Driver's Perspective Research Articles

“I will raise my hand and say ‘I over-trust Autopilot’. I use it too liberally” – Drivers’ reflections on their use of partial driving automation, trust, and perceived safety

Introduction: Partially automated cars are on the road. Trust in automation and perceived safety are critical factors determining use of automation. Background: Drivers misuse partially automated driving systems. Misuse is associated with mis-calibrated trust in the automation. Research gap: Little is known about the factors impacting the perceived safety when using partial driving automation. Research objective: The main objective of the present study is to provide a comprehensive driver perspective on the psychological aspects of automation use pertaining to trust in automation, perceived safety, and its relationship with use of automation. Method: Semi-structured interviews (n = 103) were conducted with users of partially automated driving systems. Supplemented with content analysis, natural language processing (NLP) techniques were applied to perform automatic text processing. Guided seed-term analysis was conducted to identify the number of occurrences of the subcategories in the dataset. Main results: We identified human operator-related, automation-related, and environmental factors of trust and perceived safety. The identified factors were more strongly associated with perceived safety than with trust. Participants with physical and visual impairments reported to feel safer using the automation compared to driving manually. Neurotic behavior during manual driving contributed to lower trust and perceived safety using the automation. A correct mental model of the capabilities and limitations of the automation did not guarantee proper automation use. A novel conceptual, process-oriented model, titled PTS-a (predicting trust in and perceived safety of automation use), synthesizes the results of the data analysis. Informed by the cognition-leads-to-emotions approach, the model posits that trust as cognition precedes perceived safety as affective construct. Trust and perceived safety determine how human operators (mis-, dis-)use the automation. Future research: We recommend future research to perform experimental studies to identify cognitive-related thoughts and beliefs pertaining to trust in automation and perceived safety to contribute to the operationalization of these constructs, and unravel the nature of their relationship.

Quantifying perceived risk in driving: A Monte Carlo approach for obstacle avoidance

Objective This study aims to develop a model for quantifying perceived risk in obstacle avoidance, emphasizing how drivers’ perceived risk characteristics influence their driving decisions. The research addresses the lack of attention given to modeling risk from the perspective of drivers’ risk perceptions. Methods Monte Carlo methods are employed to account for the uncertainties and complexities of driving behavior, restoring the probabilistic nature of risk. The proposed method quantifies perceived risk by incorporating drivers’ fuzzy perceptions, enabling a quantitative evaluation during obstacle avoidance. A logit model is used to link perceived risk with driving decisions, identifying key factors influencing driver behavior in obstacle avoidance scenarios. Results Experimental data revealed significant variations in vehicle trajectories and speed distributions due to differences in drivers’ experience and proficiency. The perceived risk indicator (PRI) values for leftward bypasses were higher compared to rightward bypasses, and the receiver operating characteristic (ROC) curve confirmed the PRI’s strong predictive ability with an area under the curve (AUC) of 0.820. The logit model showed that both PRI and speed significantly influenced the probability of choosing a rightward bypass, achieving 90% accuracy. Building on the model, the study predicted and visualized the probability of vehicles turning right to avoid obstacles at different positions and speeds within 200 m of the obstacle. Conclusions The research offers a framework for traffic professionals to understand driver-perceived risk and decision-making mechanisms. This understanding is beneficial for improving traffic safety and highlights the importance of considering drivers’ risk perceptions in modeling driving behavior.

Development and Validation of a Novel Night-Time Hazard Visibility Test.

Night-time driving is dangerous, with increased crash rates, particularly involving vulnerable road users. A Night-Time Hazard Visibility Test (NHVT) was developed and validated by exploring the effects of refractive and cataract blur on performance. The NHVT comprised video clips of night-time roads from the driver's perspective, including different hazards (pedestrians, cyclists, and vehicles). Participants responded when they first recognized hazards requiring them to take evasive action to avoid a collision. In experiment 1, there were 16 young visually normal drivers (mean age = 22.3, standard deviation [SD] = 2.2 years) who completed 2 NHVT sets, viewed separately through best-correction and refractive blur (+1.00 diopter sphere [DS]). In experiment 2, a refined version of the NHVT was administered to an additional 16 young visually normal drivers (mean age = 21.1, SD = 1.2 years) with best-correction and cataract blur. The order of visual conditions and NHVT sets were counterbalanced. In experiment 1, refractive blur significantly reduced photopic visual acuity (VA) compared to best-corrected vision (+0.09 vs. -0.21 logMAR, P < 0.001) and delayed response times by 0.69 seconds (3.10 vs. 2.41 seconds, P < 0.001) compared to best-corrected vision. In experiment 2, cataract blur reduced VA compared to best-corrected vision (+0.03 vs. -0.17 logMAR, P < 0.001) and delayed response times by 0.63 seconds (2.92 vs. 2.29 seconds, P < 0.001). The NHVT was sensitive to refractive and cataract blur, providing preliminary support of its validity as a measure of night-time hazard visibility performance. The NHVT has potential as an off-road assessment of visibility for night driving and application for assessment of drivers with different refractive corrections and ocular diseases.

