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Lack of communication between road users can reduce traffic efficiency and cause safety issues like traffic accidents. Researchers are exploring how intelligent vehicles should communicate with the environment, other vehicles, and road users. This study explores the impact of social information communication on traffic safety and efficiency at intersections through vehicle-to-vehicle (V2V) communication. The research examines how these factors influence drivers' decision-making and cooperative behavior by incorporating social value orientation (SVO) and driving agent identity into V2V systems and automated vehicle (AV) decision-support systems. An experimental platform simulating intersection conflict scenarios was developed, and three studies involving 334 participants were conducted. The findings reveal that providing drivers with social information about opposing vehicles significantly promotes cooperative behavior and safer driving strategies. Specifically, the waiting rate for people facing proself vehicles (Mean = 0.22) is significantly higher than when facing prosocial vehicles (Mean = 0.79). When SVO is unknown, the waiting rate is around 0.5. Participants behaved more waiting when confronted with an AV than human-driven vehicles. With AV recommendations based on SVO, participants' final waiting rate increases as the recommended waiting rate increases. The optimal recommended waiting rate for AV is most acceptable when it matches the average waiting rate of the other vehicle. This research underscores the importance of integrating social information into V2V communication to improve road safety, aiding in designing automated decision-making strategies for AV and enhancing user satisfaction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Cooperative intelligent transport systems (C-ITSs) are mass-produced and sold in Europe, promising enhanced safety and comfort. Direct vehicle communication, known as vehicle-to-everything (V2X) communication, is crucial in this context. Drivers receive warnings about potential hazards by exchanging vehicle status and environmental data with other communication-enabled vehicles. However, the impact of these warnings on drivers and their inclusion in accident reconstruction remains uncertain. Unlike sensor-based warnings, V2X warnings may not provide a visible reason for the alert, potentially affecting reaction times and behavior. In this work, a simulator study on V2X warnings was conducted with 32 participants to generate findings on reaction times and behavior for accident reconstruction in connection with these systems. Two scenarios from the Car-2-Car Communication Consortium were implemented: "Stationary Vehicle Warning-Broken-Down Vehicle" and "Dangerous Situation-Electronic Emergency Brake Lights". Volkswagen's warning concept was utilized, as they are the sole provider of cooperative vehicles in Europe. Results show that V2X warnings without visible reasons did not negatively impact reaction times or behavior, with average reaction times between 0.58 s (steering) and 0.69 s (braking). No significant distraction or search for warning reasons was observed. However, additional information in the warnings caused confusion and was seldom noticed by subjects. In this study, participants responded correctly and appropriately to the shown false-positive warnings. A wrong reaction triggering an accident is possible but unlikely. Overall, V2X warnings showed no negative impacts compared with sensor-based systems. This means that there are no differences in accident reconstruction regarding the source of the warning (sensors or communication). However, it is important that it is known that there was a warning, which is why the occurrence of V2X warnings should also be saved in the EDR in the future.

Background: Driving capacity is affected by vestibular disorders and the medications used to treat them. Driving is not considered during medical consultations, with 92 per cent of patients attending a centre for dizziness not discussing it with the doctor., Objective: To investigate if medical record prompts facilitate dizziness and driving conversations in ENT balance clinics., Methods: A questionnaire was designed to reflect the current standards of practice and advice given regarding driving and dizziness during balance clinic consultations., Results: Medical record prompts facilitated the improved frequency and recording of shared decision-making conversations about driving and dizziness in 98 per cent of consultations., Conclusion: This study highlights the benefits of medical record prompts for documented and accurate shared decision-making conversations surrounding dizziness, vertigo, vestibular conditions and driving. This potentially improves safety for all road users, and protects the patient and clinician in the event of road traffic accidents and medico-legal investigations.

Purpose: Examine brief parent interventions (PBIs) on a nationally representative sample of teenagers (ages 15-18 years) to change drinking, teens declining (i.e., saying no) to ride with impaired drivers, and increase parent communication about alcohol., Methods: Parent-teen dyads (N = 1,176) recruited from a web panel completed online surveys at baseline (T1), 30 days (T2), 6 months (T3), and 12 months (T4) post baseline (P sex : 54% female; T sex : 49% female; T age : M = 16.33, SD = 1.09; 76% White, 27% Hispanic). Dyads were randomly assigned to: Active Control (n = 390, 33.1%), Surgeon General (SG; n = 393, 33.4%), or Mothers Against Drunk Driving PBI (MADD; n = 393, 33.4%). Aim 1 was an intent-to-treat analysis of the efficacy comparing the Active Control, SG, and MADD conditions on typical weekend drinking and declining riding with an impaired driver from T1 to T4. Aim 2 examined differences in parent communication at T2 by different levels of engagement. Aim 3 examined differences in efficacy comparing the SG and MADD engagement subgroups at T4. Aims were evaluated by comparing means using Tukey's test to reduce experiment-wise error., Results: Aim 1 revealed no differences in drinking, but participants in the SG and MADD conditions were able to maintain increases in declining riding with impaired drivers. Aim 2 revealed highly engaged participants reported higher parent communication than moderate and low participants. Aim 3 revealed some highly engaged participants reported less drinking and more declining riding with impaired drivers., Discussion: PBIs may be successful in helping teens decline rides with impaired drivers. Highly engaged parents reported more positive program outcomes than moderate and low engaged parents., (Copyright © 2023 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.)

Onboard virtual assistants with the ability to converse with users are gaining favour in supporting effective human-machine interaction to meet safe standards of operation in automated vehicles (AVs). Previous studies have highlighted the need to communicate situation information to effectively support the transfer of control and responsibility of the driving task. This study explores 'interaction types' used for this complex human-machine transaction, by analysing how situation information is conveyed and reciprocated during a transfer of control scenario. Two human drivers alternated control in a bespoke, dual controlled driving simulator with the transfer of control being entirely reliant on verbal communication. Handover dialogues were coded based on speech-act classifications, and a cluster analysis was conducted. Four interaction types were identified for both virtual assistants (i.e., agent handing over control) - Supervisor, Information Desk, Interrogator and Converser, and drivers (i.e., agent taking control) - Coordinator, Perceiver, Inquirer and Silent Receiver. Each interaction type provides a framework of characteristics that can be used to define driver requirements and implemented in the design of future virtual assistants to support the driver in maintaining and rebuilding timely situation awareness, whilst ensuring a positive user experience. This study also provides additional insight into the role of dialogue turns and takeover time and provides recommendations for future virtual assistant designs in AVs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Driving is a dynamic activity that takes place in a constantly changing environment, carrying safety implications not only for the driver but also for other road users. Despite the potentially life-threatening consequences of incorrect driving behavior, drivers often engage in activities unrelated to driving. This study aims to investigate the frequency and types of errors committed by drivers when they are distracted compared to when they are not distracted., Methods: A total of 64 young male participants volunteered for the study, completing four driving trials in a driving simulator. The trials consisted of different distraction conditions: listening to researcher-selected music, driver-selected music, FM radio conversation, and driving without any auditory distractions. The simulated driving scenario resembled a semi-urban environment, with a track length of 12 km., Results: The findings of the study indicate that drivers are more prone to making errors when engaged in FM radio conversations compared to listening to music. Additionally, errors related to speeding were found to be more prevalent across all experimental conditions., Conclusions: These results emphasize the significance of reducing distractions while driving to improve road safety. The findings add to our understanding of the particular distractions that carry higher risks and underscore the necessity for focused interventions to reduce driver errors, especially related to FM radio conversations. Future research can delve into additional factors that contribute to driving errors and develop effective strategies to promote safer driving practices.

