A modular road auto-generating algorithm for developing the road models for driving simulators

Brişan, Cornel; Vasiu, Razvan-Vlad; Munteanu, Ligia

doi:10.1016/j.trc.2012.09.008

Cited by 6 publications

(5 citation statements)

References 18 publications

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“…Virtual lanes are often used to express the traffic details of intersections in lane-level road maps [37]. Popular functions for describing lanes include the circular arc curve [38], clothoid curve [39], cubic Hermite curve [40], and B-spline curve [41]. We first determined the road sections that are included in the intersection and pass through a point adjacent to the road terminal.…”

Section: Intersection Graph Constructionmentioning

confidence: 99%

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

Zheng

Song²,

et al. 2019

IJGI

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With the development of autonomous driving, lane-level maps have attracted significant attention. Since the lane-level road network is an important part of the lane-level map, the efficient, low-cost, and automatic generation of lane-level road networks has become increasingly important. We propose a new method here that generates lane-level road networks using only position information based on an autonomous vehicle and the existing lane-level road networks from the existing road-level professionally surveyed without lane details. This method uses the parallel relationship between the centerline of a lane and the centerline of the corresponding segment. Since the direct point-by-point computation is huge, we propose a method based on a trajectory-similarity-join pruning strategy (TSJ-PS). This method uses a filter-and-verify search framework. First, it performs quick segmentation based on the minimum distance and then uses the similarity of two trajectories to prune the trajectory similarity join. Next, it calculates the centerline trajectory for lanes using the simulation transformation model by the unpruned trajectory points. Finally, we demonstrate the efficiency of the algorithm and generate a lane-level road network via experiments on a real road.

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Section: Intersection Graph Constructionmentioning

confidence: 99%

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

Zheng

Song²,

et al. 2019

IJGI

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“…L. Nasar & Troyer, 2013). In addition, there have been many studies (Banducci et al, 2016;Brisan, Vasiu, & Munteanu, 2013;Dommes, Cavallo, Dubuisson, Tournier, & Vienne, 2014;Farooq et al, 2018;Ye, Xiao, & Yang, 2017) that made use of virtual environments due to their attractive features of being controlled for specific design scenarios and pose no risk to participants. Muehlbacher et al studied the benefits and challenges of multi-road user VR simulations compared to single driver simulations, and at the end recommended the case where the multi road user simulation was appropriate (Muehlbacher, Preuk, Lehsing, Will, & Dotzauer, 2018).…”

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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“…To shape of the unknown contact domain is taken as a superellipse defined by a Lamé curve [17,12,8,35,36] x aðtÞ n þ y bðtÞ n ¼ 1; n 4 0; ð2:3Þ…”

Section: The Contact and Friction Forcesmentioning

confidence: 99%

“…The aim of sonification is to create a road design algorithm as previously mentioned by Brisan et al [8] and Vasiu and Brisan [50].…”

Section: Direct and Inverse Sonification Algorithmsmentioning

confidence: 99%

On the 3D normal tire/off-road vibro-contact problem with friction

Munteanu

Chiroiu

Brişan

et al. 2015

Mechanical Systems and Signal Processing

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A modular road auto-generating algorithm for developing the road models for driving simulators

Cited by 6 publications

References 18 publications

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

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

On the 3D normal tire/off-road vibro-contact problem with friction

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