457 citations · 533 across the 13 of their papers we have counts for
13 papers
Object level footprint uncertainty quantification in infrastructure based sensing
Arpan Kusari, Asma Almutairi, Mark E. Gilbert +1
We examine the problem of estimating footprint uncertainty of objects imaged using the infrastructure based camera sensing. A closed form relationship is established between the gr…
A Novel Traffic Simulation Framework for Testing Autonomous Vehicles Using SUMO and CARLA
Pei Li, Arpan Kusari, David J. LeBlanc
Traffic simulation is an efficient and cost-effective way to test Autonomous Vehicles (AVs) in a complex and dynamic environment. Numerous studies have been conducted for AV evalua…
Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles
Arpan Kusari, Pei Li, Hanzhi Yang +4
Current autonomous vehicle (AV) simulators are built to provide large-scale testing required to prove capabilities under varied conditions in controlled, repeatable fashion. Howeve…
Vehicle Energy Dataset (VED), A Large-scale Dataset for Vehicle Energy Consumption Research
G. S. Oh, David J. Leblanc, Huei Peng
We present Vehicle Energy Dataset (VED), a novel large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset capture…
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…
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…
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…
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…
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…
Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers
Ding Zhao, Xianan Huang, Huei Peng +2
The safety of Automated Vehicles (AVs) must be assured before their release and deployment. The current approach to evaluation relies primarily on (i) testing AVs on public roads o…
Accelerated Evaluation of Automated Vehicles Safety in Lane Change Scenarios Based on Importance Sampling Techniques
Ding Zhao, Henry Lam, Huei Peng +4
Automated vehicles (AVs) must be evaluated thoroughly before their release and deployment. A widely-used evaluation approach is the Naturalistic-Field Operational Test (N-FOT), whi…