Simulation analysis of dual-end queuing ride-hailing system considering driver-side queue management

Ride-hailing services have transformed urban transportation through convenience yet introduced new complexities around efficiency and traffic management. This study investigates the dual-queuing problem in ride-hailing from the driver perspective using a multi-agent simulation approach. The focus is dissecting the dynamics between driver search times and passenger wait times, which critically influence operational efficiency especially during peak demand. Exploring these interactions aims to uncover insights that could improve service efficiency and customer satisfaction. Addressing such ride-hailing challenges is vital not just for individual providers but also for advancing sustainable mobility across rapidly growing metropolitan regions. Enhanced efficiency connects to broader urban development narratives around livability, accessibility, and responsible mobility ecosystems.

Labor issues from the perspective of drivers on the Uber and Lyft apps and the impact on riders who use wheelchairs

Wheelchair accessibility of transportation service hailed using Uber and Lyft is fraught with contention. In this research, I interview 12 drivers on the apps who work in Washington, DC to understand their experience and perception about issues surrounding service to wheelchair users. Some drivers experience transporting wheelchair users as markedly different from service to non-wheelchair users due to the uncompensated labor they perform when assisting wheelchair users and the additional time required. They perceive service decline by drivers to possibly stem from lack of compensation for their time and work. One solution to address the problem could be to use app-technology to keep a record of ride requests by wheelchair users who volunteer to disclose disability status and incentivize drivers for completed rides. The overarching purpose of the study is to create knowledge that can contribute to overcoming potential barriers to full inclusion of disabled riders in the app-hailed transportation.

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways.

While driving, drivers frequently adapt their driving behaviors according to their perception of the road's alignment features. However, traditional two-dimensional alignment methods lack the ability to capture these features from the driver's perspective. This study introduces a novel method for road alignment recognition, employing image recognition technology to extract alignment perspective features, namely alignment perspective skewness (APS) and alignment perspective kurtosis (APK), from in-real driving images. Subsequently, the K-means clustering algorithm is utilized for road segment classification based on APS and APK indicators. Various sliding step length for clustering are employed, with step length ranging from 100m to 400m. Furthermore, the accident rates for different segment clusters are analyzed to explore the relationship between alignment perspective features and traffic safety. A 150 km mountain road section of the Erlianhaote-Guangzhou freewway from Huaiji to Sihui is selected as a case study. The results demonstrate that using alignment perspective features as classification criteria produces favorable clustering outcomes, with superior clustering performance achieved using shorter segment lengths and fewer cluster centers. The road segment classification based on alignment perspective features reveals notable differences in accident rates across categories; while traditional two-dimensional parameters-based classification methods fail to capture these differences. The most significant differences in accident rates across categories are observed with segment length of 100m, with the significance gradually diminishing as segment length increases and disappearing entirely when the length exceeds 300m. These findings validate the reliability of using alignment perspective features (APS and APK) for road alignment classification and road safety analysis, providing valuable insights for road safety management.

