the influence of vehicle coordination in a mixed-traffic environment and compare the network performance under different market penetration rates of connected and automated vehicles (CAVs). For this particular study with near-capacity demand, due to extremely unstable traffic, the results show that even with high penetration of CAVs (e.g., 80%), travel time and fuel savings are much less than a network of CAVs.

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control actions aimed at optimizing energy consumption and associated benefits. Several research efforts reported in the literature to date have proposed decentralized control algorithms to coordinate CAVs in various traffic scenarios, e.g., highway on-ramps, intersections, and roundabouts. However, the impact of optimally coordinating CAVs on the performance of a transportation network has not been thoroughly analyzed yet. In this paper, we apply a decentralized optimal control framework in a transportation network and compare its performance to a baseline scenario consisting of human-driven vehicles. We show that introducing of CAVs yields radically improved roadway capacity and network performance.

Energy consumption is the major contributor associated with large and growing transportation cost in logistics. Optimal vehicle routing approaches can provide solutions to reduce their operating costs and address implications on energy. This paper outlines a solution to the single-depot capacitated vehicle routing problem with the objective of minimizing daily operation cost with a homogeneous fleet of delivery vehicles. The problem is solved using Simulated Annealing, to provide optimal routes for the vehicles traveling between the depot and destinations. Simulation results demonstrate that the proposed approach is effective to recommend an optimal route and reduce operation cost. Supplementary information and video of our proposed approach can be found at: https://sites.google.com/view/ud-ids-lab/last-mile

Vehicle-to-Vehicle (V2V) communication using Dedicated Short Range Communications (DSRC) technology provides promising benefits for drastically reducing vehicle collisions. A decentralized approach combined with DSRC allow vehicles in a highly mobile and complex network to send and receive safety messages with high reliability and low latency. Notably, there are many factors that may cause the system to become unreliable due to communication failures. While the reliability of V2V communication has been a subject of study by researchers, there is still open questions regarding how the placement of DSRC devices (inside or outside the host vehicle), the vehicle's interior elements or the differences in altitude can affect the V2V communications. This paper aims to provide experimental testing data and analysis to quantify the impact of relative vehicle speeds, differences in altitudes between two vehicles, and vehicle's interior obstacles (which can vary depending on the placement of DSRC device and when communicating with front vs. rear vehicles) on the reliability of V2V communications.

The rapid growth of traffic-related fatalities and injuries around the world including developed countries has drawn researchers' attention for conducting research on automated highway systems to improve road safety over the past few years. In addition, fuel expenses due to traffic congestion in the U.S. translate to billions of dollars annually. These issues are motivating researchers across many disciplines to develop strategies to implement automation in transportation. The advent of connected-vehicle (CV) technology has added a new dimension to the research. The CV technology allows a vehicle to communicate with roadside infrastructure (vehicle-to-infrastructure), and other vehicles (vehicle-to-vehicle) on roads wirelessly using dedicated short-range communication (DSRC) protocol. Collectively, the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies are known as V2X technology. Automotive companies have started to include On-Board Units (OBUs) on latest automobiles which can run safety-critical and assistive applications using V2X technology. For example, US Department of Transportation has already launched various applications including but not limited to lane-change assistance, collision avoidance, SPaT for emergency and transit vehicles. Merge conflicts, especially when vehicles are trying to merge from ramps to freeways, are a significant source of collisions, traffic congestion and fuel use. This paper describes a novel freeway merge assistance system utilizing V2X technology with the help of the DSRC protocol. The freeway merge assistance system uses an innovative three-way handshaking protocol and provides advisories to drivers to guide the merging sequence.