ASSESSING PERFORMANCE OF PEDESTRIAN ROAD CROSSWAY ON ADDIS ABABA LIGHT RAIL TRANSIT BASED ON PEDESTRIAN DELAY [A CASE STUDY ON ADDIS ABABA E-W (AYAT MEGENAGNA LIGHT RAIL TRANSIT LINE)]

Abstract

This research focuses on Addis Ababa East-West Light Rail Transit (LRT) line road section of Ayat to Megenagna which have a length of 7.8 km. It also consists of eight zebra stripped pedestrian crossway. The study attempts to determine the pedestrian level of service of the existing pedestrian crossways by quantifying pedestrian delays, to determine the most influencing factors to pedestrian delays and to develop a regression model for pedestrian delays. Relevant data about pedestrian level of service, pedestrian crossing facilities and pedestrian traffic data was collected and investigated through statistical analysis. Crosswalk facilities were collected from the Addis Ababa Light Rail Transit bureau and directly from geometric measurement to analyze performance of pedestrian crossings, traffic count was conducted on the selected pedestrian crossings. A random survey was done through questioner and structured interviews in order to assess pedestrian’s overall satisfaction level in terms of safety, comfort and convenience for each crossing and usage of crossing facilities based on their experiences. The study analysis shows that the level of service of selected pedestrian midblock, stairways and strail in the road section is above a LOS C, which means pedestrian does not need to alter movement and found are found enough for pedestrians. In addition, the study analysis identifies that the basic parameters that influence the pedestrian delay were age, crosswalk marking, waiting time, pedestrian speed, pedestrian perceived safety, pedestrian perceived convenience and pedestrian perceived comfort through traffic analysis, observation, interview and questioners. Gender, frequency using crosswalk and crosswalk surface condition have not found the influencing factors to pedestrian delay. The effect of each predicted variables on pedestrian delay, multiple linear regression model was developed using SPSS software, seven variables were found statistically significant to predict pedestrian delay at 95% confidence level. The resulting general model has a good correlation coefficient R2=0.716 which means about 71.6% of the variation in pedestrian delay was explained by influencing factors. The regression model is validated and is applicable for midblock crossway integrated with LRT roads. Based on such findings, the following recommendations were drawn to solve those problems, build up off-street parking, discourage private cars, avoiding poor traffic management, and improve pedestrian crossing mark