Related papers: Cooperative Driving for Speed Harmonization in Mix…
The rise of vehicle automation has generated significant interest in the potential role of future automated vehicles (AVs). In particular, in highly dense traffic settings, AVs are expected to serve as congestion-dampeners, mitigating the…
This paper presents a mixed traffic control policy designed to optimize traffic efficiency across diverse road topologies, addressing issues of congestion prevalent in urban environments. A model-free reinforcement learning (RL) approach is…
This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a…
In preparing for connected and autonomous vehicles (CAVs), a worrisome aspect is the transition era which will be characterized by mixed traffic (where CAVs and human-driven vehicles (HDVs) share the roadway). Consistent with expectations…
The rapid development of cyber-physical systems is driving a transition toward mixed traffic environments comprising both human-driven and connected and automated vehicles (CAVs). This shift presents a unique opportunity to leverage the…
The introduction of connected and automated vehicles (CAV) is believed to reduce congestion, enhance safety, and improve traffic efficiency. Numerous research studies have focused on controlling pure CAV platoons in fully connected…
We derive time and energy-optimal policies for a Connected Autonomous Vehicle (CAV) to execute lane change maneuvers in mixed traffic, i.e., in the presence of both CAVs and Human Driven Vehicles (HDVs). These policies are also shown to be…
Connected and automated vehicles (CAVs) have a great potential to improve traffic efficiency in mixed traffic systems, which has been demonstrated by multiple numerical simulations and field experiments. However, some fundamental properties…
We derive optimal control policies for a Connected Automated Vehicle (CAV) and cooperating neighboring CAVs to carry out a lane change maneuver consisting of a longitudinal phase where the CAV properly positions itself relative to the…
Connected Autonomous Vehicles (CAVs) are widely expected to improve traffic safety and efficiency by exploiting information from surrounding vehicles via V2V communication. A CAV typically adapts its speed based on information from the…
Traffic Congestions and accidents are major concerns in today's transportation systems. This thesis investigates how to optimize traffic flow on highways, in particular for merging situations such as intersections where a ramp leads onto…
Urban traffic congestion is a chronic problem faced by many cities. It is essentially inefficient infrastructure use which results in increased vehicle fuel consumption and emissions. This in turn adds extra costs to commuters and…
To investigate the impact of Autonomous Vehicles (AVs) on urban congestion, this study looks at their performance at road intersections. Intersection performance has been studied across a range of traffic densities using a simple MATLAB…
This paper devotes to the development of an optimal acceleration/speed profile for autonomous vehicles approaching a traffic light. The design objective is to achieve both short travel time and low energy consumption as well as avoid idling…
When connected and autonomous vehicles (CAVs) are widely used in the future, we can foresee many essential applications, such as platoon formation and autonomous police patrolling, which need two CAVs, originally separated in a mixed…
Vehicle-infrastructure communication opens up new ways to improve traffic flow efficiency at signalized intersections. In this study, we assume that equipped vehicles can obtain information about switching times of relevant traffic lights…
Human drivers may behave in an imprecise/unstable manner, leading to traffic oscillations which are harmful to traffic throughput. Recent field experiments have shown that the control of a single autonomous vehicle (AV) can increase traffic…
We demonstrate a new capability of automated vehicles: mixed autonomy traffic control. With this new capability, automated vehicles can shape the traffic flows composed of other non-automated vehicles, which has the promise to improve…
Connected autonomous vehicles (CAVs) can supplement the information from their own sensors with information from surrounding CAVs for decision making and control. This has the potential to improve traffic efficiency. CAVs face additional…
Compared with traditional vehicle longitudinal spacing control strategies, the combination spacing strategy can integrate the advantages of different spacing control strategies. However, the impact mechanism of different combination spacing…