Novel Map Platform based on Primitive Elements of Traffic Environments for Automated Driving Technologies

Ito, Takuma; Mio, Masahiro; Tohriyama, Kyoichi; Kamata, Minoru

doi:10.20485/jsaeijae.7.4_143

Cited by 14 publications

(24 citation statements)

References 5 publications

(2 reference statements)

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“…In our previous study [1], we developed a system for localization on a digital map, in which an intelligent vehicle detected stop lines and guardrails as landmarks for localization. However, in our previous study, the experiments were conducted on a private test course that had only well-maintained stop lines.…”

Section: Conceptual Designmentioning

confidence: 99%

“…Recent advanced driver assistance systems (ADAS) such as warning and vehicle control systems and automated driving technologies require precise location information on a digital map. Stop lines are a beneficial clue for intelligent vehicles to localize on the digital map [1,2], and thus, their detection is important. To this end, several methods of stop-line detection have been developed.…”

Section: Introductionmentioning

confidence: 99%

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Detection of Damaged Stop Lines on Public Roads by Focusing on Piece Distribution of Paired Edges

2020

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In this study, a system for detecting stop lines on roads with damaged paint is developed to enhance a digital map localization system. Existing methods to detect stop lines focus on features such as straight edges and adequate size; however, these methods are not suitable to be used in rural areas because the paint of stop lines on the roads is damaged sometimes. In addition, lane marks, which are focused on by other existing methods, are often not present on actual roads in rural areas. Thus, to enable the detection of stop lines in the absence of conditions necessary for using the abovementioned features, we focus on pieces of faint features of damaged stop lines. First, we extract the positive and negative edges from an inverse perspective mapped image of the camera input by using a Sobel filter. Next, we verify the pairs of positive and negative edges from the trinarized edge image by confirming the width between both edges. Subsequently, we detect the candidates of stop lines by analyzing the distribution of the line segments extracted by the Hough transformation. In addition, we combine the data of the estimated driving distance and the result of detection of the preceding vehicles with the proposed system to prevent false detections in terms of bicycle crossing lanes and preceding vehicles. The damaged stop lines are detected eventually using these processes. To evaluate the performance of the proposed method, we collect driving data on actual public roads. The results of offline evaluations confirm that the proposed system can detect all target stop lines without any false detections, at a reasonable speed. The findings of this study are expected to contribute to the realization of intelligent vehicles on community roads.

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Section: Conceptual Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detection of Damaged Stop Lines on Public Roads by Focusing on Piece Distribution of Paired Edges

2020

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“…Then, the waypoint map reconstructor alternately creates a dense waypoint map, as shown on the right side of the figure. More detailed explanations appear in our previous paper (Ito et al, 2016). Figure 2 shows a conceptual schematic of the coordinate system in the LeanMAP framework.…”

Section: System Design 21 Overview Of Leanmapmentioning

confidence: 99%

“…In the first study of LeanMAP (Ito et al, 2016), we prepared the content of LeanMAP, such as the information of curves, by manually reducing a precise 3D map. However, this preparation method had a problem with regard to time and cost.…”

Section: Overview and Issue Of Leanmap Deepeningmentioning

confidence: 99%

“…In other words, we need to discuss two topics: the new data structure of digital map for reducing the data size, and the preparation method of digital map contents for the new data structure with reducing the manual operations. For the first topic, in our previous studies, we proposed LeanMAP, which is a new digital map framework (Ito et al, 2016). The LeanMAP framework does not preliminarily prepare the dense waypoint map which consists of many waypoints indicating the road shape; rather, it dynamically reconstructs the dense waypoint map from elemental information of the road shape on demand.…”

Section: Introductionmentioning

confidence: 99%

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Deepening method for LeanMAP content based on a virtual trajectory by lateral transcription

Ito

Nakamura

Tohriyama

et al. 2019

Mechanical Engineering Journal

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In this study, we aim to develop a new upgrading method of digital map content for automated driving on nationwide public roads. In general, a dense waypoint map based on a digital map is necessary to realize precise motion controls of intelligent automobiles. However, current preparation methods for digital maps have two problems for practical use on public roads in wide areas: the size of the map data for onboard storage and the monetary and human resources for manual mapping processes. To solve these problems, in our previous study, we proposed a new digital map called "LeanMAP," which consists of elementary information about the road, and also proposed an upgrading method of its contents from the level of car navigation map to the level of quasi-precise map. Furthermore, in this study, we propose another upgrading method based on a virtual trajectory to reduce the number of resources necessary for the mapping process to as low as possible. First, we propose a lateral transcription method that generates a virtual trajectory of an adjacent lane. Although three or more driving data items are necessary in order to upgrade the LeanMAP contents in the previous method, the proposed method in this study requires only one item of driving data. Then, to evaluate the accuracy of the dense waypoint map based on the elemental information upgraded by the proposed method, we conduct an initial evaluation using actual driving data on a public road. As a result, we confirm that the proposed system satisfies the target value of less than 1 % lateral error. From this result, we confirm the feasibility that our proposed system can reduce the cost and manual operations of mapping a precise digital map.

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Effect of risk-predictive haptic guidance in one-pedal driving mode

Saito

Raksincharoensak

2019

Cogn Tech Work

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The research presented in this article focuses on the design of a driver support system for risk-predictive driving under a potentially hazardous situation for a pedestrian who crosses a road from the driver's blind spots. Our aim is to develop a system that would cooperate with the driver in leading the normative speed calculated by the co-driver function. The design philosophy of haptic guidance is to communicate to the drivers the potentially hazardous situation through tactile cues from the active gas pedal and to assist drivers to in preparing for possible road surprises. We intended to combine the algorithm of the haptic feedback loop with the functionality of the one-pedal driving mode interface. Three design issues for the haptic guidance system can be distinguished: the design of a one-pedal driving mode based on a one-pedal operation; the modeling of risk-predictive driving behavior; and the haptic feedback algorithm with active gas pedal. We tested our system in human-in-the-loop experiments in a driving simulator to investigate (1) the effect of the onepedal driving mode interface on the driver behavior and (2) the effect of haptic guidance support on the driver behavior. From the results of our experiments, we confirmed that haptic guidance can improve the riskpredictive driving performance for a slowdown task via the one-pedal driving mode.

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Novel Map Platform based on Primitive Elements of Traffic Environments for Automated Driving Technologies

Cited by 14 publications

References 5 publications

Detection of Damaged Stop Lines on Public Roads by Focusing on Piece Distribution of Paired Edges

Detection of Damaged Stop Lines on Public Roads by Focusing on Piece Distribution of Paired Edges

Deepening method for LeanMAP content based on a virtual trajectory by lateral transcription

Effect of risk-predictive haptic guidance in one-pedal driving mode

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