Objective: Right-of-way negotiation between drivers and pedestrians often relies on explicit (e.g., waving) and implicit (e.g., kinematic) cues that signal intent. Since effective driver-pedestrian communication is important for reducing safety-relevant conflicts, this study uses information theory to identify vehicle kinematic behaviors that provide the greatest information gain and serve as cues for pedestrians to cross safely., Data Sources: A driver-pedestrian dataset with 348 interactions was extracted from a large naturalistic driving data collection effort. It includes 325 instances of a pedestrian crossing the vehicle's path and 23 instances in which the vehicle did not yield to a pedestrian. Kinematic data were collected from the vehicle's CAN. Pedestrian behaviors, driver cues, and contextual information were manually annotated from a forward-facing video., Methods: We used kernel density estimation to quantify the probabilities of vehicle acceleration, speed, and standard deviation of speed, for a given vehicle position and pedestrian behavior. Mutual information was then calculated between the estimated distributions given a pedestrian behavior (crossing/not crossing; walking/pausing) across intersection types (protected, e.g., stop signs; designated, e.g., crosswalks; and undesignated, e.g., jaywalking)., Results: The patterns mutual information conveyed by vehicle kinematics differed across measures (acceleration, speed, and standard deviation of speed) reaching peak values (in bits of information) at different distances from the pedestrian path. The mutual information conveyed by vehicle acceleration and pedestrian crossing behaviors peaked the farthest from the pedestrian path in the designated crossings, about 18 m away from the pedestrian path, with a difference in median deceleration of 1.01 m/s 2 (p < 0.001) between pedestrian pausing and walking epochs. For protected crossings, the peak in mutual information occurred closer (10 m) to the pedestrian path, where median vehicle deceleration was significantly lower (0.55 m/s 2 ; p < 0.05) in pausing epochs compared to walking epochs. For undesignated crossings, the peak in mutual information was the closest to the pedestrian crossing path, around 5 m, and was associated with a stronger deceleration behavior in pedestrian crossing epochs (-0.33 m/s 2 ; p < 0.1). Vehicle speed demonstrated a similar sensitivity to distance from the pedestrian path across intersection types. Lastly, looking at the outcome of pedestrian behavior (i.e., crossing/not crossing), we find that the mutual information conveyed by acceleration, speed, and standard deviation of speed, peaked when the vehicle was at 30 m (stronger braking -0.37 m/s 2 ; p < 0.1) and 10 m away, with greater acceleration (0.81 m/s 2 ; p < 0.001) and faster speeds (2.41 m/s; p < 0.001) in pedestrian crossing epochs., Significance of Results: This study examined driver-pedestrian information exchange using vehicle kinematic behavioral cues. We find that the differences in mutual information are shaped by multiple factors including the intersection type. In general, there was less mutual information gain in protected crossings which may be explained by unambiguous right-of-way rules guiding driver and pedestrian behavior, reducing the need for negotiation. Driver-pedestrian interactions in designated crossings seem to take place over a larger distance range compared to undesignated or protected crossings. These findings may support the design of automated driving and pedestrian safety systems that are able to consider the type, strength, and timing of kinematic cues to optimize driver-pedestrian negotiation. Eventually, such systems may enhance safe, efficient, and social interactions with pedestrians., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

This study explored the experiences of Australian family members having conversations about driving with older adults. An exploratory cross-sectional design using an online survey was carried out with Australian family members of current or retired (former) older drivers. One hundred and fifty-six intergenerational family members across Australia completed the survey. Qualitative content analysis of free-text responses identified that the outcomes of conversations were impacted by a range of environmental and individual factors. The essence of conversations centered around two opposing (positive and negative) discourses. The findings highlighted that an individualized approach to the content of conversations is required due to; driver attributes and actions, variations in the level of support experienced by family members, differences in physical and cognitive declines with age, negative perceptions on the impact of driving retirement, and absence of acceptable alternatives to driving. We recommend using positive discourse and reappraisal techniques when initiating driving conversations with older adults.

Introduction: With an aging population there are more older drivers than ever before. To reduce unnecessary road accidents and assist older drivers to successfully transition to non-driving, a better understanding of the factors that influence planning for driving retirement is required. This review explores documented factors that may influence older adults in planning for driving retirement, thus providing new understandings that can inform future preventative road safety measures, interventions, and policies., Method: A systematic search was performed using four databases to locate qualitative studies on the factors that influenced older drivers to plan for driving retirement. To identify factors influencing planning for driving retirement, a thematic synthesis approach was utilized. Identified themes were categorized in relation to elements of the Social Ecological Model theoretical framework., Results: The systematic search resulted in 12 included studies from 4 countries. Four major themes and 11 subthemes were identified regarding planning driver retirement. Each subtheme denotes a factor that may facilitate and/or impede older drivers planning for driving retirement., Conclusion: These results indicate that it is vitally important to encourage older drivers to plan for driving retirement as early as possible. Stakeholders involved in the safety of older drivers (including family, clinicians, road authorities, and policy makers) should work together on interventions and policies that empower older drivers to successfully plan for driving retirement in order to improve road safety and quality of life., Practical Applications: Introducing conversations about driving retirement via medical appointments, family, media, and peer-support groups could facilitate planning for driving retirement. Community-based ride-sharing systems and subsidized private transport options are needed to ensure continued mobility of older adults, especially in rural and regional areas that lack alternate transport services. When devising urban and rural planning, transport, license renewal, and medical testing rules, policy makers should consider older drivers' safety, mobility, and quality of life after driving retirement., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)

In a mixed traffic environment, the connected vehicle platoon cannot communicate and collaborate with the surrounding vehicles. In this case, there is a high risk of collision in large vehicle platoon's lane change scenario where the non-connected surrounding vehicle occupies the target lane-changing space of the platoon. This study proposes a collision-avoidance lane change control method for a connected bus platoon to elude the non-connected vehicle in the target lane for completing lane change in the mixed traffic environment safely. A platoon vehicle sensor system with low-cost and low data processing complexity is designed, which equips with multiple sensors in longitudinal and lateral directions. Under control of the proposed platoon controller on the basis of vehicle-to-vehicle (V2V) communication, the platoon following vehicles are fully autonomous in both longitudinal and lateral directions. The safe lane change decision-maker is designed based on the Finite State Machine (FSM). The decision-maker fuses multiple sensor data and determines the lane change operation of the following vehicles. To verify the effectiveness of the proposed method, a three-vehicle platoon is carried out the lane change experiments in a high-fidelity mixed traffic scenario built by the PreScan-Simulink joint simulation platform. Exposure-to-Risk Index (ERI) of the platoon vehicles is adopted to evaluate the collision risk of the platoon during lane changing process. Three typical case scenarios are tested, including unimpeded lane change, passive waiting lane change, and active accelerating lane change. The simulation results show that all platoon vehicles have an excellent success rate in lane change without collision with the non-connected surrounding vehicle in these scenarios. The proposed method exhibits compelling benefits on improving the safety of platoon vehicles in the mixed traffic environment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Purpose: We aimed to identify evidence supporting emergency vehicle technology in out-of-vehicle systems and in-vehicle-systems that can be used by people with hearing impairment., Methods: We conducted a systematized review to determine what technologies, at any readiness level, are currently being developed in the area of emergency vehicle detection technology. The studies and websites of technologies for emergency vehicles that are currently available to the general public were identified by searching in one electronic database, Scopus and grey literature using Google, respectively., Results: A total of 359 studies were retrieved from Scopus. The grey literature search identified 189 websites related to the search terms under study. Technological devices have included satellite, out-of-vehicle and in-vehicle technology. The analysis shows that most of the technologies are at the stage of laboratory testing. Knowing the availability and the level of readiness of devices, as well as their effectiveness, provides rehabilitation professionals with tools for making evidence-based recommendations to clients with hearing impairment. Knowing which devices are available also provides information to individuals living with hearing impairment so that they can play an active role in the decision-making process of acquiring the existing technologies., Conclusions: So far, few technologies have been identified, and most of them are in the laboratory development stage (i.e., low product readiness level). These results indicate a justified need for the development of new in-vehicle technologies to detect emergency vehicles and actions to transform the new devices into products that are available for people with hearing impairment.IMPLICATIONS FOR REHABILITATIONThere is a need to design new assistive technology devices that are intended to detect emergency service vehicles, which in turn may reduce stress and anxiety related to driving for people with hearing impairment.The majority of the included articles discussed siren detection, with only three discussing the necessary next step of communication to humans.Due to the research being in its early stages, the evidence for emergency vehicle technology on health and participation-related outcomes in people living with hearing impairment is unknown.Most websites do not include information on where to purchase emergency vehicle technology or how much the devices cost, thus making it difficult for people with hearing impairment or rehabilitation professionals to make informed decisions about acquiring these technologies.

