Using single and multiple unmanned aerial vehicles for microscopic driver behaviour data collection at freeway interchange ramps

Abstract

This paper presents a detailed methodological framework for collecting microscopic driver and vehicle behaviour data over a long road segment with an application to the entire stretch of a freeway ramp segment using single and multiple Unmanned Aerial Vehicles (UAVs). The methodology allows users to collect reliable and complete trajectories of traffic movements at areas with challenging physical characteristics (long road segment, horizontal curvature, changing elevation, and presence of shadow), challenging traffic characteristics (high traffic volume, high speeds, and high speed changes), and restrictive regulations (UAVs prohibited from hovering over the freeway or the right-of-way). Different UAV setups were recommended and can be used depending on the site conditions. Specific commercial software and procedures used to complete the data collection are explained. The methodology was applied at two ramps and verified with speed data acquired from differential GPS receivers using three different error metrics. Results showed good performance of the proposed methodology, including when aerial videos must be taken from oblique angles.

Capitalizing on Drone Videos to Calibrate Simulation Models for Signalized Intersections and Roundabouts

“…The traffic performance analysis of signalized intersections included automatic identification of traffic flow states and shockwaves based on vehicle trajectories, and the extraction of various traffic flow parameters as well as traffic performance measures for assessing the traffic operations at a signalized intersection. Alamry and Hassan presented a framework for collecting microscopic driver behavior and traffic flow data under challenging physical characteristics and traffic conditions such as freeway ramp terminals with high traffic demands ( 21 ). Speed data collected by UAVs and extracted by commercial software were compared with the probe-vehicle data, and results showed good consistency between the two data sources.…”

Reliability Analysis of Freeway Speed Change Lanes Using Naturalistic Driving Study Data

“…One of the major reasons for the lack of complete data on drivers' speeds and behaviour at freeway ramp terminals lies behind the difficulties and risks involved with the use of traditional traffic data collection equipment, such as laser guns and fixed cameras, on freeways (Alamry and Hassan, 2022). For example, most transportation jurisdictions prohibit installing or operating such traffic data collection equipment on freeway shoulders or within the freeway right-of-way due to safety reasons.…”

“…In addition, laser guns cannot track more than one vehicle at the same time or track the same vehicle over the entire length of the ramp and SCL. Fixed cameras also cannot cover long road segments unless they are deployed on top of high structures such as neighbouring buildings (Alamry and Hassan, 2022). Furthermore, the data collection is usually conducted within a short time period (Dhahir, 2018), typically for 2 to 5 hours.…”