![](bgb.png)
Aimsun (2021). Aimsun Next 20 User’s Manual, Aimsun
Next 20.0.3 edition.
Bazzan, A. L. (2005). A distributed approach for coordina-
tion of traffic signal agents. Autonomous Agents and
Multi-Agent Systems, 10(2):131–164.
Dudek, C., Messer, C., and Nuckles, N. (1974). Incident
detection on urban freeways. Transp. Res. Rec., 495.
Dudek, C., Weaver, G., Ritch, G., and Messer, C. (1975).
Detecting freeway incidents under low-volume condi-
tions. Transp. Res. Rec., 533:34–47.
Dusparic, I. and Cahill, V. (2009). Using distributed w-
learning for multi-policy optimization in decentralized
autonomic systems. In Proc. of 6th Int. Conf. on Au-
tonomic Computing, pages 63–64. ACM.
Ester, M., