|Despite the improvements in transportation systems, the increase in the cost of natural fuel energy resources, and the imposition of more stringent environmental policies for emission levels, the demand for mobility and transportation is continuously increasing. Consequently roads are frequently congested, creating economical, social, and ecological challenges.
These problems can be addressed either by large-scale substitution of natural oil by alternative fuels, enhancing vehicle technology or/and reducing waste of fuels. The first option will be difficult to fully implement on the short to medium term. Therefore, reducing fuel consumption by reducing waste of fuel and enhancing vehicle technology are sensible strategies. Reduction of fuel consumption and emissions can be achieved by using different traffic flow control measures (such as traffic signals, on-ramp metering, variable speed limits, opening or closing of shoulder lanes, route guidance etc.).
Our goal is to use these traffic control measures to reduce fuel consumption (e.g., due to idling and frequent acceleration and deceleration) and exhaust emissions. These objectives will be addressed using a model-based control approach (also called model predictive control, or MPC for short). In this project, two possible control approaches will be investigated:
1. Infrastructure-based: In this approach, the control strategy will be driven by sensors (such as loop detectors, cameras, etc.) and control equipment (such as traffic signals, speed limit display units, and so on) on the road side.
2. Integrated road-vehicle: In this approach, the infrastructure-based framework will be integrated with the growing availability of in-car communication, sensing, and control systems to obtain an integrated road-vehicle control system, resulting in better and more sustainable mobility.