Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review

Analysis of the factors influencing overtaking in two-lane highways: A driving simulator study

Approximating Road Geometry with Multisine Signals for Driver Identification

Vehicle technologies are rapidly evolving due to their multidimensional advantages. Different vehicle technologies like connectivity and automation on the same roads with the driver-controlled vehicles in an environment of mixed vehicle technologies may increase speed disparity. Previous studies have indicated that speed disparity measures and traffic collisions are inextricably related. Therefore, identifying the relationships between speed distribution measures of different vehicles and road geometry can help identify instances of speed disparity resulting from mixed vehicle technologies and identify the effectiveness of potential countermeasures. This research used speed prediction models in three different regions to analyze the speed behaviour of connected vehicles (CVs), automated vehicles (AVs) and vehicles with no connectivity or automation (NCVs) on horizontal curves on freeways and major arterials. Safety Pilot Model Deployment (SPMD) dataset in Michigan, USA were used to model CV speed behaviour at various points on horizontal curves in major arterials and freeways. Because the data involved repeated trips by same drivers in their instrumented vehicles, LME modelling was utilized in model development. In addition, speed data collected on major arterials and freeways in Ontario, Canada, using instrumented NCVs were used to develop similar LME models for NCVs. This research also used AVs speed prediction model available in the literature to model the speed behaviour of AVs on horizontal curves in Spain. A methodology is then presented to estimate speed disparity measures on horizontal curves with no control and with different control strategies or countermeasures. The results indicated that the mixed vehicle environment can cause the combined standard deviation of all vehicles (σ_c) to considerably increase on arterials and freeways under no control, which would in turn increase the collision experience. Countermeasures were proposed, which showed the potential in reducing σ_c and reduce the negative safety impacts of the mixed vehicle environment. Sensitivity analysis confirmed that speed compliance rates of the driver operators of CVs and NCVs with the speed advisories in the proposed countermeasures have insignificant impact on the speed disparity measure σ_c.

The role of attention in horizontal curves: A comparison of advance warning, delineation, and road marking treatments

Driver behaviour at horizontal curves: risk compensation and the margin of safety

Effects of unreliable automation, non-driving related task, and takeover time budget on drivers’ takeover performance and workload

Driver behaviour can strongly affect fuel consumption, and driver training in eco-driving techniques has been shown to reduce fuel consumption by 10% on average. However the effects of this training can be short-lived, so there is an apparent need for continuous monitoring of driver behaviour. This study presents a driver advisory tool which encourages eco-driving, and its evaluation in the field. The system, developed by Ashwoods Automotive Ltd (UK) and the University of Bath (UK), is aimed at fleet operators of light commercial vehicles, where the driver is typically a company employee. A significant strength of the system is that it has been designed for easy integration with the vehicle CAN-bus, reducing complexity and cost. By considering the Inertial Power Surrogate (speed times acceleration) the core algorithm is able to identify behaviour which is likely to increase fuel consumption. The algorithm also enforces the advice of the Gear Shift Indicator to encourage earlier upshifting. Fuel saving is therefore encouraged both by reducing the power demand of the drive cycle and by operating the engine in a more efficient region. Instantaneous visual feedback to the driver is augmented by audible warnings, which avoids the need for the driver to concentrate on the display, reducing cognitive loading. Reports on driver performance are made available to the fleet manager so that fuel efficient and safe driving can be encouraged. Trials of the system ran for four weeks and included 15 vehicles from 7 companies; a total of 39 300 km of trip data were collected during more than 1 100 hours of real world driving. Results show an average fleet reduction in fuel consumption of 7.6%, with some vans showing savings up to 12%. Furthermore, reductions of over 10% in both average engine speed and throttle activation were observed. It was also noted that the system shows strong potential for synergetic use with a hybrid electric powertrain, where modifying driver behaviour may facilitate energy harvesting from regenerative braking.

Driving simulators emerged as a promising technology for the analysis of driving conditions and road users' behaviour in an attempt to tackle the problem of road accidents. The work presented herein demonstrates the design and development of a driving simulator that aims to contribute towards evaluating black spots in road networks by promoting rapid design of realistic models and facilitating the specification of test scenarios. A reliable driving simulator should be able to reproduce the driver's behaviour in a realistic way. In this study the authors examine different setups of the simulator to define the one that achieves highest levels of reliability. The chosen setup is then used to evaluate the impact of distractors (e.g. billboards) on driving behaviour of local road users for a chosen black spot in Limassol, Cyprus. Data collected from the experiments are analysed, and the main findings are presented and discussed.

Bicycle crash contributory factors: A systematic review

• The performance of Adaptive Cruise Control (ACC) is limited on road curves. • The Intelligent Speed Adaptation for Visibility (V-ISA) adjusts speed based on road conditions. • A driving simulation study assessed the influence of ACC and V-ISA on driver behaviour. • Integrating ACC and V-ISA significantly improved longitudinal driving performance. • The system achieved high system acceptance with no added mental workload. Advanced Driver Assistance Systems (ADAS) have become an integral part of modern vehicles, significantly changing the driving experience. Adaptive Cruise Control (ACC) assists drivers in maintaining a constant speed and a safe following distance; however, it does not moderate the speed along curves when sight limitations occur, thus compromising safety. To address these challenges, this study integrates the Intelligent Speed Adaptation for Visibility (V-ISA) system with ACC. The V-ISA system dynamically adjusts the vehicle speed based on real-time visibility conditions, thereby enhancing safety on road curves where sight distance is restricted. Additionally, this study evaluates the impact of the ACC + V-ISA system on driver performance, specifically focusing on speed management, lateral vehicle control, and driver experience with assistance systems. The study was conducted in a simulated environment with forty-five participants. The results revealed that the ACC + V-ISA system effectively reduced vehicle speed on curves with limited visibility. The ability of the system to regulate speed according to prevailing road conditions highlights its potential to improve road safety. Moreover, the findings suggest that using the V-ISA system integrated with ACC maintains user acceptance and satisfaction while imposing no additional mental workload compared to using ACC alone. These insights are crucial for the future design of ADAS and autonomous vehicles and emphasize the importance of introducing this system into vehicles. LED bar colour

