Development of Model-based Transit Signal Priority Control for local Arterials

AbstractThis paper presents a transit signal priority (TSP) model designed to benefit both bus riders and passenger-car users. Most of conventional priority methods are applied at the isolated intersection. However, this kind of control strategies may failed to reduce the travel time since the prioritized buses have to stop at the downstream intersections. Therefore, along the line of headway-based research, this study intends to develop a new TSP control approach with the concerns of bus passenger delay on the entire arterial. Moreover, a basic method for queue length estimation is presented to evaluate the impacts of TSP control on passenger cars. The control objective is to minimize bus passenger waiting time at the downstream bus stop, simultaneously ensuring the total person delay of entire intersection is not increased. Using the microscopic simulation, the proposed strategy has shown its benefits in reducing bus passenger waiting time and total intersection delay

Person-based Adaptive Priority Signal Control with Connected-vehicle Information

This thesis proposes a TSP (transit signal priority) strategy of person-based adaptive priority signal control with connected-vehicle information (PAPSCCI). By minimizing the total person delay at an isolated intersection, PAPSCCI can assign signal priorities to transit vehicles due to their high occupancies, while minimize the negative impact to the auto traffic. With the accurate vehicle information provided by connected-vehicle technology, PAPSCCI can estimate person delay for each passenger directly and form a MILP (mixed-integer linear program) for the optimization. Performances of PAPSCCI were evaluated through simulations. Results show decreases of both vehicle delay and person delay of all vehicle types when there are up to three bus routes running through the intersection. How different penetration rates of the connected-vehicle technology affect the performance of the PAPSCCI were tested. Necessary revisions were made to the PAPSCCI model considering different penetration rates. Results show that the effectiveness of PAPSCCI worsens with the lowering of penetration rate. The delay improvements, however, were still promising when the penetration rate is above 40%. PAPSCCI model were also developed and tested with communication range of 2000 m, 1000 m, 500 m and 250 m. Expect that the 1000 m case has the best delay improvements after PAPSCCI optimization, the effectiveness of the model worsens when the communication range getting smaller. Even when the communication range is down to 250 m, PAPSCCI can still reduce the delay for all vehicle types

Development and Evaluation of An Adaptive Transit Signal Priority System Using Connected Vehicle Technology

Transit signal priority (TSP) can be a very effective preferential treatment for transit vehicles in congested urban networks. There are two problems with the current practice of the transit signal priority. First, random bus arrival time is not sufficiently accounted for, which’ve become the major hindrance in practice for implementing active or adaptive TSP strategies when a near-side bus stop is present. Secondly, most research focuses on providing bus priority at local intersection level, but bus schedule reliability should be achieved at route level and relevant studies have been lacking. In the first part of this research, a stochastic mixed-integer nonlinear programming (SMINP) model is developed to explicitly to account for uncertain bus arrival time. A queue delay algorithm is developed as the supporting algorithm for SMINP to capture the delays caused by the interactions between vehicle queues and buses entering and exiting near-side bus stops. A concept of using signal timing deviations to approximate the impacts of TSP operations on other traffic is proposed for the first time in this research. In the second part of the research, the deterministic version of the SMINP model is extended to the arterial setting, where a route-based TSP (R-TSP) model is develop to optimize for schedule-related bus performances on the corridor level. The R-TSP model uses the real-time data available only from the connected vehicle communications technology. Based on the connected vehicle technology, a real-time signal control system that implements the proposed TSP models is prototyped in the simulation environment. The connected vehicle technology is also used as the main detection and monitoring mechanism for the real-time control of the adaptive TSP signal system. The adaptive TSP control module is designed as a plug-in module that is envisioned to work with a modern fixed-time or adaptive signal controller with connected vehicle communications capabilities. Using this TSP-enabled signal control system, simulation studies were carried out in both a single intersection setting and a five-intersection arterial setting. The effectiveness of the SMINP model to handle uncertain bus arrival time and the R-TSP model to achieve corridor-level bus schedule reliability were studied. Discussions, conclusions and future research on the topic of adaptive TSP models were made

On the Development of a New Class of Covering Path Models

The basis of this dissertation work stems from the fact that if one examines system route maps for many bus transit systems in U.S. cities, an interesting pattern emerges. Routes often utilize embedded loops to increase accessibility coverage of a system at the expense of adding a marginal amount of length to the overall path. Further, such routes frequently share a common corridor with respect to traveling in opposing directions, but they may depart spatially from each other in terms of direction. These departures in direction represent embedded loops that are traversed in only one direction. However, the literature has not explored this issue, and in fact, often discourages or outright prevents any loops from occurring whether they are loops that are traversed in both directions or traversed in only one direction. Furthermore, past research on covering path models has not accounted for travel in opposing directions, even when attempting to model transit lines. This is due in part to the roots of the covering path literature.This dissertation presents an analysis of past work and from that defines several new problems that are ‘loop agnostic’ – that is, they neither prevent nor encourage the formation of loops in an optimal route, essentially a new class of covering path problems. Although several loop agnostic models are developed in this dissertation to better represent the maximal covering shortest path problem, these models only capture one aspect of loop use. In the classic Maximal Covering Shortest Path problem, it is assumed that its use in transit will be traversed in both directions. Further, the classic formulation prevents most loops from occurring. A new form of this model is developed that allows loops to be part of a solution, whenever such loops provide an improvement in the objective function value. This model is called “loop agnostic” as the model neither prevents nor requires loops to be used in a solution. This means that a loop can be present as part of the path, as an out-and-back path or a more complex loop which visits several other nodes before returning to a previously visited node, or even as a ‘lollipop’ shaped route attached to the origin node or the destination node. If one assumes that the covering path can be traversed both in the outbound and inbound directions (which past work has done), any loops that are present will be traversed in both directions and is what we refer to as a bi-directional loop. When addressing the question of bi-directionality in real world systems it is possible that a loop is traversed in only one direction. Such “uni-directional” loops are formed whenever inbound/outbound paths diverge and can be observed in many transit system maps, like those of Bozeman, MT; Eau Claire, WI; and San Luis Obispo, CA. This dissertation also proposes a new problem, the Bi-Directional MCSP, and formulates two new models that account for travel based upon inbound and outbound path directions which allows for the use of shared arcs and uni-directional loops as well as bi-directional loops.This dissertation also presents results from the application of these new models as well as a new heuristic to a hypothetical test network as well as a real world network from Richardson/Garland, Texas. Results demonstrate that loops are present in many optimal solutions and that the route designs that utilize loop structures such as a ‘lollipop,’ ‘barbell,’ and ‘figure eight’ may well be superior to route designs that do not incorporate loops. This gives credence to the designs of virtually all transit systems in small and medium sized cities in the United States