Safety assessment of on-road cycling lanes: A comparative study of different layouts using driving simulator.

Over the past few decades, a growing attention has been directed toward cycling due to its positive impacts on social, economic, and health aspects. Various countries are adopting and implementing strategies to promote cycling as a daily mode of transport. The main objective of this study is to improve cyclists' safety by investigating the impact of different layouts of on-road cycle lanes at two-lane two-way roads on drivers' interactions with cyclists using driving simulator. Three layouts of on-road cycle lanes were tested and compared, namely, uncolored, colored, and island separation, along with a control case where no cycle lane was provided. In addition, the impact of road alignments (straight sections, left and right curves) and the presence of an opposing vehicle were investigated. The driving simulator at Qatar University was used to conduct this study. A total of 92 subjects participated in this study. According to the results, on-road cycle lanes can significantly increase the safety of cyclists compared to shared lanes with motorized traffic. Moreover, the results showed that the drivers' intrusion to the opposite lane in the presence of opposing vehicles can be eliminated by providing on-road cycle lanes. That is, drivers' crash risk can also be reduced through the provision of on-road cycle lanes. Comparison of different on-road cycle lane treatments showed that uncolored cycle lanes outperformed the other layouts in terms of lateral clearance between the driver and the cyclist for right and straight alignments. On the other hand, the colored cycle lane showed better results for the left alignment. The findings of this study could be useful for designing on-road bicycle infrastructure to eliminate possible vehicle-cyclist and vehicle-vehicle conflicts and minimize crash risk.

Aberrant driving behaviors as mediators in the relationship between driving anger patterns and crashes among taxi drivers: An investigation in a complex cultural context.

OBJECTIVE: Taxis have become an integrated component of Qatar's urban transportation network due to their convenience, comfort, and flexibility. Qatar has seen an uptick in the demand for professional taxi drivers. Most Qatari taxi drivers come from developing countries with poor awareness of road safety; therefore, they regularly engage in aberrant driving behavior, leading to traffic violations and crashes. For taxi rides to be safer, it is essential to determine the association between driving aberration and road traffic crashes (RTCs), with an emphasis on the underlying factors that trigger these behaviors. METHODS: To this end, we collected the data from taxi drivers relying on standard questionnaires, namely the Driving Anger Scale (DAS) and the Driver Behavior Questionnaire (DBQ), together with the real crash data of the same taxi drivers obtained from the police department. We relied on factor analysis to identify the main factors of these tools and then structural equation modeling to predict their causal relationship with RTCs. RESULTS: The results indicated that the component of DAS, namely "illegal driving", triggered all dimensions of aberrant driving behaviors, whereas hostile gestures had a positive correlation with lapses. In addition, the factor "error" was identified as a significant direct predictor, while the factor "illegal driving" was identified as a significant indirect predictor for RTCs. Regarding demographic characteristics, professional driving experience was found to be negatively associated with RTCs. CONCLUSION: Driving aberration mediated the impact of driving anger on RTCs. The findings from this study could help road safety practitioners and researchers better understand these relations. In addition, these results could also be very helpful for driving instructors to train taxi drivers in a way to cope with provoking situations.

Assessment of different pedestrian communication strategies for improving driver behavior at marked crosswalks on free channelized right turns.

INTRODUCTION: Previous studies have indicated low driver yielding rates to pedestrians in various countries. This study analyzed four different strategies to improve driver yielding rates at marked crosswalks on channelized right turn lanes at signalized intersections. METHOD: A sample of 5,419 drivers was collected for four gestures using field experiments for males and females in the State of Qatar. The experiments were conducted in daytime and nighttime on weekends at three different locations; two sites are located in an urban area and the third is located in non-urban area. The effect of pedestrians' and drivers' demographic characteristics, gestures, approach speed, time of the day, location of the intersection, car type, and driver distractions on yielding behavior is investigated using logistic regression analysis. RESULTS: It was found that for the base gesture, only 2.00% of drivers yielded to the pedestrians, while for hand, attempt, and vest-attempt gestures the yielding percentages were considerably higher, 12.81%, 19.59%, and 24.60%, respectively. The results also showed that females received significantly higher yielding rates compared to males. In addition, the probability of a driver yielding increased 2.8 times when drivers approached at slower speed compared to a higher speed. Further, drivers' age group, accompanied, and distractions were not significant in determining drivers' probability of yielding.

