The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
Open accessAbstract
Abstract. Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.
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“A sensor fusion strategy is often employed to avoid any single point of failure [147].”
From A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2020) · cites this paper as [147]
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Cites
Ultra-Wideband Radar Sensors for Short-Range Vehicular Applications
Gresham, I., Jenkins, A., Egri, R. G., Eswarappa, C., Kinayman, N., Jain, N., Anderson, R., Kolak, F. S., Wohlert, R. M., Bawell, S. P., et al. (2004) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2004.834185 · Cited by 285
Jones, W. D. (2001) · IEEE Spectrum · doi:10.1109/6.946636 · Cited by 272
Multisensor tracking of a maneuvering target in clutter
Houles, A., & Bar‐Shalom, Y. (1989) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/7.18679 · Cited by 185
Comparison of Lidar-Based and Radar-Based Adaptive Cruise Control Systems
Widmann, G. R., Daniels, M. K., Hamilton, L. A., Humm, L., Riley, B., Schiffmann, J. K., Schnelker, D. E., & Wishon, W. H. (2000) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2000-01-0345 · Cited by 88
Automatic track formation in clutter with a recursive algorithm
Bar‐Shalom, Y., Chang, K., & Blom, H. A. P. (2003) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.1989.70372 · Cited by 82
System aspects for future automotive radar
Schneider, R., & Wenger, J. (2003) · IEEE MTT-S International Microwave Symposium digest · doi:10.1109/mwsym.1999.779478 · Cited by 26
A wireless data link for mobile applications
Lindenmeier, S. M., Boehm, K., & Luy�, J.-F. (2003) · IEEE Microwave and Wireless Components Letters · doi:10.1109/lmwc.2003.815706 · Cited by 16
Millimeter-wave FMCW/monopulse radar front-end for automotive applications
Si, D. D., Luo, S. C., Pero, C., Wu, X., & Knox, R. (2003) · IEEE MTT-S International Microwave Symposium digest · doi:10.1109/mwsym.1999.779474 · Cited by 16
Research works printed but not linked: 2
- Bar-Shalom, Y., Li, X., and Kirubarajan, T.: Estimation with Ap- plications to Tracking an Navigation, John Wiley & Sons, Inc., New York, 2001.
- Rollmann, G., Knoll, P., Mekhaiel, M., Schmid, V., and Blöcher, H.-L.: Short Range Radar (SRR) -System for Automotive Ap- plication, IEEE MTT/AP German Newsletter, Vol. 8, No. 1, June 2004.
Cited by
Sorted by citations
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Yurtsever, E., Lambert, J., Carballo, A., & Takeda, K. (2020) · IEEE Access · doi:10.1109/access.2020.2983149 · Cited by 1,889
“An easy alternative is to use an alternate sensing modalities for perception, but lidar also has difficulties with some weather conditions like snow [144],”
BackgroundMethodInfluentialMillimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band
Hasch, J., Topak, E., Schnabel, R., Zwick, T., Weigel, R., & Waldschmidt, C. (2012) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2011.2178427 · Cited by 1,378
Automotive radars: A review of signal processing techniques
Patole, S., Torlak, M., Wang, D., & Ali, M. (2017) · IEEE Signal Processing Magazine · doi:10.1109/msp.2016.2628914 · Cited by 1,208
Autonomous vehicle perception: The technology of today and tomorrow
Van Brummelen, J., O’Brien, M., Gruyer, D., & Najjaran, H. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.02.012 · Cited by 869
An Overview of Lidar Imaging Systems for Autonomous Vehicles
Royo, S., & Ballesta-Garcia, M. (2019) · Applied Sciences · doi:10.3390/app9194093 · Cited by 505
Metadata
- Authors
- Rasshofer, R. H., & Gresser, K.
- Affiliations
- BMW (Germany) (DE)
- Venue
- Advances in Radio Science
- Publisher
- Copernicus GmbH
- Published
- 2005-05-12
- Volume
- 3
- Pages
- 205-209
- ISSN
- 1684-9965 (ISSN-L)
- 1684-9973
- OpenAlex
- W2129577383
- Cited by
- 252
- References
- 8
- Citations by year
- 2026: 8 · 2025: 21 · 2024: 22 · 2023: 17 · 2022: 26 · 2021: 31 · 2020: 33 · 2019: 20 · 2018: 18 · 2017: 21 · 2016: 5 · 2015: 7 · 2014: 4 · 2013: 3 · 2012: 5
- FWCI
- 7.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Advances in radio science (publishedVersion, cc-by-nc-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Physics and Astronomy › Instrumentation › Advanced Optical Sensing Technologies
- Keywords
- automotive radar, LiDAR, driver assistance systems, sensor fusion, sensor modeling, measurement error, sensor cost, virtual prototyping, vehicle safety
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