Analysis of Red-Light Violation Behavior of Pedestrian Two-Stage Crossing at a Signalized Intersection

Studying pedestrians’ twice-crossing behavior is of great significance to enhance safety and efficiency for pedestrians at signalized intersections. However, researchers have paid little attention to analyze and model pedestrians’ red-light running behavior on a two-stage crossing at signalized intersections. This paper focuses on analyzing the characteristics of pedestrian red-light violation behavior at the two stages, including the time distribution of violation behavior, the consistency of violation behavior, and the violation behavior in group.  A goal-oriented and time-driven red-light violation behavior model was proposed for pedestrian two-stage crossing. A video-recording method was used to collect field data, and the results show that pedestrians in the two directions present different red-light violation behaviors in time selection and violation count, as well as, pedestrians in the two stages of a direction present different red-light violation behaviors in time selection. The main reasons leading to the phenomena were analyzed, regarding from people’s cognitive psychology and visual perception. The results also show that the proposed model is effective in simulating pedestrian red-light violation behavior of twice crossing. This research provides a theoretical basis for optimizing signal timing, improving pedestrian safety and developing user-friendly transportation system

Analysis of Route Choice for Pedestrian Two-Stage Crossing at a Signalized Intersection

Studying pedestrians’ twice-crossing behavior is of great significance to enhance safety and efficiency for pedestrians at signalized intersections. However, limited attention has been paid to analyze and model pedestrians’ behavior patterns of twice crossing. The purpose of this paper is to determine pedestrians' route choices for twice crossing at a signalized intersection, focusing on the waiting position (to cross the street) and walking route. A goal-oriented and time-driven model was proposed to analyze pedestrians’ twice-crossing behavior at signalized intersections, where the two directions have different pedestrian signal timing. A video-recording method was used to collect field data in order to obtain pedestrian preferences in choosing a walking route. It was found that pedestrians in the two directions present different preferences toward walking route, in waiting position, directional change and route type. The results showed that the proposed model is effective in simulating pedestrian route-choice behavior of twice crossing. This research provides a theoretical basis for identifying pedestrian movement intention, optimizing signal timing, and improving pedestrian infrastructure at signalized intersections.

Measuring delays for bicycles at signalized intersections using smartphone GPS tracking data

The article describes an application of global positioning system (GPS) tracking data (floating bike data) for measuring delays for cyclists at signalized intersections. For selected intersections, we used trip data collected by smartphone tracking to calculate the average delay for cyclists by interpolation between GPS locations before and after the intersection. The outcomes were proven to be stable for different strategies in selecting the GPS locations used for calculation, although GPS locations too close to the intersection tended to lead to an underestimation of the delay. Therefore, the sample frequency of the GPS tracking data is an important parameter to ensure that suitable GPS locations are available before and after the intersection. The calculated delays are realistic values, compared to the theoretically expected values, which are often applied because of the lack of observed data. For some of the analyzed intersections, however, the calculated delays lay outside of the expected range, possibly because the statistics assumed a random arrival rate of cyclists. This condition may not be met when, for example, bicycles arrive in platoons because of an upstream intersection. This justifies that GPS-based delays can form a valuable addition to the theoretically expected values

