Effects of automated speed control on speeding intention and behavior on mixed-traffic urban arterial roads

Although the effectiveness of automated speed control (ASC) has been proven, the mechanism of behavioral change in developing countries remains unclear. The objective of this study was to elucidate the effect of ASC on drivers' speeding intention and behavior on mixed-traffic urban arterial roads. Before and during the implementation of ASC, questionnaires based on the theory of planned behavior (TPB) were administered to local passenger-vehicle drivers. A total of 200 participants with an average age of 38.4 years completed both survey waves. To explain the mechanism of behavioral change, the multiple indicators multiple causes (MIMIC) structural equation modeling (SEM) time-invariant was used simultaneously for both waves. The model explained 49% and 55% of the variance in intention, and 40% and 56% of the variance in self-reported speeding behavior, respectively, before and during the ASC implementation period. The findings reveal that ASC altered the cognitive factors of speeding behavior. Speeding became less favorable, had lower approval, and was more difficult to control. Drivers reported lower speeding tendency and diminished speeding behavior. Furthermore, the ASC changed the relative impact of the factors, boosted the influence of family members and close friends on drivers' speeding motivation, and increased the influence of intention and perceived control on speeding behavior. This paper provides recommendations for the implementation of ASCs on mixed-traffic urban arterial roads in developing countries.     

Driver behavior formulation in intersection dilemma zones with phone use distraction via a logit-Bayesian network hybrid approach

Use of cellular phone while driving is one of the top contributing factors that induce traffic crashes, resulting in significant loss of life and property. A dilemma zone is a circumstance near signalized intersections where drivers hesitate when making decisions related to their driving behaviors. Therefore, the dilemma zone has been identified as an area with high crash potential. This article utilizes a logit-based Bayesian network (BN) hybrid approach to investigate drivers' decision patterns in a dilemma zone with phone use, based on experimental data from driving simulations from the National Advanced Driving Simulator (NADS). Using a logit regression model, five variables were found to be significant in predicting drivers' decisions in a dilemma zone with distractive phone tasks: older drivers (50–60 years old), yellow signal length, time to stop line, handheld phone tasks, and driver gender. The identified significant variables were then used to train a BN model to predict drivers' decisions at a dilemma zone and examine probabilistic impacts of these variables on drivers' decisions. The analysis results indicate that the trained BN model was effective in driver decision prediction and variable influence extraction. It was found that older drivers, a short yellow signal, a short time to stop line, nonhandheld phone tasks, and female drivers are factors that tend to result in drivers proceeding through intersections in a dilemma zone with phone use distraction. These research findings provide insight in understanding driver behavior patterns in a dilemma zone with distractive phone tasks.     

Traffic safety culture of drivers in Canada: Implications for new traffic law implementation to enhance traffic safety

This study investigates Canada's traffic safety culture (TSC) as part of a global research project. The TSC survey data collected by an online survey is used to predict drivers' perception of changes in traffic problems in the past 3 years, driver's support, opposition towards enforcement of additional traffic laws, and drivers' perceived threat towards risky driving behaviors. A two-step procedure is followed to build models. The first step includes feature selection using the chi-square test of independence. The second step comprises building classification models using the Random Forest technique. Results suggest that drivers' personal attributes like the number of accident records, driving frequency, geographic region of nationality, and religion are top predictor variables for drivers' perception towards changes in traffic problems. In addition, compared to others most drivers perceive distracted driving as a major traffic problem today. There is strong disapproval of drivers against the following driving behaviors and strong support to implement laws against it: speeding in school zones, talking on a hand-held cell phone, tying text messages or e-mails, drowsy driving, driving without wearing their seatbelt, drive with passengers not wearing seatbelts, running through red lights, and impaired driving. In contrast, following risky driving behaviors is less of a perceived threat: speeding over limit on a freeway, on a residential street, and in an urban area and talking on a hands-free cell phone while driving. In addition, a driver's accident record is a significant indicator for a perceived threat towards risky driving behaviors followed by age and accumulated demerit points. The results from this study can be used to guide educational campaigns to transform the traffic safety culture of target groups and make more informed policy decisions.     

