The rate at which pedestrian-related traffic accidents are occurring is alarming. As nations continue to urbanize, traffic incidents involving pedestrians will be on the rise. Current infrastructure is not designed to cater to pedestrian needs. Thus, they are forced to share limited resources with vehicles. In such a setup, conflicts between drivers and pedestrians are inevitable. Research shows humans cause most traffic accidents. Pedestrians are responsible for many traffic accidents and fatalities due to unsafe traffic behaviors. Some of the actions result from errors, while most are a violation of traffic rules—jaywalking. The study sought to examine the predictors of jaywalking. Qualitative approach was adopted involving observing participants' behaviors and characteristics crossing streets. The study finds that time pressure, age, and distractions are the most significant contributors to jaywalking.
Jay Walking Research Paper
Research Background
Traffic accidents involving pedestrians have become a significant concern in many nations due to increased urbanization. Asaithambi et al. (2016) attribute these accidents to a lack of adherence to traffic rules by pedestrians and drivers. Guo et al. (2011) find that pedestrian errors account for 59 percent of vehicle-pedestrian accidents in a separate study. The act of a pedestrian illegally crossing a street is known as jaywalking (Mullen et al., 1990). Xu et al. (2013) cite that pedestrians account for 65 percent of road deaths worldwide. In most countries, road designs do not feature adequate pedestrian facilities, causing major conflict between pedestrians and vehicles sharing limited resources, as Asaithambi et al. (2016) suggest. Pedestrian crossing behavior is complex and a significant concern in roads today.
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Various parameters play into pedestrian road crossing behaviors. According to Guo et al. (2011), pedestrians are generally expected to exercise greater caution when crossing streets, waiting to cross, and walking along roads. The increasing number of road accidents involving pedestrians is because they are often found not to exercise the above cautions. Xu et al. (2013) describe unsafe road behaviors as a product of either error or violation of traffic rules. While errors constitute an unintentional deviation from correct action, the offense is a deliberate breach of regulation. As Xu et al. (2013) assert, violation, rather than error, is the leading cause of pedestrian-related road accidents.
In their study, conducted within the Chinese context, Li and his collaborators (2014) link jaywalking to situational factors such as complex roadway systems and waiting duration. According to the survey, time pressure is related to impulse and unsafe behaviors even on roads. Asaithambi et al. (2016) further link jaywalking to age, crossing patterns, gender, crossing times, waiting times, speed, and vehicle types. The increasing rate of jaywalking-related accidents prompted an investigation into the predictors of jaywalking.
1.1 Hypothesis
H1: The leading predictors of jaywalking include time pressure and age.
1.2 Justification of the Project
Pedestrian fatalities are at an all-time high. According to the National Highway Traffic Safety Administration (NHTSA), an agency of the United States Department of Transportation, pedestrians killed in traffic crashes increased by three percent in 2018, totaling 6,283 deaths—the most deaths since 1990 ("Pedestrian Safety", 2021) . The growing trend of pedestrian fatalities on the roadshows jaywalking laws' ineffectiveness makes the roads safer for users. Xu et al. (2012) further emphasize that human factors are responsible for 95 percent of traffic accidents. Therefore, research into the predictors of jaywalking would contribute to developing proper measures to curb the problem.
2.0 Methods
2.1 Participants
A total of 15 participants were selected for the survey. Age groups of the participants ranged between young (14-19), adults (20-45), and the elderly (56-65). The sample constituted nine males (60 percent) and six females (40 percent).
2.2 Materials and Procedure
Materials needed for the survey included an ethogram, a writing utensil, a notepad, and a stopwatch. The researcher went to an intersection in Queens Bridge Borough, New York City, and stood at a visual distance. The researcher observed and recorded the participants. Behavioral characteristics of the subjects such as standing location, distractors, walking on a light, direction of view, speed of crossing, mask, perceived age, and herd-walking were observed and recorded on the notepad and ethogram.
