Dynamic model for pedestrian crossing in congested traffic based on probabilistic navigation function

Hacohen, Shlomi; Shvalb, Nir; Shoval, Shraga

doi:10.1016/j.trc.2017.10.024

Cited by 18 publications

(8 citation statements)

References 51 publications

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“…M is defined as the mutation energy that is proportional to the number of mutated pixels L M , and quickly reduces the value of R 0 of the road segment. The log function is used to measure mutation energy in (15), and w M is the coefficient of mutation. Note that the logarithmic bases of the inertial energy function and mutation energy function are different: One is in the natural base e and the other is inverse of e:…”

Section: E Inertia Mutation Energy Modelmentioning

confidence: 99%

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Inertia Mutation Energy Model to Extract Roads by Crowdsourcing Trajectories

et al. 2019

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Obtaining trajectory-related data through crowdsourcing is a useful approach for acquiring and updating information on road networks because these data are easily accessible and up to date. However, it is challenging to ensure the accuracy of shape-and connectivity-related information on road networks when this is extracted from massive amounts of data. To address this challenge, this paper proposes an inertia mutation energy model (IMEM) to extract and mine information on road networks based on crowdsourced trajectories by using features of images of vehicular trajectories to mine the connectivity between roads. The central assumption of the model is that a road segment may have inertial energy to extend to another road segment that decreases in case of the change in direction. Three critical steps are involved in extracting information concerning roads. First, images of the trajectory and corresponding feature images are constructed, and high-quality trajectories are filtered to split the road into several segments. Second, the IMEM is proposed to measure the potential extension of each road segment with the aim of mining connectivity-related information between the given trajectories. Finally, the centerline of the road is obtained using mathematical morphology and a thinning algorithm. The proposed algorithm was tested by using Global Position System trajectories of the Didi Taxi in Wuhan, China, and the results show that it reduced time cost by over 99% compared with vector algorithms proposed in the literature. Moreover, it enhanced the precision of the results of extraction by 10%-20% compared with traditional kernel density evaluation algorithms. INDEX TERMS Crowdsourced trajectory data, connectivity, data mining, road reconstruction.

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Section: E Inertia Mutation Energy Modelmentioning

confidence: 99%

“…The problems in extracting high-quality trajectories and mining potential connectivity between them have been discussed in recent years [12]- [15]. In general, when a large number of GPS tracking points are repeatedly recorded on the same road, its morphology is unclear for discontinuous data.…”

Section: Introductionmentioning

confidence: 99%

Inertia Mutation Energy Model to Extract Roads by Crowdsourcing Trajectories

et al. 2019

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“…There have been several approaches to evaluating the safety of distracted pedestrian's road crossing behaviour. Some studies employed observational methods and manual data collection of real time pedestrian crossings (Banducci et al, 2016;Hacohen, Shvalb, & Shoval, 2018;Hatfield & Murphy, 2007;J. L. Nasar & Troyer, 2013).…”

Section: Past Studiesmentioning

confidence: 99%

Impact of smartphone distraction on pedestrians’ crossing behaviour: An application of head-mounted immersive virtual reality

Sobhani

Farooq

2018

Transportation Research Part F: Traffic Psychology and Behaviou

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A novel head-mounted virtual immersive/interactive reality environment (VIRE) is utilized to evaluate the behaviour of participants in three pedestrian road crossing conditions while 1) not distracted, 2) distracted with a smartphone, and 3) distracted with a smartphone with a virtually implemented safety measure on the road. Forty-two volunteers participated in our research who completed thirty successful (complete crossing) trials in blocks of ten trials for each crossing condition. For the two distracted conditions, pedestrians are engaged in a maze-solving game on a virtual smartphone, while at the same time checking the traffic for a safe crossing gap. For the proposed safety measure, smart flashing and color changing LED lights are simulated on the crosswalk to warn the distracted pedestrian who initiates crossing. Surrogate safety measures as well as speed information and distraction attributes such as direction and orientation of participant's head were collected and evaluated by employing a Multinomial Logit (MNL) model. Results from the model indicate that females have more dangerous crossing behaviour especially in distracted conditions; however, the smart LED treatment reduces this negative impact. Moreover, the number of times and the percentage of duration the head was facing the smartphone during a trial and a waiting time respectively increase the possibility of unsafe crossings; though, the proposed treatment reduces the safety crossing rate. Hence, our study shows that the smart LED light safety treatment indeed improves the safety of distracted pedestrians and enhances the successful crossing rate.

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“…Therefore, the location of tray-return spot is also a key influence factor in the normal evacuation process. Specifically, the contributions of this work can be summarized in the followings: (1) An exit choice model is proposed with the minimum evacuation time, wherein the evacuation time is estimated with explicit consideration of the effects of tray-return and pedestrians' destinations; (2) In the evacuation process, all available routes are analyzed and a route choice model considering pedestrian preference is proposed; (3) We present the layouts with two or four tray-return spots, and analyze the respective evacuation efficiency. The simulation results clearly indicate that the effect of tray-return reduces evacuation efficiency; the trayreturn spots are recommended to be set along the evacuation streamline and close to the exit.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Pedestrian Evacuation in University Canteen Based on Cellular Automata

Wang

Meng³

et al. 2019

IEEE Access

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In this study, we firstly build up an exit choice model to describe the pedestrians' exit choice behavior in a specific place, i.e., university canteens. The pedestrians are assumed to minimize their evacuation time in choosing exits by explicitly considering the estimated evacuation time and effects of pedestrians' destinations. In addition, the behavior of food tray return is also captured in the proposed route choice model for pedestrians. Fusing the exit choice model and the route choice model into a cellular automata (CA)based pedestrian simulation model, we simulate the pedestrian evacuation process in university canteen and the results illustrate the effectiveness of the modeling framework in terms of describing the evacuation process in university canteens. Specifically, destination is identified as a key influence factor for pedestrian evacuation, and pedestrians tend to select the exit that is closer to their destinations. If it is required to return the food tray to designated spots before leaving the canteen, the evacuation efficiency is significantly reduced. The simulation result can also assist in determining the optimal number of tray-return spots if maximum evacuation efficient is to be achieved. In presence of the specific parameter settings and canteen layout in the case study example, it is recommended to deploy four tray-return spots in the university canteen.INDEX TERMS University canteen, exit choice, route choice, pedestrian evacuation, cellular automata.

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Dynamic model for pedestrian crossing in congested traffic based on probabilistic navigation function

Cited by 18 publications

References 51 publications

Inertia Mutation Energy Model to Extract Roads by Crowdsourcing Trajectories

Inertia Mutation Energy Model to Extract Roads by Crowdsourcing Trajectories

Impact of smartphone distraction on pedestrians’ crossing behaviour: An application of head-mounted immersive virtual reality

Simulation of Pedestrian Evacuation in University Canteen Based on Cellular Automata

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