Technology advancement is driving electric vehicle adoption.

Electric vehicle sales have been growing rapidly in the United States and around the world. This study explores the drivers of demand for electric vehicles, examining whether this trend is primarily a result of technology improvements or changes in consumer preferences for the technology over time. We conduct a discrete choice experiment of new vehicle consumers in the United States, weighted to be representative of the population. Results suggest that improved technology has been the stronger force. Estimates of consumer willingness to pay for vehicle attributes show that when consumers compare a gasoline vehicle to its battery electric vehicle (BEV) counterpart, the improved operating cost, acceleration, and fast-charging capabilities of today's BEVs mostly or entirely compensate for their perceived disadvantages, particularly for longer-range BEVs. Moreover, forecasted improvements of BEV range and price suggest that consumer valuation of many BEVs is expected to equal or exceed their gasoline counterparts by 2030. A suggestive market-wide simulation extrapolation indicates that if every gasoline vehicle had a BEV option in 2030, the majority of new car and near-majority of new sport-utility vehicle choice shares could be electric in that year due to projected technology improvements alone.

Post Take-Over Performance Varies in Drivers of Automated and Connected Vehicle Technology in Near-Miss Scenarios.

OBJECTIVE: This study examined the impact of monitoring instructions when using an automated driving system (ADS) and road obstructions on post take-over performance in near-miss scenarios. BACKGROUND: Past research indicates partial ADS reduces the driver's situation awareness and degrades post take-over performance. Connected vehicle technology may alert drivers to impending hazards in time to safely avoid near-miss events. METHOD: Forty-eight licensed drivers using ADS were randomly assigned to either the active driving or passive driving condition. Participants navigated eight scenarios with or without a visual obstruction in a distributed driving simulator. The experimenter drove the other simulated vehicle to manually cause near-miss events. Participants' mean longitudinal velocity, standard deviation of longitudinal velocity, and mean longitudinal acceleration were measured. RESULTS: Participants in passive ADS group showed greater, and more variable, deceleration rates than those in the active ADS group. Despite a reliable audiovisual warning, participants failed to slow down in the red-light running scenario when the conflict vehicle was occluded. Participant's trust in the automated driving system did not vary between the beginning and end of the experiment. CONCLUSION: Drivers interacting with ADS in a passive manner may continue to show increased and more variable deceleration rates in near-miss scenarios even with reliable connected vehicle technology. Future research may focus on interactive effects of automated and connected driving technologies on drivers' ability to anticipate and safely navigate near-miss scenarios. APPLICATION: Designers of automated and connected vehicle technologies may consider different timing and types of cues to inform the drivers of imminent hazard in high-risk scenarios for near-miss events.

Physical and cognitive demands associated with police in-vehicle technology use: an on-road case study.

Motor vehicle crashes are a leading cause of police officers' deaths in line of duty. These crashes have been mainly attributed to officers' driving distraction caused by the use of in-vehicle technologies while driving. This paper presents a 3-h ride-along study of 20 police officers to assess the physical and cognitive demands associated with using in-vehicle technologies. The findings suggested that the mobile computer terminal (MCT) was the most frequently used in-vehicle system for the officers. In addition, officers perceived the MCT to significantly increase their visual, cognitive, and physical demands compared to other in-vehicle technologies. Evidence from electromyography and eye-tracking measures suggested that officers with more experience as a patrol officer and those who were working in more congested areas experienced higher cognitive workload. Furthermore, it was found that as the ride-along duration increased, there were indications of muscle fatigue in medial deltoid and triceps brachii muscles. Practitioner summary: This study assessed the impact of police in-vehicle technology use in an on-road case study. The findings provide new data and knowledge for police agencies and vehicle manufacturers to develop administrative measures and in-vehicle technology innovations to improve police officers' health and safety.

Effects of Mobile Computer Terminal Configuration and Level of Driving Control on Police Officers' Performance and Workload.