A driver perspective-based investigation for lane line visibility of pavements on drivers’ lane utilization behaviors

There have been significant advances in vehicle safety and road construction in all over the world and driver misbehaviours are still shown as one of the most important reasons of traffic accidents. When the current traffic accidents are examined, the negative effect of lane line quality and level of visibility related on the accidents comes to the forefront in underdeveloped and developing countries. In this study, the effect of lane line visibility level on drivers' lane utilization was investigated in detail. For this aim, a total of 17 different points in Türkiye were selected and the lateral positions of the vehicles on the road surface at these points were determined with the help of the screen scaling technique. In order to determine the level of lane line quality for an expert group and driver perspective, a face-to-face survey was conducted. From the analysis results, the lane line quality was determined low in urban and intercity roads, and the average maximum evaluation score was determined as 4.7 and the lowest score was determined as 1.42 where the best line quality was 5. This result showed that the level of lane line quality had significant differences at different points. Although, it was observed that the lateral position distributions in the examined points fit the normal distribution, the distribution of both the right/left wheels and their gravity center skewed to the right or left and deviated from the ideal conditions on road surfaces. It showed that the vehicles do not center the lanes exactly, but usually move close to the right or left edge of the lane. This situation also clearly revealed that the lane utilization disciplines of drivers are quite weak with the effect of the low lane line quality on road surfaces.

Recognition of occluded pedestrians from the driver's perspective for extending sight distance and ensuring driving safety at signal-free intersections

Recognition of occluded pedestrians from the driver's perspective for extending sight distance and ensuring driving safety at signal-free intersections

어린이 보호구역 교통안전 시설물의 관한 게슈탈트 시지각 특성 연구

In this study, when looking at statistics on traffic accidents in child protection zones, children's traffic accidents in child protection zones have continued to increase and decrease irregularly. Against this background, to prevent continuous traffic accidents in child protection zones, we would like to examine four traffic safety facilities that provide safety and recognition to children, pedestrians and drivers from the perspective of perception during gestalt. Also, the shape and size contained within it. The facility is analyzed and evaluated by color, material environmental factors, and 8 types of crustal similarity, proximity, commonality, simplicity, closure, continuity, equivalence, shapes and backgrounds. Based on the previous analysis, the type of perception at Gestalt is the shape and size of the object. It can be seen that the characteristics perceived by color, arrangement, and environmental elements are different for each individual of the traffic safety facility, and the shape and size of each individual depending on the facility. It can be seen that it is necessary to propose whether it is suitable from the perspective of children, pedestrians, and drivers, such as colors, materials, arrangements, and environmental elements, and to manufacture and install them in child protection areas.

A matter of space and perspective – Cyclists’, car drivers’, and pedestrians’ assumptions about subjective safety in shared traffic situations

Subjective safety has been considered a key factor for a successful promotion of cycling. As of yet, subjective safety and the factors affecting it have been studied almost exclusively from the cyclists’ perspective. However, subjective safety is largely determined by the interaction of cyclists with other road users. We thus argue that it is crucial to assess the subjective safety different road user groups associate with shared road situations, because street designs that increase the subjective safety of one group may have negative impacts on the subjective safety of another group. For this purpose, we conducted a large-scale, web-based survey presenting computer-generated 2D images showing various traffic situations. The entire pool of images included 1,900 variations and combinations of road designs. About 21,500 individual participants provided about 460,000 estimates with regard to the safety they associated with travelling at the shown location from the perspective of cyclists, car drivers, or pedestrians. Our analysis with generalized mixed models focused on three base scenarios and the comparison of the different perspectives: Side streets were perceived as unsafe by both cyclists and car drivers. A prominent designation as a cycling boulevard had highly positive effects, especially for cyclists. On main streets, cyclists and car drivers rated mixed traffic without cycling infrastructure as very unsafe, and situations with cyclists travelling on protected bike lanes as very safe. Whereas car drivers rated all types of cycling lanes as safe, this did not generally apply to cyclists. In particular, narrow cycling lanes adjacent to parked cars felt unsafe for cyclists. We hypothesize that this discrepancy has a self-reinforcing mechanism: Research on risk-taking suggests that the low risk perception of car drivers leads to more risky behavior (e.g. overtaking cyclists with higher speed and less lateral clearance), which in turn decreases the subjective safety of cyclists. We found an inverted pattern for sidewalks, where cyclists felt mostly safe, and the more vulnerable pedestrians did not (especially if there was no clear indication of lanes for both groups). Taken together, our research sheds light on an as-of-yet rather under-researched issue: the perception of a traffic situation may vary significantly depending on the perspective and transportation mode of a road user. More specifically, our findings suggest that the subjective safety of vulnerable road users in a traffic situation can be negatively affected by the perception of this situation by the less vulnerable road users. We present recommendations about road designs that feel safe for all road user groups.

