California Partners for Advanced Transportation Technology

Although many different railroad grade crossing control products are available, the most challenging limitation to traditional grade crossing systems is their inability to deliver consistent warning times in response to varying train speeds and station stops (particularly nearside stops). As a result, rail-roadway crossings often generate conflicts and congestion for motorist traffic and sometimes delay trains.

By conducting system level analysis, this project will investigate the interactions and conflicts between urban/suburban rail and cross traffic. The information that is obtained will then be applied to develop practical solutions to minimize impacts on motor vehicle traffic and improve or maintain schedule adherence for rail operations. In the end, this project plans to conduct field testing of the developed solutions and algorithms on the San Diego trolley system.

The proposed active LRT priority system consists of four major components: train detector, train travel and dwelling time predictor, priority request generator, and traffic signal controllers. The train detection means can be either traditional point detection, such as the loop system, or continuous detection, such as the GPS based AVL system. Based on the collected field data, a travel time predictor and the dwelling time predictor were developed. Based on the predicted arrival, a Mixed-Integer Quadratic Programming (MIQP) model was developed. The objectives of this optimization model are two-fold: 1) to minimize intersection delays for trolleys by providing signal priority; and 2) to minimize impacts on other traffic incurred by the priority. By applying the proposed optimization model, the average trolley performance index (PI), which is the expected trolley passenger delay, is reduced enormously by 89.5%. Moreover, the standard deviation of trolley PI is reduced significantly by 68.6%, which means trolleys’ travel time is more stable with signal priority. Within the priority impacted cycles, the traffic delay is increased by 30.4%. The total intersection passenger delay is reduced by 66.8%. We also conducted the simulation testing by implementing our signal control algorithm in Paramics. The PI for trolleys decreases by as much as 77% if we use the proposed signal control algorithm, although the PI of the cross street traffic increases by 27%. By adjusting the weighting factor in our MIQP model, we can reduce the delay for the cross street traffic, however, the time saved for trolley will not be so noticeable.