OBJECTIVE: The objective of this study was to assess police officers' performance and workload in using two mobile computer terminal (MCT) configurations under operational and tactical driving conditions. BACKGROUND: Crash reports have identified in-vehicle distraction to be a major cause of law enforcement vehicle crashes. The MCT has been found to be the most frequently used in-vehicle technology and the main source of police in-vehicle distraction. METHOD: Twenty police officers participated in a driving simulator-based assessment of driving behavior, task completion time, and perceived workload with two MCT configurations under operational and tactical levels of driving. RESULTS: The findings revealed that using the MCT configuration with speech-based data entry and head-up display location while driving improved driving performance, decreased task completion time, and reduced police officers' workload as compared to the current MCT configuration used by police departments. Officers had better driving but worse secondary task performance under the operational driving as compared to the tactical driving condition. CONCLUSION: This study provided an empirical support for use of an enhanced MCT configuration in police vehicles to improve police officers' safety and performance. In addition, the findings emphasize the need for more training to improve officers' tactical driving skills and multitasking behavior. APPLICATION: The findings provide guidelines for vehicle manufacturers, MCT developers, and police agencies to improve the design and implementation of MCTs in police vehicles considering input modality and display eccentricity, which are expected to increase officer and civilian safety.

Awake at the wheel: how auto technology innovations present ongoing sleep challenges and new safety opportunities.

Individuals and society are dependent on transportation. Individuals move about their world for work, school, healthcare, social activities, religious and athletic events, and so much more. Society requires the movement of goods, food, medicine, etc. for basic needs, commerce, cultural and political exchanges, and all of its dynamic, complex elements. To meet these critical daily demands, the transportation system operates globally and around the clock. Regardless of their role, a basic requirement for the individuals operating the transportation system is that they are awake and at optimal alertness. This applies to individuals driving their own cars, riding a bike or motorcycle, as well as pilots of commercial aircraft, train engineers, long-haul truck drivers, and air traffic controllers. Alert operators are a basic requirement for a safe and effective transportation system. Decades of scientific and operational research have demonstrated that the 24/7 scheduling demands on operators and passengers of our transportation system create sleep and circadian disruptions that reduce alertness and performance and cause serious safety problems. These challenges underly the longstanding interest in transportation safety by the sleep and circadian scientific community. An area currently offering perhaps the most significant opportunities and challenges in transportation safety involves vehicle technology innovations. This paper provides an overview of these latest innovations with a focus on sleep-relevant issues and opportunities. Drowsy driving is discussed, along with fatigue management in round-the-clock transportation operations. Examples of cases where technology innovations could improve or complicate sleep issues are discussed, and ongoing sleep challenges and new safety opportunities are considered.

Multimodal In-Vehicle Hypoglycemia Warning for Drivers With Type 1 Diabetes: Design and Evaluation in Simulated and Real-World Driving.

