Driver Behavior Research Papers - Academia.edu (original) (raw)

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- Engineering, Automated Guided Vehicles, Capacity analysis, Driver Behavior

The detection of fatigue in drivers has been studied by different researchers and academics. Through this review, it was intended to analyze and summarize the studies that investigate the detection of fatigue in drivers and its effects on the performance of the driving task, as well as the consequent effect of drowsiness and the persistence of drivers in continuing to drive tired. This review was based on relevant articles published in Scopus. The studies included in this review were carried out with humans at the controls of vehicles, and the fatigue of drivers was evaluated. Eight articles were included in the systematic review.
Some studies were carried out in a real road driving context and the most used methods to assess fatigue were EEG, ECG and sEMG.
Rest and recovery breaks had some positive effects, particularly on the perception of discomfort and sleepiness. The characteristics of the participants and the duration of the experiments seem to be the variable that most influences the results. Future research should focus on improving experimental protocols and instrumentation, so that the results represent the real conditions of performance of the driving task, trying to get drivers to take breaks while driving vehicles, when driving for long and uninterrupted periods of time.
Relevance for the industry: the introduction of non-invasive data collection equipment that returns to the user/driver of the vehicle the results they need to remain alert, while performing the driving task, seems to be effective in producing the alert, but inefficient in order to the driver takes a break during his journey.
The results will be useful to identify the need for future research, which will result in a decrease in the number of road and work accidents, with victims, leading to the adoption of good practices in the measures to be adopted to improve road safety, with breaks during driving will provide an improvement in the state of alertness essential for the performance of the driving task.
Keywords — Driver, Fatigue, Road Safety, Sleepiness/drowsiness.

This study explored the potential uses of feedback systems in the trucking industry as a means of improving safety. Since truck drivers spend a majority of their working time alone and do not interact with peers, it may be possible to use data gathered by in-vehicle technology to provide feedback to drivers about their driving behavior. The purpose of this study was to examine truck driversÕ attitudes toward using in-vehicle technology to provide feedback for enhancing driving safety and to understand the best ways of providing feedback to truck drivers. Nine focus groups were conducted, with a total of 66 participants, to collect qualitative data on attitudes toward technology and feedback. The focus group results were used to develop a questionnaire. Survey data were then collected from 198 long-haul truck drivers to provide quantitative information. Truck drivers reported that they would like to receive more feedback and that positive feedback was preferred over negative feedback. Feedback from truck driversÕ supervisors or managers was more desired than feedback from technology. However, most drivers were willing to accept feedback by technology if the program was designed properly. The truck drivers expressed no strong preference regarding the best form of feedback by technology on driving performance (i.e., modality, frequency and timing). Therefore it is important for a program which uses technology for providing feedback to be adaptable to different driversÕ preferences.

- by Jamie McDevitt
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- Psychology, Working Time, Negative Feedback, Focus Group

Problem: Age and gender are frequently controlled for in studies of driving performance, but the effects of time of day or circadian cycles on performance are often not considered. Previous research on time of day effects of simulated driving is contradictory and provides little guidance for understanding the impact of these variables on results. Methods: Using driving simulator data from 79 subjects ages 18 to 65, this paper focuses on the impact of age, gender, and time of day on the simulated driving performance of subjects who self-selected the time of participation. Results: Time of day effects were consistently evident for drivers' speed overall and across different simulated environments. Drivers in the late afternoon period consistently drove significantly slower than drivers in other time periods. Age and gender affected speed such that women and those participants 50 and older tended to drive more slowly. Time of day also had an effect on reaction time and on speed variability measures. Gender did not have significant effects on reaction time or variability measures, but age effects were present. Summary: Taken together, the results suggest that time of day effects should be considered as part of simulated driving performance, and that interactions between time of day and other variables, notably age, should be controlled for as part of future research. Impact on industry: Implications of these findings on current efforts for older driver testing are discussed. also been found to affect driver behavior. Given the range of variables that can influence the complex behaviors around driving, it is not surprising that no documented studies have been identified that begin to quantify any type of "normal" driver in either simulation or on-road evaluation.

- by Joseph Coughlin
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- Psychology, Adolescent, TIME, Safety

Objective: This study investigated the effect of a nondriving cognitively loading task on the relationship between drivers' endogenous and exogenous control of attention. Background: Previous studies have shown that cognitive load leads to a withdrawal of attention from the forward scene and a narrowed field of view, which impairs hazard detection. Method: Posner's cue-target paradigm was modified to study how endogenous and exogenous cues interact with cognitive load to influence drivers' attention in a complex dynamic situation. In a driving simulator, pedestrian crossing signs that predicted the spatial location of pedestrians acted as endogenous cues. To impose cognitive load on drivers, we had them perform an auditory task that simulated the demands of emerging in-vehicle technology. Irrelevant exogenous cues were added to half of the experimental drives by including scene clutter. Results: The validity of endogenous cues influenced how drivers scanned for pedestrian targets. Cognitive load delayed drivers' responses, and scene clutter reduced drivers' fixation durations to pedestrians. Cognitive load diminished the influence of exogenous cues to attract attention to irrelevant areas, and drivers were more affected by scene clutter when the endogenous cues were invalid. Conclusion: Cognitive load suppresses interference from irrelevant exogenous cues and delays endogenous orienting of attention in driving. Application: The complexity of everyday tasks, such as driving, is better captured experimentally in paradigms that represent the interactive nature of attention and processing load.

- by Linda Boyle
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- Psychology, Cognitive Science, Human Factors, Cognition

Several intelligent transportation systems focus on studying the various driver behaviors for numerous objectives. This includes the ability to analyze driver actions, sensitivity, distraction, and response time. As the data collection is one of the major concerns for learning and validating different driving situations, we present a driver behavior switching model validated by a low-cost data collection solution using smartphones. The proposed model is validated using a real dataset to predict the driver behavior in short duration periods. A literature survey on motion detection (specifically driving behavior detection using smartphones) is presented. Multiple Markov Switching Variable Auto-Regression (MSVAR) models are implemented to achieve a sophisticated fitting with the collected driver behavior data. This yields more accurate predictions not only for driver behavior but also for the entire driving situation. The performance of the presented models together with a suitable mod...