Safer pedestrian crossing facilities on low-speed roads: Comparison of innovative treatments.

Despite the international efforts to improve pedestrian safety in different regions of the world, pedestrian fatalities still account for around one-third of annual road traffic deaths. Residential areas are commonly characterized by high pedestrian flows, making pedestrian safety a highpriority public health issue. Different types of treatments such as ITS-based, road markings, and physical treatments have been implemented to improve pedestrian safety, however, their efficiency varies between different locations worldwide. Therefore, this study aims to compare different innovative crosswalk treatments and to investigate their impacts on driving behavior in residential areas using a driving simulator. In our study, we juxtapose five different types of treatments with the untreated control condition. The treatments included two ITS-based solutions [LED pavement lights (ITS_LED) and Variable Message Sign (ITS_VMS)]; two different road markings [yellow zigzag marking (Marking_zigzag) and white road narrowing marking with the word SLOW written in the middle (Marking_narrowing)] and a physical road narrowing treatment (Physical_narrowing). Each of the tested conditions (control condition and treatment conditions) was tested with a Yield/Stop-controlled marked crosswalk located in a residential area with a posted speed limit of 50 km/h for two different situations. In the first situation, there was no pedestrian at the crosswalk (Situation PA), while in the second situation, a pedestrian was present at the crosswalk (Situation PP). Sixty-one volunteers possessing a valid Qatari driving license participated in the experiment. The study results showed that compared to the control condition, Physical_narrowing, ITS_VMS, and Marking_narrowing conditions helped to improve the yielding rates by 12.7 %. In terms of drivers' speed behavior, even though a pedestrian was not present at the crosswalk in Situation PA, physical_narrowing performed best by lowering the mean travel speed by around 10.1 km/h at the conflict location compared to the control location. Finally, the participants rated the physical_narrowing condition highest among the tested conditions. Based on the findings of the study, we conclude that the physical_narrowing treatment outperform other studied treatments since it significantly limits the freedom of drivers to maneuver, forcing them to slow down and give priority to crossing pedestrians.

Driving behavior classification at signalized intersections using vehicle kinematics: Application of unsupervised machine learning.

Driving behavior is considered as a unique driving habit of each driver and has a significant impact on road safety. This study proposed a novel data-driven Machine Learning framework that can classify driving behavior at signalized intersections considering two different signal conditions. To the best of our knowledge, this is the first study that investigates driving behavior at signalized intersections with two different conditions that are mostly used in practice, i.e., the control setting with the signal order of green-yellow-red and a flashing green setting with the signal order of green-flashing green-yellow-red. A driving simulator dataset collected from participants at Qatar University's Qatar Transportation and Traffic Safety Center, driving through multiple signalized intersections, was used. The proposed framework extracts volatility measures from vehicle kinematic parameters including longitudinal speed and acceleration. K-means clustering algorithm with elbow method was used as an unsupervised machine learning to cluster driving behavior into three classes (i.e., conservative, normal, and aggressive) and investigate the impact of signal conditions. The framework confirmed that in general driving behavior at a signalized intersection reflects drivers' habits and personality rather than the signal condition, still, it manifests the intersection nature that usually requires drivers to be more vigilant and cautious. Nonetheless, the results suggested that flashing green condition could make drivers more conservative, which could be due to the limited capabilities of human to estimate the remaining distance and the prolonged duration of the additional flashing green interval. The proposed framework and findings of the study were promising that can be used for clustering drivers into different styles for different conditions and might be beneficial for policymakers, researchers, and engineers.

The impact of rural expressway environments: drivers' attention allocation to variable message signs.

Variable Message Signs (VMS) are implemented at varying locations of the expressway. In this study, we compared the drivers' attention allocation to a 'drive safely' message on several VMS gantries that were located at six sections of typical expressway conditions in Qatar. We investigated how the expressway drivers perceive the VMS when implemented in different driving conditions (e.g. higher truck or car density) and surrounding environments (landmarks, buildings, bridges, exits, etc.). Besides, it was studied whether the driver's attention to the speedometer and the side mirrors was influenced. The eye-tracking data of seventy-nine drivers from the State of Qatar was analyzed, while driving in a driving simulator. It was found that a higher truck density on the expressway before the VMS location would lead to a delayed time-to-first-fixation and a lower fixation count to the VMS. The results of an ANOVA revealed that the expressway environment did not influence the drivers' average fixation duration to the speedometer and side mirrors when encountering the VMS. Therefore, no interfering effects must be expected for 'drive safely' messages at VMS locations with varying expressway traffic and surrounding conditions.

Examining the role of road safety audits worldwide: exploring road safety expert's opinions.

Road safety audit (RSA) is a method used to proactively identify safety risks in road projects from planning, design, and construction stages. The effectiveness of the implementation of RSAs varies across the globe. This paper provides an understanding of road safety auditor's opinions and attitudes by using data collected from an online questionnaire filled by 408 road safety experts with varying demographic and technical backgrounds. Results demonstrated that majority of respondents agreed that RSA is an effective tool to improve road safety. Compared to high-income countries, respondents from low- and middle-income countries had less knowledge about RSA and less access to RSA guidelines. The results also indicate that many road safety auditors have a misunderstanding of the independence requirement for conducting RSA. The results of this paper can be used to inform and develop improved guidance to improve RSA generally and promote RSA as an effective road safety engineering tool.

A reliability-based weather-responsive variable speed limit system to improve the safety of rural highways.

Weather-responsive Variable Speed Limit (WRVSL) systems treat speed limits as weather-dependent random variables, as opposed to the conventional static speed limits. This study (i) evaluates drivers' response to a fixed speed limit in different road-weather conditions, and (ii) proposes an effective approach to set WRVSLs, for rural divided highways located in extremely cold regions. Study data: road-weather, and speed data, collected from a rural highway (fixed speed limit = 110 km/h), are used to (i) estimate the 85th percentile speeds of population-level speed distributions, and (ii) develop WRVSLs based on the reliability theory. More specifically, the WRVSLs are set based on reliability: the probability of a speed being (i) likely complied by drivers, and (ii) adequate to avoid a rear-end collision. The study results reveal that merely 73 % of the drivers at the study site comply with the existing posted speed limit under normal road-weather conditions i.e., no precipitation and dry pavements. The reliability of the current speed limit is revealed to be approximately-one under normal road-weather conditions; thus, the current speed limit is perceived credible under such road-weather conditions. Yet, reliability of the current speed limit is substantially reduced in the presence of slight snow, and ice warning pavement conditions. A set of reliability-based WRVSLs ranging from 80 to 110 km/h is proposed. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to effectively manage speed, particularly in rural highways under adverse road-weather conditions to enhance the probability of speed limits being safe and complied by drivers and as a result reduce crash propensity.

Can automated driving prevent crashes with distracted Pedestrians? An exploration of motion planning at unsignalized Mid-block crosswalks.

Pedestrian distraction may provoke severe difficulties in automated vehicle (AV) control, which may significantly affect the safety performance of AVs, especially at unsignalized mid-block crosswalks (UMCs). However, there is no available motion-planning model for AVs that considers the effect of pedestrian distraction on UMCs. This study aims to explore innovative approaches for safe and reasonable automated driving in response to distracted pedestrians with various speed profiles at UMCs. Based on two common model design concepts, two new models are established for AVs: a rule-based model that solves motion plans through a fixed calculation procedure incorporating several optimization models, and a learning-based model that replaces the deterministic optimization process with policy-gradient reinforcement learning. The developed models were assessed through simulation experiments in which pedestrian speed profiles were defined using empirical data from field surveys. The results reveal that the learning-based model has outstanding safety performance, whereas the rule-based model leads to remarkable safety problems. For distracted pedestrians with significant crossing-speed changes, rule-based AVs lead to a 5.1% probability of serious conflict and a 1.4% crash probability. The learning-based model is oversensitive to risk and always induces high braking rates, which results in unnecessary efficiency loss. To overcome this, a hybrid model based on the learning-based model was developed, which introduces a rule-based acceleration value to regularize the action space of the proposed learning-based model. The results indicate that the hybrid approach outperforms the other two models in preventing crash hazards from distracted pedestrians by employing appropriate braking behaviors. The high safety performance of the hybrid models can be attributed to the spontaneous slowing down of the vehicle that initiates before detecting pedestrians on UMCs. Although such a cautious driving pattern leads to extra delay, the time cost of the hybrid model is acceptable considering the significant improvements in ensuring pedestrian safety.

