Using the ISO detection response task to measure the cognitive load of driving four separate vehicles on two distinct highways

Biondi, FN; McDonnell, A; Cooper, JM; Strayer, DL · 2024 · publications_jsonl

DOI: 10.1016/j.trf.2024.02.013

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Summary

This study addresses the gap in standardized metrics for assessing the cognitive load imposed by driving itself, rather than secondary tasks. While the ISO Detection Response Task (DRT) is widely used to measure workload from distractions like phone calls or infotainment systems, it has rarely been applied to evaluate the cognitive demands of varying road geometries and vehicle types. The authors aimed to extend the DRT’s application to measure how distinct highway characteristics and different vehicle designs affect driver workload, providing objective data where previous research relied on self-reported ratings or complex neurophysiological equipment. The experimental design involved 71 participants driving four distinct vehicles—a 2019 Tesla Model 3, a 2018 Cadillac CT6, a 2018 Volvo XC90, and a 2019 Nissan Rogue—in manual mode on two Utah interstates: Interstate 15 (I-15) and Interstate 80 (I-80). I-15 was characterized as a straight, flat, four-to-five-lane highway with high traffic volume, while I-80 was a narrower, two-to-three-lane highway winding through a mountain canyon with lower traffic density. Participants drove each vehicle on each highway for approximately 20 minutes, with the order fully counterbalanced. Cognitive load was measured using the DRT, where participants responded to quasi-random vibrotactile stimuli on their forearm by pressing a microswitch. Reaction times (RT) and miss rates were recorded and analyzed using linear mixed-effects models, controlling for individual differences and temporal changes within drives. The results demonstrated significant effects of both roadway and vehicle type on cognitive load. Driving on I-80 resulted in significantly slower DRT reaction times (mean = 498 ms) compared to I-15 (mean = 476 ms), indicating higher cognitive demand due to the more complex road geometry. Reaction times also increased over time during drives, with a steeper decline in performance observed on I-80. Regarding vehicles, the Volvo XC90 elicited significantly slower reaction times (mean = 521 ms) compared to the Nissan Rogue (477 ms), Tesla Model 3 (480 ms), and Cadillac CT6 (469 ms). No significant differences in DRT miss rates were found between vehicles, though misses were higher on I-80. The authors attribute the higher workload in the Volvo to its larger size and SUV classification, which may require greater cognitive effort for vehicle control and spatial awareness compared to the sedans and crossover. These findings validate the ISO DRT as a robust tool for assessing the intrinsic cognitive demands of driving across different environments and vehicle platforms. The study highlights that road complexity significantly increases mental workload, even in the absence of secondary tasks. Furthermore, it suggests that vehicle size and type influence driver cognition, with larger vehicles like the Volvo imposing a measurable cognitive cost. This research advances the field by providing standardized, objective metrics for comparing vehicle and road designs, offering valuable insights for human factors engineering and road safety policy.

Key finding

Significant main effect of highway on DRT RT (chi2(1)=16.15, p<0.001, partial-eta2=0.08): I-80 produced slower RTs (M=498 ms) than I-15 (M=476 ms), with more DRT misses on I-80, consistent with I-80's narrower (2-3 lanes) winding canyon profile vs I-15's flatter 4-5-lane carriageway. RTs increased across the eight time periods (chi2(1)=103.45, p<0.001), and the rate of increase was steeper on I-80 (beta=10.83) than I-15 (beta=7.43). Significant vehicle effect (chi2(3)=71.09, p<0.001, partial-eta2=0.10): the Volvo XC90 elicited 40-50 ms slower DRT RTs (M=521 ms) than the Nissan (477), Tesla (480), and Cadillac (469); a vehicle x highway interaction showed I-80 slowing for the Tesla and Nissan but not the Volvo or Cadillac. No vehicle differences in miss rate. Authors argue interior/UI cannot fully explain the Volvo elevation and suggest vehicle-size-related driver-behavior modulations as a candidate mechanism.

Methodology

on_road

Sample size: N=71 (25 female, 46 male); mean age 40.8 years (SD 6.11)

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via tag_papers on 2026-05-30 (4 acquisition events logged).

Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• mental demand
• workload measurement
• stress driving
• road complexity
• cognitive capacity variation
• traffic density

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: physiological data
• Methodological Resource: validation psychometrics
• Theoretical Contribution: theory or model