Mapping Pedestrian-Vehicle Behavior at Urban Undesignated Mid-Block Crossings under Mixed Traffic Environment – A Trajectory-Based Approach

Golakiya, Hareshkumar Dahyabhai; Chauhan, Ritvik; Dhamaniya, Ashish

doi:10.1016/j.trpro.2020.08.148

Cited by 5 publications

(3 citation statements)

References 1 publication

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“…The three paths are superimposed in Figure 4b. The set of road nodes for path ab (R ab ) is (7,8,9,12,13,20,25,30,34). Every two consecutive nodes represent a road segment; thus, R ab has eight segments.…”

Section: Cycling Rhythm Calculation Based On Path Segmentmentioning

confidence: 99%

“…The randomness of bicycle trips, the discontinuity of scenario capture, and the acquisition difficulty of cycling speed data may be possible reasons for the less attention paid to cycling speed variability, whereas traffic flow theory focuses on readily available pedestrians and automobiles [6][7][8]. In previous limited studies, cycling speed is obtained using stopwatch, radar, video, and global positioning system instruments [9], which cannot solve the homogenous nature of data.…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

Chen

Jiang

2021

IJGI

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Cycling rhythm performance is the result of a complex interplay between active travel demand and cycling network supply. Most studies focused on bicycle flow, but little attention has been paid to cycling rhythm changes for public bicycles. Full sample data of origin–destination enables an efficient description of network-wide cycling mobility efficiency in urban public bicycle systems. In this paper, we show how the spatiotemporal characteristics of cycling speed reveal the performance of cycling rhythms. The inference method of riding speed estimation is proposed with an unknown cycling path. The significant inconsistency of docking stations in cycling rhythm was unraveled by the source–sink relationship comparison. The asymmetry of the cycling rhythm on the path is manifested as the rhythm difference among paths and bidirectional inconsistency. We found that cycling rhythm has a temporal multilayer and spatial mismatch, which shows the inflection points of the cycling rhythm where the travel behavioral preference changes and the exact road segments with different rhythms. This finding suggests that a well-designed cycling environment and occupation-residential function should be considered in active transport demand management and urban planning to help induce active travel behavior decisions.

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Section: Cycling Rhythm Calculation Based On Path Segmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

Chen

Jiang

2021

IJGI

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“…The Time Difference to Conflict (TDTC) indicator combines the concepts of the TTC indicator and the PET indicator. To some extent, the TDTC overcomes the limitations of the TTC indicator and makes up for the shortcomings of the PET indicator [11]. It has been studied for the conflict between pedestrians and vehicles.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Conflict Detection Framework for Urban Intersections Based on an Improved Time Difference to Collision Indicator

Lei

Zhu

et al. 2021

Remote Sensing

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Urban road intersections are one of the key components of road networks. Due to complex and diverse traffic conditions, traffic conflicts occur frequently. Accurate traffic conflict detection allows improvement of the traffic conditions and decreases the probability of traffic accidents. Many time-based conflict indicators have been widely studied, but the sizes of the vehicles are ignored. This is a very important factor for conflict detection at urban intersections. Therefore, in this paper we propose a novel time difference conflict indicator by incorporating vehicle sizes instead of viewing vehicles as particles. Specially, we designed an automatic conflict recognition framework between vehicles at the urban intersections. The vehicle sizes are automatically extracted with the sparse recurrent convolutional neural network, and the vehicle trajectories are obtained with a fast-tracking algorithm based on the intersection-to-union ratio. Given tracking vehicles, we improved the time difference to the conflict metric by incorporating vehicle size information. We have conducted extensive experiments and demonstrated that the proposed framework can effectively recognize vehicle conflict accurately.

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Comparative Safety Assessment of Vehicle–Pedestrian Interactions at Urban Arterial and Highway Using UAV Data

Chouhan,

Shah,

Dalal

et al. 2023

Lecture Notes in Civil Engineering

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Mapping Pedestrian-Vehicle Behavior at Urban Undesignated Mid-Block Crossings under Mixed Traffic Environment – A Trajectory-Based Approach

Cited by 5 publications

References 1 publication

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

An Automatic Conflict Detection Framework for Urban Intersections Based on an Improved Time Difference to Collision Indicator

Comparative Safety Assessment of Vehicle–Pedestrian Interactions at Urban Arterial and Highway Using UAV Data

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