#75 Network Safety Plan (pt 3.3)

The current short series of briefs explores key Network Safety Plan (NSP) principles and components. As part of this, the previous two briefs have looked at the Safe System approach (brief #73) and Movement and Place (brief #74) for road categorisation in NSP. The current entry summarises a third NSP component, termed ‘self-explaining roads’.

Self-explaining roads within the NSP

Self-explaining (or self-enforcing) roads (SER) are an integral part of Network Safety Plans[1]. The concept of self-explaining roads SER is not new, with the need to design roads which align with driver expectations articulated by European researchers since the 1980s. As described in 1995 by Theeuwes[2]:

The so-called “Self-Explaining Road” (SER) is a traffic environment which elicits safe behaviour simply by its design.

The importance of this in relation to a network-wide approach is reflected in the Austroads (2020) description of SER, where predictability and promotion of safe and appropriate road user behaviour are inherent in the road design. Regarding the delivery and implementation of relevant projects, Austroads importantly emphasises that:

This is difficult to achieve when projects are delivered on a project-by-project basis, so adoption of a network-wide approach facilitates achievement of this principle.

Research snapshot on SER

Early research explored key aspects of SER, including driver perceptions of different road categories, the role of expectations on drivers’ in-traffic search strategies, and principles and design criteria for SER development, among others.

More recently, Theeuwes et al. (2024)[3] followed up with an examination of the effects of road design on drivers’ speed choice. An experimental study was conducted, with participants (N=462) asked to indicate their speed choice for different scenarios presented through pictures of the road environment. Pictures were shown for short and longer durations to determine whether responses would differ according to the time participants were given to absorb the images. Responses to urban and rural scenarios were analysed separately.

In urban scenarios, the presence of painted bicycle lanes (relative to no bicycle lane) reduced driving speeds, while a separated bicycle lane had the opposite effect. Higher speeds were also associated with central line markings (relative to no line markings). Other elements examined in the study included the presence/absence of buildings, parking spaces, curves, speed humps, and separated lanes. The overall results on speed choice for urban (“city limits”) scenarios are shown in the reproduced Figure 1 below.

For rural (outside city limits) areas, the elements associated with the largest effects were the number of lanes (multiple lanes = higher speeds) and lane separation (no separation = lower speeds). On the question of whether responses differed according to the time participants had to absorb the images, the authors found that:

Importantly, exposure duration (200 /300 ms versus 1500 ms) only had a marginal effect, indicating that road users generally only need a brief glimpse of the road to be able to decide what speed to drive.

Figure 1: Effects of urban road element comparison in km/h (source: Theeuwes et al., 2024)

[1] Austroads (2020). Network Design for Road Safety (Stereotypes for Cross Sections and Intersections) User Guide. AP-R619-20. Sydney, Austroads. https://austroads.gov.au/publications/road-design/ap-r619-20

[2] Theeuwes, J. & Godthelp, H. (1995). Self-explaining roads. Safety Science, 19, 217-225.

[3] Theeuwes, J. et al. (2024). Self-Explaining Roads: Effects of road design on speed choice. Transportation Research Part F: Traffic Psychology and Behaviour, 102, 335-361.