Drivers' perceptions regarding speeding and driving on urban residential streets with a 30 km/h speed limit

Previous studies have shown very little information regarding drivers' opinions, attitudes and behaviours with respect to speeding and driving on urban residential streets with a 30 km/h speed limit. The present research aims to address this issue by conducting a questionnaire study with a sample of 367 Japanese drivers. The results showed that drivers tended to have positive beliefs about complying with the 30 km/h speed limit and understand the negative consequences of speeding; however, a majority of the drivers considered breaking the speed limit as a way to reduce their travel time. While the extent of speeding was found to be very serious, a number of drivers still supported the use of a 30 km/h speed limit on residential streets and favoured protecting the right of vulnerable street users. The logistic regression models developed in this study identified that the drivers who did not support the 30 km/h speed limit were associated with those who had committed traffic-law violations, who had negative beliefs about complying with the speed limit, who did not consider residents' opinions, who believed it is acceptable for them to drive at a high speed, and who felt it difficult to refrain from speeding. With regard to anti-speeding countermeasures, under drivers' point of view, streets should be designed to make the 30 km/h speed limit more credible, although this study also showed evidence supporting the application of public awareness programmes and social campaigns as speeding interventions. In addition, this research investigated drivers' speed choices in various specific driving circumstances, and six underlying factors affecting drivers' speed choices were determined. On the basic of the findings, the implications and suggestions for speeding interventions were also discussed.     

Behavioral aspects of safety culture: Identification of critical safety-related behaviors of motorcyclists in Indonesia's urban areas via the application of behavioral-based safety programs

Many violations and accidents involving motorcyclists occur in the urban areas of Indonesia. It can be said that the failure to develop a good traffic safety culture causes poor motorcyclist behavior, as shaped by existing programs and mechanisms. This study aimed to identify motorcyclists' critical behaviors by conducting investigations using the reciprocal safety culture model as a framework. We tried to identify and clarify the safe behaviors expected by local governments from the existing driving safety program. By applying the antecedent-behavior-consequence model of the behavioral-based safety program, we obtained sixty-three behaviors associated with the six criteria of safe driving. We surveyed motorcyclists (N = 97) to review the sixty-three motorcyclist behaviors in the urban area. The relationship between the behavioral and psychological aspects of the reciprocal safety culture model was investigated to obtain the motorcyclists' critical behaviors. Multiple linear regression model, optimized by the stepwise regression, described the influence motorcyclist behavior on the perception of driving safety. We identified eight critical safety-related behaviors engaged in by motorcyclists. Observation revealed some cultural issues embedded in motorcyclists' eight critical safety-related behaviors that need to be intervened by the local government. The reciprocal safety culture model could be applied in the behavioral-based safety program to approach traffic safety culture issues. In order to develop a good traffic safety culture in the urban area, the local government needs to review the existing driving safety program by understanding drivers' behaviors as they relate to such a program.     

Factors affecting lane change crashes

This study aims to investigate the contributing factors affecting the occurrence of crashes while lane-changing maneuvers of drivers. Two different data sets were used from the same drivers' population. The first data set was collected from the traffic police crash reports and the second data set was collected through a questionnaire survey that was conducted among 429 drivers. Two different logistic regression models were developed by employing the two sets of the collected data. The results of the crash occurrence model showed that the drivers' factors (gender, nationality and years of experience in driving), location and surrounding condition factors (non-junction locations, light and road surface conditions) and roads feature (road type, number of lanes and speed limit value) are the significant variables that affected the occurrence of lane-change crashes. About 57.2% of the survey responders committed that different sources of distractions were the main reason for their sudden or unsafe lane change including 21.2% was due to mobile usage. The drivers' behavior model results showed that drivers who did sudden lane change are more likely to be involved in traffic crashes with 2.53 times than others. The drivers who look towards the side mirrors and who look out the windows before lane-change intention have less probability to be involved in crashes by 4.61 and 3.85 times than others, respectively. Another interesting finding is that drivers who reported that they received enough training about safe lane change maneuvering during issuing the driving licenses are less likely to be involved in crashes by 2.06 times than other drivers.     