- by Mohamed A Khamis
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- Computer Science, Artificial Intelligence, Machine Learning, Driver Behavior

Roadside Animal Detection Systems (RADS) aim to reduce the frequency of wildlife-vehicle collisions. Unlike fencing and wildlife passages, RADS do not attempt to keep animals off the road; rather, they attempt to modify driver behavior by detecting animals near the road and warning drivers with flashing signs. A RADS was installed in Big Cypress National Park (Florida, USA) in 2012 in response to an increased number of Florida panther mortalities. To assess driver response, we measured the speed of individual cars on the road when the RADS was active (flashing) and inactive (not flashing) during the tourist season (November–March) and the off-season (April–October), which vary dramatically in traffic volume. We also used track beds and camera traps to assess whether roadside activity of large mammal species varied between seasons. In the tourist season, the activation of the RADS caused a significant reduction in vehicle speed. However, this effect was not observed in the off-season. Track and camera data showed that the tourist season coincided with peak periods of activity for several large mammals of conservation interest. Drivers in the tourist season generally drove faster than those in the off-season, so a reduction in speed in response to the RADS is more beneficial in the tourist season. Because traffic volume and roadside activity of several species of conservation interest both peak during the tourist season, our study indicates that the RADS has the potential to reduce the number of accidents during this period of heightened risk.

- by Molly Grace and +1
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- Human Behavioral Ecology, Conservation Biology, Road Ecology, Driver Behavior

This study aims to examines the contribution of personality and driver behavior on road accident among bus driver in Indonesia. The study adopts a survey method to elicit responses from a sample of 400 bus driver who were selected as a Respondent. The Data collecting using the Big Five Personality questionnaires, Driver Behavior questionnaires and Road Accident Inventory. The data collected were analysis confirmatory factor analysis and Structural Equation Model (SEM). The SEM results indicated (a) Bus Driver behavior is violent and error have contribution on road accident in Indonesia 8 (b) the big personality factor had significant influences on the latent mediator, path coefficients from-0,50 (conscientiousness) and-0.74 (openness) to-0.75 (ektraversion). As, predicted the effect of conscientiousness, openness and ektraversion were negative and the influences of Neuroticism and agreeableness were positive (path coefficient = 0.35 and 0.81). As expected by the laten mediator variable for road accident risk was relatively strongly and significantly predicted by the latent mediator variable (path coefficient = 0.13). The five personality factor accounted the 38% of the unique in aberrant driving behavior. The driving behavior have direct influences 55% of the variances in road accident among bus driver in Indonesia. The factor of driver behavior error and lapses have strong affect to road accident The implication this study show that there is need for an intervention program in order to reduce the prevalence of accident involvement due to personality factors. The latter should be focused on managing driving behavior.

- by FIKRI IDRIS
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- Social Psychology, Personality, Driver Behavior, Road accident

The use of driver behavior has been considered a complex way to solve road safety complications. Car drivers are usually involved in various risky driving factors which lead to accidents where people are fatally or seriously injured. The present study aims to dissect and rank the significant driver behavior factors related to road safety by applying an integrated multi-criteria decision-making (MCDM) model, which is structured as a hierarchy with at least one 5 5 (or bigger) pairwise comparison matrix (PCM). A real-world, complex decision-making problem was selected to evaluate the possible application of the proposed model (driver behavior preferences related to road safety problems). The application of the analytic hierarchy process (AHP) alone, by precluding layman participants, might cause a loss of reliable information in the case of the decision-making systems with big PCMs. Evading this tricky issue, we used the Best Worst Method (BWM) to make the layman's evaluator task easier and timesaving. Therefore, the AHP-BWM model was found to be a suitable integration to evaluate risky driver behavior factors within a designed three-level hierarchical structure. The model results found the most significant driver behavior factors that influence road safety for each level, based on evaluator responses on the driver behavior questionnaire (DBQ). Moreover, the output vector of weights in the integrated model is more consistent, with results for 5 5 PCMs or bigger. The proposed AHP-BWM model can be used for PCMs with scientific data organized by traditional means.

- by Sarbast Moslem
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- Decision Making, Road safety, Behavioral Decision Making, Risky Driving Behaviors

In this chapter, we present data collection activities and preliminary research findings from the real-world database collected with ''UYANIK,'' a passenger car instrumented with several sensors, CAN-Bus data logger, cameras, microphones, data acquisitions systems, computers, and support systems. Within the shared frameworks of Drive-Safe Consortium (Turkey) and the NEDO (Japan) International Collaborative Research on Driving Behavior Signal Processing, close to 16 TB of driver behavior, vehicular, and road data have been collected from more than 100 drivers on a 25 km route consisting of both city roads and The Trans-European Motorway (TEM) in Istanbul, Turkey. Challenge of collecting data in a metropolis with around 12 million people and famous with extremely limited infrastructure yet driving behavior defying all rules and regulations bordering madness could not be ''painless.'' Both the experience gained and the preliminary results from still on-going studies using the database are very encouraging and give comfort.

- by Hakan Erdogan and +2
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- Signal Processing, Data Collection, Driver Behavior, Data Logger

This paper presents the results of an online survey of licensed driver comprehension of the right-turn signal displays with a focus on the flashing yellow arrow (FYA) and also including the circular green and red and red arrow. Recruitment postcards were mailed to a random sample of 9,872 residents in Oregon. The online survey yielded 399 responses. The open-ended responses were coded for comprehension and analyzed. The results suggest that FYA for right turns is well understood by Oregon drivers despite its current novelty (only two locations at the time of the research). Importantly, survey respondents were more likely to recognize the yielding requirement of the permissive movement and associate the yielding with pedestrians with the FYA over the circular green (CG) display. The research also confirmed that the expected driver response to the red arrow display for right turns is not well understood (only 52% of the respondents correctly stated the expected driver response). Binary logistic regression modeling revealed that the driver's age and their educational level were significant factors in comprehension.

- by Hisham Jashami
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- Statistics, Survey Research, Traffic Engineering, Traffic Safety

The focus of this study is roadway safety in American Indian reservations. We provide new sources of data and policy- relevant findings to address the unusually high rates of roadway fatalities and injuries among American Indians. Qualitative methods were used to generate and analyze data from people with the most direct knowledge of and responsibility for reservation roadway safety. Four case studies were conducted in partnership with the tribal governments of the Red Lake, Fond du Lac, Leech Lake, and Mille Lacs reservations; these data sources include fieldwork (90 days), interviews (n=102), focus groups (n=8), and short surveys (n=220). These data are triangulated with data from FHWA’s 2016 nationwide survey of tribes and states (n=196). Key findings from this extensive data analysis are: 1. Pedestrian safety is a critical, yet under-recognized issue on reservations. This is unequivocal across all data sources and differentiates reservations from rural areas in general. 2. Reservation road engineering and repair are very high priorities according to both tribe and state governments. 3. Reckless driving is a multi-faceted concern, including not only impaired driving but also cell phone distraction and speeding. 4. Education and enforcement to increase seatbelt and car seat use are named as high priorities in the national survey. 5. Tribes need better cooperation with local, state, and federal agencies. Priorities include addressing data quality and sharing issues better inter-jurisdictional cooperation for infrastructure and enforcement. The study concludes with recommendations to improve roadway safety in reservations and for further research.

Road safety is a global issue; as well same issue is prevailing in Sri Lankan society too. Ignorance of road sign is a one of major issue causing for road crashes. Ignorance of road sign occurs due to lack of awareness of drivers on signs and communication errors of road signs. In this research, it describe about road sign ignorance of Sri Lankan drivers.
Ignorance of road signs caused due to lack of awareness and communication issues of drivers. This can be change with raising drivers’ awareness, behavior, attitude and perception on road sign. As a media and communication student this research is important to study of driving lifestyle, behavior, communication disturbances, noises and issues in a society.

- by Senith Gajanayake
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- Road safety, Driver Behavior

Collisions with other vehicles represent the biggest threat to riders of powered-two-wheeler (PTW), and while emergency braking is the evasive manoeuvre most frequently required in PTW riding, many riders fail to perform it adequately due to constraints on response time precipitated by failures of perception, cognition and control actions. Effective rider training methods are necessary for the development of braking proficiency in response to emergency situations. This study proposes a testing and training paradigm that exploits a closer similitude with the real-world scenario by maintaining the natural coupling of action (vehicle manoeuvring) and perception (higher order skill) that underlies any coordinated response to an emergency event. The aim of this study was to understand the behaviour of the riders in the execution of emergency braking coupled with visual perception of vehicle motion as a response to an imminent collision and determine parameters that can be used to identify differences in skill level. Participants performed emergency braking trials in a realistic and controlled scenario using a mock-up of an intersection conflict with a real car initiating a left turn manoeuvre across the path of a PTW approaching from the opposite direction (Left Turn Across Path/Opposite Directions). Analysis of the deceleration patterns recorded during 12 trials per participant revealed that performance of braking in response to an unpredicted moving hazard differs from that in a planned self-timed hard braking. In addition, our results indicate that PTW rider performance may be assessed in a reliable and objective way using the combination of vehicle kinematics and human performance measures. The study identified four categories of riders classified by their level skills. Finally, an important finding was the lack of correlation of both years of riding experience and self-assessed overall riding skill with an objective measure of emergency braking performance such as effective deceleration. The results of this study will support a new training approach and provide insights for future design of active safety systems.

- by Pedro Huertas Leyva and +1
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- Perception-Action, Road safety, Traffic engineering , Transportation engineering, Driver Behavior, Motorcycle Safety

Traffic control (TC) is a challenging problem in today’s modern society. This is due to several factors including the huge number of vehicles, the high dynamics of the system, and the nonlinear behavior exhibited by the different components of the system. Poor traffic management inflicts considerable cost due to the high rate of accidents, time losses, and negative impact on the economy as well as the environment. In this paper, we develop a traffic control system based on the Bayesian interpretation of probability that is adaptive to the high dynamics and non-stationarity of the road network. In order to simulate the traffic non-stationarity, we extend the Green Light District (GLD) vehicle traffic simulator. The change in road conditions is modeled by varying vehicle spawning probability distributions. We also implement the acceleration and lane changing models in GLD based on the Intelligent Driver Model (IDM).
Index Terms—reinforcement learning, traffic control, traffic simulation, multi agent systems, driver behavior

- by Walid Gomaa
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- Reinforcement Learning, Machine Learning, Multiagent Systems, Traffic Simulation

The two-fluid model for vehicular traffic flow explains the traffic on arterials as a mix of stopped and running vehicles. It describes the relationship between the vehicles' running speed and the fraction of running vehicles. The two parameters of the model essentially represent 'free flow' travel time and level of interaction among vehicles, and may be used to evaluate urban roadway networks and urban corridors with partially limited access. These parameters are influenced by not only the roadway characteristics but also by behavioral aspects of driver population, e.g., aggressiveness. Two-fluid models are estimated for eight arterial corridors in Orlando, FL for this study. The parameters of the two-fluid model were used to evaluate corridor level operations and the correlations of these parameters' with rates of crashes having different types/severity. Significant correlations were found between two-fluid parameters and rear-end and angle crash rates. Rate of severe crashes was also found to be significantly correlated with the model parameter signifying inter-vehicle interactions. While there is need for further analysis, the findings suggest that the two-fluid model parameters may have potential as surrogate measures for traffic safety on urban arterial streets.

- by Vinayak Dixit
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- Psychology, Safety, Cities, Traffic Safety

Despite research findings indicating attitudinal differences among drivers with and without a history of driving under the influence (DUI) offenses, there are no well-established instruments specifically designed to clinically assess drinking and driving attitudes and behaviors among adults. The purpose of this current series of three studies was to investigate the psychometric properties of the Behaviors & Attitudes Drinking & Driving Scale (BADDS). The BADDS was developed in previous studies by the authors and assesses respondents' rationalizations for drinking and driving, likelihood of future drinking and driving, drinking and driving behaviors, and riding with a drinking driver behavior in the previous month. Study 1 (N = 179) and Study 2 (N = 338) assessed college participants, while Study 3 gathered data from adult DUI offenders (N = 160) and non-DUI offenders (N = 166). Results indicate good to excellent test-retest reliability and internal consistency estimates for BADDS scale scores. Support for the construct validity as well as concurrent and predictive criterion validity of BADDS scores was also demonstrated. Potential applications for the measure, as well as need for future research are described.

- by Jeremy Jewell
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- Psychology, Psychometrics, Behavior, Risk Taking

—In this paper, we propose an approach to understand the driver behavior using smartphone sensors. The aim for analyzing the sensory data acquired using a smartphone is to design a car-independent system which does not need vehicle mounted sensors measuring turn rates, gas consumption or tire pressure. The sensory data utilized in this paper includes the accelerometer, gyroscope and the magnetometer. Using these sensors we obtain position, speed, acceleration, deceleration and deflection angle sensory information and estimate commuting safety by statistically analyzing driver behavior. In contrast to state of the art, this work uses no external sensors, resulting in a cost efficient, simplistic and user-friendly system.

- by Semiha Makinist
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- Driver Behavior, Gyroscope, Accelerometer, Magnetometer

With research revealing low road safety campaign efficacy and links between reckless driving behaviors and crash frequency, further investigation into the foundations and composition of driver education and training is required. Through two studies, the current research aimed to develop a measure that utilized the principles of Kelly’s (1955) personal construct theory to a) elicit constructs, or construals, specific to selected elements of reckless driving behaviors, b) pilot a method in which the elicited constructs could be measured by asking participants to choose those they deemed most important, c) group participants based on their constructs, and d) assess between-group differences in self-reported reckless driving behavior. Results suggest that drivers can be categorized based on the constructs they use, and that rates of self-reported past engagement in reckless driving behavior, and willingness to do so in the future, vary systematically between these construal-based driver categories. Continuing research is required to develop and test applications of these findings.

- by Brenton McNally
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- Psychology, Applied Psychology, Social Psychology, Health Psychology

When Elaine Herzberg was killed while crossing a road with her bicycle in Tempe, Arizona, confidence in autonomous vehicle technology was at an all-time high. In their accident report, the National Transportation Safety Board (NTSB) said that the vehicle in autonomous mode had failed to identify Herzberg until 1.2 seconds before impact. NTSB also said the system design did not include consideration for jaywalking pedestrians [1]. The accident created an uproar among the public and made the AV makers rethink testing beta-software on an actual road. Fast forward to 2021; there are announcements about deploying fully autonomous driving systems from big tech and car manufacturers. There is no government regulation or any other regulatory body to verify and validate the safety of these technologies. Since a market launch without safety assurance would not be acceptable by society or lawmakers, much time and resources have been invested into AV's safety assessment in recent years. There are several motivations behind the introduction of AVs, including road safety, driving comfort, energy efficiency, and broader mobility access [2]. According to the National Highway Traffic Safety Administration (NHTSA) report, 94% of serious vehicle crashes in the US are caused by human factors [3]. AVs promise to significantly reduce this public health crisis by removing many of the mistakes human drivers recurrently make. However, many challenges are creating bottlenecks, including the AV's perception system's performance, safety validation, legal and ethical issues, human-machine interaction, etc. Between September 2014 and January 2017, 11 suppliers and manufacturers reported 26 crashes while testing self-driving technology on public roads in California [4]. Before AVs can be deployed at scale, traffic safety issues related to automation need to be adequately addressed to avoid unacceptable situations like the one that happened in Arizona. The Society of Automotive Engineers (SAE) defines six levels of driving automation ranging from level 0 (fully manual) to level 5 (fully autonomous) [5]. "Driving automation" refers to both Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS). ADAS encompasses features such as cruise control, adaptive cruise control. These systems support human drivers and enhance safety. Next-generation ADAS (traffic jam chauffeur, automated valet parking) and ADS may ultimately be able to operate a vehicle without human intervention. SAE classified ADAS features as level 0-2 and ADS as level 3-5. Verified testing methods accepted by all stakeholders for ADAS are already in place. The safety validation of next-generation ADAS to ADS (SAE level 3-5) in complex environments calls for newer approaches because of increased Operational Design Domain (ODD) 1 and less scope for human intervention. Due to the high degree of realism required for the measurement, conducting tests in the real road with other traffic users is the highest fidelity form of testing. However, testing AVs' response in unsafe situations in the real world is not feasible without placing the other road users, such as other human-driven vehicles, bicyclists, pedestrians, in danger. Moreover, these tests take a considerable amount of time before achieving a statistical conclusion regarding safety. Repeatability of the tests is also an issue. These factors make depending solely on real-world testing infeasible. Virtual testing can complement this real-world testing. Virtual testing has previously been used to verify and validate SAE level 0-2, and currently, companies like Waymo, Zoox, and Aurora are using virtual environments to train and test vehicle automation of SAE level 4-5. Waymo is using their virtual environment CarCraft to simulate 25000 AVs every day to drive 8 million miles in the virtual world [6]. Scenario-based testing is a promising method where individual traffic situations are tested using virtual simulation. These tests are repeatable, safe, and can be done in parallel, reducing the amount of time required for testing. Domain experts usually handcraft these scenarios to explore the underlying system's vulnerabilities. However, handcrafted critical scenarios from the domain experts suffer from limited variation. It only accounts for known-safe and known-unsafe situations and does not handle unknown-unsafe situations. State-of-the-art scenario-based validation focuses mainly on the variation of the static part of the scenarios, namely the environment, infrastructure, road network. These variations would have been sufficient for the previous generation driver autonomy features (e.g., automatic braking, lane following) because of limited ODD and scope for human intervention during critical situations. But newer technologies up to fully autonomous driving require the vehicle to perceive its surroundings with dynamic traffic participants (other human-driven vehicles, pedestrians, cyclists) and take decisions appropriately, with limited to no human intervention. To ensure the safety and appropriateness of these decisions, high/full autonomous driving systems need to be tested with a wide variety of combinations of the dynamic elements.

- by Abdul Jawad
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- Software Testing, Autonomous Vehicles, Driver Behavior

Objective The objective of this research was to evaluate the immediate impact of the demerit points system on speeding behavior of drivers in Al Ain. Al Ain is the fourth largest city in the United Arab Emirates, located about 120 Km from Dubai. Methods The spot speed data of randomly selected vehicles using speed guns was collected from three major arterial urban roads.The data was collected three months before and three months after the implementation of the demerit points system. The free flow conditions were considered during the data collection. The data was analyzed using SPSS program. Results and Conclusions The results revealed that the demerit points system has statistically no significant impact on the speeding behavior of drivers in Al Ain. One of the plausible reasons for insignificance affect of the demerit point system could be the lack of effective traffic monitoring system. This study recommends that to influence the drivers’ behavior an effective traffic monitoring system should be provided to achieve the desired outcomes of introducing tougher laws such as demerit point system. The study also recommends to collect more data to investigate the changes in the speeding behavior of drivers.

