Perception, Planning, Control, and Coordination for Autonomous Vehicles
Open accessAbstract
Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed.
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Human-sentient design, implementation, and distribution of automated systems is indispensable.
“However, from a social and technological aspect, the basic notion seems to be that human-sentient design, implementation, and distribution of automated systems is indispensable [87], [88].”
From A Review of Trustworthy and Explainable Artificial Intelligence (XAI) (2023) · cites this paper as [88]
The Conclusions (page unavailable) say that autonomous driving must address safety, reliability, and social and legal acceptability. This supports attention to people and social concerns in autonomous vehicles, but the paper does not say that human-sentient design, implementation, and distribution are indispensable for automated systems generally. (LLM, conf=0.78)
Experimental — accuracy not yet measuredAVs, as part of shared mobility, make access to mobility more affordable and could strongly benefit neighbourhoods with lower accessibility.
“Therefore, Pendleton et al. [35] argue that AVs, as part of shared mobility, make access to mobility more affordable and could strongly benefit neighbourhoods with lower accessibility.”
From The opportunity of shared autonomous vehicles to improve spatial equity in accessibility and socio-economic developments in European urban areas (2021) · cites this paper as [35]
Feedback controllers like PID are employed to prevent deviations from intended trajectories, but they have limits and only react to errors as they happen.
“Although they have limits and only react to errors as they happen [46], feedback controllers like the proportional-integral-derivative (PID) are employed to prevent deviations from intended trajectories.”
From Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches (2024) · cites this paper as [46]
There are still issues to be solved to enhance the driving capabilities of autonomous vehicles.
“Pendleton et al. (2017) review the development of autonomous vehicle software systems and conclude that there are still issues to be solved to enhance the driving capabilities of autonomous vehicles.”
From Shared autonomous vehicle services: A comprehensive review (2020) · cites this paper as Pendleton et al., 2017
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A survey of deep learning techniques for autonomous driving
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Shared autonomous vehicle services: A comprehensive review
Narayanan, S., Chaniotakis, E., & Antoniou, C. (2020) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2019.12.008 · Cited by 691 · see citing works
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Currie, G. (2019) · Journal of Transport and Land Use · doi:10.5198/jtlu.2019.1405 · Cited by 427 · see citing works
“Researchers also managed to place AVs on urban roads through the DARPA’s Urban Challenge Program (Pendleton et al., 2017; Shladover, 2018).”
BackgroundInfluentialA Review of Trustworthy and Explainable Artificial Intelligence (XAI)
Chamola, V., Hassija, V., Sulthana, A. R., Ghosh, D., Dhingra, D., & Sikdar, B. (2023) · IEEE Access · doi:10.1109/access.2023.3294569 · Cited by 352 · see citing works
“However, from a social and technological aspect, the basic notion seems to be that human-sentient design, implementation, and distribution of automated systems is indispensable [87], [88].”
BackgroundEnd-to-End Learning of Driving Models with Surround-View Cameras and Route Planners
Hecker, S., Dai, D., & Van Gool, L. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_27 · Cited by 191 · see citing works
Machine learning for next-generation intelligent transportation systems: A survey
Yuan, T., Da Rocha Neto, W., Rothenberg, C. E., Obraczka, K., Barakat, C., & Turletti, T. (2022) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.4427 · Cited by 179 · see citing works
Tahir, N. U. A., Zhang, Z., Asim, M., Chen, J., & ELAffendi, M. (2024) · Algorithms · doi:10.3390/a17030103 · Cited by 145 · see citing works
Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities
Lim, H. S. M., & Taeihagh, A. (2019) · Sustainability · doi:10.3390/su11205791 · Cited by 136 · see citing works
Hong, J.-W., Wang, Y., & Lanz, P. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1785693 · Cited by 130 · see citing works
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- Authors
- Pendleton, S., Andersen, H., Du, X., Shen, X., Meghjani, M., Eng, Y., Rus, D., & Ang, M.
- Affiliations
- National University of Singapore (SG)
- Singapore-MIT Alliance for Research and Technology (SG)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Pendleton, Scott
- ORCID
- Venue
- Machines
- Publisher
- MDPI AG
- Published
- 2017-02-17
- Volume
- 5
- Issue
- 1
- Pages
- 6
- ISSN
- 2075-1702 (ISSN-L)
- OpenAlex
- W2588289902
- Cited by
- 657
- References
- 304
- Citations by year
- 2026: 61 · 2025: 66 · 2024: 67 · 2023: 101 · 2022: 84 · 2021: 113 · 2020: 74 · 2019: 61 · 2018: 24 · 2017: 5 · 2014: 1
- FWCI
- 28.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Machines (publishedVersion, cc-by)
- National University of Singapore (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- autonomous vehicles, perception, planning, control, coordination, urban transport, sensor technology
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