Objective: To measure the looming threshold for when drivers perceive closing and an immediate hazard and determine what factors affect these thresholds., Background: Rear-end collisions are a common type of crash. One key issue is determining when drivers first perceive they need to react. The looming threshold for closing and an immediate hazard are critical perceptual thresholds that reflect when drivers perceive they need to react., Method: Two driving simulator experiments examined whether engaging in a cell phone conversation and whether the complexity of the roadway environment affect these thresholds for the perception of closing and immediate hazard. Half of the participants engaged in a cognitive task, the last letter task, to emulate a cell phone conversation, and all participants experienced both simple and complex roadway environments., Results: Drivers perceived an immediate hazard later when engaged in a cell phone conversation than when not engaged in a conversation but only when the driving task was relatively less demanding (e.g., simple roadway, slow closing velocity). Compared to simple scenes, drivers perceived closing and an immediate hazard later for complex scenes but only when closing velocity was 30 mph (48.28 km/h) or greater., Conclusion: Cell phone conversation can affect when drivers perceive an immediate hazard when the roadway is less demanding. Roadway complexity can affect when drivers perceive closing and an immediate hazard when closing velocity is high., Application: Results can aid accident analysis cases and the design of driving automation systems by suggesting when a typical driver would respond.

The performance of vehicular communication technologies changes dynamically according to the application requirements considering data rate, communication ranges, latency, etc. These applications are evolving rapidly and should enhance intelligent transport systems (ITS) such as road safety and automated driving. However, to reach the required quality, these applications need many radio resources to carry the potential traffic load resulting from the environmental perception and data exchanged between the different entities. Therefore, an assessment of vehicular communication technologies' reliability and resilience under these conditions is required to address the multiple challenges of the ITS services. The paper's main contribution is to propose a comprehensive analysis model able to evaluate and compare the performances of ITS technologies according to different constraints related to environment-changing situations. This analysis examines the channel occupancy and provides simulation results which allow the identification of the suitable configurations and the most appropriate technology for a given use case. We also propose a coexistence solution between these technologies based on density-sharing according to the use case requirements and the availability of the technology. Finally, we present the challenge of adaptive configuration in vehicular networks, which helps to provide the optimal structure through road profiles and environment variability (infrastructure, data, etc.). Results show different trade offs and limitations between the considered ITS technologies, which are essential to understand their behaviour in a realistic environment.

Light Detection and Ranging (LiDAR) technology has the advantages of high detection accuracy, a wide range of perception, and not being affected by light. The 3D LiDAR is placed at the commanding height of the traffic scene, the overall situation can be grasped from the perspective of top view, and the trajectory of each object in the traffic scene can be accurately perceived in real time, and then the object information can be distributed to the surrounding vehicles or other roadside LiDAR through advanced wireless communication equipment, which can significantly improve the local perception ability of an autonomous vehicle. This paper first describes the characteristics of roadside LiDAR and the challenges of object detection and then reviews in detail the current methods of object detection based on a single roadside LiDAR and multi-LiDAR cooperatives. Then, some studies for roadside LiDAR perception in adverse weather and datasets released in recent years are introduced. Finally, some current open challenges and future works for roadside LiDAR perception are discussed. To the best of our knowledge, this is the first work to systematically study roadside LiDAR perception methods and datasets. It has an important guiding role in further promoting the research of roadside LiDAR perception for practical applications.

An advanced driver simulator methodology facilitates a well-connected interaction between the environment and drivers. Multiple traffic information environment language processing aims to help drivers accommodate travel demand: safety prewarning, destination navigation, hotel/restaurant reservation, and so on. Task-oriented dialogue systems generally aim to assist human users in achieving these specific goals by a conversation in the form of natural language. The development of current neural network based dialogue systems relies on relevant datasets, such as KVRET. These datasets are generally used for training and evaluating a dialogue agent (e.g., an in-vehicle assistant). Therefore, a simulator for the human user side is necessarily required for assessing an agent system if no real person is involved. We propose a new end-to-end simulator to operate as a human driver that is capable of understanding and responding to assistant utterances. This proposed driver simulator enables one to interact with an in-vehicle assistant like a real person, and the diversity of conversations can be simply controlled by changing the assigned driver profile. Results of our experiment demonstrate that this proposed simulator achieves the best performance on all tasks compared with other models.

As automated vehicles become more common, there is a need for precise measurement and definition of when and in what ways a driver can use a mobile phone in L2 autonomous driving mode, for how long it can be used, the complexity of the call content, and the accumulated mental workload. This study uses a 2 (driving mode) × 2 (call content complexity) × 6 (driving stage) three-factor mixed experimental design to investigate the effect of these factors on the driver's mental workload by measuring the driver's performance on Detection response tasks, pupil diameter, and EEG components in various brain regions in the alpha band. The results showed that drivers' mental workload levels converge between manual and automatic driving modes as the duration of driving increases, regardless of the level of complexity of the mobile phone conversation. This suggests that mobile phone conversations can also disrupt the driver's cognitive resource balance in L2 automatic driving mode, as it increases mental workload while also impairing the normal functioning of brain functions such as cognitive control, problem solving, and judgment, thereby compromising driving safety., (© 2022. The Author(s).)

To ensure road safety in mixed traffic, automated vehicles (AVs) must be equipped with distinct and easy-to-understand communication strategies. For this, the communication design of AVs might be oriented toward implicit communication between manually driven vehicles. This research focused on how drivers interpret observable vehicle behavior (vehicle trajectory) to predict vehicle intentions and planned maneuvers. In addition, the processing and interpretation of contradictory cues were examined as a possible cause for misunderstandings and failed coordination. Two video-based experiments investigated the presumed intention (yielding or insisting on priority), intention recognition time, distinctiveness, and cooperativeness of a vehicle's implicit communication at narrow road passages. For this, two vehicles approached a bottleneck from opposite sides, and only one vehicle could pass at a time. The driving behavior of the oncoming vehicle consisted of longitudinal (decelerating, stopping, accelerating, maintaining speed) and lateral movements (driving to the center, driving to the edge of the road, no lateral deviation) at different timings (early, late). The results indicated advantages of lateral vehicle movements for distinct intention communication. Lateral movements were interpreted the fastest, perceived more distinct, and were more decisive for the presumed intention than longitudinal movements. Early communication was preferred by drivers but increased the intention recognition time, especially for longitudinal movements. However, early lateral communication was interpreted as fast as late longitudinal communication. Furthermore, lateral and longitudinal vehicle movements within a driving pattern that contradicted each other led to ambiguous perceptions. For AVs, early distinct communication via lateral vehicle movement is recommended. Minimizing ambiguity in the interpretation of communication cues might maximize the probability of the safest response from human drivers and contribute to accident prevention in mixed traffic., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This driving simulator study aimed to encourage cooperative lane changes through vehicle-to-vehicle (V2V) communication and explore whether emotional or rational communication content is better in promoting cooperative lane change. A total of 960 lane-changing datapoints from 30 participants in a driving simulation environment were collected. The participants' behavior, driving-related data, and emotional responses were recorded and analyzed. The results revealed that the trigger time to collision (TTC) between the lane changer and the following vehicle in the target lane and communication types were all important factors influencing the willingness of drivers to cooperate. V2V communication could significantly increase the willingness of the driver in the following vehicle to cooperate compared to the traditional method in which desire to change lanes is conveyed with only turn lights. The effect of different communication contents on willingness to cooperate did not vary significantly; however, emotional communication was superior to rational communication in some cases. This indicates that changing lanes owing to an emergency was more likely to be successful. The results of this study can provide a reference for V2V communication design for a safer and more comfortable driving experience., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

