Unsignalized Mid-block Crosswalks Research Articles

Predicting Pedestrian Crossing Behavior at Unsignalized Mid-Block Crosswalks Using Maximum Entropy Deep Inverse Reinforcement Learning

Predicting Pedestrian Crossing Behavior at Unsignalized Mid-Block Crosswalks Using Maximum Entropy Deep Inverse Reinforcement Learning

Pedestrian–vehicle interactions at unsignalized mid-block crosswalks: Effects on traffic flow, CO[formula omitted] emissions, and energy dissipation

Unsignalized mid-block crosswalks are adopted to regulate unauthorized crossings by promoting drivers’ yielding to pedestrians. Although pedestrian–vehicle interactions at crosswalks have been widely studied, the effects of such facilities regarding traffic flow and emissions have been overlooked. This paper presents a vehicle–pedestrian cellular automata model to analyze the effects of two types of crosswalk systems: raised and zebra, on traffic characteristics. The model allows microscopically studying the impact of the induced speed heterogeneity in terms of traffic flow, CO2 emissions, and kinetic energy dissipation. Simulation results show that traffic flow experiences four phases in both systems: maximum current, congestion, jamming, and blocking; with second-order transitions among them. The maximum current phase is the only one with free-flow conditions shrinking faster in the system with a raised crosswalk than in the one with zebra. Both systems reach the blocking phase when the pedestrian entrance rate surpasses a critical value. However, raised crosswalk has lesser repercussions in CO2 emission and energy dissipation by eliciting traffic calm. This study enhances the comprehension of the impacts of mid-block crosswalks, depending on the manner in which they are deployed.

Red LED Strip Signalling Pedestrian Presence at Uncontrolled Mid-block Crosswalks

A relevant number of collisions between vehicles and pedestrians occur at night because of the reduced capacity of a driver to perceive and react to the presence of pedestrians at crosswalks. To reduce this risk of collision, new smart road technologies have been introduced. This study aims to evaluate the effectiveness of a red LED strip that warns the driver of the presence of pedestrians at unsignalized mid-block crosswalks at night-time. The technology consists of LED strips installed near the crosswalk on the side of oncoming vehicles. The LED is activated when a sensor detects a pedestrian approaching the crosswalk. In this driving simulation experiment, three different urban mid-block crosswalks were evaluated: (i) without an LED strip (baseline), (ii) with a fixed LED strip, and (iii) with a flashing LED strip. Each scenario was tested for three different levels of pedestrian time gap acceptance (PTGA) (i.e., 4, 6, 8 s) and two road sections (i.e., 1 lane vs. 2 lanes). Thirty-six participants took part in a within-subjects’ design. During the experiment, the minimum time to collision (mTTC), the post-encroachment time (PET), maximum vehicle speed, and reaction distance were monitored to quantitatively compare the different levels of vehicle-pedestrian interaction. Compared to the baseline, the LED strip resulted in a safer driver-pedestrian interaction, with an average increase in mTTC of 1.13 s, PET of 0.66 s, and a longer average reaction distance of 7.9 m. However, a slight (albeit not statistically significant) increase in speed was observed following installation of the LED strip. Furthermore, no significant differences were observed between fixed and flashing LED strips. Overall, these results confirm the LED strips effectiveness in alerting the driver to the presence of a pedestrian, thus increasing the safety of their interaction. Further studies should confirm these findings in a more ecological way, e.g., evaluating the safety impact of this technology under different weather and distracted driving conditions.

Defensive or competitive Autonomous Vehicles: Which one interacts safely and efficiently with pedestrians?

The emergence of Autonomous Vehicles (AVs) could provoke unexpected challenges in urban traffic environments. One such crucial challenge is the conflicts between pedestrians and AVs, particularly on unsignalized mid-block crosswalks (UMC), where pedestrians are exposed to the AV flow. This study investigates the efficiency and safety performance of a UMC in the presence of both AVs and pedestrians considering the diversities in their behaviors. Through empirical analyses, two pedestrians’ crossing decision models are built and four groups of speed profiles are classified. Meanwhile, based on previous literature, defensive and competitive driving strategies are assumed for AVs. The simulation is implemented on an agent-based framework that can dynamically reproduce the kinematic interactions between pedestrians and vehicles. Results indicated that with a reasonable safety margin (2.5 s), percentages of low post encroachment time events for competitive AVs with different pedestrian types are smaller than defensive AVs with differences of 0.2% to 2.9%. The average delays of competitive AVs for all pedestrian types are smaller than defensive AVs with a maximum estimated difference of 39 s. Moreover, the analysis showed that lowering the speed limit may reduce the crash rate of competitive AV up to 0%. It is also found that the pedestrians who make reckless crossing decisions and change their speed drastically during the crossing process are more likely to incur crashes with competitive AVs. Therefore, if pedestrian behaviors can be regulated reasonably, competitive AVs with appropriate parameter settings are most suitable for UMC in the future.

