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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

 
REPORT
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Publication Number:  FHWA-HRT-17-024    Date:  June 2017
Publication Number: FHWA-HRT-17-024
Date: June 2017

 

Cooperative Adaptive Cruise Control Human Factors Study: Experiment 4—Preferred Following Distance and Performance in An Emergency Event

CHAPTER 1. INTRODUCTION

This report describes the fourth and final experiment in a series of four studies that explore cooperative adaptive cruise control (CACC). CACC combines three driver assist systems: (1) conventional cruise control, which automatically maintains the speed a driver has set, (2) adaptive cruise control, which uses radar or lidar sensors to automatically maintain a gap the driver has selected between the driver’s vehicle and a slower-moving vehicle ahead, and (3) dedicated short-range communications to transmit and receive data with surrounding vehicles so that the cruise control system can more quickly respond to changes and speed and location of other CACC vehicles (including vehicles that the driver cannot see).(1)

When using CACC, drivers share vehicle control with an automated system that includes vehicle-to-vehicle and vehicle-to-infrastructure communications. Communications between nearby CACC-equipped vehicles will enable automated coordination and adjustment of longitudinal control through throttle and brake activations. Automated control should enable CACC-equipped vehicles to safely travel with smaller gaps between vehicles than drivers could safely manage on their own. Smaller gaps should subsequently increase the roadway capacity without increasing the physical amount of roadway. However, shorter following gaps lead to problematic human factors issues.

At 104.6 km/h (65 mi/h), a 1-s gap leaves approximately 28.96 m (95 ft) between vehicles. Previous studies have shown that drivers feel both comfortable and safe travelling at gaps shorter than 1 s. For example, in an on-road study testing drivers’ choices in following distances, drivers regularly used gap settings shorter than 1 s.(2) In fact, overall, when following another vehicle, drivers elected to set the gap at 0.7 or 0.6 s 80 percent of the time. However, with a 0.6-s gap, there was only approximately 17.37 m (57 ft) between vehicles. If an average vehicle length is assumed to be around 6.10 m (20 ft), then this leaves less than 5.64 m (18.5 ft) of buffer on either side for a merging vehicle. As a result of these shorter distances, drivers may not feel comfortable merging or having a vehicle merge in front of them in a CACC platoon. Furthermore, gap-based discomfort may vary from person to person.

It is possible that individual differences in preferred following time gap may influence performance in the event that a driver needs to overtake the CACC system and regain manual control of the vehicle. For this reason, preferred following distance as it relates to performance is considered.

Another important assumption made in this study is that the CACC system will require dedicated infrastructure in its early implementation. This infrastructure requires that the CACC lane (or lanes) is physically separated from “normal” travel. This is important for several reasons. CACC will be of the most use in congested regions. This congestion often leads to lower travelling speeds and a great deal of speed variation (i.e., stop-and-go or slow-and-go traffic). Because CACC-equipped vehicles travelling in a separate lane will travel at fairly constant speeds with standard gap distances, the lane will be less susceptible to speed variability. As a result, vehicles in the CACC lane are likely to be travelling at speeds greater than the normal travel lanes. The speed differential between the two types of lanes will introduce problems reaching speeds great enough to transfer from one type of lane to the other. Instead, drivers will be required to enter the lane from a separate on ramp (much like drivers entering and exiting dedicated high-occupancy vehicle lanes). The physical separation between the two types of lanes also prevents non-CACC-equipped vehicles from entering the CACC lane and disrupting travel flow stability. To mimic this anticipated initial early implementation of CACC, participants drove in a dedicated and physically separated lane.

Current cruise control systems, both conventional and adaptive, are marketed as convenience systems that reduce driver workload and stress by relieving the driver of the need to continuously regulate vehicle speed and following distance.(3,4) The desired effect of stress reduction is to optimize drivers’ performances and feelings of well-being. However, the Yerkes-Dodson law suggests that for tasks of moderate difficulty, low and high levels of arousal will lead to lower levels of performance than some moderate levels of arousal.(5) As a result, a less favorable CACC outcome might be to reduce driver arousal below the optimum level and result in poorer driver performance. Driver performance remains important in semi-autonomous systems such as CACC. CACC systems do not maintain lateral control of the vehicle, and braking is not always the best or safest response to a slower or stopped vehicle ahead. This can be especially problematic in the case of system failure or an emergency event (e.g., a crash upstream).

This study (the fourth in a series of four experiments) explored driver performance while using CACC. The goal of this research was to address some of the critical human factors issues for CACC usage related to the abilities and limitations of the drivers using the system.

In CACC experiment 1, the CACC system was effective in preventing crashes.(6) Participants rated their workload as low. However, the gap (the time gap is the distance between the front bumper of the host to the rear bumper of the preceding vehicle) was 1.1 s. For a CACC system to greatly increase highway capacity, it would need to maintain smaller gaps. The question then arises whether (1) drivers would accept smaller gaps, (2) drivers’ preferred following distance influences crash avoidance performance, and (3) preferred following distance influences perceived workload.

As previously noted, many drivers already accept gaps smaller than 1.1 s. For instance, Taieb-Maimon and Shinar reported a study in which the perceived minimum safe gaps were 0.7 s or less, and comfortable perceived gaps were less than 1 s.(7) It is possible and likely that acceptable gap perception varies greatly between drivers and driving environments. The present experiment will explore the gap acceptability and driving performance in a driving simulator experiment.

This experiment was divided into two parts. The goal of part 1 was to determine median preferred following distance. That median distance was then used to determine whether participants would be classified as near or far preferred followers in part 2.

The goals of part two were as follows:

 

 

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