3-D Data Processing to Extract Vehicle Trajectories from Roadside LiDAR Data

Sun, Yuan; Xu, Hao; Wu, Jianqing; Zheng, Jianying; Dietrich, Kurt M.

doi:10.1177/0361198118775839

Cited by 60 publications

(27 citation statements)

References 16 publications

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“…Furthermore, the LiDAR is insensitive for light variation. The roadside LiDAR, also named side-fire LiDAR or stationary LiDAR, refers to the LiDAR deployed in a fixed LiDAR position, which is different from the traditional applications of LiDAR (airborne LiDAR and on-board LiDAR) [16]. The roadside LiDAR can be temporarily or permanently installed along the roads or at intersections.…”

Section: High-resolution Micro Traffic Data (Hrmtd) Collection Wimentioning

confidence: 99%

An Automatic Trigged Rectangular Rapid Flashing Beacons (RRFB) System Using the Roadside LiDAR Sensor

Cui

Jian

et al. 2019

IEEE Access

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The existing rectangular rapid flashing beacons (RRFB) could not be automatically trigged with acceptable accuracy. This paper introduces a strategy to develop an automatic trigged RRFB system using the roadside Light Detection and Ranging (LiDAR). The trajectories of the road users can be extracted in real-time with the proposed LiDAR data processing algorithms. The pedestrian/bicycle crossing intention was predicted with Naïve Bayes (NB) classifier. Different detection zones were provided to detect the pedestrian/bicycle crossing movements in real-time. The updated RRFB system was implemented at one intersection in Henderson, Nevada, United States. The results of the field test showed that the overall false rate of the updated RRFB system is very low (0.68%). The performance of the proposed method is superior compared to the state-of-the-art method. The updated RRFB system can greatly improve pedestrian safety at unsignalized intersections. INDEX TERMS Roadside LiDAR, vehicle-pedestrian conflicts, object tracking, rectangular rapid flashing beacons, pedestrian safety.

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Section: High-resolution Micro Traffic Data (Hrmtd) Collection Wimentioning

confidence: 99%

An Automatic Trigged Rectangular Rapid Flashing Beacons (RRFB) System Using the Roadside LiDAR Sensor

Cui

Jian

et al. 2019

IEEE Access

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“…The currently popular lidars also have some limitations and they are also relatively expensive. In this case, an estimation of the traffic exploits optical opacity of cars and laser beam reflections as the physical principle of working is often accompanied by advanced data processing [5]. Setting the sensor perpendicular to the axis of the road makes it impossible to count vehicles in the case of occlusion (vehicles present on both lanes simultaneously), which causes many missed detections.…”

Section: Introductionmentioning

confidence: 99%

Estimating Traffic Intensity Employing Passive Acoustic Radar and Enhanced Microwave Doppler Radar Sensor

2019

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Innovative road signs that can autonomously display the speed limit in cases where the traffic situation requires it are under development. The autonomous road sign contains many types of sensors, of which the subject of interest in this article is the Doppler sensor that we have improved and the constructed and calibrated acoustic probe. An algorithm for performing vehicle detection and tracking, as well as vehicle speed measurement, in a signal acquired with a continuous wave Doppler sensor, is discussed. A method is also experimentally presented and studied for counting vehicles and for determining their movement direction by means of acoustic vector sensor application. The assumptions of the method employing spatial distribution of sound intensity determined with the help of an integrated three-dimensional (3D) sound intensity probe are discussed. The enhanced Doppler radar and the developed sound intensity probe were used for the experiments that are described and analyzed in the paper.

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“…Other researchers using light detection and ranging (LiDAR) to generate the trajectories of road users for vehiclepedestrian conflicts analysis [26]. Compared to the video sensor, the LiDAR can work day and night with the influence of different light conditions [27].…”

Section: Introductionmentioning

confidence: 99%

Automatic Vehicle-Pedestrian Conflict Identification With Trajectories of Road Users Extracted From Roadside LiDAR Sensors Using a Rule-Based Method

Sun

et al. 2019

IEEE Access

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Vehicle-pedestrian conflicts have been the major concern for traffic safety. Surrogate safety measures are widely applied for pedestrian safety evaluation. However, how to quickly identify the vehiclepedestrian surrogate safety measures at the individual site is challenging due to the difficulty of obtaining the high-resolution trajectories of road users. This paper presented an effective method to generate the highresolution traffic trajectories from the roadside deployed Light Detection and Ranging (LiDAR) sensor. The vehicle-pedestrian conflicts can then be identified from the trajectories simply using the speed-distance profile (SDP) of the vehicles. The SDP can be used to develop a rule-based method for vehicle-pedestrian identification. The events can be divided into different risk levels based on the spatial distribution of the SDP. The case study shows that the rule-based method can detect vehicle-pedestrian near-crash events effectively. The other indicators, such as widely used time-to-collision (TTC) or deceleration rate to avoid a crash (DRAC), can be also obtained from the SDP. The engineers can also adjust the thresholds in the rule-based method to meet the specific requirements at different sites. The proposed method can be extended to identify vehicle-vehicle conflicts or vehicle-bicycle conflicts in future studies. INDEX TERMS Roadside LiDAR, vehicle-pedestrian conflicts, surrogate safety measures, high-resolution trajectories, pedestrian safety.

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3-D Data Processing to Extract Vehicle Trajectories from Roadside LiDAR Data

Cited by 60 publications

References 16 publications

An Automatic Trigged Rectangular Rapid Flashing Beacons (RRFB) System Using the Roadside LiDAR Sensor

An Automatic Trigged Rectangular Rapid Flashing Beacons (RRFB) System Using the Roadside LiDAR Sensor

Estimating Traffic Intensity Employing Passive Acoustic Radar and Enhanced Microwave Doppler Radar Sensor

Automatic Vehicle-Pedestrian Conflict Identification With Trajectories of Road Users Extracted From Roadside LiDAR Sensors Using a Rule-Based Method

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