Attention, or more generally, driver monitoring systems have been identified as a necessity to address overreliance on driving automation. However, research suggests that monitoring systems may not be sufficient to support safe use of advanced driver assistance systems (ADAS), also evidenced by a recent major recall of Tesla’s monitoring software. The objective of the current study was to investigate whether different training approaches improve driver behaviour while using ADAS with an attention monitoring system. A driving simulator study was conducted with three between-subject groups: no training, limitation-focused training (highlighted situations where ADAS would not work), and responsibility-focused training (highlighted the driver’s role/responsibility while using ADAS). All participants (N = 47) experienced eight events which required the ego-vehicle to slow down to avoid a collision. Anticipatory cues in the environment indicated the potential for the upcoming events. Event type (covered in training vs. not covered) and event criticality (action-necessary vs. action-not-necessary) were within-subject factors. The responsibility-focused group made fewer long glances (≥ 3 s) to a secondary task than the no training and limitation-focused groups when there were no anticipatory cues. Responsibility-focused training and no training were associated with faster takeover time at the events than limitation-focused training. There were additional benefits of responsibility-focused training for events that were covered in training (e.g., higher percent of time looking at the anticipatory cues). Overall, our results suggest that even if attention monitoring systems are implemented, there may be benefits to driver ADAS training. Responsibility-focused training may be preferable to limitation-focused training, especially for situations where minimizing training length is advantageous.

A vehicle negotiating a curve experiences a centripetal force that is partially supplied by the tire–pavement friction. The American Association of State Highway and Transportation Officials’ design handbook, A Policy on Geometric Design of Highways and Streets (“Green Book”), dictates the design of horizontal curve segments according to the side friction (demand) factor, which is a fraction of the available friction used during a maneuver. However, the Green Book casts the side friction factor not as a measure of tire–pavement friction but as a measure of lateral acceleration. In this way, the Green Book conflates these independent concepts (tire–pavement friction versus lateral acceleration). It is shown in this work that keeping these curve design parameters independent has meaningful benefits. A rigorous mathematical clarification of the differences among the side friction (demand) factor, lateral acceleration, and coefficient of friction is developed. It is shown that changing the coefficient of friction affects the side friction factor, but the opposite is not necessarily true. An alternate metric is proposed, the performance margin [Formula: see text], that has several advantages for assessing friction margins. Currently, horizontal curves are designed only with a lateral friction reserve. Excluding longitudinal dynamics may not be realistic given the manner in which drivers react in limit handling maneuvers. The [Formula: see text] accounts for both bidirectional dynamics and road geometry, and highlights regions where the Green Book’s standards are inconsistent with vehicle performance capabilities. The work concludes by posing recommendations aimed at implementing the [Formula: see text] in future Green Book editions.

Objective This study investigates the interaction between human perception and driver behavior on horizontal curves, focusing on how road geometry and visibility affect driving performance. Methods A driving simulator replicated 3 curve types by radius—200 m (sharp), 400 m (moderate), and 600 m (loose)—under day and night conditions. The focus of expansion (FOE) is the source point of optical flow, and an FOE model was established to linked the driver’s visual perception with vehicle dynamics. Data on eye movement and vehicle dynamics were collected from 24 drivers (mean age: 27 years, mean driving experience: 3.8 years). Results The results indicate that driving at night on sharp curves significantly impairs the ability of drivers to align their perception with vehicle motion, leading to delayed steering adjustments and increased lateral errors. The most dangerous areas, identified as the back half of the test curves and corresponding to the minimum FOE radius, were where the misalignment between perception and motion was most significant. On loose curves, decreased driver vigilance was observed, potentially due to a perceived reduction in steering demands, underscoring the role of psychological and contextual factors during curve negotiation. Conclusion This study underscores the importance of optimizing curve radii and enhancing the alignment between drivers’ visual perceptions and vehicle dynamics to reduce accident risks. In real traffic, placing traffic guidance mid-curve may better prompt drivers to slow down, particularly at night. Integrating FOE-based feedback into advanced driver assistance systems (ADAS) could further enhance performance by offering real-time cues tailored to curve geometry in low visibility.

The objective of this paper is to investigate the relationship between road geometry and severe bus accidents in Brazil, based on an adaptation of the Umbrella Handle Model (UHM) and emphasizing the influence of unbalanced centripetal acceleration in the occurrence of these events. Three accidents of this type were selected for study, all of them recorded along or close to horizontal curves of Brazilian highways (Trindade Access, RJ 155 and SP 125 roads). The variation in centripetal acceleration of vehicles traveling under operating speed along each “smoothed tangent” was measured using the Keuwlsoft Accelerometer Counter app for smartphone. Transverse and longitudinal acceleration peaks were highlighted for each study section, and, in the first case, the critical variations refer precisely to the locations of the RJ 155 and SP 125 roads where bus accidents were recorded. With regard to the Road Risk Index (RRI), with the exception of the RJ 155 road, the highest RRI values among all combinations between a tangent and a sequential horizontal curve were also observed for the places of occurrence of the investigated accidents.

Safety of professional drivers in an ageing society – A driving simulator study