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.

Analysis of Pedestrian Stress Level Using GSR Sensor in Virtual Immersive Reality

Level of emotional arousal of one's body changes in response to external stimuli in an environment. Given the risks involved while crossing streets, particularly at unsignalized mid-block crosswalks, one can expect a change in the stress level of pedestrians. In this study, we investigate the levels and changes in pedestrian stress, under different road crossing scenarios in immersive virtual reality. To measure stress level of pedestrians, we used Galvanic Skin Response (GSR) sensors. To collect the required data for the model, Virtual Immersive Reality Environment (VIRE) tool is used, which enables us to measure participant's stress levels in a controlled environment. Detailed experiments were conducted over a 5-month period, with 180 participants from four different places in Toronto to cover a heterogeneous population. Data collected are used to develop behavioural models, to observe the contribution of different variables on increasing pedestrian stress level. The initial modelling results suggested that the density of vehicles has a positive effect, meaning as the density of vehicles increases, so does the stress levels for pedestrians. The sociodemographic information has a relationship to individual’s stress levels. It was noted that younger pedestrians have lower amount of stress when crossing as compared to older pedestrians which have higher amounts of stress. Geometric variables has an impact on the stress level of pedestrians. The greater the number of lanes the greater the observed stress, which is due the crossing distance increasing, while the walking speed remaining the same.

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.

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.

Modeling the interaction between vehicle yielding and pedestrian crossing behavior at unsignalized midblock crosswalks

The interaction between pedestrians and vehicles is an inevitable phenomenon at unsignalized midblock crosswalks. This study aims to contribute to a better understanding of the interaction between vehicle yielding and pedestrian gap acceptance (VY and PGA). A microscopic traffic flow model was established to describe the interaction and explores its effect on traffic flow. The VY and PGA behaviors were converged into the proposed model. The proposed model was accomplished in a time step simulation. The results stability and descriptive power of the proposed model were analyzed. The proposed model was also validated using empirical data. The effects of the traffic and geometric factors on the operation of the unsignalized midblock crosswalks were discussed based on numerical experiments. Accordingly, the recommendations on choosing the proper control mode of midblock crosswalks (unsignalized or signalized) were proposed.

Pedestrian walking speed at un-signalized midblock crosswalk and its impact on urban street segment performance

The Urban Street Segment Chapter of the Highway Capacity Manual (HCM) includes a methodology for evaluating the level of service urban street segments provide to automobile users. The methodology does not account for pedestrian activity at un-signalized midblock crosswalk on an urban street segment. Pedestrian activity at un-signalized midblock crosswalk on urban street segments causes friction conditions between automobiles and pedestrians. As a consequence, the average time it takes vehicles to travel along the segment is increased. Increasing segment running time decreases both the travel speed of automobiles and the level of service provided to automobile users. There is an inverse relationship between the delay incurred by interrupted vehicles and the speeds at which pedestrians walk while crossing at midblock. To account for this delay, there is a need to investigate pedestrian walking speeds at un-signalized midblock crosswalks. This study measured pedestrian walking speeds by age-group at two un-signalized midblock crosswalks on urban street segments. The first objective of this paper is to perform statistical analyses to examine the measured free-flow pedestrian walking speeds. The second objective is to demonstrate how the findings of this study can be incorporated into the Urban Street Segment Analysis Chapter of the HCM. Pedestrian walking speeds were recorded and analyzed for 2937 pedestrians. The results show teenagers walk at an average speed of 1.45 m/s, young adults walk at an average speed of 1.55 m/s, middle age pedestrians walk at a speed of 1.45 m/s, older pedestrians walk at speed of 1.09 m/s, and elderly or physically disabled pedestrians walk at a speed of 1.04 m/s. • Statistical analyses to examine measured free-flow pedestrian walking speeds at un-signalized midblock crosswalks. • Measurement of pedestrian walking speeds by age group. • Theory of gap-acceptance on pedestrian crossing behavior on urban street segments. • The Highway Capacity Manual (HCM) methodology for evaluating level of service urban street segments. • Relationship between pedestrian walking speed and urban street level of service.