Mining of the association rules between driver electrodermal activity and speed variation in different road intersections

It is commonly acknowledged that the human factor and the interaction between the human factor and the road environment are among the most common causes of road accidents. Physiological signals can provide a real-time assessment of the driver's state because they can be collected continuously without interfering with the driver's task performance or the drivers' perception of the road. This study presents a method for measuring and quantifying drivers' physiological responses when approaching T-junctions and roundabouts using electrodermal activity and speed variations. Speed and electrodermal activity were collected continuously during a driving study which took place on a test environment based at Cranfield University and surrounding roads. Twenty participants were involved in the study. The analysis focused on four crossing manoeuvres on two T-junctions and a roundabout. The association Rule with the Apriori algorithm was used in order to evaluate associations between the variables related to electrodermal activity, i.e. the number and amplitude of the SCR peaks (assessed by the Electrodermal Impact Index in aggregate form), and the variables related to speed, i.e. the speed variation and its sign (positive or negative), for each type of intersection. The main results of this study can be summarized as follows: 1) the rules obtained for the manoeuvres on the T-Junctions show that the T-junctions induce low variations in the electrodermal activity and are often associated with a significant speed increase (between 20% and 30%); 2) the rules obtained for the manoeuvres on the roundabout highlights that the roundabout induces high variations in the electrodermal activity and is associated with a significant speed reduction (between 20% and 40%).     

基于嗅觉刺激的驾驶员负向情绪正向调控方法研究

针对驾驶员在异常情绪下更容易导致交通事故发生的问题，研究一种用于智能座舱的驾驶员异常情绪正向调控方法。招募 30 名被试者进行试验，利用视频素材诱发驾驶员愤怒等负向情绪，利用 E-prime 软件控制的嗅觉体验测试仪释放薰衣草、甜橙、沉香木气味对驾驶员负向情绪进行正向调节，采用 ErgoLab 多通道生理仪检测记录在气味刺激下被试者的心电信号 （ECG）、光电容积脉搏波信号 （PPG）、呼吸信号 （RESP） 等生理特征信号；采用问卷调查获取被试者的主观感受；使用面部表情识别软件对驾驶员情绪进行分析，联合主客观数据分析驾驶员的情绪调节效果，通过 30组对照试验研究3种嗅觉刺激气体对负向情绪的调节效果，结果表明，沉香木调节效果最好，甜橙其次，薰衣草最差。     

Hardware and software for collecting microscopic trajectory data on naturalistic driving behavior

This article presents a method to collect naturalistic microscopic longitudinal vehicle trajectory data with a modest budget. The drivers studied are not aware that they are participating in an experiment; hence one can collect naturalistic driving behavior. This article presents the hardware and software developed, and we include a detailed example of a particular case study that was conducted with data collected from the system. The case study examines drivers' willingness to accept very short headways, and casts that behavior in light of their subsequent lane-changing decisions. The data show a statistically defensible connection between these behaviors. These phenomena are not new, but highlight the importance of the data quality and of observing naturalistic driving behavior, and this article demonstrates a method to calibrate specific parameters related to the behavior.     

基于自然驾驶数据的切入场景队列跟驰仿真

车辆切入是常见的驾驶行为，频繁的变道切入行为影响了通行效率与交通安全。因此，揭示切入场景下的驾驶特性对研究交通拥堵和行驶安全机理具有重要意义。在自然驾驶数据的基础上，根据驾驶人的主观风险感知特性，探究驾驶人的切入行为发生条件，并在期望安全裕度（DSM）模型的基础上，标定了切入场景下的相关参数，根据标定结果进行切入场景下的队列跟驰仿真。仿真结果表明:在仿真区间内，队列的长度、行驶速度以及切入车的切入位置不同会影响队列的稳定性以及队列的调整，当队列长度由4辆变为13辆，速度由5 m/s增至20 m/s，切入车的位置由贴近前后车变为前后2辆车中间时，切入行为对队列的稳定性影响变得越小，队列越容易恢复到稳定状态。      

Speed management strategies and drivers' attitudes in Thailand

In Thailand where speeding on highways and roads has been a key contributing factor in road traffic crashes, considerable efforts to control vehicle speeds have been made, mostly through speed limit enforcement. However, the fact that speed limits are very often violated on a large scale in Thailand suggests the need for implementing more effective speed management strategies such as automatic speed cameras, increasing speeding penalty, and smart vehicle design to control vehicle speeds. While the effectiveness of such measures depends mainly on how well they could lead drivers to change speeding behavior, public acceptability is also vital as a key to sustainability of most speed management programs. This paper attempts to identify public acceptability of speed management measures, both currently implemented and under consideration, in Thailand. In doing so, data from the questionnaire surveys based on a random sample of 2180 drivers in Thailand including a wide range of individual characteristics of respondents and their attitudes to select speed management schemes are analyzed using an econometric technique. In particular, we introduce a simplified methodological framework to develop a better understanding of factors that explain drivers' attitudes towards speeding behavior and alternative speed management strategies. Findings from this research provide several important implications that could improve the current practices of speed management in Thailand.     

Role of steering wheel feedback on driver performance: driving simulator and modeling analysis

When driving in curves, how do drivers use the force appearing on the steering wheel? As it carries information related to lateral acceleration, this force could be necessary for drivers to tune their internal model of vehicle dynamics; alternatively, being opposed to the drivers' efforts, it could just help them stabilize the steering wheel position. To assess these two hypotheses, we designed an experiment on a motion-based driving simulator. The steering characteristics of the vehicle were modified in the course of driving, unknown to drivers. Results obtained with standard drivers showed a surprisingly wide range of adaptation, except for exaggerated modifications of the steering force feedback. A two-level driver model, combining a preview of vehicle dynamics and a neuromuscular steering control, reproduces these experimental results qualitatively and indicates that adaptation occurs at the haptic level rather than in the internal model of vehicle dynamics. This effect is related to other theories on the manual control of dynamics systems, wherein force feedback characteristics are abstracted at the position control level. This research also illustrates the use of driving simulation for the study of driver behavior and future intelligent steering assistance systems.     

Self- and peer-assessments of ambulance drivers' driving performance

The aim of the present study was to develop and examine the quality of the Ambulance Driver Self-assessment Questionnaire (ADSQ) and the Ambulance Driver Peer-assessment Questionnaire (ADPQ) measuring aspects of, driving performance, driving style and driving competence. In addition the ADSQ measures self-reflection and safety-attitudes. The aim of the study was also to examine ambulance drivers' self- and peer-assessments as well as to examine the accuracy of self-assessments by comparing self-assessed and peer-assessed driving performance, driving style and competence. 76 ambulance drivers employed at two ambulance stations in northern Sweden completed ADSQ and ADPQ. Item analyses were conducted to examine the psychometric properties of the items, and based on the results some revisions were made to improve the questionnaires. The revised questionnaires were functioning rather well, although some subscale demonstrated low internal consistency. Subscale inter-correlations provided support for construct validity. Self- and peer-assessments indicated safe driving performance and good driver competence, which is positive from a traffic safety perspective. A comparison of mean self- and peer-assessment ratings, controlling for age, gender and driving experience showed no significant differences, except for the subscale overtaking. This indicates that ambulance drivers' self-assessments are realistic in most areas.     

Ergonomic and biomechnical analysis of automotive general assembly using XML and digital human models