BACKGROUND: Hypoglycemia threatens cognitive function and driving safety. Previous research investigated in-vehicle voice assistants as hypoglycemia warnings. However, they could startle drivers. To address this, we combine voice warnings with ambient LEDs. OBJECTIVE: The study assesses the effect of in-vehicle multimodal warning on emotional reaction and technology acceptance among drivers with type 1 diabetes. METHODS: Two studies were conducted, one in simulated driving and the other in real-world driving. A quasi-experimental design included 2 independent variables (blood glucose phase and warning modality) and 1 main dependent variable (emotional reaction). Blood glucose was manipulated via intravenous catheters, and warning modality was manipulated by combining a tablet voice warning app and LEDs. Emotional reaction was measured physiologically via skin conductance response and subjectively with the Affective Slider and tested with a mixed-effect linear model. Secondary outcomes included self-reported technology acceptance. Participants were recruited from Bern University Hospital, Switzerland. RESULTS: The simulated and real-world driving studies involved 9 and 10 participants with type 1 diabetes, respectively. Both studies showed significant results in self-reported emotional reactions (P<.001). In simulated driving, neither warning modality nor blood glucose phase significantly affected self-reported arousal, but in real-world driving, both did (F2,68=4.3; P<.05 and F2,76=4.1; P=.03). Warning modality affected self-reported valence in simulated driving (F2,68=3.9; P<.05), while blood glucose phase affected it in real-world driving (F2,76=9.3; P<.001). Skin conductance response did not yield significant results neither in the simulated driving study (modality: F2,68=2.46; P=.09, blood glucose phase: F2,68=0.3; P=.74), nor in the real-world driving study (modality: F2,76=0.8; P=.47, blood glucose phase: F2,76=0.7; P=.5). In both simulated and real-world driving studies, the voice+LED warning modality was the most effective (simulated: mean 3.38, SD 1.06 and real-world: mean 3.5, SD 0.71) and urgent (simulated: mean 3.12, SD 0.64 and real-world: mean 3.6, SD 0.52). Annoyance varied across settings. The standard warning modality was the least effective (simulated: mean 2.25, SD 1.16 and real-world: mean 3.3, SD 1.06) and urgent (simulated: mean 1.88, SD 1.55 and real-world: mean 2.6, SD 1.26) and the most annoying (simulated: mean 2.25, SD 1.16 and real-world: mean 1.7, SD 0.95). In terms of preference, the voice warning modality outperformed the standard warning modality. In simulated driving, the voice+LED warning modality (mean rank 1.5, SD rank 0.82) was preferred over the voice (mean rank 2.2, SD rank 0.6) and standard (mean rank 2.4, SD rank 0.81) warning modalities, while in real-world driving, the voice+LED and voice warning modalities were equally preferred (mean rank 1.8, SD rank 0.79) to the standard warning modality (mean rank 2.4, SD rank 0.84). CONCLUSIONS: Despite the mixed results, this paper highlights the potential of implementing voice assistant-based health warnings in cars and advocates for multimodal alerts to enhance hypoglycemia management while driving. TRIAL REGISTRATION: ClinicalTrials.gov NCT05183191; https://classic.clinicaltrials.gov/ct2/show/NCT05183191, ClinicalTrials.gov NCT05308095; https://classic.clinicaltrials.gov/ct2/show/NCT05308095.

Safety potential of crash avoidance features, improved headlights, and V2V-enhanced technologies for older drivers.

INTRODUCTION: Age-related changes and frailty are among the reasons that older drivers are overrepresented in certain crash types. Vehicle safety features that address these crash types may therefore deliver greater safety benefits for older drivers than for other age groups even though they are designed for the general population. METHODS: U.S. crash data from 2016-2019 were used to estimate the proportion of crash involvements and fatal and nonfatal driver injuries for older (70 years old and above) and middle-aged (35-54 years old) drivers from crash scenarios to which current crash avoidance features, improved headlights, and forthcoming vehicle-to-vehicle (V2V)-connected intersection-assistance features could be relevant. Risk ratios were then calculated to determine the relative benefits of each technology for older drivers compared with middle-aged drivers. RESULTS: Combined, these technologies were potentially relevant to 65 % of older driver and 72 % of middle-aged driver fatalities during the study period. Intersection assistance features showed the most promise for older drivers. Such features were potentially relevant to 32 % of older driver crash involvements, 38 % of older driver injuries, and 31 % of older driver fatalities. Intersection assistance features were significantly more likely to be relevant to older driver deaths than middle-aged driver fatalities (RR, 3.52; 95 % CI, 3.33-3.71). CONCLUSIONS: Vehicle technologies have the potential to substantially reduce or mitigate crashes and the injuries that they cause for everyone, but the potential safety impact of each technology varies by driver age because different age groups are over- or underrepresented in specific crash scenarios. PRACTICAL APPLICATIONS: With the older driver population growing, these findings underscore the need to bring intersection assistance technologies to the consumer market. At the same time, everyone stands to benefit from currently available crash avoidance features and improved headlights, so their use should be promoted among all drivers.

Impact assessment of crude oil mix, electricity generation mix, and vehicle technology on road freight emission reduction in China.

To achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China's version of the GREET model was established to evaluate the impact of crude oil mix, electricity mix, and vehicle technology on China's reduction in road freight emissions. The results show that the import share of China's crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China's coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), by approximately 6.5% in 2020 compared to 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potentials for energy-saving and emission reduction at various stages of the fuel life cycle are different. In addition, in a comparative study of vehicle technology, the results show that (1) for medium-duty trucks (MDTs) and heavy-duty trucks (HDTs), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty trucks (LDTs), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.

Energy-saving and emission-reduction potential of fuel cell heavy-duty trucks in China during the fuel life cycle.

Exploring alternative fuels and advanced vehicle technology is a crucial strategy for vehicle emission reduction. Fuel cell heavy-duty trucks (FC-HDTs) have a promising application prospect to alleviate the high energy consumption and emissions of road freight, but their environmental performance during the fuel life cycle should be further studied. This study is aimed at evaluating the fossil fuel consumption and GHG emissions of FC-HDTs in China using the updated GREET model. The results show that (1) comparing various hydrogen production pathways, it is found that the coke oven gas (COG) pathway can provide the best environmental performance, while the energy consumption and greenhouse gas (GHG) emissions of the coal gasification (CG) and grid power water electrolysis (GPWE) pathways will be significantly decreased in the future. (2) Among the involved vehicles in China, FC-HDT with GVWR18 has the greatest energy-saving and emission-reduction potential. (3) The application of carbon capture and storage (CCS) technology in hydrogen production is conducive to improving the emission-reduction effect of FC-HDT while increasing its energy consumption slightly. The key to achieving upstream carbon neutrality is to optimize the hydrogen production structure and electricity mix, along with adjusting the hydrogen production process and transportation mode. Furthermore, the fuel economy and payload of the FC-HDT affect its environmental performance, indicating the importance of improving the technology of the drivetrain, fuel cell, and hydrogen storage tank.

Development and application of connected vehicle technology test platform based on driving simulator: Case study.

To ensure safety, it is necessary to test the connected vehicle (CV) technology before application. The goal of this study is to provide a case reference for the testing of the connected vehicle technology. The connected vehicle technology test platform is built based on the driving simulator. Taking fog zone, tunnel zone, and work zone as analysis cases, drivers were invited to participate in driving simulation experiments, related data was collected, and the impact of connected vehicle technology on driving behavior and safety was analyzed. The results of the fog zone imply that drivers have a high degree of compliance with the connected vehicle technology. However, it also increases the visual workload of drivers to a certain extent. The results of the tunnel zone indicate that the connected vehicle technology can enhance driving safety by enabling drivers to remain cautious. The results of the work zone demonstrate that the connected vehicle technology is able to promote drivers' ability of controlling speed and lane-changing. Overall, the results show that the connected vehicle technology has a positive effect on enhancing driving behavior and safety. The research framework and the development of the connected vehicle technology test platform based on the driving simulator given in the paper are dynamic and reproducible, which provides a reference for researchers in related fields, and the case analysis in this paper enriches the research of connected vehicle technology.

Stated acceptance and behavioral responses of drivers towards innovative connected vehicle applications.

This research is aimed at investigating drivers' attitudes towards connected vehicle technology in general and two connected vehicle applications in particular-Lane Speed Monitoring and High Speed Differential Warning-which have been demonstrated via simulation to be effective in enhancing traffic mobility and safety, respectively. An online survey was sent to customers of an automobile manufacturer in the United States. Out of the 1453 survey responses that were received, 650 complete and valid responses were used to analyze the respondents' stated acceptance of and expected behavioral responses to the two connected vehicle applications under a variety of scenarios. Statistical analyses were conducted to examine the influence of demographic and socioeconomic factors. The results reveal that the respondents express high willingness to use connected vehicle technology and the two applications under various circumstances, and the willingness is strongly associated with age, gender, education level, and income. Higher levels of acceptance are observed in older, male, higher-educated, or higher-income respondents, while the patterns of conditional acceptance and expected behavioral responses vary with specific scenarios. These results provide useful information for application developers, traffic operators, and policy makers to steer connected vehicle technology development and deployment in the direction that will benefit both the users and the society.

