17-11 Evaluation of Transit Priority Treatments in Tennessee

Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

Development of a highway geometry based noise abatement model

Exposure to noise generated from traffic has led to significant annoyance and sleep deprivation in people. Continuous exposure to traffic noise can lead to mental instability and reduce the learning rate of children. Many cases of cardiovascular diseases, sleep disturbance, and cognitive impairment have been reported as a result of traffic noise. With increasing population of cars, health problems resulting from traffic noise will continue to increase and it is of utmost priority to abate this noise. Noise abatement is one of the most effective strategies in reducing noise level for communities close to roadways, although it is also one of the major cost drivers in highway projects to reduce noise. Extensive noise modeling is required to determine the feasibility of abatement choices; however, traffic noise models usually do not interact with highway geometries in selecting optimized noise abatement options. The Traffic Noise Model (TNM) developed by Federal Highway Administration (FHWA) was used to compute highway traffic noise and evaluate the effect of noise abatements. A parametric study was conducted on a total of 23,093 scenarios generated to examine ten major variables influencing roadway noise level. A noise prediction model was developed using multiple regression analysis incorporating parameters such as roadway geometry (horizontal offsets and elevation differences), barrier height, receiver height, traffic volume, roadway section, road-surface material, barrier types, speed and roadway section. This model can be used to examine possible noise mitigation strategies to make the best decision at design stage of a roadway