3.0 Results
Data collection was categorized into three themes—pedestrian behaviors, characteristics, and environment. The behavior theme covered seven elements, including walking on light, waiting, distractors, crossing speed, herd walking, and direction looked. Characteristics covered four aspects, including the size of group crossing, mask, dependents, and perceived age. The theme of the environment was concerned with the day of the week, type of street, lanes, presence of police, date, time of day, temperature, and location. The results are summarized in Table 1.
Table 1: Findings
| Theme | Questions | Participants | |
| Behavior | Looked left, right, neither | Left | 6 |
| Right | 1 | ||
| Both ways | 4 | ||
| Neither | 4 | ||
| Walked on red, green, or flashing | Red | 4 | |
| Green | 11 | ||
| Flashing | 0 | ||
| If waited, where? | Curb/sidewalk | 9 | |
| Street/crosswalk | 6 | ||
| How many seconds waited? | Less than 5 | 7 | |
| 6-10 | 0 | ||
| 11-15 | 3 | ||
| 16-20 | 1 | ||
| More than 20 | 4 | ||
| Distractors | Phone | 3 | |
| Bags | 1 | ||
| Food/drink | 6 | ||
| Others | 5 | ||
| Speed of crossing | Slow | 4 | |
| Normal | 10 | ||
| Jog | 1 | ||
| Run | 0 | ||
| Herd-walking | Yes | 6 | |
| No | 9 | ||
| Characteristics | Size of crossing group | 1 person | 7 |
| 2-5 people | 4 | ||
| More than 6 | 4 | ||
| Cross with dependents | Child | 2 | |
| Pets | 0 | ||
| Disabled | 0 | ||
| No | 13 | ||
| Did they wear masks | Yes | 13 | |
| No | 2 | ||
| Perceived age group | Young | 3 | |
| Adult | 11 | ||
| Older | 1 | ||
| Environment | Weekend or weekday | Weekend | 5 |
| Weekday | 10 | ||
| One-way or two-way | One-way | 15 | |
| Two-way | 0 | ||
| Number of lanes of traffic crossed | 1 | 0 | |
| 2 | 15 | ||
| Presence of police | Yes | 1 | |
| No | 14 |
Diagram 1: Behaviors Contributing to Jaywalking
Diagram 2: Walked on light
4.0 Discussion
The project sought to determine the predictors of jaywalking among pedestrians in Manhattan. Data was collected in three themes depicting pedestrians' behaviors and characteristics and the environment for street crossing. Unsafe pedestrian behaviors, as previous studies such as Asaithambi et al. (2016), Li et al. (2014), and Xu et al. suggest, are responsible for jaywalking. For instance, waiting time, speed of crossing, waiting for location, and distractors are joint. Close to half the participants waited less than five seconds before crossing, with 27 percent of them crossing despite the red light. From the data, a significant number of pedestrians do not check both sides of the street before crossing, are distracted by food/drink, phone, or other objects when crossing, and cross at abnormal speeds. Even though jaywalking occurs in the absence of police, some pedestrians cross illegally, even in the presence of law enforcement agents. The study confirms the hypothesis that time pressure and age are leading factors of jaywalking.
References
Asaithambi, G., Kuttan, M. O., & Chandra, S. (2016). Pedestrian road crossing behavior under mixed traffic conditions: a comparative study of an intersection before and after implementing control measures. Transportation in Developing Economies , 2 (2), 1-12.
Guo, H., Wang, W., Guo, W., Jiang, X., & Bubb, H. (2012). Reliability analysis of pedestrian safety crossing in urban traffic environment. Safety Science , 50 (4), 968-973.
Li, D., Li, Y., & Yuan, X. (2014, October). Effect of situational factors on pedestrian intention to jaywalk. In 17th International IEEE Conference on Intelligent Transportation Systems (ITSC) (pp. 1770-1774). IEEE.
Mullen, B., Copper, C., & Driskell, J. E. (1990). Jaywalking as a function of model behavior. Personality and Social Psychology Bulletin , 16 (2), 320-330.
Pedestrian Safety. (2021). Retrieved 7 March 2021, from https://www.nhtsa.gov/road-safety/pedestrian-safety
Xu, Y., Li, Y., & Zhang, F. (2013). Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China. Accident Analysis & Prevention , 50 , 811-819.