- by arif mehmood
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- Road safety, United Arab Emirates, Data Collection, European Transport Policy

Grab is one of the Transport Network Vehicle Service (TNVS) in the Philippines. GrabCar is one of services that Grab provides. GrabCar driving is one of the transportation services in the Philippines. The study focuses on the advantages... more

- by Emem Dioso
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- Case Study Research, Case Study, Driver Behavior

This paper supplies a roadmap on how a researcher can effectively perform real vehicular experiments oriented to high-speed driving research. It provides detailed guidelines for constructing versatile low-cost instrumentation suitable to be fitted on race cars. The custom-built equipment, consisting of wheel-speed sensors, steering angle-torque sensors, electronic boards, etc., is thoroughly described. Furthermore, this paper depicts the required processing from raw measurements to user-friendly data suitable for driver behavior studies. As an illustration, a case study on driving behavior analysis is presented, during the execution of high-speed circular maneuvers. The recorded data showed markedly different driving behaviors between expert and novice drivers. The mechanical designs and the open-source-based software are freely available online.

- by David Abbink
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- Computer Vision, Mechanism Design, Behavior Analysis, Open Source

Reckless driving is a major contributing factor to road morbidity and mortality. While further research into the nature and impact of reckless driving, particularly among young people, is urgently needed, the measurement of reckless driving behaviour also requires increased attention. Three major shortcomings apparent in established measures of driver behaviour are that they do not target the full range of reckless driving behaviours, they measure characteristics other than driving behaviours, and/or they fail to categorise and label reckless driver behaviour based on characteristics of the behaviours themselves. To combat these shortcomings, this paper reports the development and preliminary validation of a new measure of reckless driving behaviour for young drivers. Exploratory factor analysis of self-reported driving data revealed four, conceptually distinct categories of reckless driving behaviour: those that increase crash-risk due to (a) distractions or deficits in perception, attention or reaction time (labelled “distracted”), (b) driving under the influence of drugs or alcohol (labelled “substance-use”), (c) placing the vehicle in an unsafe environment beyond its design expectations (labelled “extreme”), and (d) speed and positioning of the vehicle relative to other vehicles and objects (labelled “positioning”). Confirmatory factor analysis of data collected from a separate, community sample confirmed this four-factor structure. Multiple regression analyses found differences in the demographic and psychological variables related to these four factors, suggesting that interventions in one reckless driving domain may not be helpful in others.

- by Brenton McNally
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- Psychology, Applied Psychology, Social Psychology, Health Psychology

The Project entitled “Eye Tracking based Driver Fatigue Monitoring and Warning System”
consists of the hardware and the software modules. The main idea behind this project is to
develope a non-intrusive system which can detect fatigue of driver and issue a timely warning.
Since large number of road accidents are caused by driver drowsiness. Hence this system will
be helpful in preventing many accidents, and consequently save money and reduce personal
suffering.
This system will detect eye movement to detect the fatigue state of driver. By monitoring the
eyes using camera and developing an algorithm we can detect symptoms of driver fatigue early
enough to avoid an accident. So this project will be helpful in detecting driver fatigue in
advance and will gave a warning output in form of sound and vibration. For indication of
warning we will use two approaches i.e one by blowing alarm and second by seat belt vibration
whose frequency will vary between 100 to 300 Hzs. Moreover the warning will be deactivated
manually rather than automatically. So for this purpose a deactivation switch will be used to
deactivate warning.
Moreover if driver felt drowsy there is possibility of sudden acceleration or de-acceleration
hence we can judge this by plotting a graph in time domain and when all three input variables
shows a possibility of fatigue at one moment then a warning signal is shown in form of text or
red colour circle. This will directly give an indication of drowsiness/fatigue which can be
further used as record of driver performance or can be used by traffic police which can take
further action accordingly.

Road traffic is known to have its own complex dynamics. One implication of complexity is that road traffic collisions have become an unwelcome but unavoidable part of human life. One of the major causes of collisions is the human factor. While car manufacturers have been focusing on developing feasible solutions for autonomous and semi-autonomous vehicles to replace or assist human drivers, the proposed solutions have been designed only for individual vehicles. The road traffic, however, is an interaction-oriented system including complex flows. Such a system requires a complex systems approach to solving this problem as it involves considering not only pedestrians, road environment, but also road traffic which can include multiple vehicles. Recent research has demonstrated that large-scale autonomous vehicular traffic can be better modeled using a collective approach as proposed in the form of vehicular cyber-physical systems (VCPS) such as given by Li et al. (IEEE Trans Parallel Distrib Syst 23(9):1775–1789, 2012) or Work et al. (Automotive cyber physical systems in the context of human mobility. In: National workshop on high-confidence automotive cyber-physical systems, Troy, MI, 2008). To the best of our knowledge, there is currently no comprehensive review of collision avoidance in the VCPS. In this paper, we present a comprehensive literature review of VCPS from the collision-avoidance perspective. The review includes a careful selection of articles from highly cited sources presented in the form of taxonomy. We also highlight open research problems in this domain.

In this paper, we present data collection activities and preliminary research findings from the real-world database collected with "UYANIK," a passenger car instrumented with various sensors, CAN-Bus data logger, cameras, microphones, data acquisitions systems, computers, and support systems. Within the shared frameworks of Drive-Safe Consortium (Turkey) and the NEDO (Japan) International Collaborative Research on Driving Behavior Signal Processing, close to 9 Terabytes of driver behavior, vehicular, and road data has been collected from more than 50 drivers on a 25 km route consisting of both city roads and highway in Istanbul, Turkey. Challenge of collecting data in a metropolis with around 12 million people, famous with extremely limited infrastructure yet driving behavior defying all rules and regulations bordering madness could not be "PAINLESS." Both the experience gained and the preliminary results from still ongoing studies using the database are very encouraging and give comfort.

- by Baran Curuklu
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- Signal Processing, Data Collection, Driver Behavior, Data Logger

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues; other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected.