Assessment and optimization of tunnel lighting quality based on drivers' visual comfort: From methodology to application

Drivers' visual comfort is directly affected by tunnel lighting quality. Currently, many built tunnels have poor-quality lighting with varying degrees of visual interference, which may lead to visual discomfort and traffic accidents. To solve this problem, this study proposes a method to assess and optimize the tunnel lighting quality, aiming to evaluate the lighting quality from the perspective of drivers' visual comfort and improve the lighting effect in each lighting zone of the tunnel. First, the visual characteristics of drivers and quantitative relationship between visual comfort and tunnel lighting environment are derived through field tests and mathematical statistics. Second, the comfort range based on visual characteristic indicators (VCIs) is obtained via a comprehensive analysis of objective physiological responses and subjective questionnaire survey results of drivers, which is used as the comfort criteria to assess the tunnel lighting quality. Subsequently, the effects of luminance, luminance uniformity, and flicker frequency on drivers' visual comfort are considered, and a lighting optimization model based on the adaptive penalty function particle swarm optimization algorithm is established by combining comfort constraints and energy-saving objectives. Finally, driving simulation experiments are performed using virtual reality technology, which verify the effectiveness of the assessment and optimization methods. The results show that drivers' visual comfort in the tunnel threshold zone increases with an increase in the luminance reduction coefficient and decrease in the vehicle speed, and drivers' visual comfort in the tunnel interior zone increases with an increase in the road surface illuminance and visibility. The comfort range of the VCIs classify the tunnel lighting quality into four evaluation levels. Therefore, the proposed method can accurately and quantitatively assess the comfort of the tunnel lighting environment, improving drivers' visual comfort in the tunnel by 48.08 %, while saving 12.03 % of energy.

Acceptance of e-vehicles for last-mile parcel delivery from the perspective of drivers: a study in Turkiye

Acceptance of e-vehicles for last-mile parcel delivery from the perspective of drivers: a study in Turkiye

Development of a Road Protection Value Model as an Indicator for National Road Safety Performance Assessment from the Perspective of Drivers of Four or More Wheeled Motorized Vehicles

This paper introduces the model of Star Rating Scores (SRS) or Road Protector Scores (RPS) for Indonesian National Roads from the perspective of motorized vehicle drivers with four or more wheels, which are explored from the characteristics of traffic accidents along Indonesia's national roads. This SRS model takes into account 2 different main parameters and 4 main parameters that are the same as the main parameters of the SRS International Road Assessment Program (iRAP) and a total of 51 road attributes. The two main parameters that differ from the SRS iRAP model are the parameters for front-rear crashes and fore-side crashes when turning around. While the 4 parameters are the same as front-side collision accidents at property access, single accidents leaving the road body, front-to-front collision accidents, and accidents at intersections. In the early stages, the National Road SRS model was designed using 51 road attributes. After analysis using the Importance and Performance Analysis (IPA) method, 43 road attributes were successfully formulated for the SRS National Road model, consisting of 30 likelihood factor attributes, 10 severity factor attributes, 2 external traffic influence factor attributes, and 1 factor attribute operational speed. In addition, it is proven that the SRS National Road model is significantly different from the SRS iRAP model. The three main parameters of the National Road SRS model, namely the front-rear hit accident parameter, the front-side hit accident parameter when turning around, and the front-side hit accident parameter at property access are significantly different from the parameters of the SRS iRAP model.

Promoting trust in HAVs of following manual drivers through implicit and explicit communication during minimal risk maneuvers

The successful integration of highly automated vehicles (HAV) in future mixed traffic environments will depend, among other things, on their seamless, safe, and accepted interaction with other road users. Therefore, appropriate combination of light signals, as external human-machine interface (eHMI), and driving behavior, as dynamic human-machine interface (dHMI), is required consistently in order to develop trust of following manual drivers in HAVs. Especially, in borderline traffic scenarios where HAVs are confronted with challenges, such as loss of connectivity, so-called minimal risk maneuvers (MRMs) are performed abruptly. Here, understanding communication via eHMI and dHMI is crucial for road safety, as drivers need to prepare for maneuvers themselves. Therefore, two consecutive, explorative online video studies were conducted. Firstly, the appropriate braking dynamics for an MRM were evaluated. Secondly, insights into the eHMI communication strategy of an HAV during an MRM were gained. The overall aim of this work is to present strategies for implicit and explicit communication channels of an HAV in order to promote learned trust during MRMs from the perspective of drivers who follow them. The results show that adding novel eHMI designs (e.g., warning sign, 360° LED light-band) to conventional light signals positively affects the user experience in a first contact interaction. The findings could have a positive impact on the development of trust in HAVs. In conclusion, specific eHMI communication strategies can be highly supportive for following manual drivers in MRM scenarios, which may lead to legislative considerations in the future.

