{'fraction_non_alphanumeric': 0.030890369473046637, 'fraction_numerical': 0.0012113870381586917, 'mean_word_length': 5.661290322580645, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Challenges in Hazard Detection for Commercial Motor Vehicle Drivers: A Driving Simulator Training Study

There are few research studies that have assessed the hazard detection (HD) challenges of experienced, skilled drivers. This paper presents the pilot study results of an HD training program, Commercial Driver Assessment and Training System (CDATS), developed for commercial motor vehicle (CMV) drivers. The training involved simulation-based videos that highlight potential vehicle, pedestrian, and visually hidden hazards during unprotected intersection maneuvers: left-turn, right-turn, and straight-thru. Low-fidelity driving simulations were designed to reinforce video lessons and increase the expectation and detection of potential hazards. Training efficacy was assessed using a driving simulator HD task presented to short-haul CMV drivers (N = 16) at pre-/post-assignment to CDATS training or a control condition. Results suggested that CMV drivers had highest HD task accuracy (% correct) for vehicle hazards and lowest accuracy for visually hidden hazards. Performance for pedestrian hazards was dependent on the intersection maneuver, with performance decreases for left-turn, right-turn and straight-thru intersections, respectively. Post-test results suggested overall HD improvement in the CDATS training group with no change in the control group; however, there was no significant change in relative hazard type by intersection maneuver pattern. Similar to prior research, experienced CMV drivers may also exhibit challenges in HD, particularly for visually hidden and visible pedestrian hazards, and may benefit from HD training.