Contributing Factors on Drivers Yielding Behaviors at Uncontrolled Intersections

Abstract The present study aims at analyzing drivers yielding behaviors to pedestrians’ right of way, who are attempting to cross at uncontrolled crosswalks. Three types of variables were identified to be collected for this research including characteristics of the locations as well as demographic, and behavioral characteristics of pedestrians and drivers. The behavioral characteristics of drivers and pedestrians is recorded only when a pedestrian arrives at the crosswalks trying to cross and a vehicle is approaching the intersection; so, the driver makes a decision whether or not yield to the pedestrian waiting to cross. Some behavioral characteristics of pedestrians include the pedestrian’s assertiveness, standing location and waiting time at the crosswalk to find a gap in traffic to be able to cross. The demographic characteristics also include age, gender, race. Some location specific variables include the presence of marked crosswalks, pedestrian crossing sign, near side bus stop, right turn lane, whether or not the location has had pedestrian-vehicle crash, type of land use surrounding the un-signalized intersections, crossing distance, AADT, the distance of last car parked from the intersection, the distance difference between the downstream and upstream signalized intersection to the un-signalized intersection, and the last location specific variable is the distance of uncontrolled intersection from the Atwater park locates in eastside of the city nearby the Lake Michigan. After identifying the variables and instructing the data collection process, the location studies were investigated. Twenty un-signalized intersections were selected that specific characteristics were similar among them to maintain consistency across all locations. Ten different uncontrolled intersections are selected as study locations, which each has had at least two pedestrian crashes in 2010 to 2014, and the other ten are selected as comparison locations, which none of them has had any crashes history in the same period of time. To analyze the collected data, five different models are proposed using logistic regression and random effect models. Ultimately, the preferred model that has a better goodness of fit is selected. This model well displays that what variables are most statistically significant with the driver yielding behavior. Based on the final model, each variable may have a positive or negative impact on the driver yielding behavior. The variables that cause drivers yield to the pedestrians at crosswalks include the assertiveness of pedestrians to cross, standing in the street, and the pedestrians’ race with the ethnicity of white as well as the second crosswalk marked, nearside bus stop, and the distance of uncontrolled intersection from the Lake Michigan. Some other independent variables that cause drivers not yield to the pedestrian at crosswalks are the type of land use (commercial area), having a crash history, AADT, crossing distance, and the distance difference between the downstream and upstream signalized intersection to the un-signalized intersection. Note that many professionals cited the importance of land use (proximity to commercial districts, downtown,.etc) on driving yielding behavior because of its relationship with pedestrian volumes. This study does not include a variable representing pedestrian volumes, so that could be explored in future studies. To better illustrate the effect of the variables on the likelihood of the driver yielding, the elasticity analysis was conducted. So, depends on the type of data, they were categorized into continuous and categorical variables. The elasticity from the continuous variable represents that 1% change in crossing distance variable reduces the driver yielding by 15.469%. For categorical variables, the sensitivity of the driver yielding variable is made by pseudo –elasticity. It represents that the existence of the near side bus stop at uncontrolled intersections increases the probability of drivers yielding by 0.54% while the existence of crash history reduces the probability of drivers yielding by 0.82%. It means that drivers still not tend to yield to pedestrians at crashes locations. Eventually, to improve the drivers yielding behaviors at uncontrolled intersections, five E approaches including engineering, enforcement, education, encouragement and evaluation are recommended. The engineering treatments with the minimum cost have a capability of being implemented in a short period of time. Simultaneously, a designed program for applying the law enforcement and for increasing people’s awareness and education in a longer run is anticipated to have a significant impact on improving the drivers yielding behaviors to pedestrians’ right of way at crosswalks. At the end of the program, through evaluation and comparison of the before and after implementation of the engineering, enforcement, education and encouragement strategies, we can determine if the desired result have been met. As part of the focus on enhancing traffic safety and reducing fatal crashes at the assigned locations, High Visibility Enforcement pilot program is also recommended. HVE combines highly visible and proactive law-enforcement strategies to target the violated drivers not yielding to the pedestrian right of way at crosswalks. It offers law enforcement agencies a proven alternative for preventing many of the unsafe driving practices that passenger and drivers engage in on roads. By targeting passenger and drivers, they raise everyone’s awareness of the joint responsibility that we all have to drive carefully and share the road safely

Development of a New Jughandle Design for Facilitating High-Volume Left Turns and U-Turns

The jughandle is a category of unconventional intersection that redistributes left turns to improve capacity and safety. The New Jersey Department of Transportation, a pioneer in jughandle design, classifies jughandles as either Type A (forward ramp intersecting the cross street), Type B (forward ramp curving left to intersect the mainline), or Type C (reverse loop ramp). This research has developed a new type of jughandle design referred to as Type A+B. This design closes the minor approaches at intersections and directs traffic through a jughandle onto the mainline. It also accommodates U-turns and mainline left turns in a manner similar to traditional Type B jughandles. A unique type of signal phasing, developed to accommodate this design, allows both jughandles to move concurrently. This type of intersection is hypothesized to be most appropriate for the retrofit of suburban arterials requiring installation of a median barrier. The retrofit would install a median barrier with the jughandles, and eliminate signals at intersections with low cross-street volumes, replacing them with right turns followed by U-turns (RTUT). The objective of this research is to determine whether this is an appropriate context for the design, and under what general volume conditions the Type A+B jughandle can reduce delay. Simulation software was used to compare performance measures for the Type A+B jughandle against a conventional intersection and a traditional Type A jughandle, for a wide range of traffic volumes whose turn movement proportions were modeled after a suburban arterial. The research also tested use of this design on an existing suburban arterial in the Pittsburgh region. Measures of performance evaluated include intersection delay, additional footprint, fuel consumption, and number of stops. It was found that the Type A+B jughandle significantly reduced delay under high-volume conditions, and resulted in a much larger intersection footprint

14-06 Development of Safety Performance Functions and Other Decision Support Tools to Assess Pedestrian and Bicycle Safety