Design of Real-time Pedestrian Trajectory Prediction System based on Jetson Xavier

This paper presents a vehicle-mounted real-time pedestrian trajectory prediction system based on the embedded device Jetson Xavier. It achieves low-cost real-time pedestrian trajectory prediction using only the front camera of the vehicle. Firstly, pedestrian detection and tracking are implemented based on YoLoV7, while also estimating pedestrian poses and optical flow to provide multiple information sequences for the trajectory prediction network. Secondly, the pedestrian trajectory algorithm from a driver's perspective is studied, and a trajectory prediction algorithm that considers pedestrian pose, optical flow, and trajectory information is proposed. A novel multi-information fusion network is designed to better integrate multiple features. The algorithm is tested on the JAAD and PIE datasets, and the displacement errors are reduced by 6.35% and 3.28%, respectively, compared to BiTraP. Finally, the algorithm is ported to the embedded device Xavier and installed on a simulated vehicle for testing. By predicting pedestrian future trajectories based on pedestrian detection, collisions can be avoided in advance, improving the safety of autonomous driving. The proposed system has significant practical value.

Spatiotemporal evolution and driving factors of the coupling coordination between county land urbanization and grain production: the case of Jiangsu province, China

How to ensure a coordinated development between land urbanization and grain production has been a key issue that needs to be urgently addressed to achieve sustainable development in China. Taking Jiangsu province as an example, this paper measures the coupling coordination degree (CCD) between county land urbanization and grain production from 2010 to 2020 based on the coupling coordination degree model (CCDM). In addition, the exploratory spatial data analysis method and the space Durbin model are combined to explore the spatial correlation and influencing factors of the CCD between land urbanization and grain production. The main conclusions are as follows: (1) From a temporal perspective, the CCD between county land urbanization and grain production in Jiangsu is dominated by basically coordinated, with an overall stable rising trend and a distribution pattern of Northern Jiangsu &amp;gt; Central Jiangsu &amp;gt; Southern Jiangsu. (2) From the perspective of spatial distribution, the CCD between the two is dominated by basically coordinated in the Southern, Central and Northern Jiangsu regions. The spatial clustering characteristics are significant, and the distribution of counties with basically coordinated shows concentrated and contiguous characteristics. (3) From the perspective of spatial correlation, the CCD between the two shows a low level of positive spatial autocorrelation. The state of agglomeration is significant in Northern Jiangsu, while spatial agglomeration is sporadic in Southern Jiangsu and insignificant in Central Jiangsu. (4) The factors affecting the CCD between county land urbanization and grain production in Jiangsu province are determined by many factors together. Based on a driver perspective, Per capita GDP and chemical fertilizer application intensity have a negative effect on it. Highway network density and mobile internet penetration rate have a positive effect on it. Population density, advanced industrial structure, per capita grain planting area and agro-industrial agglomeration are not significant. This study offers useful insights for promoting the coupled and coordinated development of county urbanization and grain production in China.

A Project Report on Optimization of an Off Road Vehicle Ergonomics

Abstract: This paper contain the behaviour of A BAJA vehicle chassis which undergo the various load test like’’Front impact test, Side impact test, Rear impact test, Roll over impact”all the analysis of the test has been performed with the help of ANSYS WORKBENCH 18.1,where maximum deformation ,stress and strain calculated over duration of the particular impact.For the theoretical calculation we have use the INELASTIC COLLISION THEORY with this we have applied a force at a point .The boundary conditions and loading use different methodology. Study of ergonomics which help to give the ergonomically safer design according to the driver perspective. Keywords: Front impact test, Side impact test, Rear impact test, Roll over impact, Ansys Workbench ,ergonomic study