Automotive general assembly requires many manual assembly operations to be carried out by human workers. Ergonomic analysis is an important part of the design and evaluation of products, jobs, tools, machines and environments for safe, comfortable and effective human functioning. Most recent researches have involved the evaluation of working conditions to prevent work-related musculoskeletal disorders. The majority of previous research on automotive companies has mainly considered the results of ergonomic analyses such as RULA (Rapid Upper Limb Assessment), REBA (Rapid Entire Body Assessment) and OWAS (Ovako Working Posture Analysis System). Analysis of static posture including reachability, clearances for arm, hand and tool has also been used to evaluate working conditions. However, in addition to static posture analysis, a biomechanical analysis in dynamic conditions should also be conducted. There are no integrated frameworks or standard schema for ergonomic analysis using digital human models in digital environments. The purpose of this paper is to propose a new framework for the evaluation of working conditions by ergonomic and biomechanical analysis using digital models based on XML standard schema, including: products, processes, manufacturing resources and human workers. This paper presents the analysis results using the proposed framework for automotive general assembly operations. We propose a new framework for the evaluation of the assembly operations and their environments. Then we apply a digital human model to the dynamic simulation of general automotive assembly operations based on standard schemas in XML and PPRH (Product, Process, Resource and Human). Using PPRH information based on a standard XML schema to analyze the ergonomic and biomechanical results, the engineer can visualize, analyze and improve assembly operations and working environments in automotive general assembly shops using digital models.     

Impact of driving style,behaviour and anger on crash involvement among Iranian intercity bus drivers

In developing countries such as Iran, due to the inadequate infrastructure for rail and air transportation facilities, intercity buses are the most common type of transportation for long distances. Because of the long hours of driving, bus driving is considered a challenging job. Moreover, given the high capacity of these vehicles, a small error from the driver could endanger many passengers' health. So, studying drivers' behaviours can be a key factor in decreasing the risk factors of crash involvement in these drivers. However, few studies have focused on intercity bus drivers' behaviours. This research uses a sample of 254 professional drivers that answered a self-report questionnaire on driving style (MDSI), driving behaviour (DBQ), and driving anger (DAS). A structural equation modelling (SEM) is used to investigate the psychometric properties of these questionnaires. The results show a positive correlation between maladaptive driving styles and driving behaviour, and a negative correlation between adaptive styles and driving behaviour. Significant differences are observed among drivers with and without crash history on their maladaptive driving styles and their driving anger scale. A binary logistic regression model is also developed to predict traffic crashes as a function of driving misbehaviour. The results suggest that factors related to driving anger are the main factors that increase the probability of misbehaviour and traffic crashes. The results also suggest that driving style and driving behaviour significantly predict crash risk among bus drivers. Aggressive driving is associated with an increased probability of crash involvement among intercity bus drivers. The findings can be used to inform the health promotion policies and provide regular interventions designed to improve driving safety among intercity bus drivers.     

Intelligent speed adaptation: Preliminary results of on-road study in Penang,Malaysia

The first field experiment with intelligent speed adaptation (ISA) in Malaysia was held in December 2010 in the State of Penang. Eleven private cars were instrumented with an advisory system. The system used in the present study included a vocal warning message and a visual text message that is activated when the driver attempts to exceed the speed limit. When the driver decreases the speed, the warning stops; otherwise it is continuously repeated. The test drivers drove the vehicles for three months with the installed system, and the speed was continuously logged in all vehicles. The warning was however only activated in the second month of the three month period. The present study aimed to evaluate the effects of an advisory ISA on driving speed, traffic safety, and drivers' attitude, behavior, and acceptance of the system. To examine these effects, both the survey and the logged speed data were analyzed and explored. The results show a significant reduction in the mean, maximum and 85th percentile speed due to the use of the system. However, there was no long-lasting effect on the speed when the system was deactivated. In the post-trial survey, drivers declared that the system helped them well in following the speed limits and that it assisted them in driving more comfortably. Furthermore, the warning method was more accepted compared to a supportive system, such as active accelerator pedal (AAP). After the trial, most drivers were willing to keep an ISA system.     

Driver behavior at Kuwait roundabouts and its performance evaluation

This research aimed to evaluate the roundabout performance in Kuwait and to study drivers' behavior at roundabouts. A questionnaire was designed to obtain the needed information. Also, a field observation was done to link the survey data with the real situation on Kuwait roads. A sample of 804 participated in the survey with the collected data being analyzed by SPSS and Excel. The analysis showed that a large percent of drivers have a good knowledge regarding roundabout rules. Moreover, this research analyzed the roundabout capacity and performance. Two roundabouts were chosen for the study located in AL-Salmiya and Al-Jabriya of Hawali governorate. A few modifications for the selected sites were done to compare the roundabout overall performance before and after the change based on several measures of effectiveness. The collected data was analyzed using SIDRA Intersection software. The analysis showed that in Kuwait, for vital and active areas and for traffic volumes greater than 3000 veh/h, the level of service ranges between B and C, and the control delay ranges between 10 s to 30 s. The study help traffic planners and designers in the decision making process providing several intersection alternatives.     

