Validation of driving behaviour as a step towards the investigation of Connected and Automated Vehicles by means of driving simulators

Connected and Automated Vehicles (CAVs) are likely to become an integral part of the traffic stream within the next few years. Their presence is expected to greatly modify mobility behaviours, travel demands and habits, traffic flow characteristics, traffic safety and related external impacts. Tools and methodologies are needed to evaluate the effects of CAVs on traffic streams, as well as the impact on traffic externalities. This is particularly relevant under mixed traffic conditions, where human-driven vehicles and CAVs will interact. Understanding technological aspects (e.g. communication protocols, control algorithms, etc.) is crucial for analysing the impact of CAVs, but the modification induced in human driving behaviours by the presence of CAVs is also of paramount importance. For this reason, the definition of appropriate CAV investigations methods and tools represents a key (and open) issue. One of the most promising approaches for assessing the impact of CAVs is operator in the loop simulators, since having a real driver involved in the simulation represents an advantageous approach. However, the behaviour of the driver in the simulator must be validated and this paper discusses the results of some experiments concerning car-following behaviour. These experiments have included both driving simulators and an instrumented vehicle, and have observed the behaviours of a large sample of drivers, in similar conditions, in different experimental environments. Similarities and differences in driver behaviour will be presented and discussed with respect to the observation of one important quantity of car-following, the maintained spacing

How do drivers avoid crashes: the role of driving headway

Rear-end crashes are a major part of road injury burden, accounting for one-third of all vehicle-to-vehicle crashes in New South Wales, Australia. Close following or driving with short headways is a key cause, yet the role of driver behaviour in rear-end crash risk is not well researched. The primary aim of this research was to develop a better understanding of rear-end crashes by assessing headways on Australian roads and investigating driver behaviour and performance associated with close following in crash and non-crash scenarios. Two systematic reviews of headway were conducted. First, a review of research on headway identified the need for a consistent and accurate definition of headway, so the thesis puts forward an improved definition. The second review identified the range of external factors that increase the risk of short headway and increase crash risk including speed, task engagement, lead vehicle type, traffic conditions, road characteristics, weather/visibility, drug use, driving fatigue, innovative lane markings, and various warning systems. These factors were then explored in New South Wales data on rear-end casualty and multiple vehicle crashes. The modelling of these associated factors were confirmed as contributing factors in rear-end crashes, congruent with the review of headway. Higher speed, free flowing traffic, volitional task engagement, low cue environments, and collision warning lead to longer headway. Despite lower fatalities, higher odds of injury were observed for rear-end crashes than other crash types. Rear-end crashes were more likely to lead to multiple vehicle crashes, which had a higher chance of fatality than other types of crashes. Finally, naturalistic driving study data was used to investigate headway during normal driving, exploring close following at different speeds and classifying potential risky driving at various headways. In 64 hrs accumulated across 2101 trips, short headways of under 1 s occurred in around 15% of driving. Common manoeuvres to avoid rear-end crashes when close following were changing lanes, or braking, almost always by the following driver. Headway was associated with both driver speed and posted speed limits, decreasing as posted speed limits increased. Over-the-speed-limit driving was observed in all headway scenarios, but especially in higher speed zones. The findings challenge the notion that rear-end crashes are less severe with low injuries. Road users should be made aware of how frequently safe headways are violated and severity of injury outcomes. Driver education, community engagement, application of driver assistance technology consistent with driver behaviour and safety campaigns need to focus on safer speed and headway management to reduce rear-end crash risk