01620079

Component

https://doi.org/10.3141/2615-05

A baseline case was created for the following behavior of heavy-truck drivers with the use of naturalistic driving data to support the development of automated platooning. A truck platoon is a string of trucks following each other in the same lane at short distances. Grouping vehicles in platoons can increase capacity on roads, save significant fuel, reduce emissions, and potentially result in improved safety. However, these benefits can be realized only if the platoons operate in an automated, coordinated manner. Because little literature of truck following behavior exists to support the development of such truck platoons, this research focused on how closely trucks follow other vehicles on highways under various environmental conditions, how closely a truck follows a leading vehicle when other vehicles cut in between, and the safety impact of following at different headways. Findings indicate that trucks follow other vehicles at an average headway of about 2 s overall, and those headways are shorter when following a passenger car rather than a heavy truck, on state highways rather than on Interstates, in clear weather rather than in rain or snow, and during the day rather than during at night. Vehicles usually do not cut in when a truck is following another vehicle at less than 25-m (82-ft) or 1.0-s headway. For manual response times, the rear-end crash risk increases considerably at headways of less than 1.0 s; for automated response times, crash risk is almost negligible at headways as low as 0.5 s.

01628078

17-00702

English

pp 35–42

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309442040

Digital/other

Figures (8) ; References (13) ; Tables (2)

Automatic data collection systems; Following distance; Headways; Traffic platooning; Trucks

Freight Transportation; Highways; Operations and Traffic Management

PRP, TRIS, TRB, ATRI

Dec 8 2016 10:09AM

• Application of High-Resolution Vehicle Data for Free-Flow Speed Estimation
• Calibrating Vissim to Analyze Delay at Signalized Intersections
• Car Drivers’ Experienced Level of Service on Freeways
• Estimating the Effects of Urban Street Incidents on Capacity
• Estimation of Saturation Headway in Work Zones on Urban Streets
• Evaluation and Testing of Driver-Assistive Truck Platooning: Phase 2 Final Results
• How Weather Events Affect Freeway Demand Patterns
• Influence of Remotely Operated Stop–Slow Controls on Driver Behavior in Work Zones
• Measuring Performance on Two-Lane Highways: Empirical Investigation
• Modeling Pedestrian Delays at Signalized Intersections as a Function of Crossing Directions and Moving Paths
• Novel Area Occupancy–Based Method for Passenger Car Unit Estimation on Multilane Urban Roads Under Heterogeneous Traffic Scenario
• Operational Analysis of a Single-Lane Roundabout with a Mix of Driverless Vehicles
• Optimizing and Modeling Tollway Operations Using Microsimulation: Case Study Sanand Toll Plaza, Ahmedabad, Gujarat, India
• Preparing Oregon for Connected Vehicle Deployment: Application Prioritization Process
• Proposed Framework for Evaluating Spillback in the Highway Capacity Manual
• Queue Length at Signalized Intersections from Red-Time Formula and the Highway Capacity Manual Compared with Field Data
• Relationship Between Cycle Overflow Probability and Capacity at Signalized Intersections: Application for Delay Estimation