An examination of the influence of crosswalk marking removal on pedestrian safety as reflected in road user behaviours

In some local authorities in Israel, road markings were removed from non-signalised crosswalks situated on multilane divided urban roads. This study examined whether this treatment contributes to pedestrian safety, based on the analysis of differences in road user behaviours and pedestrian crossing conditions at sites without crosswalk markings (treatment sites) versus those with the markings (comparison sites). Field observations were conducted at two treatment and four comparison sites, including video-recordings and free-flow speed measurements. The speed data analysis indicated that treatment sites were associated with higher speeds as compared to other sites, at least in one travel direction, and that speed values were sufficiently high to create a threat of severe injury for the crossing pedestrians. Examinations of other road user behaviours showed that treatment sites are associated with higher obedience of pedestrians to safe crossing rules and low rates of pedestrian-vehicle conflicts during the crossing, but also with long waiting times by pedestrians prior to crossing, low rates of giving-way to pedestrians and more vehicles ignoring pedestrian needs to cross. In general, pedestrian crosswalk removal brought about a worsening in the possibility of crossing the road for pedestrians that in combination with high vehicle speeds cannot be recognised as a safety-improving measure. The study did not support the claim that removing a marked crosswalk leads to safety benefits for pedestrians.     

Surrogate safety indicator for unsignalised pedestrian crossings

ProblemAlthough the road safety situation in Poland is generally improving, the number of accidents at pedestrian crossings has not decreased in the last four years. This paper presents the results of the MOBIS research project, the aim of which was to develop surrogate safety indicators, based on detection of pedestrian-vehicle conflicts using video analysis.MethodPedestrian and vehicle traffic was filmed at two unsignalised pedestrian zebra crossings in Warsaw and Wrocław for over 40 days. Motion trajectories of vehicles and pedestrians were determined based on video processing. Several variables describing pedestrian-vehicle interactions were calculated, such as speed, post-encroachment time, distance between the participants, decelerations, etc. Classification of encounters was based on interactions of pedestrians and vehicles i.e. drivers yielding to pedestrians, vehicles passing just in front of, or behind pedestrians.Results and discussionCriteria for identification of dangerous encounters were selected with the assumption that it should be possible to automate the assessment process. The selected variables were: pedestrian-vehicle passing distance and the vehicle speed at that moment. Other criteria were used in cases of abrupt braking – deceleration exceeding 4 m/s² and vehicle speed. A Dangerous Encounter Index is proposed as a surrogate safety indicator for pedestrian crossings. It relates the occurrence of dangerous events to exposure, defined as the number of pedestrian-vehicle encounters.Practical applicationsThe proposed index shows that crossing two lanes involves more risk than crossing one lane, given similar traffic flow. Some improvement of safety at both types of crossing was observed after active signage involving blinking lights had been introduced. The proposed method is a step towards automation of safety assessment.     

Evaluating the influence of approaching vehicles on pedestrian’s visual patterns and crossing behaviors at an uncontrolled crosswalk

The visual behaviors and movement characteristics of pedestrians are related to their surrounding potential safety hazards, such as approaching vehicles. This study primarily aimed to investigate the visual patterns and walking behaviors of pedestrians interacting with approaching vehicles. Field experiments were conducted at two uncontrolled crosswalks located at the Cuihua and Yanta roads in Xi’an, China. The visual performance of pedestrians was assessed using the eye tracking system from SensoMotoric Instruments (SMI). Moreover, motion trajectories of the pedestrians and approaching vehicles were obtained using an unmanned aerial vehicle. Subsequently, the visual attributes and movement trajectories of pedestrians and motion trajectories of approaching vehicles were statistically analyzed. The results showed that approaching vehicles distracted the fixation of crossing pedestrians significantly, and occupied 29.5% of the total duration of fixation; that is, pedestrians always directed more fixation points to the approaching vehicles compared to other stimuli. As a vehicle approached, pedestrians’ fixation shifted from other areas of interest to the vehicle. Moreover, an increase in the velocity of the vehicle and a closer distance between pedestrian and the vehicle resulted in an increase in the pedestrians’ duration of fixation on the approaching vehicle, and they implemented more saccades. Furthermore, approaching vehicle’s velocity and distance between pedestrian and approaching vehicle are not significantly associated with pedestrian’s movement attributes. These findings provide insights into the crossing behavior of pedestrians during pedestrian-vehicle interactions, which could assist future researchers and policy makers.     