- by Araz 𝖳aeihagh and +1
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- Business, Information Systems, Management, Risk Management and Insurance

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about driving environment.
Studies have proved that automated vehicles have a potential to decrease traffic congestion on road networks by reducing the time headway, enhancing the traffic capacity and improving the safety margins in car following. Furthermore, vehicle movement and driver’s behavior of conventional vehicles will be affected by the presence of automated vehicles in traffic networks. Despite different encouraging factors, automated driving raises some concerns such as possible loss of situation awareness, overreliance on automation and degrading driving skills in absence of practice. Moreover, coping with complex scenarios, such as merging at ramps and overtaking, in terms of interaction between automated vehicles and conventional vehicles need more research.
This thesis work aims to investigate the effects of automated vehicles on driver’s behavior and traffic performance. A broad literature review in the area of driving simulators and psychological studies was performed to examine the automated vehicle effects on driver’s behavior. Findings from the literature survey, which has been served as setup values in the simulation study of the current work, reveal that the conventional vehicles, which are driving close to the platoon of automated vehicles with short time headway, tend to reduce their time headway and spend more time under their critical time headway. Additionally, driving highly automated vehicles is tedious in a long run, reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of automated vehicles on traffic performance, a microscopic simulation case study consisting of different penetration rates of automated vehicles (0, 50 and 100 percentages) was conducted in VISSIM software. The scenario network is a three-lane autobahn segment of 2.9 kilometers including an off-ramp, on-ramp and a roundabout with some surrounding urban roads.
Outputs of the microscopic simulation in this study reveal that the positive effects of automated vehicles on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably decreased by 8.09% during p.m. peak hours in scenario with automated vehicles. Besides, Smoother traffic flow with less queue in the weaving segment was observed. Result of the scenario with 50% share of automated vehicles moreover shows a feasible interaction between conventional vehicles and automated vehicles. Meaningful outputs of this case study, based on the input data from literature review, demonstrate the capability of VISSIM software to simulate the presence of automated vehicles in great extent, not only as an automated vehicle scenario but also a share of them, in traffic network. The validity of the output values nonetheless needs future research work on urban and rural roads with different traffic conditions.

- by Erfan Aria
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- Automated Guided Vehicles, Capacity analysis, Driver Behavior, Highway Capacity Manual

This article explores what the legal, sociological, and scientific literature tells us about risky behavior and what the law can – and can’t - do about it. The article focuses on cell phone use – and the push to regulate it - as a parable... more

This article reviews a transactional model of driver stress and fatigue, and its ergonomic application to designing vehicle systems for `stress-tolerance’. Disturbances of subjective state are controlled by cognitive stress processes of appraisal and coping. Both personality factors and situational stressors may elicit maladaptive patterns of cognition that generate subjective stress symptoms, elicit potentially dangerous coping strategies, and interfere with information-processing and attention to the task at hand. Studies using a driving simulator have explored the behavioural consequences of several qualitatively di. erent forms of `stress’, that can be loosely labelled as anxiety, anger and fatigue. Implications of the model for design are reviewed, focusing on road engineering, in-car systems, and automation of vehicle functions. A transactional analysis focuses on evaluation of the cognitions produced by vehicle systems, problems of distraction and overload, and maintaining active task involvement. The article concludes with guidelines for design to minimize safety problems associated with stress and fatigue.

- by Gerald Matthews
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- Driver Behavior

Recently we have witnessed the worldwide adoption of many different types of innovative technologies, such as crowdsourcing, ridesharing, open and big data, aiming at delivering public services more efficiently and effectively. Among them, ridesharing has received substantial attention from decision-makers around the world. Because of the multitude of currently understood or potentially unknown risks associated with ridesharing (unemployment, insurance, information privacy, and environmental risk), governments in different countries apply different strategies to address such risks. Some governments prohibit the adoption of ridesharing altogether, while other governments promote it. In this article, we address the question of how risks involved in ridesharing are governed over time. We present an in-depth single case study on Singapore and examine how the Singaporean government has addressed risks in ridesharing over time. The Singaporean government has a strong ambition to become an innovation hub, and many innovative technologies have been adopted and promoted to that end. At the same time, decision-makers in Singapore are reputed for their proactive style of social governance. The example of Singapore can be regarded as a revelatory case study, helping us further to explore governance practices in other countries.

- by Yanwei Li and +1
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- Management, Risk Management and Insurance, Information Technology, Policy Analysis/Policy Studies

The processing of vehicles at unsignalized intersections is a complex and highly interactive process, whereby each driver makes individual decisions about when, where, and how to complete the required maneuver, subject to his perceptions of distances, velocities, and own car's performance. Typically, the performance of priority-unsignalized intersections has been modeled with probabilistic approaches that consider the distribution of gaps in the major-traffic stream and their acceptance by the drivers of minor street vehicles based on the driver's "critical gap". This paper investigates the aggressive behavior of minor street vehicles at intersections that are priority-unsignalized but operate with little respect of control measures. The objective is to formulate a behavioral model that predicts the probability that a driver performs an aggressive maneuver as a function of a set of driver and traffic attributes. Parameters that were tested and modeled include driver characteristics (gender and age), car characteristics (performance and model year), and traffic attributes (number of rejected gaps, total waiting time at head of queue, and major-traffic speed). Binary probit models are developed and tested, based on a collected data set from an unsignalized intersection in the city of Beirut, to determine which of the studied variables are statistically significant in determining the aggressiveness of a specific driver.

- by Isam Kaysi
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- Psychology, Aggressive Behavior, Aggression, Statistical Significance

With a marked increase in advanced driver assistance systems (ADAS) being designed and deployed for cars, there is a logical emergence of studies that critically examine the influence these have on driver behavior and attitudes towards risk and safety. The research question addressed within this paper asks to what extent the level of perceived criticality or risk on the part of drivers influences their acceptance of advanced assistance.

Lane changing of traffic flow is a complicated and significant behavior for traffic safety on the road. Frequent lane changing can cause serious traffic safety issues, particularly on a two-lane road section of a freeway. This study aimed to analyze the effect of significant traffic parameters for traffic safety on lane change frequency using the studied calibrated values for driving logic "conscious" in VISSIM. Video-recorded traffic data were utilized to calibrate the model under specified traffic conditions, and the relationship between observed variables were estimated using simulation plots. The results revealed that changes in average desired speed and traffic volume had a positive relationship with lane change frequency. In addition, lane change frequency was observed to be higher when the speed distribution was set large. 3D surface plots were also developed to show the integrated effect of specified traffic parameters on lane change frequency. Results showed that high average desired speed and large desired speed distribution coupled with high traffic volume increased the lane change frequency tremendously. The study also attempted to develop a regression model to quantify the effect of the observed parameters on lane change frequency. The regression model results showed that desired speed distribution had the highest effect on lane change frequency compared to other traffic parameters. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency.