Study on construction of a rider robot for two-wheeled vehicle

In this study, we constructed a fully autonomous two-wheeled vehicle (the Rider Robot) which was used for evaluation of dynamics. As the first step of the study, we constructed the control algorithms and the control system.The control algorithms consist of the standing stability control which keeps the perpendicular motion, and the directional control which follows the target course. These algorithms were determined based on human rider's behavior. The system was constructed using some actuators and sensors.The results show that Rider Robot could follow the target course while keeping the standing stability. Consequently, there is considerable validly in these constructed algorithms and the system.     

Investigating fatal and injury crash patterns of teen drivers with unsupervised learning algorithms

Teenagers have been emphasized as a critical driver population class because of their overrepresentation in fatal and injury crashes. The conventional parametric approaches rest on few predefined assumptions, which might not always be valid considering the complicated nature of teen drivers' crash characteristics that are reflected by multidimensional crash datasets. Also, individual attributes may be more speculative when combined with other factors. This research employed joint correspondence analysis (JCA) and association rule mining (ARM) to investigate the fatal and injury crash patterns of at-fault teen drivers (aged 15 to 19 years) in Louisiana. The unsupervised learning algorithms can explore meaningful associations among crash categories without restricting the nature of variables. The analyses discover intriguing associations to understand the potential causes and effects of crashes. For example, alcohol impairment results in fatal crashes with passengers, daytimes severe collisions occur to unrestrained drivers who have exceeded the posted speed limits, and adverse weather conditions are associated with moderate injury crashes. The findings also reveal how the behavior patterns connected with teen driver crashes, such as distracted driving in the morning hours, alcohol intoxication or using cellphone in pickup trucks, and so on. The research results can lead to effectively targeted teen driver education programs to mitigate risky driving maneuvers. Also, prioritizing crash attributes of key interconnections can help to develop practical safety countermeasures. Strategy that covers multiple interventions could be more effective in curtailing teenagers' crash risk.     

Fusion de données pour l'estimation des temps de parcours via la théorie de l'évidence

The emergence of new information technologies and the transformation that has occurred in traffic management have both increased drivers' already considerable need for road traffic information. The travel time is one of the forms in which this information is presented, and a number of systems are based on its dissemination. In this context, this indicator is used as a measure of the impedance (or cost) of routes on the network and/or a congestion indicator. This raises the problem of estimating travel times with an acceptable degree of accuracy, which is a particularly difficult task in urban areas as a result of difficultes of a theoretical, technical and methodological nature. Thus, in order to find out the traffic conditions that prevail on an urban road, the traffic sensors that are usually used to measure traffic conditions are ineffective under certain circumstances. New measurement devices (cameras, GPS or cellphone tracking, etc.) mean that other sources of data are increasingly used in order to supplement the information provided by conventional measurement techniques and improve the accuracy of travel) time estimates. As a result, travel time estimation becomes a typical data fusion problem. This study deals with a multisource estimate of journey times and attempts to provide a comprehensive framework for the utilization of multiple data and demonstrate the feasibility of a travel time estimation system based on the fusion of data of several different types. In this case two types of data are involved, data from conventional induction loop sensors (essentially flow and occupancy measurements) and data from probe vehicles. The selected modelling framework is the Dempster-Shafer Evidence Theory, which has the advantage of being able to take account of both the imprecision and uncertainty of the data. The implementation of this methodology has demonstrated that, in each case, better results are achieved with fusion than with methods based on a single source of data and that the quality of the information, as measured by correctly classified rates, improves as the degree of precision required of the estimate is increased.