To control autonomous vehicles (AVs) in urban unsignalized intersections is a challenging problem, especially in a hybrid traffic environment where self-driving vehicles coexist with human driving vehicles. In this study, a coordinated control method with proximal policy optimization (PPO) in Vehicle-Road-Cloud Integration System (VRCIS) is proposed, where this control problem is formulated as a reinforcement learning (RL) problem. In this system, vehicles and everything (V2X) was used to keep communication between vehicles, and vehicle wireless technology can detect vehicles that use vehicles and infrastructure (V2I) wireless communication, thereby achieving a cost-efficient method. Then, the connected and autonomous vehicle (CAV) defined in the VRCIS learned a policy to adapt to human driving vehicles (HDVs) across the intersection safely by reinforcement learning (RL). We have developed a valid, scalable RL framework, which can communicate topologies that may be dynamic traffic. Then, state, action and reward of RL are designed according to urban unsignalized intersection problem. Finally, how to deploy within the RL framework was described, and several experiments with this framework were undertaken to verify the effectiveness of the proposed method.

It may be necessary to introduce new modes of communication between automated vehicles (AVs) and pedestrians. This research proposes using the AV's lateral deviation within the lane to communicate if the AV will yield to the pedestrian. In an online experiment, animated video clips depicting an approaching AV were shown to participants. Each of 1104 participants viewed 28 videos twice in random order. The videos differed in deviation magnitude, deviation onset, turn indicator usage, and deviation-yielding mapping. Participants had to press and hold a key as long as they felt safe to cross, and report the perceived intuitiveness of the AV's behaviour after each trial. The results showed that the AV moving towards the pedestrian to indicate yielding and away to indicate continuing driving was more effective than the opposite combination. Furthermore, the turn indicator was regarded as intuitive for signalling that the AV will yield. Practitioner Summary: Future automated vehicles (AVs) may have to communicate with vulnerable road users. Many researchers have explored explicit communication via text messages and led strips on the outside of the AV. The present study examines the viability of implicit communication via the lateral movement of the AV.

Cooperative driving is an essential component of intelligent transport systems (ITSs). It promises greater safety, reduced accidents, efficient traffic flow, and fuel consumption reduction. Vehicle platooning is a representative service model for ITS. The principal sub-systems of platooning systems for connected and automated vehicles (CAVs) are cooperative adaptive cruise control (CACC) systems and platoon management systems. Based on vehicle state information received through vehicle-to-vehicle (V2V) communication, the CACC system allows platoon vehicles to maintain a narrower safety distance. In addition, the platoon management system using V2V communications allows vehicles to perform platoon maneuvers reliably and accurately. In this paper, we propose a CACC system with a variable time headway and a decentralized platoon join-in-middle maneuver protocol with a trajectory planning system considering the V2V communication delay for CAVs. The platoon join-in-middle maneuver is a challenging research subject as the research must consider the requirement of a more precise management protocol and lateral control for platoon safety and string stability. These CACC systems and protocols are implemented on a simulator for a connected and automated vehicle system, PreScan, and we validated our approach using a realistic control system and V2V communication system provided by PreScan.

The introduction of automated vehicles (AVs) into urban areas initially leads to mixed traffic, consisting of AVs, human drivers, and vulnerable road users. Since the AV's passenger is no longer actively involved in the driving task, there may be changes in the interaction between AVs and surrounding human road users. Therefore, it is essential for an AV to behave in a comprehensible manner in order to maintain or even enhance traffic efficiency and traffic safety. This work investigates the interaction of an AV and a simultaneously oncoming human driver at road bottlenecks due to double-parked vehicles on both sides of the road. Based on findings derived from AV-pedestrian interaction, comfort limits in terms of driving dynamics, and traffic observations, we designed nine AV movements to either yield the right of way or to insist on it by varying the AV's speed (maintain speed, one-step deceleration, two-step deceleration) and its lateral offset (no offset, close offset, distant offset). The different vehicle movements were evaluated with 34 participants in a driving simulator study. The results show participants' shorter passing times, fewer crashes, and significantly higher ratings of the AV's communication if the AV movement contained a lateral offset. In addition to the regular encounters, we analyzed the controllability of an automation failure and its aftereffect on participants' trust in AVs. The experience of the automation failure reduced the trust rating significantly. From the results we conclude that the AV should communicate the right of way not only via speed adjustments but also via the performance of a lateral offset to enhance traffic efficiency and safety. Moreover, a change in the AV's maneuver due to an automation failure must be avoided since it is not controllable by the human driver., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: This study investigates the effect of naturalistic visual cues on human avoidance behavior for a potential use in telerobotic user interfaces incorporating mixed-reality environments (e.g., augmented reality)., Background: Telerobotic systems used in hazardous environments require interfaces that draw operators' attention to potential dangers. Existing means of hazard notification can often distract or induce stress in operators. In the design and implementation of such interfaces, visual semiotics plays a critical role in creating more effective interfaces. Naturalistic visual cues such as Aposematism or Kindchenschema have proven effective to communicate danger or caution in nature, but the application of these cues in visual systems have yet to be thoroughly investigated., Method: A study was conducted where 40 volunteering participants were asked to control a remote vehicle in a simulated environment. The environment contained a set of neutral and visually augmented obstacles that were designed to provoke avoidance behavior., Results: The use of visual cues triggered greater avoidance behaviors in participants compared to neutral obstacles. The distance of avoidance was correlated with the type of cue present, with obstacles augmented by Aposematism (Cue A) having a greater participant-obstacle distance than Kindchenschema (Cue K)., Conclusions: This study shows the potential for the incorporation of naturalistic visual cues as a means to designate warning or caution in telerobotic environments., Applications: The findings can offer practical guidelines for the design of visual cues in telerobotic interfaces. The further incorporation of such cues may reduce operator stress and the amount of human errors in telerobotic operations.

This study was conducted to assess comprehension of existing road hazard communication designs (RHCDs) in relation to culturally adapted designs among commercial vehicle drivers using a two-part study. In study 1, nine participants were recruited and their comprehension of 20 existing RHCDs was tested. Results of the analysis revealed that only 50% of the designs met the acceptance criterion of 67% set by the International Organization for Standardization (ISO). Culturally adapted symbols were then developed for the 10 symbols which failed to meet the ISO acceptance criterion through a longitudinal focus group discussion involving the nine participants. In study 2, 226 commercial vehicle drivers were drawn from four bus terminals. Results of a paired-samples t test showed that comprehension of the culturally adapted designs was significantly better than comprehension of their equivalent existing designs. The findings are discussed in the context of extant literature and practice.

In complex traffic environments, collision warning systems that rely only on in-vehicle sensors are limited in accuracy and range. Vehicle-to-infrastructure (V2I) communication systems, however, offer more robust information exchange, and thus, warnings. In this study, V2I was used to analyze side-collision warning models at non-signalized intersections: A novel time-delay side-collision warning model was developed according to the motion compensation principle. This novel time-delay model was compared with and verified against a traditional side-collision warning model. Using a V2I-oriented simulated driving platform, three vehicle-vehicle collision scenarios were designed at non-signalized intersections. Twenty participants were recruited to conduct simulated driving experiments to test and verify the performance of each collision warning model. The results showed that compared with no warning system, both side-collision warning models reduced the proportion of vehicle collisions. In terms of efficacy, the traditional model generated an effective warning in 84.2% of cases, while the novel time-delay model generated an effective warning in 90.2%. In terms of response time and conflict time difference, the traditional model gave a longer response time of 0.91 s (that of the time-delay model is 0.78 s), but the time-delay model reduced the driving risk with a larger conflict time difference. Based on an analysis of driver gaze change post-warning, the statistical results showed that the proportion of effective gaze changes reached 84.3%. Based on subjective evaluations, drivers reported a higher degree of acceptance of the time-delay model. Therefore, the time-delay side-collision warning model for non-signalized intersections proposed herein can improve the applicability and efficacy of warning systems in such complex traffic environments and provide reference for safety applications in V2I systems.

