With the growth of population and increase of travelling requirements in metropolitan areas, public transit has been recognized as a promising remedy and is playing an ever more important role in sustainable transportation systems. However, the development of the public transit system has not received enough attention until the recent emergence of Bus Rapid Transit (BRT). In the conventional public transit system, little to no communication passes between transit vehicles and the roadside infrastructure, such as traffic signals and loop detectors. But now, thanks to advancements in automatic vehicle location (AVL) systems and wireless communication, real-time and high-resolution information of the movement of transit vehicles has become available, which may potentially facilitate the development of more advanced traffic control and management systems. This dissertation introduces a novel adaptive traffic signal control system, which utilizes the real-time location information of transit vehicles. By predicting the movement of the transit vehicle based on continuous detection of the vehicle motion by the on-board AVL system and estimating the measures of effectiveness (MOE) of other motor vehicles based on the surveillance of traffic conditions, optimal signal timings can be obtained by solving the proposed traffic signal optimization models. Both numerical analysis and simulation tests demonstrate that the proposed system improves a transit vehicle’s operation as well as minimizes its negative impacts on other motor vehicles in the traffic system. In summary, there are three major contributions of this dissertation: a) development of a novel AVL-based adaptive traffic signal control system; b) modeling of the associated traffic signal timing optimization problem, which is the key component of the proposed system; c) applications of the proposed system to two real world cases. (Author/publisher)
Samenvatting