学术文献库

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 businesses. Addressing this issue is therefore of paramount interest due to the perceived dual benefit. Many technologies were and are being developed. These include adaptive traffic signals, dedicated lanes, etc. This paper presents a simple platooning algorithm that maintains relatively small distances (pre-specified time gap) between consecutive vehicles to enhance mobility, increase transportation capacity and ultimately reduce travel costs. Several dynamic and kinematic constraints governing the motion of vehicles are also accounted for. These include acceleration, velocity, and distance constraints. This developed logic was tested on highways that traverse the downtown area of Los Angeles. Depending on the market penetration rate of connected automated vehicles versus non-connected automated vehicles, a reduction in travel time, delay and fuel consumed across the city can be observed. Vehicles are expected to reach their destination in less travel time, delay and consumed fuel. The reduction percentages range from 0 to 5 percent, 0 to 9.4 percent, and 2.58 to 8.17 percent, respectively.