Connected vehicle (CV)technologies offer promising solutions to several problems in transportation systems. The trajectory data generated from CV technology can be used to identify real-time conflicts in intersections. To perform such identification, accurate vehicle localisation should be obtained to clearly recognise the conflicts between left-turning vehicles and straight-through vehicles in the opposite direction at the signal control intersection. This study presents a CV framework that uses the two-way time of arrival to locate the vehicles on the basis of the Intelligent Vehicle Infrastructure Cooperative Environment. Kalman Filter (KF) is used to improve the accuracy of the vehicle location, and the corresponding algorithm is used to estimate the vehicle trajectory to obtain the vehicle kinematics information via the on-board system. The traffic conflict areas of the left-turning vehicles and straight-through vehicles in the opposite direction are determined through vehicle trajectory extrapolation, and the left-turn collision at the signal intersection is identified using the post-encroachment time algorithm and vehicle movement information. In addition, Anderson-Darling and modified Kolmogorov-Smirnov tests are performed to verify the goodness of fit of the data. Results show that the vehicle speed and localisation errors of the proposed method decreased by 66.67 % and 83.33 % compared with the results before filtering, respectively. Moreover, the results of the conflict recognition method based on CV trajectory reconstruction is consistent for both goodness of fit tests under real-time communication conditions. This study can provide driving decision for drivers of left-turning vehicles under the Intelligent Vehicle Infrastructure Cooperative Environment and provide technical support for the research and development of left-turn anti-collision systems., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

We examined the effects of different types of cognitive distraction coming from a hands-free phone conversation on the processing of information provided by variable message signs (VMS), on driving performance indicators, and on a physiological index of mental effort (heart rate). Participants drove a route in a driving simulator and had to respond to VMS messages under three conditions: no-distraction, visuospatial distraction (attending phone calls with questions inducing visuospatial processing), and conceptual distraction (attending phone calls with questions requiring semantic memory). Results showed more errors responding to VMS messages in the visuospatial distraction condition. In addition, both types of questions increased the intraindividual variability of response distances and the heart rate, as compared to the no-distraction condition. These results provide new evidence that talking on a hands-free phone entails costs in the processing of traffic information (in particular, text messages displayed on VMS) and it increases the driver's cognitive effort. Interestingly, the cognitive distraction had no effect on the driver's control of the vehicle speed or lateral position. Therefore, the effects of potential risk factors can critically vary among the different driving subtasks due to modulatory factors, such as the level of attentional task demands (relatively high in the processing of messages on VMS, but relatively low in controlling the speed and lateral position of the vehicle in quiet traffic conditions). In consequence, the current paper provides new evidence to discuss hands-free phone policies and highlights the importance of designing technological countermeasures to prevent drivers missing critical information displayed on VMS., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: A frequently overlooked factor contributing to traffic crashes is driver medical conditions, including cognitive and physical impairments, which can compromise individuals' ability to drive safely. Clinicians are in a critical position (and often legally mandated) to identify patients with impairments that may affect their driving ability and counsel them on appropriate next steps. However, prior studies revealed that provider-patient discussions about driving occurred relatively infrequently and that clinician recommendations about when patients could resume driving varied substantially (Chen et al. 2008; Drazkowski et al. 2010). This research aimed to document current driver fitness assessment practices among neurology and neurosurgery clinicians at an academic medical center, with the overall purpose of informing quality improvement efforts. Methods: A cross-sectional, anonymous survey was distributed to physicians and advanced practice providers working in the neurosurgery and neurology departments of a large, Pennsylvania-based academic medical center. Survey question domains included: 1) frequency of discussions about driving, 2) comfort discussing driving with patients, 3) criteria used to assess patient fitness to drive, 4) driver rehabilitation program referral practices, and 5) Pennsylvania Department of Transportation (PennDOT) reporting. Results: The survey revealed that although most providers (68%) had high levels of perceived responsibility for counseling patients about driving, a minority regularly discussed driving issues with their patients (19% prior to discharge, 49% during clinic visits). In addition, only about half (54%) of providers reported having ever filed a report about a patient with the PennDOT, despite Pennsylvania's mandatory driver reporting law. Likelihood of PennDOT reporting was found to be strongly associated with provider knowledge of Pennsylvania unsafe driver reporting laws ( p  < 0.001). Conclusions: These findings highlight a need to enhance standard of care practices related to driver screening, counseling, and reporting. Overall, providers recognized the importance of their role in advising patients about safe driving and desired standardized protocols for guiding conversations about driving with patients, PennDOT reporting, and referring patients to driver rehabilitation services.

Objective: Motor vehicle crashes remain a significant problem. Advanced driver assistance systems (ADAS) have the potential to reduce crash incidence and severity, but their optimization requires a comprehensive understanding of driver-specific errors and environmental hazards in real-world crash scenarios. Therefore, the objectives of this study were to quantify contributing factors using the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS), identify potential ADAS interventions, and make suggestions to optimize ADAS for real-world crash scenarios., Methods: A subset of the SHRP 2 NDS consisting of at-fault crashes ( n  = 369) among teens (16-19 yrs), young adults (20-24 yrs), adults (35-54 yrs) and older adults (70+ yrs) were reviewed to identify contributing factors and potential ADAS interventions. Contributing factors were classified according to National Motor Vehicle Crash Causation Survey pre-crash assessment variable elements. A single critical factor was selected among the contributing factors for each crash. Case reviews with a multidisciplinary panel of industry experts were conducted to develop suggestions for ADAS optimization. Critical factors were compared across at-risk driving groups, gender, and incident type using chi-square statistics and multinomial logistic regression., Results: Driver error was the critical factor in 94% of crashes. Recognition error (56%), including internal distraction and inadequate surveillance, was the most common driver error sub-type. Teens and young adults exhibited greater decision errors compared to older adults ( p  < 0.01). Older adults exhibited greater performance errors ( p  < 0.05) compared to teens and young adults. Automatic emergency braking (AEB) had the greatest potential to mitigate crashes (48%), followed by vehicle-to-vehicle communication (38%) and driver monitoring (24%). ADAS suggestions for optimization included (1) implementing adaptive forward collision warning, AEB, high-speed warning, and curve-speed warning to account for road surface conditions (2) ensuring detection of nonstandard road objects, (3) vehicle-to-vehicle communication alerting drivers to cross-traffic, (4) vehicle-to-infrastructure communication alerting drivers to the presence of pedestrians in crosswalks, and (5) optimizing lane keeping assist for end-departures and pedal confusion., Conclusions: These data provide stakeholders with a comprehensive understanding of critical factors among at-risk drivers as well as suggestions for ADAS improvements based on naturalistic data. Such data can be used to optimize ADAS for driver-specific errors and help develop more robust vehicle test procedures.