Road safety status during COVID-19 pandemic: exploring public and road safety expert's opinions.

The main objective of this study is to investigate the status of traffic safety and the public perception of traffic safety during the during COVID-19 pandemic. Three different data sets are used in this study: road crash and traffic violation data from Qatar, and two separate questionnaire surveys (from general public and road safety experts). Results showed that during COVID-19 period, the total number of crashes in Qatar significantly reduced during the pandemic compared with the previous 5 years. However, the rates of serious and fatal injuries significantly increased. Regarding the general public perceptions, more than 80% reported that roads became safer while driving behaviours improved during the pandemic. On the other hand, more than 50% of the experts disagreed that roads became safer, 55% disagreed that driving behaviours improved and 70% agreed that less attention from governments was directed toward road safety during the pandemic. The findings from this study could help policy makers to understand the road safety status during the pandemic to make appropriate adjustments in the traffic laws and regulations on a temporary basis. This could help in reducing crash-related injuries and as a result reduce pressure on health and other emergency services.

Interactions between autonomous vehicles and pedestrians at unsignalized mid-block crosswalks considering occlusions by opposing vehicles.

Visibility can be identified as one of the critical determinants for the safety performance of autonomous vehicles (AVs) on unsignalized mid-block crosswalks (UMC), which may be significantly influenced by build-up environment and surrounding vehicles. This study investigates the safety performance when AVs interact with pedestrians approaching from far-side sidewalks to UMCs considering the visual occlusion of opposing vehicles. A mathematical model is proposed for judging the visibilities of objects from observers' location under the impact of visual obstacles and is embedded into an agent-based pedestrian-vehicle interaction framework. Two yielding decision modules is assumed for AVs: The normal decision module implements the pedestrian priority rule simply based on the current detectable information, whereas the memory aid decision module extends AVs' detection abilities by incorporating the memory data. Through simulation experiments, it is found that the percentages of short post encroachment time (%SPET) between AVs and far-side pedestrians reach peaks when the pedestrian flow rate is 300-400 ped/h. When opposing vehicles are in stationary queue conditions, %SPETs are only sensitive to the net distance between the last opposing vehicles in the queue and crosswalks (Dqueue). As the Dqueue decreases to lower than 15 m, %SPETs start to increase drastically. However, when opposing vehicles are in free flow conditions, %SPETs are influenced by multiple factors such as pedestrians' crossing decisions, sizes and flow rates of opposing vehicles. Furthermore, only when opposing vehicles are in free flow conditions, memory aid AVs can significantly eliminate the impacts of opposite vehicles. Finally, several countermeasures are developed to enhance the visibility and safety at UMCs based on the findings of this study.

Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions.

This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.

Improved traffic safety at work zones through animation-based variable message signs.

Work zones are established to provide a safe environment for all road users and road workers. However, based on the statistics, they can be considered as crash prone zones due to changes in the road alignments and the posted speed limits. In this driving simulator study, we aimed at investigating the safety impacts of a newly proposed system composed of graphical and animation-based variable message signs (VMSs) in the state of Qatar. The proposed VMS condition was compared with a control condition that was designed following the Qatar Work Zone Traffic Management Guide. A total of seventy subjects were invited to participate in the experiment voluntarily. Study results showed that in the VMS condition, drivers reduced their traveling speeds in advanced compared to the control condition. Drivers' traveling speed in the VMS condition was significantly reduced by 6.3 and 11.1 km/h on the leftmost and the second leftmost lanes, respectively. Next, the results uncovered that the proposed system motivated drivers to initiate early lane changing maneuvers, i.e., 150 m earlier than the control condition. Finally, the VMS condition was effective in stimulating drivers to keep larger headways with a merging vehicle. In sum, the proposed VMS system outperformed the control condition in terms of speed reduction, early merging, and higher headways between the through and the merging vehicle.