Hazard-based duration approach for understanding pedestrian crossing risk exposure at signalised intersection crosswalks – A case study of Kolkata,India

Pedestrian signal violation is a significant concern among policymakers and traffic engineers as this leads to a pedestrian-vehicle crash. The waiting time for a pedestrian at intersections is crucial in street-crossing decision-making. Once pedestrians terminate their waiting behaviour during the red-light period, they would cross in the red light and put themselves in danger. A total of 2089 red-light arriving pedestrian observations were made at eight intersection crosswalks across Kolkata city (India). With the help of hazard-based duration models, the waiting duration till signal violation has been analysed. Kaplan–Meier curve has been plotted to understand the survival probabilities. A semi-parametric Cox Proportional Hazard model was used to understand the different factors influencing signal violation behaviour. However, the proportional hazard assumption was not satisfied. Therefore, a parametric Accelerated Failure Time (AFT) model was used to understand the various covariates that affect the waiting duration. The results highlighted that 49.5% of pedestrians crossed immediately after arriving at the intersection in the red-light phase. A pedestrian’s probability of crossing the road when it is unsafe, i.e., motor vehicles still have green or yellow, varies with the waiting time. As waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at an increased risk of being struck by a motor vehicle. The covariate analysis using the AFT model showed that pedestrian glance/looking behaviour, different types of distractions, signal cycle length, carrying luggage, and traffic plying on the road impacted signal violation behaviour. Signal modifications by reducing red-light phase length for pedestrians might be the most efficient means of reducing the likelihood of signal violation and being hit by a motor vehicle.     

Pedestrian compliance and cross walking speed adaptation due to countdown timer installations: A self report study

Although they are aware of the possible risk, a high number of pedestrians still violate the red light indication and cross the road illegally. This hazardous behaviour may cause incidents between them and the road vehicles. In order to reduce this illegal behaviour, the traffic signals are equipped with countdown timers, in order to provide more information and decrease pedestrians’ noncompliant behaviour. The main purpose of the present paper is to investigate the influence of countdown timers on pedestrians’ compliance regarding their crossing behaviour at intersections as well as to examine the parameters affecting walking speed adaptation. In the context of this analysis two regression models were developed. The first model is a binary logistic regression model which examines pedestrians’ self reported compliance. The results showed that the gender, the age, the perceived comfort and the seconds remaining for the onset of red light are the main parameters that affect compliance. The second model is an ordinal regression model which examines the factors that make pedestrians adapt their walking speed as they are crossing the road and are informed by the countdown timers about the second remaining for the termination of the green phase. The results of the second model revealed that the age, the compliance and the perceived assistance that the countdown timer provides for the walking speed adaptation affect the minimum remaining time before a pedestrian accelerates.     

Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks

Pedestrian is vulnerable to mortality and severe injury in road crashes. Red light running violation of pedestrians is one of the leading causes to the crashes at signalized intersections, at which the crash involvement rates of pedestrians are high. Therefore, it is important to identify the factors that affect the propensity of red light running of pedestrian. In this study, effects of both personal factors (pedestrians’ demographics and behavior) and environmental factors (presence and behavior of other pedestrians, signal time, and traffic condition) on the individual decision of red light running violation are examined, using the video observation surveys at the signalized crossings that are prone to pedestrian-vehicle crashes and have moderate pedestrian and vehicular traffic volumes in the urban area. Crossing behaviors of 6320 pedestrians are captured. Results of a random parameter logit model indicate that pedestrian gender, age, number of lanes, presence of a companion, number of pedestrians around, presence of other violators in the same cycle, time to green, red time, traffic volume, and percentage of heavy vehicles all affect the propensity of red light running violation of pedestrians. Also, there are significant interaction effects by pedestrian’s gender and age, presence of other violators, with a companion, and traffic volume on the propensity. Findings are indicative to the development of effective engineering, enforcement and educational initiatives combating the red light running violation behavior of pedestrians. Therefore, pedestrian safety level at the signalized intersections can be enhanced.     

The gait of visually impaired pedestrians

The stride lengths, stride durations and walking speeds of visually impaired pedestrians were recorded under two conditions: firstly accompanied by a sighted guide, secondly walking independently. The same outdoor route was used for both conditions. When accompanied subjects walked at approximately the same speed as they would have on a force platform. However, when independent they were significantly slower (p = 0.051), with smaller strides (p = 0.083) which were of a longer duration (p = 0.062). Research into the gait of visually impaired pedestrians needs to take account of the effect of route conditions and the type of mobility aid being used.     