Rear-end crashes are closely related to car-following situation of vehicles. Speeding and insufficient headway are the major reasons as the drivers have not enough time to react to a sudden brake from the leading vehicle. Perceptual countermeasures, like speed reduction markings, are widely used in practice for accident prevention, and are verified with substantial effectiveness. However, compared with its practical application, the perceptual countermeasures are rarely analyzed in depth from the perspective of drivers' visual perception where the meaning of "perceptual" actually dwells. In addition, its effect on drivers' headway (distance) choice is almost ignored in previous research. Given this, the present study explored the effects of a certain type of perceptual treatment, i.e., the peripheral transverse line markings (PTLMs), on drivers' choice of speed and headway (distance) in car-following by a series of on-road experiments. In the on-road experiments, temporary line markings were installed on a real-world freeway in China to shape the PTLMs. The intersection angle (α) and the longitudinal spacing (λ) of the PTLMs were manipulated to attempt to associate the line markings with drivers' visual perception. Results of general and sectional relative differences of time headway (η h , θ h ), speed (η v , θ v ), and distance (η d , θ d ) suggests that 1) the speed was reduced, the distance and time headway were increased significantly after the installation of PTLMs when compared with the original condition; 2) a larger intersection angle (α) and a smaller longitudinal spacing (λ) of PTLMs could lead to a greater variations in speed and headway (distance); in particular, the PTLMs in a form of α=150°, λ=2m resulted in 0.44 s increase in time headway, 1.33 m/s reduction in speed, and 4.07 m increase in distance in maximum; 3) the real-time crash risk variations under the influence of PTLMs were evaluated by two modified and extended surrogate safety indicators. The effects of PTLMs were discussed and explained considering the influences of optical illusion on lane width narrowing, edge rate on speed and "discontinuity effect" on distance, respectively. The findings of this study provide theoretical support for the perceptual countermeasures and suggest comparative advantages of PTLMs in dealing with rear-end crashes by intervening drivers' speed and headway choice., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

We use a controlled experiment to analyze the impact of watching different types of educational traffic campaign videos on overconfidence of undergraduate university students in Brazil. The videos have the same underlying traffic educational content but differ in the form of exhibition. We find that videos with shocking content (Australian school) are more effective in reducing drivers' overconfidence, followed by those with punitive content (American school). We do not find empirical evidence that videos with technical content (European school) change overconfidence. Since several works point to a strong association between overconfidence and road safety, our study can support the conduit of driving safety measures by identifying efficient ways of reducing drivers' overconfidence. Finally, this paper also introduces how to use machine learning techniques to mitigate the usual subjectivity in the design of the econometric specification that is commonly faced in many researches in experimental economics., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The rapid development of expressways has led to an increasing number of place names that must be displayed on road guide signs. As a result, multi-board guide signs have been increasingly set up on expressways. The main aim of this study was to analyze the effect of the directional road sign displayed on multi and single-board signs on driver mental workload and behavior. 32 participants including 16 females (mean age = 24.7 years, standard deviation = 1.9 years) participated in the experiment and completed 3 driving simulation scenes. The setting of each scene-sign board was different: 1 board, 2 boards, and 3 boards. The driver needed to reach the designated destination according to the guidance of the road signs. Eye tracker was used to measure the fixation, saccade and electroencephalogram (EEG) was used to measure the alpha (8-13 hz) band absolute power in different signage scenarios. There are two major findings of the study. First, when the number of place names is less than or equal to 7, the multi-board sign generates more mental workload than the single-board sign does. The alpha band power of the driver's frontal area under the multiple boards is lower and affects driving performance (the deceleration is greater). Second, when the number of place names is more than 7, there is no significant difference in the effect on mental workload whether multi or single-board sign is used. However, compared to the single-board sign, drivers in the case of multi-board sign are likely to reduce the fixation duration and increase the number of saccades. The results suggest that it is not necessary to use multi-board signs when the number of place names is less than 7. These findings provide more safety considerations for the setting of multi-board guide signs in the future., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

This paper employed a high-fidelity driving simulator to investigate the impacts of the Wyoming Department of Transportation (WYDOT) Connected Vehicle (CV) Pilot's Traveler Information Messages (TIMs) on drivers' speed selection and the safety benefits of their speed harmonization. Three driving simulator experiment scenarios were developed to simulate the typical traffic and weather conditions on the rural Interstate 80 (I-80) in Wyoming. A total of 25 professional drivers from the WYDOT and trucking industry were recruited to participate in the driving simulator experiment. Participants' instantaneous speeds at various locations were collected to reveal the effects of CV TIMs on their speed selection. The results showed that average speed profiles under CV scenarios were generally lower than under baseline scenarios, particularly for winter conditions (snowy and severe weather). The variance of speed under CV scenarios was found to be significantly lower than the baseline scenarios, indicating that CV TIMs have the potential to harmonize the variations in speed. In addition, for the work zone driving simulator experiment, this research revealed that the mean time-to-collision (TTC) under baseline scenario is approximately 40 % lower than CV scenario, and the mean deceleration to avoid a crash (DRAC) under baseline scenario is approximately 19.3 % higher than CV scenario. These findings suggest that CV TIMs can reduce the risk of crashes. Research findings would provide the WYDOT with early insights into the effectiveness of CV TIMs, which could assist with developing more efficient transportation management strategies under adverse weather conditions., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Adaptive traffic signal control (ATSC) is a promising technique to improve the efficiency of signalized intersections, especially in the era of connected vehicles (CVs) when real-time information on vehicle positions and trajectories is available. Numerous ATSC algorithms have been proposed to accommodate real-time traffic conditions and optimize traffic efficiency. The common objective of these algorithms is to minimize total delay, decrease queue length, or maximize vehicle throughput. Despite their positive impacts on traffic mobility, the existing ATSC algorithms do not consider optimizing traffic safety. This is most likely due to the lack of tools to evaluate safety in real time. However, recent research has developed various real-time safety models for signalized intersections. These models can be used to evaluate safety in real time using dynamic traffic parameters, such as traffic volume, shock wave characteristics, and platoon ratio. Evaluating safety in real time can enable developing ATSC strategies for real-time safety optimization. In this paper, we present a novel self-learning ATSC algorithm to optimize the safety of signalized intersections. The algorithm was developed using the Reinforcement Learning (RL) approach and was trained using the simulation platform VISSIM. The trained algorithm was then validated using real-world traffic data obtained from two signalized intersections in the city of Surrey, British Columbia. Compared to the traditional actuated signal control system, the proposed algorithm reduces traffic conflicts by approximately 40 %. Moreover, the proposed ATSC algorithm was tested under various market penetration rates (MPRs) of CVs. The results showed that 90 % and 50 % of the algorithm's safety benefits can be achieved at MPR values of 50 % and 30 %, respectively. To the best of the authors' knowledge, this is the first self-learning ATSC algorithm that optimizes traffic safety in real time., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Adaptive traffic signal control (ATSC) systems improve traffic efficiency, but their impacts on traffic safety vary among different implementations. To improve the traffic safety pro-actively, this study proposes a safety-oriented ATSC algorithm to optimize traffic efficiency and safety simultaneously. A multi-objective deep reinforcement learning framework is utilized as the backend algorithm. The proposed algorithm was trained and evaluated on a simulated isolated intersection built based on real-world traffic data. A real-time crash prediction model was calibrated to provide the safety measure. The performance of the algorithm was evaluated by the real-world signal timing provided by the local jurisdiction. The results showed that the algorithm improves both traffic efficiency and safety compared with the benchmark. A control policy analysis of the proposed ATSC revealed that the abstracted control rules could help the traditional signal controllers to improve traffic safety, which might be beneficial if the infrastructure is not ready to adopt ATSCs. A hybrid controller is also proposed to provide further traffic safety improvement if necessary. To the best of the authors' knowledge, the proposed algorithm is the first successful attempt in developing adaptive traffic signal system optimizing traffic safety., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Autistic adults have decreased independence in community mobility and driving, which is associated with decreased participation in work, education and community participation. This is the first exploration of the development of community mobility, driving and participation skills over adolescence and emerging adulthood. Interviews with 15 mothers of autistic youth, capable of independence, were qualitatively analysed using grounded theory. Four major themes emerged: mothers gently pushing, teaching, letting go and working towards hopes and dreams. These results suggest earlier intervention across adolescence to address social skills, communication and anxiety in normative community environments, is required for successful development of community mobility and driving skills. Further understanding the critical role of confidence, feeling safe and accepted, could ultimately improve independence.

Determining the dissemination and communication plans and activities of research projects is an important part for transferring research outputs to the target audience. This paper presents the dissemination and communication plans and activities of the CrowdHEALTH project. Towards this end, the methodology and results are presented in this paper.

Vehicle platoons involve groups of vehicles travelling together at a constant inter-vehicle distance, with different common benefits such as increasing road efficiency and fuel saving. Vehicle platooning requires highly reliable wireless communications to keep the group structure and carry out coordinated maneuvers in a safe manner. Focusing on infrastructure-assisted cellular vehicle to anything (V2X) communications, the amount of control information to be exchanged between each platoon vehicle and the base station is a critical factor affecting the communication latency. This paper exploits the particular structure and characteristics of platooning to decrease the control information exchange necessary for the channel acquisition stage. More precisely, a scheme based on radio environment map (REM) reconstruction is proposed, where geo-localized received power values are available at only a subset of platoon vehicles, while large-scale channel parameters estimates for the rest of platoon members are provided through the application of spatial Ordinary Kriging (OK) interpolation. Distinctive features of the vehicle platooning use case are explored, such as the optimal patterns of vehicles within the platoon with available REM values for improving the quality of the reconstruction, the need for an accurate semivariogram modeling in OK, or the communication cost when establishing a centralized or a distributed architecture for achieving REM reconstruction. The evaluation results show that OK is able to reconstruct the REM in the platoon with acceptable mean squared estimation error, while reducing the control information for REM acquisition in up to 64% in the best-case scenario.

Sand-dust environment affects drivers' perceptions of surrounding traffic conditions, resulting in unsafe operations. From an ergonomics perspective, such adverse effects could be alleviated by environment control as well as the assistance of machines. Vehicle-to-vehicle (V2V) communication appears to be an important component of machines in future traffic systems, which could support the driving task. In order to explore what influences V2V communication would generate on traffic systems, this paper proposes a car-following model accounting for V2V communication in a sand-dust environment. The results indicate that V2V communication helps to reduce the fluctuations of acceleration, headway, and velocity, when a small perturbation is added to the traffic flow in sand-dust environment. If a vehicle in the traffic flow stops suddenly, the number of crumped vehicles decreases with V2V communication taken into account. Furthermore, the residual velocities of the crumped vehicles decrease, which means the severity of collision is suppressed. It is concluded that V2V communication can play an active role in the improvement of traffic safety in a sand-dust environment., Competing Interests: The authors declare no conflicts of interest.

Introduction: In an aging society that is more and more information-oriented, being able to replace human passengers' protective effects on vehicle drivers with those of social robots is both essential and promising. However, the effects of a social robot's presence on drivers have not yet been fully explored. Thus, using a driving simulator and a conversation robot, this experimental study had two main goals: (a) to find out whether social robots' anthropomorphic qualities (i.e., not the practical information the robot provides drivers) have protective effects by promoting attentive driving and alleviating crash risks; and (b) by what psychological processes such effects emerge., Method: Participants were recruited from young (n = 38), the middle-aged (n = 39), and the elderly (n = 49) age groups. They were assigned to either the treatment group (simulated driving in a conversation robot's presence) or the control group (simulated driving alone), and their driving performance was measured. Mental states (peaceful, concentrating, and reflective) also were assessed in a post-driving questionnaire using our original scales., Results: Although the group of older participants did not experience protective effects (perhaps due to motion sickness), the young participants drove attentively, with the robot enhancing peace of mind. The protective effect was also observed among the middle-aged participants, and the verbal data analysis ascribed this to the robot's role of expressing sympathy, especially when the middle-aged drivers nearly had not-at-fault crashes, which caused them to be stressed. In conclusion, we discuss the practical implications of the results., (Copyright © 2019 National Safety Council and Elsevier Ltd. All rights reserved.)

This study investigates how timing of the introduction of unpleasant emotional tone in a traffic safety video impacts the intensity of the viewer's emotional experience. Traffic safety advertising is a multi-million-dollar business in the United States. In many instances, 30-60 s ads are produced to raise awareness of the consequences of unsafe behaviors with the expectation that simply providing information will motivate safer behaviors. Producing videos intended to generate behavior change requires a complex understanding of what motivates behavior. Behavior change theory, neuroscience, and psychophysiology all provide guidance to improve the persuasive power of traffic safety videos. This study consisted of a 3 (message tone) × 3 (video) × 4 (order) repeated measures within subjects designed experiment. Participants ( N  = 75) were 20-30-year-old men who were shown nine traffic safety videos. Arousal intensity, attention, and negative emotion were tracked with the psychophysiological measures of skin conductance (measuring intensity of arousal), heart rate (measuring attention paid during the video), and corrugator muscle activation (measuring the negative emotional experience). Videos with three different aversive tones were used, low, high, and videos in which the tone switched from low to high aversive. Aversive tone is defined as stimuli that motivate a desire to escape or avoid something like death or pain. All videos were designed to prevent motor vehicle crashes. The results obtained from this study indicate that when attempting to persuade males aged 20-30 to practice safer driving behaviors, switched message tone appears to be the most effective message design in terms the intensity of emotional arousal and maintenance of attention.

This randomized controlled trial evaluated the impact of integrating Steering Teens Safe, a parent communication intervention, with feedback from an in-vehicle video recording system. In-vehicle video systems that trigger a recording when the vehicle exceeds a g-force threshold have been used to provide feedback to young drivers. Few of these programs have involved parental engagement. Parent-teen dyads were randomized to three groups and 150 dyads completed the study. All groups received an in-vehicle video system that recorded driving events. The control group received no feedback or intervention. In the first intervention group, teens received real-time feedback, and parent-teen dyads received summary feedback, based on information recorded by the in-vehicle system. The second intervention group received the same feedback, plus parents were taught strategies to improve communication with their teen about safe driving. The primary outcome variable was unsafe driving event rates per 1000 miles driven and the primary independent variable was group assignment. Generalized linear models were used to calculate effect estimates. Compared with the control group, the Event Recorder Feedback group had a rate ratio of 0.35 (95% CI = 0.24 - 0.50) and the combined intervention group (Event Recorder Feedback and parent communication) had a rate ratio of 0.21 (95% CI = 0.15 - 0.30). Furthermore, the combined intervention group had a significantly lower event rate than the Event Recorder Feedback only group (rate ratio = 0.60, 95% CI = 0.41 - 0.87). While in-vehicle feedback systems can help reduce unsafe driving events in early independent driving, teaching parents strategies for effective communication with their young driver may further improve impact., (Copyright © 2019. Published by Elsevier Ltd.)

Objectives: Teen drivers are at increased crash risk, largely due to lack of experience. Parents play a key role in influencing teen behaviors and attitudes around driving safety. Parent-involved interventions may improve teen driving safety but tend to be resource intensive and have limited scalability. In this study, we examined how family communication patterns (FCPs) impact teen risky driving and the effectiveness of a parent-focused teen driving intervention. Methods: Our data came from a large randomized controlled teen driving intervention trial. We randomized parent-teen dyads into one of 3 groups: parent communication intervention plus in-vehicle event recorder feedback ; in-vehicle event recorder feedback only ; or control . The primary outcome variable was teen risky driving (self-reports and triggered events); the primary exposure variables were FCPs and intervention group. We used generalized linear models to calculate effect estimates. Results: Teens' baseline risky driving did not vary by family communication pattern. The impact of the parent-focused intervention was stronger in families with a laissez-faire FCP. The laissez-faire FCP focuses little on child conformity and downplays communication. Conclusions: These results provide a framework for targeting high-resource teen driving interventions (event recorder feedback and parent-communication training) to families with laissez-faire communication patterns to attain the greatest risk reductions.

