This paper presents a methodology that enhances the priority signal control model in the Multi-Modal Intelligent Traffic Signal System (MMITSS). To overcome the range limit of Dedicated Short Range Communication (DSRC), peer-to-peer intersection communications are integrated with the DSRC communications. Through the integrated communication, the peer priority control strategy can create a long-term signal plan for prioritized vehicles, which include transit vehicles in this study. The long-term plan provides a flexible signal schedule that allows phase actuation. The peer priority strategy is effective in reducing the number of stops and delay for priority requests, while minimizing the negative impact on regular vehicles. To validate the strategy, a simulation experiment was designed to compare: Fully actuated control, coordination, and MMITSS priority control using two different VISSIM simulation networks (Arizona and Utah). The result shows that the peer-to-peer long term planning strategy can improve transit service reliability, limiting adverse impact on other traffic.

To contend with the negative impacts of intersection-based transit system priority (TSP) control on side-street traffic and also to enhance its effectiveness from the entire arterial’s perspective, this study presents an integrated arterial-based TSP system to promote the bus operations. The proposed system employs an off-line transit-based progression system to produce the base signal plan, which is embedded with a feature to minimize the negative impacts of local TSP implementation on non-priority movements at critical intersections.  With its specially designed evaluation function, the proposed system is capable of minimizing ineffective activations of local TSP which often results in undesirable arriving patterns to its downstream intersection and excessive delays of all vehicles. Extensive evaluation with simulation experiments confirms that the proposed system, integrating local TSP with transit-based signal progression systems, can indeed circumvent the deficiencies of conventional TSP and produce the expected benefits to both passenger cars and transit vehicles over the entire arterial.

Freight deliveries on signalized urban streets are known to cause lane blockages during deliveries. When delivery vehicles block lanes of traffic near signalized intersections, the capacity of the intersection is affected. Current practice is for traffic signals to be timed assuming that each approach can serve vehicles at the unobstructed saturation flow. The goal of this research is twofold: 1) to develop models to quantify the capacity and delay effects of a lane blocking freight delivery on a signalized urban street, and 2) to develop a model for adapting the traffic signal timing in real time for signal cycles during which a delivery blocks a link upstream of the intersection. The results of the queueing model show that accounting for the dynamics of queuing provides closed form analytical formulas for delay and capacity that can account for varying locations of deliveries and different impacts on different lane groups.  The signal control algorithm requires real-time information about the location of the double-parked delivery vehicle, which is assumed to be available from connected vehicle data from urban freight vehicles or from another detection system.  The results show that for low levels of traffic demand, the signal control method reduces intersection delay compared to a signal that is timed for unblocked traffic.  The algorithm also keeps the intersection approach undersaturated for higher levels of demand, which is important because deliveries can last for many signal cycles.

Multimodal traffic control at intersections aims at balancing the mobility of general traffic as well as pedestrians and bicyclists and the throughput of special vehicles with various priorities from ambulance requiring a rather precise time window to buses having relatively loose requirements to cross intersections. With the increase of special vehicles, it is necessary to investigate an intersection’s capacity of serving special vehicles without hurting traffic mobility. In this paper, we focus on special vehicles and present a new multimodal traffic signal representation: the phase-time network containing green requests with time windows as well as a new search algorithm to examine the solvability of the multimodal traffic signal optimization in the phase-time network. The numerical results show that under the moderate traffic environment, an intersection can serve most special vehicles when their rate is 5% to 10% of overall traffic. Beyond that range, the requests from the special vehicles will be mostly rejected due to the inherent restrictions in traffic signal systems.