- by Janos Juhasz
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- Road safety, Pedestrians and Cyclists, Driver Behavior

This paper presents a preliminary view of learner driver education in Ireland, comparing and contrasting with other international regions1. In so doing, it discusses accident statistics, learner driver experiences, the Irish system comparing with
other international countries, and future direction of driver education and safety. This study is being done from the perspective of public policy, health and safety, and driver education best practices, to provide safer driving environments for learner drivers and other road users.
Learning to drive in Ireland, requires drivers to pass a theory test, and then obtain` a learner’s permit, which allows learners practice driving whilst supervised. The objective of driver education is to produce safer drivers, typically defined as drivers less likely to involved in road traffic accidents. Driver education programmes have been shown to achieve important objectives related to mobility and independent driving by providing an efficient and effective means for learner drivers to learn how to drive and pass the practical driving test (Mayhew & Simpson, 1996; Williams, 2006). Driver education gives new drivers a stronger foundation of training on which they can build their knowledge and skills. Lessons cover the most important skills, knowledge and behaviours needed to become a safe driver and draw on our knowledge as to the major causes of collisions in Ireland. (RSA.ie)
According to Mayhew, D.R., (2007), it is possible that improved driver education could potentially augment the known safety effectiveness of graduated driver licensing systems (GDL). In particular, there are opportunities to improve driver education so that it achieves its safety objectives, and ensure that programmes in the future complement GDL, and the Essential Driver Training (EDT) programme in Ireland, contributing to overall safety benefits2.
Learner and novice drivers remain a major danger on the road, to themselves, their passengers and other road users, with
study after study showing that young people are far more likely to be involved in a crash than older drivers. Young drivers are
grossly overrepresented in the official accident figures and each statistic represents a tragic waste of life that could be
prevented. Inexperience, youthful bravado and sheer recklessness can all play a part in these accidents. Tough action, and
meaningful reform to better equip learner drivers to handle the dangers of driving is required. We have always approached
the young driver problem primarily from a road safety perspective. The key objective is to improve the safety of learner
drivers3 and provide a safe driving environment in which learners can practice safe driving skills. In primary research
undertaken by the author in 2018, 31% of Advanced Driving Instructors (ADIs) surveyed were of the opinion that EDT did not
provide a safe driving environment for learner drivers4.
Current and future efforts to improve driver education, and better integrate it with GDL programmes, need to be rigorously evaluated to determine what does and does not work to reduce learner/novice driver crashes, and as importantly, to understand why this is the case. Driving provides a terrific sense of freedom, but it’s also potentially the most dangerous action we do daily. Learning to drive isn’t just about passing a test – it’s about learning skills from experience and continually improving and advancing the quality of those skills.

Objectives: The purpose of this study was to assess the relationships among the following elements: unhealthy work indicators (job stress and emotional exhaustion at work), the decision to drive (or not), and driving crashes suffered by Spanish workers. Methods: For this cross-sectional study, a full sample of 1,200 Spanish drivers (44% women and 56% men) with a mean age being 42.8 years was used. They answered a questionnaire divided into three sections: demographic and driving-related data; burnout, job stress, and life stress; and self-reported road behaviors and driving safety indicators. Results: Overall, 41.6% of drivers reported emotional exhaustion at work. Furthermore, 80.2% of the participants showing substantial signs of job stress or exhaustion had experienced one or more important stressful life events during the previous year. Job stress was associated with the number of driving crashes suffered along the last 3 years. Also, and especially in situations where drivers admit not feeling well enough to drive, job stress and emotional exhaustion seem to be independent from the decision to drive, and from perceiving these variables as potential impairers of driving performance. Conclusions: First of all, this study showed a high prevalence of job stress and emotional exhaustion symptoms experienced at work by Spanish workers. Moreover, significant relationships were found among self-rated driving performance, workplace stress and burnout indicators, which suggests that job stress and emotional exhaustion levels may, indeed, impair driving performance, but they do not influence the decision to drive or not. In other words, even when they are significantly affected by job stress or emotional exhaustion at work, most Spanish drivers still drive.

- by Francisco Alonso and +1
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- Job Stress (Psychology), Domestic workers, Spain, Burnout

Mental overload is a problem drivers are increasingly exposed to in today's complex task of vehicle operation and is one of the causes of traffic accidents or hazards. To keep road safety high but allow for additional information to be forwarded to the driver, we propose to employ subliminal persuasion: a technique where the information is transferred below the level of conscious awareness. Thus, the driver becomes aware of the information, but his/her cognitive load is unaltered. To analyze the potential of this approach, we have designed a case study implementing an "ecodriving" strategy operating in the background. Driving economy is thereby estimated based on vehicles' mileage gathered in real time from numerous sensors in and around the car, and information is conveyed to the driver with very light, not attentively perceivable, vibration patterns originating from tactor elements integrated into the safety belt or the car seat. The main research hypothesis followed in this paper and investigated in real driving studies is that drivers would operate their vehicles more economically on vibrotactile instructions perceived inattentively, as compared with the case without any notifications. Indeed, results indicate an improvement in driving economy for segments driven with subliminal feedback compared with routes driven without assistance but not without qualifications. Statistical significance has been proven for the safety belt interface, whereas it has not been substantiated for the tactile car seat. (However, more research is needed to validate the applicability of subliminal persuasion across a wider range of driving and in-vehicle tasks.) Index Terms-Driving economy, safety belt interface, subliminal persuasion, tactile driver seat, vibrotactile stimulation.

- by Andreas Riener
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- Civil Engineering, Visualization, Road safety, Cognition

In two experiments we explored the influence of individual differences in working memory capacity (WMC) on hazard perception performance in a simulated driving task. In Experiment 1, we examined the relationship between WMC and hazard perception performance under control and dual task conditions, and self-reported driving behavior. Results revealed significant relationships between WMC, hazard perception performance and self-reported driving behavior. Participants lower in WMC performed poorer in dual task conditions and reported more instances of inattention when driving. In Experiment 2 we explored the gaze behavior of low and high WMC individuals whilst completing the hazard perception test under control and dual task conditions. Results revealed that low-WMC individuals had poorer hazard perception performance under dual task conditions and these performance decrements were mirrored in reductions in mean fixation durations on the hazard. Interestingly, pupillary dilation appears to discriminate between low- and high-WMC individuals and might be a useful index of attention for future research.