Safety effectiveness and performance of lane support systems for driving assistance and automation - Experimental test and logistic regression for rare events.

As of 2022, lane-keeping assistance systems and other selected safety technologies will become mandatory in new European vehicles to increase safety for passengers, pedestrians and cyclists. Lane support systems (LSS) are based on advanced computer vision technologies and they are expected to give safety benefits in reducing Ran of Road and head-on crashes comparable to already consolidated physical countermeasures like rumble strips. Anyway, despite the assumed technology readiness, there is still much uncertainty regarding the needs of vision systems for "reading" the road and limited results are still available from in field testing. In such framework the paper presents an experimental test of LSS performance carried out in two lane rural roads with different geometric alignments and sections characterized by variable maintenance conditions for pavement and markings. LSS faults were detected in 2.6 % of the sections, running the roads in day light and dry pavement conditions. Logit models were developed to better understand road characteristics and conditions that can affect the system performance. The Firth penalized maximum-likelihood method was applied to estimate the logistic regression coefficients and standard errors to account for the rareness of the events. Results show that luminance coefficient of marking in diffuse lighting conditions (Qd) and horizontal curvature radius (1/R) are the main predictors of system fault. Based on the case study and test conditions, other marking characteristics, longitudinal cracking, verge width and running speed resulted not significant in explaining the probability of fault. Thresholds values for Qd and 1/R are suggested and remarks on road maintenance and design standards presented.

Transportation and Aging: An Updated Research Agenda for Advancing Safe Mobility.

This article discusses what is currently known about three important topics related to older driver safety and mobility: screening and evaluation, education and training interventions, and in-vehicle technology. Progress is being made to improve the safe mobility of older adults in these key areas; however, significant research gaps remain. This article advances the state of knowledge by identifying these gaps, and proposing further research topics will improve the lives of older adults. In addition, we discuss several themes that emerged from the review, including the need for multidisciplinary, community-wide solutions; large-scale, longitudinal studies; improved education/training for both older adults themselves and the variety of stakeholders involved in older adult transportation; and programs and interventions that are flexible and responsive to individual needs and differences.

Driving difficulties as reported by older drivers with mild cognitive impairment and without neurological impairment.

Objective: Considerable evidence indicates that medical conditions prevalent among older individuals lead to impairments in visual, cognitive, or psychomotor functions needed to drive safely. The purpose of this study was to explore the factors determining driving difficulties as seen from the viewpoint of 30 older drivers with mild cognitive impairment (MCI) and 30 age-matched controls without cognitive impairment. Methods: Perceptions of driving difficulties from both groups were examined using data from an extensive questionnaire. Samples of drivers diagnosed with MCI and age-matched controls were asked to report the frequency with which they experienced driving difficulties due to functional deficits and knowledge of new traffic rules and traffic signs. Results: The analysis revealed that 2 factors underlie MCI perceptions of driving difficulties, representing (1) difficulties associated with late detection combined with slowed response to relevant targets in the peripheral field of view and (2) difficulties associated with divided attention between tasks requiring switching from automatic to conscious processing particularly of long duration. The analysis for healthy controls revealed 3 factors representing (1) difficulties in estimating speed and distance of approaching vehicles in complex (attention-dividing) high-information-load conditions; (2) difficulties in moving head, neck, and feet; and (3) difficulties in switching from automatic responses to needing to use cognitive processing in new or unexpected situations. Conclusions: Though both group analyses show difficulties with switching from automatic to decision making, the difficulties are different. For the control group, the difficulty in switching involves switching in new or unexpected situations associated with high-information-load conditions, whereas this switching difficulty for the MCI group is associated with divided attention between easier tasks requiring switching. These findings underline the ability of older drivers (with MCI and without cognitive impairment) to indicate probable impairments in various driving skills. The patterns of difficulties perceived by the MCI group and the age-matched healthy control group are indicative of demanding driving situations that may merit special attention for road designers and road safety engineers. They may also be considered in the design of older drivers' fitness to drive evaluations, training programs, and/or vehicle technologies that provide for older driver assistance.

