Jing Dong-O'Brien

Dr. Jing Dong-O'Brien

orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2014 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Open access
JDJing Dong-O'Brien
Jing Dong-O'Brien
CLChangzheng Liu
Changzheng Liu
Zhenhong LinZhenhong Lin
Zhenhong Lin

1 May 2019 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
LHLiang Hu
Liang Hu
JDJing Dong-O'Brien
Jing Dong-O'Brien
Zhenhong LinZhenhong Lin
Zhenhong Lin

1 February 2018 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
LHLiang Hu
Liang Hu
JDJing Dong-O'Brien
Jing Dong-O'Brien
Zhenhong LinZhenhong Lin
Zhenhong Lin
JYJie Yang
Jie Yang

20 June 2019 in IEEE Intelligent Transportation Systems Magazine
Verified
Journal Article
Closed access
CLChaoru Lu
Chaoru Lu
JDJing Dong-O'Brien
Jing Dong-O'Brien
LHLiang Hu
Liang Hu
This paper presented an energy-efficient adaptive cruise control, called Energy-Efficient Electric Driving Model (E3DM), for electric, connected, and autonomous vehicles (e-CAVs) in a mixed traffic stream. E3DM is able to maintain high energy efficiency of regenerative braking by adjusting the spacing between the leading and the following vehicles. Moreover, a power-based energy consumption model is proposed to estimate the on-road energy consumption for battery electric vehicles, considering the impact of ambient temperature on auxiliary load. Using the proposed energy consumption model, the impact of E3DM on vehicle energy consumption is investigated. In particular, single-lane vehicle dynamics in a traffic stream with a mixed of e-CAVs and human-driven vehicles are simulated. The result shows that E3DM outperforms existing adaptive cruise control (i.e. Nissan-ACC) and cooperative adaptive cruise control (i.e. Enhanced-IDM and Van Arem Model) strategies in terms of energy consumption. Moreover, higher market penetration of e-CAVs may not result in better energy efficiency of the entire fleet. The reason is that more e-CAVs in the traffic stream results in faster string stabilization which decreases the regenerative energy. Considering mix traffic streams with battery electric (BEVs) and internal-combustion engine (ICEVs) vehicles, the energy consumption of entire fleet reduces when the market penetration of BEV (contains both e-CAV and human-driven BEV) increases. A higher ratio of e-CAV to human-driven BEV results in higher energy efficiency.

1 September 2018 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
BWBo Wang
Bo Wang
SHShauna L Hallmark
Shauna L Hallmark
PSPeter Savolainen
Peter Savolainen
JDJing Dong-O'Brien
Jing Dong-O'Brien

1 December 2017 in Journal of Safety Research
Verified
Journal Article
Closed access
BWBo Wang
Bo Wang
SHShauna L Hallmark
Shauna L Hallmark
PSPeter Savolainen
Peter Savolainen
JDJing Dong-O'Brien
Jing Dong-O'Brien