457 citations · 1.2k across the 55 of their papers we have counts for
20 papers · 1 filter
Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles
Xun Gong, Yaohui Guo, Yiheng Feng +2
The energy efficiency of Connected and Automated Vehicles (CAVs) is significantly influenced by surrounding road users. This paper presents the evaluation of energy efficiency of C…
Interpenetrating Cooperative Localization in Dynamic Connected Vehicle Networks
Huajing Zhao, Zhaobin Mo, Macheng Shen +2
In this paper, we proposed the Interpenetrating Cooperative Localization (ICL) method to enhance the localization accuracy in dynamic connected vehicle networks. This mechanism mak…
Semi-Interpenetrating Cooperative Localization in Connected Vehicle Networks
Macheng Shen, Huajing Zhao, Jing Sun +1
We proposed a fusion mechanism for the distributed cooperative map matching (CMM) within the vehicular ad-hoc network. This mechanism makes the information from each node reachable…
A Kinodynamic Aggressive Trajectory Planner For Narrow Passages
Yaohui Guo, Zhaolun Su, Dmitry Berenson +1
Planning a path for a nonholonomic robot is a challenging topic in motion planning and it becomes more difficult when the desired path contains narrow passages. This kind of scenar…
Optimal design of three-planetary-gear power-split hybrid powertrains
Weichao Zhuang, Xiaowu Zhang, Ding Zhao +2
Many of today's power-split hybrid electric vehicles (HEVs) utilize planetary gears (PGs) to connect the powertrain elements together. Recent power-split HEVs tend to use two PGs a…
Gap Acceptance During Lane Changes by Large-Truck Drivers-An Image-Based Analysis
Kazutoshi Nobukawa, Shan Bao, David J. LeBlanc +3
This paper presents an analysis of rearward gap acceptance characteristics of drivers of large trucks in highway lane change scenarios. The range between the vehicles was inferred…
Analysis of mandatory and discretionary lane change behaviors for heavy trucks
Ding Zhao, Huei Peng, Kazutoshi Nobukawa +3
The behaviors of heavy vehicles drivers in mandatory and discretionary lane changes are analyzed in this paper. 640 mandatory and 2,035 discretionary lane change events were extrac…
Towards Affordable On-track Testing for Autonomous Vehicle - A Kriging-based Statistical Approach
Zhiyuan Huang, Henry Lam, Ding Zhao
This paper discusses the use of Kriging model in Automated Vehicle evaluation. We explore how a Kriging model can help reduce the number of experiments or simulations in the Accele…
An Accelerated Testing Approach for Automated Vehicles with Background Traffic Described by Joint Distributions
Zhiyuan Huang, Henry Lam, Ding Zhao
This paper proposes a new framework based on joint statistical models for evaluating risks of automated vehicles in a naturalistic driving environment. The previous studies on the…
Sequential Experimentation to Efficiently Test Automated Vehicles
Zhiyuan Huang, Henry Lam, Ding Zhao
Automated vehicles have been under heavy developments in major auto and tech companies and are expected to release into market in the foreseeable future. However, the road safety o…
The Impact of Road Configuration in V2V-based Cooperative Localization: Mathematical Analysis and Real-world Evaluation
Macheng Shen, Jing Sun, Ding Zhao
Cooperative map matching (CMM) uses the Global Navigation Satellite System (GNSS) position information of a group of vehicles to improve the standalone localization accuracy. It ha…
Analysis of Unprotected Intersection Left-Turn Conflicts based on Naturalistic Driving Data
Xinpeng Wang, Ding Zhao, Huei Peng +1
Analyzing and reconstructing driving scenarios is crucial for testing and evaluating automated vehicles. This research analyzed left turn / straight-driving conflicts at unprotecte…
Towards Secure and Safe Appified Automated Vehicles
Yunhan Jack Jia, Ding Zhao, Qi Alfred Chen +1
The advancement in Autonomous Vehicles (AVs) has created an enormous market for the development of self-driving functionalities,raising the question of how it will transform the tr…
Improving Localization Accuracy in Connected Vehicle Networks Using Rao-Blackwellized Particle Filters: Theory, Simulations, and Experiments
Macheng Shen, Ding Zhao, Jing Sun +1
A crucial function for automated vehicle technologies is accurate localization. Lane-level accuracy is not readily available from low-cost Global Navigation Satellite System (GNSS)…
Development and Evaluation of Two Learning-Based Personalized Driver Models for Car-Following Behaviors
Wenshuo Wang, Ding Zhao, Junqiang Xi +2
Personalized driver models play a key role in the development of advanced driver assistance systems and automated driving systems. Traditionally, physical-based driver models with…
The Impact of Road Configuration on V2V-based Cooperative Localization
Macheng Shen, Ding Zhao, Jing Sun
Cooperative localization with map matching has been shown to reduce Global Navigation Satellite System (GNSS) localization error from several meters to sub-meter level by fusing th…
Evaluation of A Semi-Autonomous Lane Departure Correction System Using Naturalistic Driving Data
Ding Zhao, Wenshuo Wang, David J. LeBlanc
Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficient evaluation method f…
Evaluation of Lane Departure Correction Systems Using a Stochastic Driver Model
Wenshuo Wang, Ding Zhao
Evaluating the effectiveness and benefits of driver assistance systems is crucial for improving the system performance. In this paper, we propose a novel framework for testing and…
Accelerated Evaluation of Automated Vehicles Using Piecewise Mixture Models
Zhiyuan Huang, Ding Zhao, Henry Lam +1
The process to certify highly Automated Vehicles has not yet been defined by any country in the world. Currently, companies test Automated Vehicles on public roads, which is time-c…
Evaluation of Automated Vehicles in the Frontal Cut-in Scenario - an Enhanced Approach using Piecewise Mixture Models
Zhiyuan Huang, Ding Zhao, Henry Lam +2
Evaluation and testing are critical for the development of Automated Vehicles (AVs). Currently, companies test AVs on public roads, which is very time-consuming and inefficient. We…