Lessons learned from pedestrian-driver communication and yielding patterns

Understanding the hidden patterns of tacit communication between drivers and pedestrians is crucial for improving pedestrian safety. However, this type of communication is a result of the psychological processes of both pedestrians and drivers, which are very difficult to understand thoroughly. This study utilizes a naturalistic field study dataset and explores the hidden patterns from successful and failed communication events using a pattern recognition method known as Taxicab Correspondence Analysis (TCA). The successful communication scenarios indicate the combinations of variable attributes such as eye contact, facial expression, the assertion of crossing, and effective traffic control devices are strongly associated with successful scenarios. The patterns for failed scenarios are most likely to be on the roadway with a relatively higher speed limit (e.g., 35 mph) and a relatively lower speed limit (e.g., 15 mph) under different conditions. On roadways with a higher speed limit, the failed scenarios are highly associated with passive and undecisive pedestrians, pedestrians far away from the crosswalk, regardless of pedestrian-driver eye contact and facial expression of the pedestrians. Instead of waiting for pedestrians to making a crossing decision, overspeeding drivers are more likely to speed up and pass the crosswalk. On roadways with a lower speed limit, the failed scenarios are often associated with distracted pedestrians, vehicles having the right of way, and the absence of effective traffic control devices. These findings could help transportation agencies identify appropriate countermeasures to reduce pedestrian crashes. The findings on driver-pedestrian communication patterns could provide scopes for improvement in computer vision-based algorithms designed for autonomous vehicle industries.     

Analysis of the occurrence and severity of vehicle-pedestrian conflicts in marked and unmarked crosswalks through naturalistic driving study

BackgroundAlthough many studies have been conducted on the safety of pedestrian crossings, few researches have been focused on drivers' behavior in unmarked crosswalk and marked crosswalk areas. Considering that statistics of pedestrian accidents are not the same in the two types of crossing area, based on the last report of the World Health Organization, it is very critical to evaluate driver yielding behavior to determine the differences in the actions of drivers when encountering pedestrians in the two areas.MethodsThis study was conducted based on surrogate measures of safety (SMoS) collected through a Naturalistic Driving Study on 52 participants in Iran. The study was carried out from April 2017 to April 2018 using the installation of cameras in the private vehicle of the participants. The analysis of the recorded films showed that 956 conflicts have occurred in unmarked crosswalks and 392 conflicts in marked crosswalks, respectively.ResultsA model was developed for driver yielding behavior using binary logistic regression, and showed that yielding rates in unmarked crosswalsk were about fifty percent of the yielding rates in marked crosswalks. Based on the model, it is indicated that the aggressive behavior of pedestrians during the crossing, such as running, zigzag and diagonal crossing, as well as the late detection of pedestrians by drivers resulting from high-speed driving in the unmarked crossing areas, will reduce the yielding behavior rate. Also, using the Swedish traffic conflicts technique, the severity of the conflicts was classified into four general categories: encounter, potential, slight, and serious conflict, through 30 different levels on the basis of conflicting speed and time to the accident. The results showed that pedestrians behavior during conflicts of the group “encounter” and drivers’ behavior during conflicts of the groups of “potential”, “slight” and “serious”, were the principal factors in preventing collision through an evasive maneuver. The results showed that increasing the level of conflict severity, which indicates an increase of the conflicting speed and a decrease of the time remaining to point of a possible collision with pedestrian, causes drivers to yield a harsh-maneuver to prevent collision. Soft-maneuvers such as deceleration and acceleration, as well as harsh-maneuvers such as changing the lane/stop during conflicts were most driver yielding behavior during conflict groups of slight and serious. According to the results of the analysis, the behavior of drivers in marked crossing areas is better than in the unmarked crossing area, leading to safer crossing for pedestrians.ConclusionsThis study suggests that the significant differences in driver yielding behavior in the two areas is due to the late detection of pedestrians by drivers and also the less proper action by them in unmarked crosswalk areas. Thus, the probability of accidents in Unmarked Crossing areas is higher than in marked crossing areas. Consequently, the design of improved advanced driver assistance systems to identify the risk of pedestrian accident may improve the driver yielding behavior and thus increase the safety of pedestrians.     

The influence of the built environment on pedestrians’ perceptions of attractiveness,safety and security

Perceptions of the walking environment can encourage or discourage walking for transport. However, the influence of the built environment (BE) on pedestrians’ perceptions of the walking environment has not been fully understood. To address this gap, the present research investigates how BE characteristics of a suburban walking environment are associated with the perceptions of attractiveness (i.e., pleasantness, friendliness), safety, and security. Using a cross-sectional design, 995 participants reported their perceptions about the attractiveness, safety, and security of different suburban BE scenarios in Brisbane (Australia). Univariate and bivariate random effect ordered probit models were estimated to identify the associations between BE characteristics and perceived attractiveness, safety, and security whilst controlling for psychosocial factors. Results indicated that perceived attractiveness (i.e., pleasantness and friendliness) was higher for recreational areas than residential land use. Women perceived the walking environment as more pleasant with trees. The perception of safety was higher for recreational and vacant land compared to residential areas. Young pedestrians perceived that the likelihood of being assaulted/robbed/harassed at night was lower if they walked through an area with commercial and mixed land use. Women pedestrians perceived that the corresponding risk at night was higher in recreational areas. Overall, the findings suggest that urban design strategies such as increasing land use diversity and providing adequate trees enhance perceived environmental attractiveness, safety, and security, ultimately resulting in more walking for transport.     

Survival analysis: Pedestrian risk exposure at signalized intersections

Pedestrian behaviour was observed at seven selected intersections in Delhi, India. Data collection occurred at these intersections by placing a video camera at each zebra crossing. Pedestrian crossing behaviour was then obtained from careful review of the videotapes. Pedestrian crossing behaviour was analyzed using survival analysis statistical methodology. The analyses produce Kaplan–Meier survival curves for waiting time prior to crossing unsafely, separately for males and females, and for each intersection. Mean observed waiting time and model-based waiting time of 90% of pedestrians were then studied. Mean waiting time of females are 27% more than for males, while the waiting time of 90% of female pedestrians are 44% more than the corresponding number for males. The probability for a pedestrian to cross the road, when it is unsafe, i.e. motor vehicles still have green or yellow, varies with waiting time. People do not want to wait too long to cross streets. As signal waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at increased risk of being struck by a motor vehicle. Thus, reducing the waiting time for pedestrians are likely to decrease the probability of pedestrian crossers being hit by a motor vehicle.     

Effects of speed display signs on driving speed at pedestrian crossings on collector streets

This study was designed to evaluate the short- and long-term effects of speed display signs on driving speed at pedestrian crossings in a low-speed (40 km/h) urban environment. Driving speeds were compared 1 week before installation, after installation (1 week; 1 month; 3 months; 5 months) and 1 week after removal. The main results showed that the speed displays decreased the mean speed by 0.5–2.9 km/h, which translates to a 4–22% drop in pedestrian fatality risk. Furthermore, there was a drop in the proportion of speeding vehicles and approaching speed of individual vehicles. The decrease in speed persisted over time, suggesting that speed displays may reduce speeds in the long term. In conclusion, installing speed displays at pedestrian crossings on collector streets reduces driving speeds and could contribute to the safety of pedestrians.     

Changes in road-user behaviors following the installation of raised pedestrian crosswalks combined with preceding speed humps,on urban arterials

In this study, raised pedestrian crosswalks were installed at non-signalized mid-block crosswalks situated on urban arterial and collector roads. A raised crosswalk is built by installing a trapezoidal speed hump on the crosswalk area, building a preceding circular speed hump, in each travel direction, and adding traffic signs. A controlled field-study was conducted at eight sites, sixteen pedestrian crosswalks, where road user behaviors were compared in the after versus before the treatment periods. Two settings of raised crosswalks were applied at the study sites: a 15 cm high trapezoidal hump combined with 8–10 cm high circular humps, and a 10–12 cm high trapezoidal hump combined with 6–8 cm high circular humps. Field observations included video-recordings and free-flow speed measurements. Following the installation of the raised crosswalks, at most sites, a substantial decrease was observed in vehicle travel speeds while approaching the crosswalks, which was maintained over-time. In addition, at some crosswalks, improvements were found in the rates of giving-way to pedestrians by the vehicles, vehicle-pedestrian conflicts and shares of pedestrians who cross within the crosswalk boundaries, while the changes in keeping safe crossing rules by pedestrians were mixed. Overall, the changes in road user behaviors following the installation of the raised crosswalks were positive and associated with safety improvement of pedestrian crossing conditions. Based on the study results, raised crosswalks with preceding speed humps can be promoted as a pedestrian safety-improving measure on busy urban roads.     

