Pedestrian behaviour analysis at intersection in Vijayawada for road user safety and infrastructure design

Abstract

Abstract Pedestrian behaviour analysis is crucial for improving safety, urban planning, public health, and transportation infrastructure planning to establish a pedestrian-friendly zone and enhance people’s overall quality of life in urban contexts. Micro-level infrastructure improvements, such as better lighting, crosswalks, and sidewalks, are essential for communities to be sustainable and walkable. Safe and practical infrastructure encourages active mobility and reduces dependency on energy-intensive modes of transportation. Giving pedestrian safety as a priority in urban construction enhances the environmental significance of sustainable cities. Safe pedestrian environments encourage walking and other non-motorized modes of transportation, which lessens the pollution and emissions that come from driving. In the majority of developing countries, such as India, rapid urbanization, an increase in the number of vehicles, and a lack of adherence to traffic regulations by both automobiles and pedestrians contribute to a significant problem at junctions. The objective of this paper is to investigate how pedestrians behave at three junctions in Vijayawada say the Moghalrajpuram intersection, high school road junction, and kanuru junction (Andhra Pradesh, India). Approximately 69% of people in the study area prefer to cross in a perpendicular manner. At Kanuru, oblique crossing speeds range from 1.88 to 3.08 m/sec, whereas perpendicular crossing speeds range from 1.88 to 2.09 m/sec. Oblique crossing speeds at the High School Road intersection range from 3.35 to 3.49 m/sec, and perpendicular crossing speeds range from 2.00 to 2.45 m/sec. Oblique crossing speeds at Moghalrajpuram junction range from 1.05 to 1.61 m/sec, while perpendicular crossing speeds range from 1.76 to 2.50 m/sec for all the genders and age groups. At every intersection, pedestrian flow variables like crossing patterns, crossing speeds in relation to demographics like age and gender, total pedestrian counts, waiting times, and directions are analysed.