A field study was performed at 40 uncontrolled midblock crosswalks and 26 signalized intersections on low-speed roadways selected from the areas surrounding three major urban college campuses across lower Michigan. An array of existing traffic control devices existed at the study sites, including various crosswalk marking strategies, along with additional treatments, such as pedestrian hybrid beacons (PHBs), rectangular rapid-flashing beacons (RRFBs) and single in-street R1-6 signs. The sites also collectively included a diverse set of roadway and traffic characteristics, including crossing widths, number of lanes, and median presence, along with vehicular, pedestrian, and bicyclist volumes. Three primary evaluations were performed for the midblock segments and signalized intersection study sites, including: driver yielding compliance, vehicle-pedestrian conflicts, and non-motorized traffic crash data. The yielding compliance study found that the type of crosswalk treatment has a strong influence over driver yielding compliance. While yielding compliance improves substantially when crosswalk markings are utilized, the highest compliance rates are achieved when an additional enhancement device (i.e., RRFB, PHB, or R1-6 sign), is also provided. To supplement small crash sample sizes at the study sites, Michigan statewide pedestrian and bicyclist crash data were collected and utilized to develop safety performance functions (SPFs) and other methods for predicting pedestrian and bicyclist crashes at road segments and intersections. Because pedestrian and bicyclist volumes were not available statewide, each model was developed for pedestrian and bicycle crashes based solely on vehicular AADT. In general, the models showed that pedestrian and bicycle crashes tend to increase with increasing traffic volumes. However, even in the highest volume cases, only a fraction of crashes involved a pedestrian or bicyclist. Pedestrian and bicycle crashes were further estimated based on the respective proportion of the Michigan specific SPF models for total crashes. The primary limitation towards prediction of pedestrian and bicycle crashes is the lack of a reliable exposure data to represent the amount of pedestrian or bicyclist activity on a given segment or intersection

Safety in Numbers: Models of Pedestrian and Bicycle Crash Frequency and Severity at Signalized Intersections in Utah Using Innovative Measure of Exposure

Recent trends indicate a dramatic increase in both the number and share of pedestrian and bicyclist injuries and fatalities nationally and in many states. This study aimed at understanding (geometric, traffic, operational, and other) factors associated with pedestrian and bicycle safety and also to assist in the prioritization and selection of counter measures to improve pedestrian and bicycle safety at signalized intersections. Several negative binomial models were estimated to investigate factors affecting pedestrian and bicycle crash frequency. The models suggested several characteristics of the road network, land use, built environment, and neighborhood sociodemographics were significantly associated with more (or fewer) pedestrian and bicycle crashes. Ordered logit models were fitted to investigate factors affecting injury severity in pedestrian and bicycle crashes. The model results indicated that vehicle size, vehicle maneuvering direction, and involvement of teenage/older drivers and DUI/drowsy/distracted driving in crashes had significant effects on injury severity in pedestrian and bicycle crashes. The study also found strong support for the “safety in numbers” effect, in which pedestrian/bicycle crash rates decrease with an increase in pedestrian/bicycle volumes

A Knowledge-based System for Pedestrian’s Roadway Crossing Behavior through Video Cameras

An attempt was made to investigate behavioral responses for pedestrian crossing roadways using a normal-based camera setup and a Personal Computer (PC)-based vision system along with an expert system developed specifically to help non-experienced people to perform a safe roadway crossing. This process was demonstrated by studying conflicts between pedestrians and vehicles as an indicator for a pedestrian crash. Two normal-based cameras were used to film pedestrian-traffic movements. A vision system was used to extract about 3317 conflict observations through digital images at six different locations in Irbid-City, Jordan. A database of pedestrian, traffic and geometric related information was developed. The collected variables in this database included: pedestrian’s speed, vehicle’s speed, vehicle distance, type of vehicle, geometry of the road, land use, location of conflict, pedestrian facility, pedestrian distance from the crossing location, age of pedestrian, gender of pedestrian and angle of crossing. Statistical regressions were carried out to establish useful models to estimate pedestrian’s speed from the mentioned variables. An expert system with the basic If... Then forward and backward chaining of the knowledge-based rules along with decision trees was developed using the VP-Expert Shell in order to help nonexperienced pedestrians in making safe decisions to perform roadway crossing. The system was validated and checked with actual data of pedestrians crossing in different locations for both: safe crossing and not crossing cases. Results of this investigation indicated that: 1) The linear multiple regression model was the most significant model to predict the relationship between pedestrian’s speed and the developed database variables; 2) Vehicle’s speed, gender of pedestrian, distance between vehicles, geometry of the road, land use and location of the road, and pedestrian’s facility variables were found to be the most significant contributors to pedestrian behavior while crossing the road; 3) Normal-base camera setup has proven to be a useful, practical and accurate camera configuration and data acquisition system for pedestrian and traffic studies; 4) Conflicts between vehicles and pedestrians can be used as an indicator for pedestrian crashes; and 5) Expert systems have proven to be useful educational systems to assist non-experienced pedestrians to perform decisions regarding safe roadway crossing