Background: Older adult drivers may experience decreases in driving safety with age or health status change. Discussing driving safety may help them plan for driving restriction and eventual cessation. Here, we sought to examine conversations between older adults and their family members and physicians., Methods: In this multi-site cross-sectional analysis of baseline data from the AAA Longitudinal Research on Aging Drivers (LongROAD) cohort study, we measured the prevalence and characteristics of family and physician driving discussions. We examined associations between having driving discussions and participant characteristics using multivariate logistic regression., Results: Of 2990 current drivers aged 65 to 79 years (53% female, 85.5% White), only 14.2% reported discussing driving safety with family and 5.5% had discussions with physicians. Men (adjusted OR, 1.32; 95% CI, 1.05 to 1.66) and those with Master's degrees or higher (adjusted OR, 1.65; 95% CI, 1.27 to 2.13) more often had family discussions. Those with at least a Master's degree were also more likely to speak with their physician (adjusted OR, 1.77; 95% CI, 1.17 to 2.68)., Conclusion: Few older adults had driving safety conversations with their family or physicians. Practical and effective interventions are needed to engage family and physicians in assisting older adults with risk assessment and driving cessation planning to maintain mobility and well-being., Competing Interests: Conflict of interest: none declared., (© Copyright 2019 by the American Board of Family Medicine.)

Operators of highly automated driving systems may exhibit behaviour characteristic for overtrust issues due to an insufficient awareness of automation fallibility. Consequently, situation awareness in critical situations is reduced and safe driving performance following emergency takeovers is impeded. A driving simulator study was used to assess the impact of dynamically communicating system uncertainties on monitoring, trust, workload, takeovers, and physiological responses. The uncertainty information was conveyed visually using a stylised heart beat combined with a numerical display and users were engaged in a visual search task. Multilevel analysis results suggest that uncertainty communication helps operators calibrate their trust and gain situation awareness prior to critical situations, resulting in safer takeovers. In addition, eye tracking data indicate that operators can adjust their gaze behaviour in correspondence with the level of uncertainty. However, conveying uncertainties using a visual display significantly increases operator workload and impedes users in the execution of non-driving related tasks. Practitioner Summary: This article illustrates how the communication of system uncertainty information helps operators calibrate their trust in automation and, consequently, gain situation awareness. Multilevel analysis results of a driving simulator study affirm the benefits for trust calibration and highlight that operators adjust their behaviour according to multiple uncertainty levels.

In the near future, more vehicles will have automated functions. The traffic system will be a shared space of automated and manually driven vehicles. In our study we focused on the perspective of vulnerable road users, namely pedestrians, in cooperative situations with automated vehicles. Established communication methods, such as eye-contact between pedestrians and drivers, may no longer work when automated vehicles represent the interaction partner. Therefore, we evaluated several human-machine-interfaces (HMI) in order to implement smooth and comfortable communication. We conducted a two-stage study consisting of an explorative focus group discussion with naïve pedestrians (n = 6), followed by an experimental video simulation study (n = 25) based on the results of the focus group discussion. From the focus group we sought member opinion about various HMI, upon presentation of acoustic and visual communication systems such as projections, displays and LED light strips, in addition to portable communication systems, specifically smart watches. On the basis of the focus group discussion, an evaluation criteria was derived. For the video simulation study, HMI designs were created with variations in position, type and coding of the message, and technology. These were assessed by 25 subjects according to the focus discussion derived evaluation criteria: recognizability, unambiguousness, interaction comfort and intuitive comprehensibility. The results show that direct instructions to cross the street are preferred over status information of the vehicle and that large-scale text-based messages from the vehicle to the pedestrian, deliver better results. Design recommendations for HMIs for communication between automated vehicles are derived, and the extent external HMIs may supplement informal communication strategies such as vehicle movement or braking maneuvers, is discussed., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: Connected and automated vehicles (CAV) can monitor multiple vehicles ahead via vehicle-to-vehicle (V2V) communication. Although feedback information from more vehicles ahead may be more helpful for anticipations, it also makes control more complex and increases the probability of data packet loss. Then it needs an appropriate number of CAV feedback links, and the maximum number may be not suitable. Therefore, this article focuses on the influence of CAV feedback links on rear-end collision risks., Methods: To deal with this, stability analysis of a CAV car-following model was conducted to obtain the designs of CAV feedback gains for maintaining stable CAV flow. Simulation experiments were performed to describe a traffic accident on freeway, using car-following models of manually driven vehicles (MDVs) and CAV under different CAV penetration rates. Four scenarios are considered in simulation experiments; that is, the CAV monitors 1, 2, 3, and 4 preceding vehicles, respectively. Based on the simulation experiments, surrogate safety indicators, time-exposed time-to-collision (TET), and time-integrated time-to-collision (TIT) are used to evaluate risks of rear-end collisions., Results: Results indicated that CAV helped to decrease the collision risks, especially the more serious collision risks with smaller threshold values of time-to-collision (TTC). In addition, the reductions in collision risks are more obvious when CAV feedback changes from one link to 2 links. In addition, reducing amplitudes are not significant if the CAV feedback is extended from 2 links to 3 or 4 links., Conclusions: Two links of CAV feedback are appropriate when control complexity is a priority, whereas 3 links is the better choice when reductions in collisions are a priority. The findings of this study provide helpful reference for CAV control and design before larger-scale implementation in real vehicles.

Purpose: Analyze qualitative and quantitative data to determine the relative effectiveness of theoretically-developed anti-speeding messages, as judged by relatively inexperienced and experienced drivers, both for themselves as a driver, and for drivers in general., Method: Eight focus groups and three individual interviews were conducted. Participants initially completed a questionnaire, ranking sets of three anti-speeding messages representing each of the six components of protection motivation theory (PMT). Participants were encouraged to write down the reasons for their rankings. During group and individual facilitation sessions, the rankings and reasons for them were discussed to identify salient reasons for participants' judgments. The ranking data were analyzed quantitatively, with individual and group-based comments being analyzed thematically., Results: Quantitative analyses of message pairs revealed five third-person effects (TPEs). Three messages were perceived as more relevant to drivers in general than to the participant-as-driver while two were associated with reverse TPEs, which participants perceived as more relevant to themselves-as-driver than for drivers in general. For four PMT components (rewards, self-efficacy, response efficacy, response costs), one or more messages received significantly higher rankings than one or more other messages representing the same component. Substantial variation was found within the individual and group discussion comments in respect of nearly all the messages, reflecting different driver perspectives and demographics., Discussion: A general preference for shorter messages was evident, leading to a revision of most of the messages comprising the stimuli for this study. On the basis of the focus group and interview responses, consideration was given as to which messages would be recommended for a pilot field study., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

As the desire for deploying automated ("driverless") vehicles increases, there is a need to understand how they might communicate with other road users in a mixed traffic, urban, setting. In the absence of an active and responsible human controller in the driving seat, who might currently communicate with other road users in uncertain/conflicting situations, in the future, understanding a driverless car's behaviour and intentions will need to be relayed via easily comprehensible, intuitive and universally intelligible means, perhaps presented externally via new vehicle interfaces. This paper reports on the results of a questionnaire-based study, delivered to 664 participants, recruited during live demonstrations of an Automated Road Transport Systems (ARTS; SAE Level 4), in three European cities. The questionnaire sought the views of pedestrians and cyclists, focussing on whether respondents felt safe interacting with ARTS in shared space, and also what externally presented travel behaviour information from the ARTS was important to them. Results showed that most pedestrians felt safer when the ARTS were travelling in designated lanes, rather than in shared space, and the majority believed they had priority over the ARTS, in the absence of such infrastructure. Regardless of lane demarcations, all respondents highlighted the importance of receiving some communication information about the behaviour of the ARTS, with acknowledgement of their detection by the vehicle being the most important message. There were no clear patterns across the respondents, regarding preference of modality for these external messages, with cultural and infrastructural differences thought to govern responses. Generally, however, conventional signals (lights and beeps) were preferred to text-based messages and spoken words. The results suggest that until these driverless vehicles are able to provide universally comprehensible externally presented information or messages during interaction with other road users, they are likely to contribute to confusing and conflicting interactions between these actors, especially in a shared space setting, which may, therefore, reduce efficient traffic flow., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)