Looking at the inside edge of the road when steering a bend seems to be a well-established strategy linked to using a feature called the tangent point. An alternative proposal suggests that the gaze patterns observed when steering result from looking at the points in the world through which one wishes to pass. In this explanation fixation on or near the tangent point results from trying to take a trajectory that cuts the corner. To test these accounts, we recorded gaze and steering when taking different paths along curved roadways. Participants could gauge and maintain their lateral distance, but crucially, gaze was predominantly directed to the region proximal to the desired path rather than toward the tangent point per se. These results show that successful control of high-speed locomotion requires fixations in the direction you want to steer rather than using a single road feature like the tangent point.

This is a repository copy of The role of gaze and road edge information during high-speed locomotion..

Old age is associated with poorer movement skill as indexed by reduced speed and accuracy.Nevertheless, reductions in speed and accuracy can also reflect compensation as well as deficit. We used a manual tracing and a driving task to identify generalised spatial and temporal compensations and deficits associated with old age. In Experiment 1 participants used a handheld stylus to trace a path. In Experiment 2 participants steered along paths in a virtual reality driving simulator. In both experiments, participants were required to stay within the boundaries whilst we manipulated task difficulty by changing path width or movement speed. The older group showed worse performance in the highly constrained conditions. Corner-cutting effectively reduces the curvature of bends but yields a greater risk of error (i.e. clipping the path/road-edge). Corner-cutting is thus less risky on wider paths and we found that cornercutting increased for both age-groups in both tasks when paths were wider. Crucially, we observed a greater degree of corner-cutting in the young group compared to the old, suggesting the old group compensated for decreased motor skill with "middle-of-the-road" behaviour. Enforcing increased speed caused all participants to increase corner-cutting. Thus, older participants showed spatial compensation for decreased skill by biasing their position towards the middle of the path in both a manual and steering task. External constraints (narrow paths and fast speeds) prevented this strategy and revealed age-related declines in skills central to manual control and driving.

How do animals follow demarcated paths? Different species are sensitive to optic flow and one control solution is to maintain the balance of flow symmetry across visual fields; however, it is unclear whether animals are sensitive to changes in asymmetries when steering along curved paths. Flow asymmetries can alter the global properties of flow (i.e. flow speed) which may also influence steering control. We tested humans steering curved paths in a virtual environment. The scene was manipulated so that the ground plane to either side of the demarcated path produced larger or smaller asymmetries in optic flow. Independent of asymmetries and the locomotor speed, the scene properties were altered to produce either faster or slower globally averaged flow speeds. Results showed that rather than being influenced by changes in flow asymmetry, steering responded to global flow speed. We conclude that the human brain performs global averaging of flow speed from across the scene and uses this signal as an input for steering control. This finding is surprising since the demarcated path provided sufficient information to steer, whereas global flow speed (by itself) did not. To explain these findings, existing models of steering must be modified to include a new perceptual variable: namely global optic flow speed.

Responding to changes in the road ahead is essential for successful driving. Steering control can be modeled using 2 complementary mechanisms: guidance control (to anticipate future steering requirements) and compensatory control (to stabilize position-in-lane). Drivers seem to rapidly sample the visual information needed for steering using active gaze patterns, but the way in which this perceptual information is combined remains unclear. Influential models of steering capture many steering behaviors using just ‘far’ and ‘near’ road regions to inform guidance and compensatory control respectively (Salvucci & Gray, 2004). However, optic flow can influence steering even when road-edges are visible (Kountouriotis, Mole, Merat, & Wilkie, 2016). Two experiments assessed whether flow selectively interacted with compensatory and/or guidance levels of steering control, under either unconstrained gaze or constrained gaze conditions. Optic flow speed was manipulated independent of the veridical road-edges so that use of flow would lead to predictable understeering or oversteering. Steering was found to systematically vary according to flow speed, but crucially the Flow-Induced Steering Bias (FISB) magnitude depended on which road-edge components were visible. The presence of a guidance signal increased the influence of flow, with the largest FISB in ‘Far’ and ‘Complete’ road conditions, whereas the smallest FISB was observed when only ‘Near’ road-edges were visible. Gaze behaviors influenced steering to some degree, but did not fully explain the interaction between flow and road-edges. Overall the experiments demonstrate that optic flow can act indirectly upon steering control by modulating the guidance signal provided by a demarcated path.