The safety margin and perceived safety of pedestrians at unmarked roadway

Many pedestrians cross out of crosswalks (i.e., unmarked roadway) in developing countries, but researches about their safety are under reported. This study explored safety related factors and their casual relations at unmarked roadway. Videos of 254 pedestrians’ crossing process were analyzed objectively on safety and evaluated subjectively on perceived safety. The two safety indexes are consistent on important factors, with higher running frequency reduce safety while bigger group size increase safety. The two factors had contrary effect on pedestrian speed, which is positively related with safety. Higher looking frequency before crossing also enhance safety, partly by reducing running frequency and increasing going backwards with its planning nature. Longer waiting time before crossing can facilitate this planning behavior while at the same time leads to bigger group size. Buses are safer than cars, but they are not perceived as safer. In situations where only some vehicles yield, yielding ones bring danger due to sight blocking of unyielding ones in adjacent lanes. These findings can be applied to the design of intelligent transportation systems and the education of drivers and pedestrians to improve safety.     

自动驾驶汽车与行人交互中的沟通界面设计：基于行人过街决策模型的评估

自动驾驶汽车要进入人车混行的普通道路, 需确保与过街行人之间的交互安全和效率。为解决这一问题, 高等级自动驾驶汽车往往在车辆外部装置显示设备, 即外部人机界面(eHMIs)以和行人沟通信息。在具体设计上, 已有研究主要采用文字、图形、投影等视觉沟通形式, 传达车辆状态(是否在自动驾驶模式)、意图和对行人的过街建议等沟通信息, 并在真实路段实验、虚拟场景及实验室实验等情境中评估了界面的使用对行人过街意向、速度和准确性等指标的影响。然而, 以行人为中心的外部界面设计需系统地支持行人过街决策前各阶段的信息加工需求。因此, 我们结合行人过街决策过程和情境意识理论, 提出行人与自动驾驶汽车交互中的动态过街决策模型, 从行人认知加工视角评估各种界面的沟通效果。评估的结果启示, eHMIs应促进行人对车辆信息的感知、理解和预测。在感知阶段, 应采用多种类型界面、多呈现载体相结合, 增强信息的可识别性。在理解阶段, 需结合文字说明、合理选择沟通视角、信号标准化和培训提高可理解性。在预测阶段, 应结合车辆内隐运动信息, 帮助行人快速准确获取车辆未来行动意图。更重要的是, 未来研究应关注在多行人、多车辆混行情境下的信息沟通设计及其对行人的影响。理论方面, 未来研究也需要关注外部界面如何通过自下而上的通路影响情境意识和心智模型的形成。     

A method in modeling interactive pedestrian crossing and driver yielding decisions during their interactions at intersections

Investigating pedestrian crossing and driver yielding decisions should be an important focus considering the high risks of pedestrians in exposed to motorized traffic. Limitations, however, exist in previous studies – variables considered previously have been limited; how their behavior affect each other (defined as interactive impacts) were not sufficiently considered. This paper aims to provide a methodological approach for pedestrian crossing and driver yielding decisions during their interactions, considering of different variable types including interactive impact variables, traffic condition variables, road design variables, and environment variables. A Distance-Velocity (DV) framework proposed in an earlier study is introduced for definitions and concepts in studying pedestrian-vehicle interactions. Logistic regression, support vector machines, neural networks and random forests, are introduced as candidate models. A case study involving six crosswalk locations is conducted, focusing on interactions between pedestrians and right-turn vehicles. The proposed methodological approach is applied, with the performance of the four machine learning methods compared in terms of model generalization and confusion matrix. The model with the best performance is further compared to the typical gap-based model. Results show that random forest and logistic regression models performed the best in modeling pedestrian crossing and driver yielding decisions respective, in terms of model generalization. Besides, the DV-based modeling method (average accuracy of over 90% for pedestrians and 80% for drivers) outperformed the traditional gap-based method in all test seeds. As a key finding, interactive impacts from each other (the pedestrian and the driver) act as a key contributing variable on their decisions.     