Evaluation of the communication means of lateral driving dynamics at motorway slip roads

Abstract Modelling the behaviour of automated vehicles requires an understanding of the acceptance towards certain behaviours by the human cooperation partners. This work addresses the evaluation of two communication means on the motorway slip road from the perspective of drivers in the target lane. In a video study (N = 68) two implicit communication means (position and duration of lane change) were investigated. The cooperation partner is either a manual vehicle or a car labelled as automated by a status eHMI. The results show no significant differences in the cooperation and criticality ratings between non-automated or automated cooperation partners. A slow lane change is rated as less critical and more cooperative. A non-linear relationship emerges for the position of the change. A change in the middle of the slip road is rated most cooperative and least critical.

How to Design the eHMI of AVs for Urgent Warning to Other Drivers with Limited Visibility?

The importance of an external interaction interface (eHMI) has grown in recent years. Most eHMI concepts focus on communicating autonomous vehicle (AV)'s yielding intention to pedestrians at a crossing. However, according to previous studies, pedestrians at a crossing rely mainly on the vehicle's movement information (implicit communication) rather than information from eHMIs (explicit communication). This paper has the purpose of proposing a specific use case in which the eHMI of future AVs could play an indispensable role in the safety of other road users (ORUs). Often VRUs cannot see the traffic flow due to a series of parked or stopped vehicles, which is a frequent cause of fatal traffic collision accidents. Drivers may also not be able to see approaching pedestrians or other cars from the side for the same reason. In this paper, the impact of an eHMI is tested from the perspective of drivers with limited visibility when a jaywalker steps into the road. A combination of colors, shapes, and information levels is presented on an eHMI. We show that our proposed eHMI design, in the deadlock scenario of a jaywalker and a driver who both lack visibility, significantly reduced the reaction time compared to when there was no eHMI. In the experiment, the willingness to stop, varying from 0 to 5, was measured from the driver's perspective. The results showed that most users felt uncertainty and did not move quickly when seeing the light band color alone. Textual information on the eHMI was significantly more effective in providing an urgent warning of this specific scenario than vertical and horizontal light bands with color without text. In addition, red color, blinking rapidly above 3 Hz, and egocentric messages were also necessary to reduce the PRT(perception response time). By using text-added eHMI (Vertical + Text eHMI), the mean time to achieve a score above 4 for willingness to stop was 2.113 s faster than when there was no eHMI. It was 2.571 s faster than the time until the slider of the participants reached the maximum level for willingness to stop. This is a meaningful amount of difference when considering a PRT of 2.5 s, which is the Korean road design standard. As eHMIs tend to be applied for smarter mobility, it is expected that they will be more effective in preventing accidents if the eHMI is standardized in autonomous driving level 2 to 3 vehicles driven by humans before fully autonomous driving becomes a reality.

An Empirical Investigation on the Acceptance of Autonomous Vehicles: Perspective of Drivers’ Self–AV Bias

In autonomous vehicles (AVs), especially in fully AVs, “drivers” perceive vehicle operation from a passenger’s perspective. This study focuses on the perspective change of drivers especially in fully AVs. To investigate the effect of change in perspective on drivers’ assessment of AVs, this study conducted a driving simulator experiment and a survey using different samples. The driving simulator experiment was a within-subjects design including 40 participants. The experimental results indicated that although AVs drive exactly the same as the drivers, 85% of these drivers had different assessments for AVs compared to driving themselves (self-AV bias). Among these biased drivers, 80% changed the direction of their assessments (e.g., satisfied with their own driving behaviors but dissatisfied with the same behaviors from the AVs). Additionally, self-AV bias increased with the level of self-evaluation of their own driving skills. The higher the level of self-evaluation, the higher the optimism bias (drivers think they drive better than AVs) of drivers. Thereafter, to show whether and how self-AV bias affects drivers’ intuitive acceptance of AVs, a survey was conducted, which included 381 valid questionnaires. The survey results showed that self-AV bias was a critical factor promoting perceived usefulness of AVs; particularly, highly self-AV-biased drivers responded more to the perceived usefulness of AVs. Moreover, drivers who could accept more risky driving behaviors of AVs compared to themselves also perceived AVs to be more useful. The findings from this study provide insights for understanding drivers’ assessment and acceptance of AVs’ driving behaviors.