A novel agent-based framework for evaluating pedestrian safety at unsignalized mid-block crosswalks.

A critical safety problem in road networks is the conflicts on unsignalized crosswalks. Thus, a proactive approach to assess pedestrian safety performance is required. Simulating the microscopic road user behavior in a virtual platform is one of the typical approaches. However, current simulation tools are not flexible enough to properly reproduce various behaviors of pedestrians and drivers considering their interactions with the road environment and other road users. Therefore, the objective of this paper is to propose a novel agent-based framework for evaluating pedestrian safety at unsignalized crosswalks. Unsignalized mid-block crosswalks with refuge islands (UMCR) are considered as an example facility to implement the proposed framework, where relevant behavioral elements such as the reaction time, visual field with obstacles, and minimum safety margin time are addressed. Not only the pedestrian-vehicle interaction is modeled but also the vehicle-vehicle interaction is considered. Empirical validation on a UMCR shows that the proposed framework can reproduce reliable distributions of the post encroachment time compared to the observed distributions within an acceptable error range. The sensitivity analysis reveals that the high reaction time of drivers, small safety margin time, and visual obstacles near crosswalks increase the probability of serious conflicts. The results also show that the framework can reproduce traffic crashes under assumed extreme road conditions.

Do detection-based warning strategies improve vehicle yielding behavior at uncontrolled midblock crosswalks?

Pedestrians being the most vulnerable road users account for a large proportion of injuries and fatalities from road traffic crashes. Pedestrians are involved in around one-third of the whole fatalities coming from the road traffic crashes in the state of Qatar. In areas with uncontrolled midblock crosswalks, it is very crucial to improve drivers' alertness and yielding behavior. The objective of this driving simulator study is to investigate the impact of pedestrian detection strategies and pavement markings on driving behavior at high-speed uncontrolled crosswalks. To this end, an untreated condition (i.e. Control) was compared with three treatment conditions. The three treated conditions included two detection strategies, i.e., advance variable message sign (VMS) and LED lights, and road markings with pedestrian encircled. Each condition was tested with a yield/stop controlled marked crosswalk for two situations, i.e. with vs. without a pedestrian present. The experiment was conducted using the driving simulator at Qatar University. In total, 67 volunteers possessing a valid Qatari driving license participated in the study. Different analyses were conducted on vehicle-pedestrian interactions, driving speed, variations in acceleration/deceleration and lateral position. The results showed that both the LED and VMS conditions were helpful in increasing yielding rates up to 98.4 % and reducing the vehicle-pedestrian conflicts significantly. Furthermore, both treatments were effective in motivating drivers to reduce vehicle speed in advance. Considering the findings of this study, we recommend LED and VMS conditions as potentially effective solutions to improve safety at yield/stop controlled crosswalks.

Optical pavement treatments and their impact on speed and lateral position at transition zones: A driving simulator study.

Transition zones are a road section where posted speed drops from higher to lower limits. Due to the sudden changes in posted speed limits and road environment, drivers usually do not adapt to the posted speed limits and underestimate their traveling speed. Previous studies have highlighted that crash rates are usually higher in these sections. This study aims at improving the safety at transition zones by introducing perceptual measures that are tested using a driving simulator. The proposed measures are speed limit pavement markings with a gradual increase of brightness and/or size that were placed at transition zones in simulation scenarios replicating the real-world environment of the Doha Expressway in Qatar. These innovative measures aim to produce the impression of increased speed that could stimulate drivers to better adapt speed limits. The driving behavior of 81 drivers possessing a valid Qatari driving license was recorded with a driving simulator interfaced with STISIM Drive® 3. Results showed that pavement markings combining size and brightness manipulations were the most effective treatment, keeping drivers' traveling speed significantly below the traveling speed recorded in the untreated control condition. In this regard, the maximum mean speed reductions of 5.3 km/h and 4.6 km/h were observed for this treatment at the first transition (120 to 100 km/h) and second transition (100 to 80 km/h) zones, respectively. Regarding the variations in drivers' lateral position, the results showed that the proposed pavement markings did not negatively influence drivers' lateral control on the road as the maximum observed standard deviation of lateral position was around 0.065 m. This study shows that the proposed pavement markings are recommended for improving the speed adaptation of drivers in the transition zones.

