The impact of CCT on driving safety in the normal and accident situation: A VR-based experimental study
Introduction
The past few decades have witnessed the rapid development of tunnels. In China, by the end of 2019, the total length of road tunnels reached 18.9 million meters, with an increase of 10.04% compared to that of the previous year [1], which also increases the possibility of traffic accidents. Unlike open road sections, as a tubular and semi-enclosed structure, accidents in tunnels cause more catastrophic impact, as is illustrated in accidents in Italy [2], Singapore [3], etc. A variety of factors contribute to accidents in tunnels, among which the narrow and monotonous environment inside the tunnel is a crucial one, affecting the drivers’ correct perception of the surrounding environment information. This can result in a propensity of driving errors such as driving distraction and reduced perception of distance and speed [4], which is prone to accidents.
More than 80% of the information driver obtained while driving is through visual access, thus improving the visual environment inside the tunnel can reduce the probability of crashes [5]. Many research endeavors have been allocated to improve the visual performance of drivers from the respect of lighting environment, most of which mainly focused on luminance level [6], [7]. In addition, current international and national lighting standards for tunnel, e.g. CIE technical report 88-2004 [8] and Highway Tunnel Lighting Design Rules JTG/T D70/2-01-2014 [9], mainly include recommended values for luminance. However, as an important factor which affects visual performance [10], correlated color temperature (CCT) of the light source is rarely mentioned. In fact, previous studies have demonstrated that CCT can influence both visual performance and non-visual performance [11], [12], [13], [14]. Among the factors affected by CCT, visual fatigue, reaction time and other driving-related factors are crucial to driving safety, especially when driving in a monotonous environment like a tunnel. According to [14], light sources with different CCTs had a significant effect on reaction time and pupil area difference, both of which were highly related to driving safety. Hence, it is essential to investigate the optimal CCT of the light source inside the tunnel.
Because of the infeasibility of changing CCT in real tunnels, studies on the CCT inside the tunnel usually simplify the experimental conditions. The most commonly used alternative is to adopt an observation box with a semi-cylindrical space and have participants look directly at the light source with different CCTs through the observation box. During the process, their visual or non-visual performance is measured. Such approach can be seen in [15], [16], [17]. Another alternative is to use the luminaire to emit light and use the screen to show the visual environment of the tunnel. Similarly, all the participants need to do is just to look at the screen. Such simulation method was used in [18], [19]. However, both of these simulation methods cause high loss in terms of ecological validation, which refers to the extent to which the virtual environment corresponds to its operational equivalent in the real world [20]. In other words, the afore-mentioned methods fail to replicate the real driving experience. Understanding whether and how the CCT would influence participants who are performing driving tasks rather than participants who are not performing driving tasks could have more practical application value.
More than 90% of tunnel fires are caused by vehicle crashes and rear-end crashes constitute about 70% out of all the crashes [21], [22]. Previous studies have focused on human behavior after accidents, e.g. movement speed [23] and route choice [24]. However, human behavior at the time of the accident has been rarely explored. When it comes to the effect of CCT on human behavior in the accident situation, visual performance, especially reaction time, is usually adopted to evaluate CCT effect. In [14], [15], [18], reaction time is defined as the time from the appearance of the target light spot to the detection by the participants. Obviously, the light spot cannot represent traffic accident, so it still remains unclear how the CCT influences drivers’ visual performance when a rear-end accident occurs. Investigating such influences may have more important implications than the counterpart under normal condition. This knowledge could be applied to establish traffic laws on minimum following distance, which evidently benefits from knowledge about the maximum reaction time when a rear-end crash occurs.
Hence, to fill these knowledge gaps, this paper proposes a novel VR-based method for the design of CCT of the light source inside the tunnel. The immersive virtual environment (IVE) was modeled after a real tunnel in Hangzhou, China. A rear-end accident was designed in the IVE and an IVE-based driving experiment was conducted. Participants were asked to perform driving task in the tunnel model with light sources of different CCTs, whose visual and non-visual performance were collected and analyzed to answer the questions about how CCT would influence drivers in normal driving situation and accident situation respectively. The overall framework of the proposed method, the experimental setup, research findings and validation are given in the remainder of the paper. These findings are expected to provide practical recommendations for the design of CCT of light source inside the tunnel and advance the existing knowledge about CCT from a different perspective.
Section snippets
Visual performance under different CCTs inside the tunnel
Visual performance refers to the visual ability evaluated based on the speed and accuracy of visual task [25], which is closely related to lighting condition. Hence, visual performance is often selected as an indicator to help establish a foundation for lighting recommendations inside the tunnel. As mentioned above, the experiments on the CCT inside the tunnel are usually carried out in a simulated environment. A common practice is to place light sources with different CCTs in a dark
Research methodology
The major aim of this study is to examine the influence of CCT on the drivers who are performing driving tasks under different driving conditions (normal vs. accident). To this end, a VR-based framework was designed, where HMD and analog driving equipment were integrated to display virtual tunnel environment and simulate driving experience. Detailed description of the VR-based framework and experimental setup are given in the following subsections.
Results
According to the questionnaire results, two participants felt sick due to simulation sickness, thus a total of 28 records of data were obtained.
The influence of CCT on driving fatigue in normal driving situation
To sum up, the results of this study revealed that the CCT of the light source inside the tunnel would significantly influence driving fatigue of the drivers. Specifically, when driving to the middle of the tunnel, regardless of the CCT environment, drivers were prone to driving fatigue (Table 2). Driving in the environment with 3000 K CCT may induce more driving fatigue than other counterparts, while driving in the environment with a relatively higher CCT (i.e., 6000 K, 7000 K and 8000 K) may
Conclusions
A VR experimental study was conducted in a virtual tunnel to analyze the impact of CCT on the drivers who were performing driving task both in the normal driving situation and in the accident situation. The non-visual performance (attention level) and the visual performance (reaction time) of the participants were collected and analyzed. Results show that the CCT of light source inside the tunnel was significant on the driving fatigue of the driver who was performing driving task. And CCT also
CRediT authorship contribution statement
Xiaojun Li: Writing – review & editing. Jiaxin Ling: Conceptualization, Writing – original draft. Yi Shen: Methodology, Visualization, Investigation. Tong Lu: Validation. Shouzhong Feng: Resources. Hehua Zhu: Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This study was supported by the National Key R&D Program of China (No. 2018YFB2101000), Shanghai Sailing Program (20YF1451400), and the Research Fund of State Key Laboratory for Disaster Reduction in Civil Engineering (SLDRCE19-A-14).
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