Creating the environment for driver distraction: A thematic framework of sociotechnical factors.

As modern society becomes more reliant on technology, its use within the vehicle is becoming a concern for road safety due to both portable and built-in devices offering sources of distraction. While the effects of distracting technologies are well documented, little is known about the causal factors that lead to the drivers' engagement with technological devices. The relevance of the sociotechnical system within which the behaviour occurs requires further research. This paper presents two experiments, the first aims to assess the drivers self-reported decision to engage with technological tasks while driving and their reasoning for doing so with respect to the wider sociotechnical system. This utilised a semi-structured interview method, conducted with 30 drivers to initiate a discussion on their likelihood of engaging with 22 different tasks across 7 different road types. Inductive thematic analysis provided a hierarchical thematic framework that detailed the self-reported causal factors that influence the drivers' use of technology whilst driving. The second experiment assessed the relevance of the hierarchical framework to a model of distraction that was established from within the literature on the drivers use of distracting technologies while driving. The findings provide validation for some relationships studied in the literature, as well as providing insights into relationships that require further study. The role of the sociotechnical system in the engagement of distractions while driving is highlighted, with the causal factors reported by drivers suggesting the importance of considering the wider system within which the behaviour is occurring and how it may be creating the conditions for distraction to occur. This supports previous claims made within the literature based model. Recommendations are proposed that encourage a movement away from individual focused countermeasures towards systemic actors.

What technologies do people engage with while driving and why?

This paper presents the findings of a semi-structured interview study that was conducted to identify drivers' self-reported likelihood of engaging with technologies that are now commonly found in modern automobiles. Previous research has focused on the effect these technological tasks have on driving performance, but there has been less focus on how, why and when drivers choose to engage with them. As distraction remains a significant contributor to road accidents, an understanding of why it occurs will give important insights into how it can be prevented. A semi-structured interview schedule was developed to allow drivers to discuss the factors that influence their decision to engage with a variety of different technologies. The methodology facilitated both quantitative ratings of the drivers' likelihood of engaging in a variety of tasks and qualitative insights into why. Age and gender had some influence on the propensity to engage, in line with other findings in the literature, as did road type and task type. The reasons drivers gave for why they engage with potentially distracting tasks inform recommendations for preventing distraction related accidents from the increasingly prevalent sources of technologies available to drivers.

A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.

In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of seven months. The system provided headway monitoring, lane departure, forward collision and pedestrian collision warnings, using audio and visual alerts. The purpose of the trial was to determine whether the technology could change the driving behaviour of fleet vehicle drivers and improve their safety. The evaluation consisted of three components: (1) analysis of objective data to examine effects of the technology on driving behaviour, (2) analysis of video footage taken from a sample of the vehicles to examine driving circumstances that trigger headway monitoring and forward collision warnings, and (3) a survey completed by 122 of the 199 individuals who drove the trial vehicles to examine experiences with, and attitudes to, the technology. Analysis of the objective data found that the system resulted in changes in behaviour with increased headway and improved lane keeping, but that these improvements dissipated once the warning alerts were switched off. Therefore, the system is capable of altering behaviour but only when it is actively providing alerts. In-vehicle video footage revealed that over a quarter of forward collision warnings were false alarms, in which a warning event was triggered despite there being no vehicle travelling ahead. The surveyed drivers recognised that the system could improve safety but most did not wish to use it themselves as they found it to be distracting and felt that it would not prevent them from having a crash. The results demonstrate that collision avoidance technology can improve driving behaviour but drivers may need to be educated about the potential benefits for their driving in order to accept the technology.

Perceived safety benefits, concerns, and utility of advanced driver assistance systems among owners of ADAS-equipped vehicles.

