Delay or travel time information? The impact of advanced traveler information systems on drivers’ behavior before freeway work zones

Peak travel times contribute to congestion formation at freeway work zones. Advanced Traveler Information Systems (ATIS) can inform drivers in real-time about the delays and travel times en-route and can provide information about an alternative route to a destination. Different ATIS display strategies are available; however, road authorities lack insights into how time display methods and sign characteristics influence the driving behavior (decelerations, lateral position), the drivers’ attention allocation ability and the subsequent route choice before the freeway diversion. A driving simulator study was conducted with 80 drivers in the State of Qatar to investigate drivers' behavior and voluntary route choices when encountering total travel time (default setting) or delay time updates for two freeway routes on Variable Message Signs (VMS) and Graphical Route Information Panels (GRIP). The GRIPs are a graphical alternative to conventional VMS that can provide drivers with a visual map of the most direct route or an alternative less congested route to a destination using different color schemes. The time difference ratio between the two routes was kept constant to compare the effectiveness of the information designs and investigate the drivers’ attention towards the signs with an eye-tracker. The results showed that the display of zero delays for a detour did influence 74–83% of the drivers to take the alternative route when being displayed on a VMS and a GRIP with free flow attribute framing. When displaying equal total travel times, the GRIP did influence 25% more drivers to follow the alternative route than the VMS. Generally, displaying zero delays for the alternative route resulted in an efficient attention allocation to the first ATIS location and fewer mean decelerations before the repeated ATIS location nearing the diversion. Road authorities are advised to activate the display of delay times to support efficient route choices among freeway drivers.     

Judgments of mean speed and predictions of route choice

How are driving speeds integrated when speeds vary along a route? In a first study, we examined heuristic processes used in judgments of mean speed when the mean speeds on parts of the trip varied. The judgments deviated systematically from objective mean speeds because the distances driven at different speeds were given more weight than travel time spent on the different distances. The second study showed that when there was a 10–15 min pause during a travel the effect on the mean speed decrease was underestimated for driving speeds of 90 km/h and higher. In the third study, the objective mean speeds and the subjective biased mean speed judgments were used to predict choices between routes with different speed limits. The results showed that subjective judgments predicted decisions to maximize mean speed significantly better than objective mean speeds. Finally, some applied and basic research implications of the results were discussed.     

A simulator study of factors influencing drivers’ behavior at traffic lights

Drivers’ reactions to changing traffic lights have an impact on safety at intersections. We examined the influence of transient factors – more specifically time pressure and social context, both conducive to traffic-light violation – on behavior behind the wheel when a traffic light changes. We carried out an experiment on a driving simulator. The participants were 94 car drivers (53 males) with a mean age of 21.7 years. They drove under time pressure vs. no time pressure. At several intersections the participants were alone (no other drivers present), whereas at several other intersections they were behind a line-up of vehicles, the last of which ran the yellow light (other drivers present). As expected, time pressure and social context (presence of other drivers) increased participants’ risky behaviors while approaching, and going through traffic lights, as well as undesirable rapid accelerations when the signal changes to green. The effect of time pressure on yellow-light running was not mediated by approach speed, which showed that participants in a hurry were likely to run lights intentionally. The results are interpreted in view of proposing effective measures for reducing yellow-light running and rapid accelerations at traffic lights.     

Can prosocial attitude reduce the risk behavior in simulated driving?

High traffic density may lead to more traffic accidents because of more frequent lane change and overtaking behaviors, but drivers with different characteristics may exhibit different driving behaviors. The present study explored the difference in driving behaviors between drivers with a high/low prosocial attitude under high/low traffic density. In this study, a 2 (high/low prosocial attitude) *2 (high/low traffic density) mixed design was used to investigate the interaction between prosocial attitude and traffic density on lane change and overtaking behavior. The implicit association test paradigm was used to measure prosocial attitude, and drivers were divided into two groups. Forty subjects were asked to complete simulated driving tasks under the two conditions of high and low traffic density, and driving behaviors were recorded by driving simulators. The results show that high traffic density leads to more lane change and overtaking behavior. Drivers with a high prosocial attitude have better driving performance under both high and low traffic density, but drivers with a low prosocial attitude maintain a smaller transverse distance from adjacent vehicles in high traffic density, which may increase risk. This study provides support for the selection, training and intervention of professional drivers.     

