How do long combination vehicles perform in real traffic? A study using Naturalistic Driving Data.

Area of Science:

• Transportation Engineering
• Vehicle Dynamics
• Human Factors in Driving

Background:

• Long combination vehicles (LCVs) offer economic benefits but require careful performance evaluation.
• Assessing LCV stability and driver workload is crucial for safe deployment.
• Naturalistic driving studies provide realistic data for vehicle performance analysis.

Purpose of the Study:

• To evaluate and compare the performance of A-double and DuoCAT LCVs.
• To assess vehicle stability and tracking performance across various driving scenarios.
• To investigate driver cognitive workload in low-speed maneuvers.

Main Methods:

• Utilized naturalistic driving data from A-double and DuoCAT vehicles.
• Analyzed four scenarios: lane changes, roundabouts, intersections, and tight curves.
• Applied performance metrics: rearward amplification, high-speed transient offtracking, low-speed swept path, high-speed steady-state offtracking, and steering reversal rate.

Main Results:

• Both A-double and DuoCAT LCVs demonstrated good performance in most scenarios.
• A-double exhibited superior stability during high-speed lane changes.
• DuoCAT showed better maneuverability in low-speed scenarios like roundabouts and intersections.

Conclusions:

• Both LCV types are viable, with distinct strengths in different driving conditions.
• Vehicle design influences stability and maneuverability, impacting operational suitability.
• Further research can optimize LCV design for enhanced safety and efficiency.