Jackeline Rios-Torres

A Survey on the Coordination of Connected and Automated Vehicles at Intersections and Merging at Highway On-Ramps

Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable changes. This paper summarizes the developments and the research trends in coordination with the CAVs that have been reported in the literature to date. Remaining challenges and potential future research directions are also discussed.

Automated and Cooperative Vehicle Merging at Highway On-Ramps

Recognition of necessities of connected and automated vehicles (CAVs) is gaining momentum. CAVs can improve both transportation network efficiency and safety through control algorithms that can harmonically use all existing information to coordinate the vehicles. This paper addresses the problem of optimally coordinating CAVs at merging roadways to achieve smooth traffic flow without stop-and-go driving. We present an optimization framework and an analytical closed-form solution that allows online coordination of vehicles at merging zones. The effectiveness of the efficiency of the proposed solution is validated through a simulation, and it is shown that coordination of vehicles can significantly reduce both fuel consumption and travel time.

Online Optimal Control of Connected Vehicles for Efficient Traffic Flow at Merging Roads

This paper addresses the problem of coordinating online connected vehicles at merging roads to achieve a smooth traffic flow without stop-and-go driving. We present a framework and a closed-form solution that optimize the acceleration profile of each vehicle in terms of fuel economy while avoiding collision with other vehicles at the merging zone. The proposed solution is validated through simulation and it is shown that coordination of connected vehicles can reduce significantly fuel consumption and travel time at merging roads.

Energy impact of different penetrations of connected and automated vehicles: a preliminary assessment

Previous research reported in the literature has shown the benefits of traffic coordination to alleviate congestion, and reduce fuel consumption and emissions. However, there are still many remaining challenges that need to be addressed before a massive deployment of fully automated vehicles. This paper aims to investigate the energy impacts of different penetration rates of connected and automated vehicles (CAVs) and their interaction with human-driven vehicles. We develop a simulation framework for mixed traffic (CAVs interacting with human-driven vehicles) in merging roadways and analyze the energy impact of different penetration rates of CAVs on the energy consumption. The Gipps car following model is used along with heuristic controls to represent the driver decisions in a merging roadways traffic scenario. Using different penetration rates of CAVs, the simulation results indicated that for low penetration rates, the fuel consumption benefits are significant but the total travel time increases. The benefits in travel time are noticeable for higher penetration rates of CAVs.

An overview of driver feedback systems for efficiency and safety

Driver feedback systems have the potential to improve driving safety and efficiency by providing instructions to drivers aimed at improving their driving style. There is already a rich body of available literature devoted to the derivation of energy efficient speed profiles to develop driver feedback or eco-driving systems. While most of them can be applied to any type of vehicle, their effectiveness will be maximized if their formulation involves the dynamics of the particular vehicle powertrain configuration. This paper summarizes the research trends in the development of these systems that have been reported in the literature to date classifying them according to the powertrain structure and the nature of the control strategy. The study concludes with a discussion on the remaining challenges and potential future research directions.