OBJECTIVE: There are many unknowns regarding drivers' use and acceptance of advanced vehicle technologies. This research aimed to examine drivers' perceptions of advanced driver assistance systems (ADAS). METHODS: This research was conducted using structured interviews and focus groups of owners of vehicles with advanced technologies. RESULTS: Drivers' perceptions about ADAS were mixed, but generally safety was considered to be the greatest value of the systems. There was recognition that the systems may result in overreliance and thus encourage distraction behaviors or other bad driving habits, and participants generally expressed that they were ultimately responsible for the vehicle's operation and needed to be ready to override the system if it failed. CONCLUSIONS: The findings indicate that driver characteristics and individual factors may influence perceptions, behaviors, and interactions with safety technology, and this research is a first step toward understanding any influences. Human factors issues related to automated vehicle technologies are critical for design and deployment, including those of trust, acceptance, and understanding of systems.

Comparison of proposed countermeasures for dilemma zone at signalized intersections based on cellular automata simulations.

The Type II dilemma zone describes the road segment to a signalized intersection where drivers have difficulties to decide either stop or go at the onset of yellow signal. Such phenomenon can result in an increased crash risk at signalized intersections. Different types of warning systems have been proposed to help drivers make decisions. Although the warning systems help to improve drivers' behavior, they also have several disadvantages such as increasing rear-end crashes or red-light running (RLR) violations. In this study, a new warning system called pavement marking with auxiliary countermeasure (PMAIC) is proposed to reduce the dilemma zone and enhance the traffic safety at signalized intersections. The proposed warning system integrates the pavement marking and flashing yellow system which can provide drivers with better suggestions about stop/go decisions based on their arriving time and speed. In order to evaluate the performance of the proposed warning system, this paper presents a cellular automata (CA) simulation study. The CA simulations are conducted for four different scenarios in total, including the typical intersection without warning system, the intersection with flashing green countermeasure, the intersection with pavement marking, and the intersection with the PMAIC warning system. Before the specific CA simulation analysis, a logistic regression model is calibrated based on field video data to predict drivers' general stop/go decisions. Also, the rules of vehicle movements in the CA models under the influence by different warning systems are proposed. The proxy indicators of rear-end crash and potential RLR violations were estimated and used to evaluate safety levels for the different scenarios. The simulation results showed that the PMAIC countermeasure consistently offered best performance to reduce rear-end crash and RLR violation. Meanwhile, the results indicate that the flashing-green countermeasure could not effectively reduce either rear-end crash risk or RLR violations. Also, it is found that the pavement-marking countermeasure has positive effects on reducing the rear-end risk while it may increase the probability of RLR violation. Lastly, the implementation of the proposed warning system is discussed with the consideration of connected-vehicle technology. It is expected that the dilemma zone issues can be efficiently addressed if the proposed countermeasure can be employed within connected vehicle technology.

Assessment of the safety benefits of vehicles' advanced driver assistance, connectivity and low level automation systems.

The Connected Vehicle (CV) technologies together with other Driving Assistance (DA) technologies are believed to have great effects on traffic operation and safety, and they are expected to impact the future of our cities. However, few research has estimated the exact safety benefits when all vehicles are equipped with these technologies. This paper seeks to fill the gap by using a general crash avoidance effectiveness framework for major CV&DA technologies to make a comprehensive crash reduction estimation. Twenty technologies that were tested in recent studies are summarized and sensitivity analysis is used for estimating their total crash avoidance effectiveness. The results show that crash avoidance effectiveness of CV&DA technology is significantly affected by the vehicle type and the safety estimation methodology. A 70% crash avoidance rate seems to be the highest effectiveness for the CV&DA technologies operating in the real-world environment. Based on the 2005-2008 U.S. GES Crash Records, this research found that the CV&DA technologies could lead to the reduction of light vehicles' crashes and heavy trucks' crashes by at least 32.99% and 40.88%, respectively. The rear-end crashes for both light vehicles and heavy trucks have the most expected crash benefits from the technologies. The paper also studies the effectiveness of Forward Collision Warning technology (FCW) under fog conditions, and the results show that FCW could reduce 35% of the near-crash events under fog conditions.