The estimation of vehicle speed and stopping distance by pedestrians crossing streets in a naturalistic traffic environment

The ability to estimate vehicle speed and stopping distance accurately is important for pedestrians to make safe road crossing decisions. In this study, a field experiment in a naturalistic traffic environment was conducted to measure pedestrians’ estimation of vehicle speed and stopping distance when they are crossing streets. Forty-four participants (18–45 years old) reported their estimation on 1043 vehicles, and the corresponding actual vehicle speed and stopping distance were recorded. In the speed estimation task, pedestrians’ performances change in different actual speed levels and different weather conditions. In sunny conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 40 km/h but were able to accurately estimate speeds that were lower than 40 km/h. In rainy conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 45 km/h but were able to accurately estimate speeds ranging from 35 km/h to 45 km/h. In stopping distance estimation task, the accurate estimation interval ranged from 60 km/h to 65 km/h, and pedestrians generally underestimated the stopping distance when vehicles were travelling over 65 km/h. The results show that pedestrians have accurate estimation intervals that vary by weather conditions. When the speed of the oncoming vehicle exceeded the upper bound of the accurate interval, pedestrians were more likely to underestimate the vehicle speed, increasing their risk of incorrectly deciding to cross when it is not safe to do so.     

Modelling pedestrian crossing behaviour in urban roads: A latent variable approach

As pedestrians are the most exposed and vulnerable road users to traffic accidents, urban planners frequently propose alternatives to improve their safety. However, some solutions, such as pedestrian bridges and crosswalks at signalized intersections, usually imply longer walking distances compared to the direct crossing alternative which, in its turn, involves a higher risk.In this article, a hybrid framework is proposed to analyse the pedestrians’ choice on how to cross an urban road where three crossing options are available: crossing directly, crossing by using a pedestrian bridge or using a crosswalk at a signalized intersection. The decision process is modelled as a discrete choice model incorporating latent variables to consider perceptions and psychological factors, using stated preference data coming from a survey applied in Bogotá, Colombia.Results show that the latent variables security/safety and attractiveness of each crossing alternative are relevant to understand the pedestrian crossing behaviour. These latent variables are strongly determined by socioeconomic characteristics of the individual (age, gender, level of study) and conditioned by the circumstances of the trip (main mode of transport, walking or not with children). It was found that a longer walking distance to a pedestrian bridge or a signalized crosswalk increases the probability of direct crossing, having a more relevant effect in the case of the pedestrian bridge.     

Please stop now,automated vehicle! – Passengers aim to avoid risk experiences in interactions with a crossing vulnerable road user at an urban junction

The success of highly automated vehicles (HAVs; SAE Level 4) will depend to a large extent on how well they are accepted by their future passengers. This is especially true for the interaction of these vehicles with other human road users in mixed traffic. In future urban traffic, passengers of HAVs will observe from a passive position how the automated system resolves space-sharing conflicts with crossing vulnerable road users (VRUs; e.g., pedestrians and cyclists) at junctions. For one such crossing-paths conflict, we investigated when passengers would want the HAV to start braking and how much perceived risk passengers accept in the interaction of their vehicle with VRUs. To this end, we conducted 1) an online video study (N = 118), 2) a driving simulator study (N = 28), and 3) a human&vehicle-in-the-loop (Hu&ViL) study at a test site (N = 10). We varied the speed of the HAV (30 km/h vs. 50 km/h), the type (cyclist vs. pedestrian), and crossing direction of the VRU (left vs. right). During the approach to the junction, passengers' task was to trigger the HAV's braking maneuver, in a first trial at the point they considered ideal and in a second trial at the last point they still considered safe enough to decelerate and come to a stop at the stop line. For each braking maneuver, we analyzed the HAV’s distance and time-to-arrival (TTA) to the VRU at braking onset, as well as passengers’ perceived risk in the VRU interaction. The results showed that most passengers preferred harmless interactions with VRUs (at the ideal braking onset time), and accepted unpleasant, but not dangerous interactions at most (at the last acceptable braking onset time). Methodologically, the results were very similar in the three different environments (online, driving simulator, real vehicle). These results clearly show that, in addition to the technical considerations of safe automated driving, passengers’ perception and evaluation of HAV driving behavior should also be taken into account to achieve a satisfying level of acceptance of these vehicles.     

What characterizes a “free vehicle” in an urban area?

The concept “free vehicle” is used widely in the transportation research literature, but as yet there is no common standard for a definition. In this article a standard is provided that is based on the assumption that a vehicle can be considered free, when its speed is not influenced by the speed of the vehicle traveling ahead. In order to determine empirically a threshold for free vehicles in urban areas, speed, distance headway, and time headway data of more than 100 000 vehicles were analyzed. Analyses showed that the speeds of two vehicles are linearly dependent on time headway for headways up to 6 s. It is important to distinguish between this value and the drivers' preferred headway, which is in the region of 2 s.