Pedestrian Crossing Behaviour Analysis at Intersections

Jain, Akash; Gupta, Ankit; Rastogi, R. G.

doi:10.7708/ijtte.2014.4(1).08

Cited by 83 publications

(53 citation statements)

References 17 publications

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“…10, in the study by [107] in India, the pedestrians were observed to take higher risks while crossing and thus the mean speed was higher in comparison to other studies. Similarly, in the case of study by [103] in Iran, the attire contributed towards the lower pedestrian crossing speeds at unsignalized crosswalks.…”

Section: Crosswalk and Crossing Facilitymentioning

confidence: 42%

“…Similar studies in India studies were conducted by [50,[105][106][107][108][109] over crosswalk and mid-block crossings respectively, and gap acceptance behaviour was mainly measured under mixed traffic condition. The study by [105] observed the average accepted gaps to cross intersections were 4.75 s, 3.35 s and 3.50 s by elderly, middle-aged and young pedestrians; while in 2014 the same authors [106] used Artificial Neural Network (ANN) technique to predict gap acceptance behaviour under different mixed traffic conditions.…”

Section: Crosswalk and Crossing Facilitymentioning

confidence: 76%

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Pedestrian flow characteristics and level of service on dissimilar facilities: A critical review

2018

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Present paper reviewed the past studies on pedestrian flow characteristics (such as speed, flow, density, space, free-flow speed and jam density) and development of Pedestrian Level of Service (PLOS) for various pedestrian facilities (i.e., sidewalk, walkway, crosswalk, grade separated, stairways and escalators. Fundamental relationships (between speed and density) were observed over different facilities and were found to be significantly different. The fundamental relationships for sidewalk facility predicted the range of free flow speeds to be 65 − 85 m/min and jam densities to be 3.5 − 5.3 ped/m 2 . The minimum and maximum pedestrian speeds over sidewalk facility in different countries observed were 52 m/min and 98 m/min respectively, with a mean speed of 79 m/min. The male pedestrians walked at 4 − 9 m/min higher speed in comparison to their female counterparts; while the older pedestrians walked at 15 − 20 m/min lower speed than the younger ones over the various types of crosswalk facilities. Similarly, speed-density relationships for ascending and descending stairways showed that the difference between the two directions varied between 4 − 12 m/min, and that the speed was significantly higher in case of descending direction. Moreover, the jam densities for stairways were also observed to be lower in case of descending direction, as the pedestrians generally maintain higher gap (than in ascending direction) with other pedestrians in front to avoid pushing and the risk of falling down. The flow characteristics were significantly influenced by the type of facility, width, age, gender and location of the study. Primarily factors such as physique (height), culture (dress), attractions (presence of hawkers located along sidewalks), friction (due to parked vehicles), purpose of walking trip and environmental conditions were the main reasons for pedestrians of countries such as Saudi Arabia, Iraq, Bangladesh, Indonesia and Sri-Lanka to walk significantly slower than the counterparts pedestrians in the USA, UK or Canada. The review conducted on the PLOS mainly looked into the type of survey conducted (qualitative vs. quantitative), LOS parameters and the various software/models used in development of LOS. Researchers from the USA and Japan preferably used both qualitative and quantitative approaches in defining LOS over sidewalks; while in India, China and Malaysia qualitative method was highly preferred. Pedestrian volume, safety, surface, obstruction and width were observed as essential parameters for qualitative survey while density, flow rate, pedestrian speed and width were used in quantitative survey for sidewalks. In developing the PLOS over sidewalk facility; Conjoint analysis, Landis method, HCM method, affinity propagation cluster algorithm and Gainesville method were preferred by various researchers. Studies conducted over crosswalk facility measured space, flow rate, vehicle volume and delay as the most significant factors in developing LOS based on quantitative technique; while vehicle speed, ...

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Section: Crosswalk and Crossing Facilitymentioning

confidence: 42%

Section: Crosswalk and Crossing Facilitymentioning

confidence: 76%

Pedestrian flow characteristics and level of service on dissimilar facilities: A critical review

2018

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“…Based on the gap acceptance theory researchers have developed mathematical models to represent the gap acceptance behavior of pedestrian with the help of pedestrian demographic characteristics such as gender and age [5], types of vehicle and waiting time [6], effect of rolling gap [7], effect of parked vehicles [8], non-compliant road crossing behavior at midblock locations [9], [10] and non-compliant road crossing behavior at signalized intersection [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Pedestrian Gap Acceptance and Crossing Decision in Kuala Lumpur

Nor

Daniel

Hamidun³

et al. 2017

MATEC Web Conf.

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Abstract:Pedestrians are most vulnerable of all road users. This research aims to investigate and model pedestrian road crossing behaviour at crossing facilities. In particular, they have two aspects of pedestrians crossing behaviour are examined, namely the size of traffic gaps acceptance by pedestrians and the decision of pedestrians either to cross the road or not. A fields survey was carried out at six crossing facilities which from a zebra crossing at midblock. In this survey, the data were recorded in real traffic condition using video recorder. Determine the associations between characteristics of pedestrians, crossing facilities and vehicular traffic through on-site observations of pedestrian behaviour. This data will analysis using statistical analysis which is multiple regression and binary logit regression method. It is hope that through this research, the model of pedestrian gap acceptance and pedestrian crossing decision can be reached and what are the indicators that pedestrians look for when accepting gaps to cross the road.

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“…Under mixed traffic conditions a model for the pedestrian level of service has been developed by considering pedestrian delay and the perception on safety and comfort (Nagraj and Vedagiri, 2013). Analysed about pedestrian safety at intersections also been studied with respect to the safety margin and gap accepted by pedestrian considering different aspects like age, gender, carrying baggage as well as crossing pattern (Jain et al, 2014). Empirical test for the renowned delay models taking a case study on the city center of Bologna, Italy shows that simple models relaying only on cycle timing and geometric parameters are not adequate to represent the actual delay (Mantecchini and Paganelli, 2015).…”

Section: Introductionmentioning

confidence: 99%

Defining Pedestrian Level of Service at Signalized Intersections Through Modelled Parameters and Som Clustering

2017

IJTTE

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Aim of this study is to define pedestrian levels of service (PLOS) categories (A-F) at signalized intersections under the influence of mixed traffic flow. Both quantitative and qualitative factors affecting the service measure have been identified and modelled using ridge regression method. Along with road geometric and traffic operational data, effective 675 pedestrian perceptions of real-time sense of satisfaction have been used in the model development. A PLOS score model has been developed taking perceived satisfaction score as the dependent variable and factors such as no of lanes, 85 th percentile speed of vehicles, volume of through moving vehicles, left turning motorized and non-motorized vehicles, permissible right turning motorized and non-motorized vehicles and pedestrian delay as independent variables. Delays used in PLOS model were estimated by the combination of waiting time delay and vehicle interaction delay. Having R 2 value of 0.986 PLOS model was well validated. PLOS scores of six categories were defined by applying Self-Organizing Map (SOM) in Artificial Neural Network (ANN) clustering. Analysis shows that about 75% of total crosswalks were offering average or above service levels, whereas only 4 % were contributing very poor kind of service to pedestrians in the study areas.

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Pedestrian Crossing Behaviour Analysis at Intersections

Cited by 83 publications

References 17 publications

Pedestrian flow characteristics and level of service on dissimilar facilities: A critical review

Pedestrian flow characteristics and level of service on dissimilar facilities: A critical review

Analysis of Pedestrian Gap Acceptance and Crossing Decision in Kuala Lumpur

Defining Pedestrian Level of Service at Signalized Intersections Through Modelled Parameters and Som Clustering

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