Myra Blanco

Field Demonstration of Heavy Vehicle Camera/Video Imaging Systems

To help drivers monitor the road and to reduce blind spots, Camera/Video Imaging Systems (C/VISs) display video from cameras mounted on the truck’s exterior to drivers using displays inside the truck cabin. This report investigated drivers’ performance with C/VISs in a real-world trucking operation. Twelve commercial drivers’ performance with and without a C/VIS was continuously recorded while they each drove for four months. Half of the drivers used a commercially available C/VIS that had a side-view camera on each fender. The other drivers used an advanced C/VIS (A-C/VIS) that had side-view cameras, a rear-view camera, and night-vision capabilities. The results show that when a C/VIS was provided: 1) drivers’ involvement in safety-critical events (SCEs) did not change, 2) the probability that drivers looked forward did not change, 3) drivers were more likely to use the C/VIS at night and when making right lane changes, and 4) drivers indicated that the C/VISs helped them become aware of surrounding objects and merge into traffic. In terms of disbenefits, some drivers indicated that glare from the commercially available C/VIS monitors, as positioned to specifications, could be uncomfortable at night. The A-C/VIS’s advanced features were highly rated by drivers. The rear-view camera was also used more than the left or right fender cameras.

Evaluation of Safety Benefits from a Heavy-Vehicle Forward Collision Warning System

Forward collision warning (FCW) systems are designed to alert drivers to an impending rear-end (RE) crash, to allow drivers to respond to a crash threat sooner, and thus to reduce their impact speed or allow them to avoid a crash altogether. This study estimates the safety benefits that may be attained by deploying an FCW system across the national fleet of heavy vehicles. The approach involved identifying RE conflicts within a heavy-vehicle naturalistic driving data set with the use of algorithms that identified potential RE events and removed nonthreatening events. Since the heavy vehicles in this data set were not equipped with FCW systems, the FCW auditory alarm severity and timing were introduced into the data with existing FCW system algorithms. Driver perception–response times and braking levels to the computed FCW alarms were modeled with actual driver alarm response behavior recorded in a previous heavy-vehicle FCW field operational test. Driver RE collision avoidance behavior, both with and without FCW alarm feedback, was then simulated with a Monte Carlo simulation approach. The simulation assumed that drivers selected the optimal braking response in the event that multiple FCW alarms were triggered. The number of conflicts avoided and the additional response time available before a crash were then used to assess the safety benefits. This study estimated that FCW systems may afford a 21% reduction in heavy-vehicle RE crashes, which translates to 4,800 crashes per year on U.S. highways.

Automated Vehicles: Take-Over Request and System Prompt Evaluation

As automated driving technology advances, the driver’s role continues to shift from active vehicle control to passive monitoring of the automated driving system and environment. This study comprised three experiments on controlled test tracks in mixed traffic that investigated driver interactions with prototype Level 2 and Level 3 partially automated driving systems. The study investigated which human-machine interface (HMI) characteristics are most effective at issuing a Take-Over Request (TOR) during the operation of a Level 2 automated driving system, how to prompt drivers to attend to the road when distracted during the operation of a Level 2 automated driving system (and whether these prompts are effective over time), and which HMI characteristics are most effective at issuing a TOR during the operation of a Level 3 automated driving system. In addition, participants’ trust in the automated driving system they experienced was gauged through multiple Likert-type surveys and an after-experience interview.

Commercial Driver Acceptance of Heavy Vehicle Camera/Video Imaging Systems

Large trucks are estimated to be involved in 20,311 crashes annually as a result of making improper lane changes, turns, and backing maneuvers. Camera/Video Imaging Systems (C/VISs) are designed to be a low cost countermeasure to these crash types by reducing the blind spots located around large trucks. Their effectiveness, however, depends on whether drivers accept and use this technology. This paper investigates drivers’ opinions of C/VISs that were measured from 12 drivers who each partook in a four-month C/VIS technology field demonstration (TFD). The TFD investigated the utility of two C/VISs in assisting commercial drivers as they drove on revenue-producing routes. Drivers completed questionnaires pertaining to their perceptions of their driving performance and the C/VISs every two weeks while in the study. Drivers’ indicated that the C/VISs reduced surrounding blind spots, improved their spatial awareness, and helped them merge into traffic. Overall, commercial drivers should accept C/VISs provided that they cover the right-side blind spot, allow monitors to be substantially dimmed to reduce glare, and do not create new blind spots.

Experienced CMV Driver Opinions of Advanced Driving Simulator Scenarios

There is an increasing interest in providing refresher training for commercial motor vehicle (CMV) drivers. Truck driving simulators offer the potential to provide this type of training to CMV drivers in an efficient and effective manner. However, the success of truck simulator-based training depends on drivers’ acceptance of the simulator and scenarios. The present study investigated 48 experienced CMV drivers’ (across three trailer types and two levels of experience) opinion on the realism of 12 emergency maneuvers and 10 extreme conditions in a truck driving simulator. Drivers provided feedback as to the realism of each event in the simulation. Results indicated that, in general, drivers rated the scenarios as realistic as compared to the real-world equivalent situations. There was no pattern of differences between driver experience levels or operation types. These findings have implications for both future simulation-based training programs and future driving scenarios, and suggest that simulation-based refresher training may be accepted by drivers.