Gap acceptance probability model for pedestrians at unsignalized mid-block crosswalks based on logistic regression

Gap acceptance represents a pedestrian’s assessment of how safe it may be to use an available gap in traffic flow at a particular point in time. Though walking is a major component of urban mobility, the high rate of fatal interaction with motor vehicle traffic raises safety issues around how pedestrians decide to accept the available gap. This paper explored these interactions by modeling gap acceptance behavior at the midblock crosswalks. Unlike other pedestrian gap acceptance studies that focus on individual psychological and sociological factors that are difficult to control or manage, this study focused on six environmental factors that we considered important and as having the potential to affect the pedestrians’ gap acceptance decision at the crosswalks, i.e. gap size, crossing distance, number of waiting pedestrians, waiting time, vehicle traffic volume and position of pedestrian (whether on street kerb or median). Video data was collected on pedestrian gap acceptance from 13 midblock crosswalk locations in Shanghai, China. A Logit model with 96% accuracy was developed to describe and predict the pedestrian gap acceptance behaviors. The results show that gap size and crossing distance have the highest effect on the pedestrian gap acceptance decision. Pedestrians waiting at the kerbside could confidently accept gaps (with a 95% probability) when the gap is longer than 2.2s, 5.9s, and 9.6s under the condition that the crossing distance is 4 m (one lane), 7.5 m (two lanes), and 11 m (three lanes), respectively while pedestrians waiting at the median could confidently accept gaps when the gap is longer than 1.6s, 5.3s, and 8.5s respectively under the same conditions. The recommendations on improving the crossing safety are proposed accordingly.

Vehicle yielding probability estimation model at unsignalized midblock crosswalks in Shanghai, China.

The vehicle-pedestrian encounter at midblock crosswalks in urban centers is inevitable but the challenge to urban transportation planners is in achieving a balance between traffic flow efficiency and pedestrian safety. Vehicles are expected to yield to pedestrians who have a right of way at the midblock unsignalized crosswalks but, failure to yield causes conflicts that at times are fatal. This study investigated the effect of macroscopic factors on the vehicle yielding. Six environmental factors are considered: temporal gap size, number of traffic lanes, number of waiting pedestrians, position of pedestrian (whether on street kerb or median), traffic flow direction and presence (or absence) of monitoring ePolice. Video Data on six observed variables that influenced vehicle yielding was collected from 13 uncontrolled crosswalk locations in Shanghai city in the Peoples Republic of China. A Logit model with a 95.9% accuracy was developed to describe the vehicle yielding behavior. The results showed that gap size and number of traffic lanes had the highest influence on driver yielding decision and that drivers were more likely to yield if ePolice was present. The sensitivity analysis was conducted and appropriate recommendations on improving the pedestrians crossing safety were proposed accordingly.

Drivers’ effective decelerating zone in an urban Vehicle-Pedestrian conflict situation: Observational studies and analyses

To analyse the drivers’ decelerating behavior in conflict avoidance process under Vehicle-Pedestrian conflict situation is accordingly a surrogate method for the guidance of driver evasive manoeuvre and improving the active driving safety. Field observation data has been collected by video recording and image processing at urban unsignalized midblock crosswalks in Beijng, China and Munich, Germany. The relationship between deceleration rate and vehicle speed has been statistically described. By analyzing how the time-related measures (Vehicle Time to Conflict Point and Pedestrian Time to Conflict Point) and the distance-related measures (Vehicle longitudinal distance to Conflict Point and Pedestrian Lateral distance to Conflict Point) affect the deceleration rate choice, the drivers‘ effective decelerating zone with sight angle has been proposed with the consideration of longitudinal & lateral conflict behavior. Minimum Vehicle-Pedestrian conflict distance is calculated and a 2 m minimum distance is suggested as the threshold for collision discrimination. Comparisons which address the needs to make the intercultural adaptation when introducing Driver Assistance Systems to developing countries have also been made to show the significant differences between China and Germany. The whole work could hopefully be the groundwork in the target of conflict pre-scanning by decelerating zones under various conflict situations and the design of vehicle active safety systems.