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures.

INTRODUCTION: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. METHOD: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. RESULTS: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers' negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. CONCLUSION: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.

Innovative countermeasures for red light running prevention at signalized intersections: A driving simulator study.

The change interval, which includes the yellow and all-red times, plays a crucial role in the safety and operation of signalized intersections. During this interval, drivers not only need to decide to stop or go but also have to interact with drivers both in front and behind, trying to avoid conflicting decisions. Red light running and inconsistent stopping behavior may increase the risk for angular and rear-end crashes. This study aims to investigate the effect of different innovative countermeasures on red light running prevention and safe stopping behavior at signalized intersections. Five different conditions were tested inviting sixty-seven volunteers with a valid driving license. The conditions include a default traffic signal setting (control condition), flashing green signal setting (F-green), red LED ground lights integrated with a traffic signal (R-LED), yellow interval countdown variable message sign (C-VMS), and red light running detection camera warning gantry (RW-gantry). Drivers in each condition were exposed to two different situations based on the distance from the stop line. In the first situation, drivers were located in the indecision zone while in the second situation they were located in the likely stopping zone. A series of logistic regression analyses and linear mixed models were conducted to investigate the overall safety effects of the different countermeasures. The probability of red light running (RLR) was significantly reduced for R-LED in both analyses (i.e. in the total sample, and in the sample of crossed vehicles). Moreover, a clearly inconsistent stopping behavior was observed for the flashing green condition. Furthermore, a unit increase in speed (kph) at the onset of yellow interval significantly increases the probability of RLR by 5.3 %. The study showed that R-LED was the most effective solution for improving red light running prevention and encouraging a consistent stopping behavior at the intersection. In conclusion, the R-LED and the RW-gantry treatments are recommended as effective tools to improve safety at signalized intersections.

Drivers' estimation of their travelling speed: a study on an expressway and a local road.

Correctly estimating the travelling speed is essential for safety on the roads to ensure safer interactions with other drivers and to avoid violations of traffic regulations. Therefore, it is important to create understanding of the pattern of speed perception of drivers and the influencing factors. This study invited 40 drivers to participate in a field experiment measuring speed perception. The experiment was conducted using a test car equipped with high fidelity Global Positioning System (GPS). Data were collected for two settings (hidden versus revealed speedometer) and four requested speeds (50, 70, 80 and 100 km/h). An analysis of variance test was conducted along with separate t-tests and cumulative distributions for each speed independently. The results clearly show that there were significant differences in perceived speed between a hidden and revealed speedometer, between the first and second trial and among all the requested speeds. Participants drove significantly faster for all the requested speeds in the hidden speedometer setting. This shows that participants underestimated their speed. In case of complex situations, drivers may not be able to rely on speedometers and may cause a violation of law, unintentionally. Therefore, it is recommended to jurisdictions to consider these results while making decisions regarding speed management.

Modeling pedestrian crossing speed profiles considering speed change behavior for the safety assessment of signalized intersections.

Pedestrian safety is one of the most challenging issues in road networks. Understanding how pedestrians maneuver across an intersection is the key to applying countermeasures against traffic crashes. It is known that the behaviors of pedestrians at signalized crosswalks are significantly different from those in ordinary walking spaces, and they are highly influenced by signal indication, potential conflicts with vehicles, and intersection geometries. One of the most important characteristics of pedestrian behavior at crosswalks is the possible sudden speed change while crossing. Such sudden behavioral change may not be expected by conflicting vehicles, which may lead to hazardous situations. This study aims to quantitatively model the sudden speed changes of pedestrians as they cross signalized crosswalks under uncongested conditions. Pedestrian speed profiles are collected from empirical data and speed change events are extracted assuming that the speed profiles are stepwise functions. The occurrence of speed change events is described by a discrete choice model as a function of the necessary walking speed to complete crossing before the red interval ends, current speed, and the presence of turning vehicles in the conflict area. The amount of speed change before and after the event is modeled using regression analysis. A Monte Carlo simulation is applied for the entire speed profile of the pedestrians. The results show that the model can represent the pedestrian travel time distribution more accurately than the constant speed model.