- by Greg Wood
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- Driving, Working Memory, Eye Movements (Psychology), Driver Behavior

The proposed method comprises a computer vision-based system highly applicable in the detection of a possible accident while driving. A stereo depth camera is placed in front of the vehicle at a point through which all crucial viewing angles are captured. The camera will be covering a viewing angle of 180°. This idea proposes an efficient framework for accurate object detection using CNN along with an object tracking algorithm. This system will determine the probability of an accident based on the three parameters, which are: object approaching towards the line of movement, relative distance between the object and vehicle, and relative speed of the object with respect to the vehicle. It will provide a reliable technique to attain an efficient rate of detection with less erroneous indication of an accident. Since it covers 180°, it can accurately detect any object/vehicle coming from either side. By judging the speed of the vehicle and the trajectory of the object, the system will calculate the expected time of collision and in order to avoid the impact, an automatic braking mechanism will take place to cautiously reduce the speed of the vehicle in a calculated manner. In conclusion, this computer vision-based system will be a game-changer in accident detection and will make driving safer, easier, and more efficient.

- by Arpit Singh
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- Electrical Engineering, Computer Science, Programming Languages, Computer Vision

Objective: The goal of this study was to provide a better understanding of driver behavior in fog. Background: Impaired perception of changes in headway is hypothesized to be one of the reasons for shorter following distances in foggy conditions as compared with clear weather. Method: In the experiments described here, we measured response time for discriminating between whether the vehicle ahead is getting closer or farther away. Several visibility conditions were studied, ranging from a no-fog condition to a condition in which the vehicle could be seen only by its rear fog lights. Results: Fog conditions increased response times when the outline of the vehicle was barely visible or not visible at all. The longer response times in fog were attributable to the low contrast of the vehicle outline when still visible and to the smaller spacing between the two lights when the outline could not be properly perceived. Moreover, response times were found to be shorter for shorter following distances and for faster accelerations. Conclusion: Reducing headway could be a way for drivers to achieve faster discrimination of relative motion in foggy weather. More specifically, shortening one's following distance until visibility of the lead vehicle changes from bad to good may have a perceptual control benefit, insofar as the response time gain compensates for the reduction in headway under these conditions. Applications: Potential applications include improving traffic safety. The results provide a possible explanation for close following in fog and point out the importance of rear-light design under these conditions. by guest on April 10, 2016 hfs.sagepub.com Downloaded from

- by Stéphane Caro
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- Psychology, Cognitive Science, Perception, Human Factors

Kecelakaan lalu lintas adalah suatu peristiwa di jalan yang tidak terduga dan tidak disengaja yang melibatkan kendaraan dengan atau tanpa pengguna jalan lain yang mengakibatkan korban manusia dan atau harta benda (UU. RI. No. 22 Tahun 2009). Studi Epidemiologi Cedera akibat Kecelakaan Lalu lintas di RSUD Dokter Soesilo Kabupaten Tegal menunjukan bahwa korban cedera akibat kecelakaan sebagian besar berumur 16-45 tahun, jenis kelamin laki-laki, jenis kendaraan sepeda motor (Wahyu dalam Notosiswoyo, 2014).
Tingginya angka fatalitas pengendara sepeda motor disebabkan oleh beberapa faktor antara lain pengendara sepeda motor sering kali melakukan manuver yang membahayakan (www.kompas.com diakses pada tanggal 12 Februari 2014 dalam Finiarty, 2014). Hal ini dibuktikan dengan dijumpai para pengemudi sepeda motor menghentikan kendaraannya melewati batas palang pintu. Bahkan, beberapa kali terlihat pengendara yang nekat menerobos meski palang pintu kereta api sudah tertutup (Resmadi, 2014).
Penyebab perilaku agresifitas pengemudi sepeda motor di perlintasan sebidang kereta api antara lain (1) faktor internal dan faktor eksternal dari setiap individu yang berdampak pada tingkat kesadaran hukum, (2) tayangan televisi yang belum digunakan sebagai sarana komunikasi yang baik, dan (3) keinginan seseorang agar cepat sampai tempat tujuan.
Cara mengatasi perilaku agresifitas pengemudi sepeda motor di perlintasan sebidang kereta api antara lain (1) peningkatan kesadaran hukum (2) menyisipkan tayangan-tayangan yang bertemakan keselamatan berlalu lintas, dan (3) manajemen yang baik serta pemilihan rute yang benar

Road transportation simulators are increasingly used by transportation stakeholders around the world for the analysis of intricate transportation systems. Model calibration is a crucial prerequisite for transportation simulators to reliably reproduce and predict traffic conditions. This paper considers the calibration of transportation simulators. The methodology is suitable for a broad family of simulators. Its use is illustrated with stochastic and computationally costly simulators. The calibration problem is formulated as a simulationbased optimization (SO) problem. We propose a metamodel approach. The analytical metamodel combines information from the simulator with information from an analytical differentiable and tractable network model that relates the calibration parameters to the simulation-based objective function. The proposed algorithm is validated by considering synthetic experiments on a toy network. It is then used to address a calibration problem with real data for a large-scale network: the Berlin metropolitan network with over 24300 links and 11300 nodes. The performance of the proposed approach is compared to a traditional benchmark method. The proposed approach significantly improves the computational efficiency of the calibration algorithm with an average reduction in simulation runtime until convergence of more than 80%. The results illustrate the scalability of the approach and its suitability for the calibration of large-scale computationally inefficient network simulators. 215 This paper focuses on the calibration of simulators that are computationally costly to evaluate. The high computational cost can be due to: (i) the simulation of high levels of demand along with a high-resolution representation of demand (e.g., disaggregate representation of travelers), (ii) the simulation of a large-scale network, (iii) the use of a stochastic simulator requiring the evaluation of numerous simulation replications, (iv) the desire to evaluate performance under equilibrium conditions, which requires running sequentially multiple simulation-based assignment iterations .