A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks

At unsignalized crosswalks, interactions between pedestrians and vehicles often lead to traffic safety hazards due to absence of traffic control and unclear right-of-ways. To address this safety problem, there is a need to understand the interaction behaviors of pedestrians and vehicles that are complicated by a variety of traffic and roadway attributes. The prime objective of this study is to establish a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at unsignalized crosswalks in a realistic way. The model is calibrated with detailed behavioral data collected and extracted from field observations. The capability of the calibrated model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay are also tested and demonstrated. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the proposed model is capable to evaluate the pedestrian safety. Thereby, the simulation model has the potential to serve as a useful tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing.

Analyses of pedestrian behavior on mid-block unsignalized crosswalk comparing Chinese and German cases

A large number of pedestrian fatalities are caused by the vehicle-pedestrian accidents. The application of new theory and technological approaches may hold great potential to reduce the accident frequency and severity for pedestrians. Considered the different driving cultures between China and Germany, the adaptation of such application in new market triggers an “intercultural comparison” related to the road user behavior and traffic safety. Field traffic data have been collected by video recording and image processing at unsignalized mid-block crosswalks both in Beijing, China and Munich, Germany. Centered Vehicle-Pedestrian conflict situation, pedestrian speed performance in different pedestrian categories and walking phases, pedestrian waiting behavior related to waiting decision choice and waiting time, pedestrian gap acceptance were statistically analyzed for understanding the pedestrian behavior in the conflict process. Intercultural comparisons were made between China and Germany. The research results addressed how the conflict participants (pedestrians only) behave differently and would hopefully be the impetus for further intercultural analyses from urban traffic side.

Dynamic analysis of pedestrian crossing behaviors on traffic flow at unsignalized mid-block crosswalks

It is important to study the effects of pedestrian crossing behaviors on traffic flow for solving the urban traffic jam problem. Based on the Nagel–Schreckenberg (NaSch) traffic cellular automata (TCA) model, a new one-dimensional TCA model is proposed considering the uncertainty conflict behaviors between pedestrians and vehicles at unsignalized mid-block crosswalks and defining the parallel updating rules of motion states of pedestrians and vehicles. The traffic flow is simulated for different vehicle densities and behavior trigger probabilities. The fundamental diagrams show that no matter what the values of vehicle braking probability, pedestrian acceleration crossing probability, pedestrian backing probability and pedestrian generation probability, the system flow shows the "increasing–saturating–decreasing" trend with the increase of vehicle density; when the vehicle braking probability is lower, it is easy to cause an emergency brake of vehicle and result in great fluctuation of saturated flow; the saturated flow decreases slightly with the increase of the pedestrian acceleration crossing probability; when the pedestrian backing probability lies between 0.4 and 0.6, the saturated flow is unstable, which shows the hesitant behavior of pedestrians when making the decision of backing; the maximum flow is sensitive to the pedestrian generation probability and rapidly decreases with increasing the pedestrian generation probability, the maximum flow is approximately equal to zero when the probability is more than 0.5. The simulations prove that the influence of frequent crossing behavior upon vehicle flow is immense; the vehicle flow decreases and gets into serious congestion state rapidly with the increase of the pedestrian generation probability.

Method to Determine Pedestrian Level of Service for the Overall Unsignalized Midblock Crossings of Road Segments

This paper aims at developing a pedestrian level of service (LOS) model for the overall unsignalized midblock crossings of road segments from the perspective of the pedestrian's perception of safety and convenience in Chinese midblock crossing environment. Firstly, the potential primary factors influencing pedestrian LOS at unsignalized midblock crosswalks were summarized from four respects: traffic conflicts, the distance between crosswalks, crossing facilities, and delay. Secondly, 948 participants’ real-time sense of safety and convenience when they were crossing the 30 selected unsignalized midblock crosswalks and the design and operational characteristics of the selected road segments were collected. The selected midblock crosswalks were typical of those prevalent in the medium-sized urban areas of China, and the participants of questionnaire survey covered a broad cross section of Chinese population of pedestrians. Finally, Pearson correlation analysis and stepwise regression analysis were carried out to develop pedestrian LOS model for the overall unsignalized midblock crossings of road segments. The results revealed that the factors significantly influencing pedestrian LOS of the overall unsignalized midblock crossings of road segments included volume of two-way motor vehicle, the distance between marked midblock crosswalks, and the distance between unmarked crosswalks. A reliable, statistically calibrated pedestrian LOS model was developed ( R2 = 0.80).