Does the effect of traffic calming measures endure over time? – A simulator study on the influence of gates

Accident statistics show that transitions from rural to urban areas are accident prone locations. Inappropriate speed and mental underload have been identified as important causal factors nearby such transitions. A variety of traffic calming measures (TCM) near rural–urban transitions has been tested in field experiments and driving simulator studies. Simulator experiments repeatedly exposing participants to the same treatment are scarce, hence it is unclear to what extent the effects of a TCM endure over time.This is precisely the objective of the current study: to examine what happens with the behavior of drivers when they are exposed multiple times to the same treatment (in this case a gate construction located at a rural–urban transition). Over a period of five successive days, seventeen participants completed a 17 km test-drive on a driving simulator with two thoroughfare configurations (gates present or absent) in a within-subject design. Results indicate that gates induced a local speed reduction that sustained over this five-day period. Even though participants were inclined to accelerate again once passed by this gate configuration, they always kept driving at an appropriate speed. We did not find any negative side effects on SD of acceleration/deceleration or SDLP.Overall we conclude that gate constructions have the potential to improve traffic safety in the direct vicinity of rural–urban transitions, even if drivers are repeatedly exposed. Notwithstanding, we advise policy makers to appropriately use this measure. Best is to always carefully consider the broader situational context (such as whether the road serves a traffic- rather than a residential function) of each particular location where the implementation of a gate construction is one of the options.     

Can driving condition prompt systems improve passenger comfort of intelligent vehicles? A driving simulator study

The main trend in the development of intelligent vehicles has been on ensuring comfort, safety, efficiency, and environmental sustainability. However, current research focuses primarily on the safety and energy saving of intelligent vehicles, and a comfortable driving experience through a human–machine interaction system has not been sufficiently investigated. This study used a high-fidelity 6-degree-of-freedom driving simulator to evaluate the impact of an independently-designed vehicle driving condition prompt (DCP) systems on subjective passenger comfort and motion sickness. The experiment showed that when future driving information is obtained through the vehicle DCP systems, the passengers' subjective comfort is improved, motion sickness is alleviated, and the degree of passenger posture instability is reduced. These conclusions contribute toward improving the comfort of autonomous vehicles and providing a reference for the future design of human–machine interaction systems for intelligent vehicles.     

Driving errors,estimated performance and individual characteristics under simulated and real road traffic conditions – A validation study

BackgroundThe suitability of driving simulators for the prediction of driving behaviour in road traffic has been able to be confirmed in respect of individual assessment parameters. However, there is a need for overarching approaches that take into account the interaction between various influencing factors in order to establish proof of validity. The aim of this study was to explore the validity of our driving simulator in respect of its ability to predict driving behaviour based on participants‘ observed driving errors and driver’s individual characteristics.Method41 healthy participants were assessed both in a Smart-Realo-Simulator and on the road. By means of linear modelling, the correlation between observed driving errors was investigated. In addition, the influence of self-reported and externally assessed driving behaviour as well as individual parameters (education and training; driving history) were analysed.ResultsBy including these factors, 58% of the variance could be explained. For observed driving errors, a relative validity was established. For self-reported and externally assessed driving behaviour, an absolute to relative validity emerged. The amount of time spent in education and training proved to have a significant influence on driving performance in the simulator, but not on the road.DiscussionIn general, our results confirmed the validity of our driving simulator with regard to observed and self-reported driving behaviour. It emerged that education and training as potential indicators of cognitive resources played a differential role regarding the study conditions. Since real road driving is considerably automated in experienced drivers, this result suggests that simulation-related behavioural regulation is challenged by additional cognitive demands as opposed to behavioural regulation extending to real road driving. However, the source of these additional cognitive demands remains currently elusive and may form the subject of future research.