Pedestrian Crossing Behavior at Unsignalized Mid-block Crosswalks Around the Primary School

To obtain the laws of pedestrians’ crossing behaviors, especially children, this paper analyzes the characteristics of four crossing behaviors (crossing speed, waiting time before crossing, running across the street, not looking before crossing) of three groups of pedestrians (adults, adult-child pairs, and children alone) at unsignalized mid-block crosswalks. 579 pedestrians are recorded. The data are analyzed by mean, analysis of variance (ANOVA), and Chi-Square test. The results show that: 1) pedestrians’ crossing speed on the second half of the crosswalk is systematically faster than the first half; 2) children's behaviors are influenced by adults and children rely on their parents; 3) children often feel overwhelmed because of the difficulty judging when and how to cross the street. Children's crossing behavior should be considered when people plan and design the crossing facilities where children may use. And it is necessary to improve children's skills of crossing street.

Event-Based Modeling of Driver Yielding Behavior at Unsignalized Crosswalks

This research explores factors associated with driver yielding behavior at unsignalized pedestrian crossings and develops predictive models for yielding using logistic regression. It considers the effect of variables describing driver attributes, pedestrian characteristics and concurrent conditions at the crosswalk on the yield response. Special consideration is given to 'vehicle dynamics constraints' that form a threshold for the potential to yield. Similarities are identified to driver reaction in response to the 'amber' indication at a signalized intersection. The logit models were developed from data collected at two unsignalized mid-block crosswalks in North Carolina. The data include 'before' and 'after' observations of two pedestrian safety treatments, an in-street pedestrian crossing sign and pedestrian-actuated in-roadway warning lights.The analysis suggests that drivers are more likely to yield to assertive pedestrians who walk briskly in their approach to the crosswalk. In turn, the yield probability is reduced with higher speeds, deceleration rates and if vehicles are traveling in platoons. The treatment effects proved to be significant and increased the propensity of drivers to yield, but their effectiveness may be dependent on whether the pedestrian activates the treatment.The results of this research provide new insights on the complex interaction of pedestrians and vehicles at unsignalized intersections and have implications for future work towards predictive models for driver yielding behavior. The developed logit models can provide the basis for representing driver yielding behavior in a microsimulation modeling environment.

Pedestrian behaviors at and perceptions towards various pedestrian facilities: an examination based on observation and survey data

This paper presents findings from an observational study of pedestrian behaviors at various urban crosswalks and a pedestrian user survey which sought pedestrian perceptions toward various pedestrian facilities in a divided urban boulevard located next to a large university campus, Michigan State University, East Lansing, MI, USA. Such facilities included signalized and unsignalized intersection crosswalks, unsignalized marked and non-striped midblock crosswalks, physical barriers (vegetation and two-foot high concrete wall), midblock crosswalk shelters, colored paving (red brick pavement) at medians and curbs, and pedestrian warning signs at midblock crossing locations, messaging “cross only when traffic clears.” Pedestrian behavior data were obtained from the reduction of video images of pedestrian movements recorded throughout the study site. Pedestrian perceptions information was obtained through a user survey completed by pedestrians using the study site. It was found that unsignalized midblock crosswalks were the treatment of preference to pedestrians (83% reported a preference to cross) and also showed high crossing compliance rate of pedestrians (71.2%). It was also evident that the crosswalk location, relative to the origin and destination of the pedestrian, was the most influential decision factor for pedestrians deciding to cross at a designated location (90% said so). Proper traffic control can further encourage pedestrian crossings at designated locations since the effect of the availability of pedestrian signal to influence pedestrians’ decisions to cross at a specific location was quite high (74% said so). Moreover, vegetation and concrete barriers influenced the decision to cross of a significant number of pedestrians surveyed (65%). It is expected that the findings from this study will help traffic engineers, urban planners and policy makers understand pedestrian behaviors and attitudes at/towards pedestrian crosswalks.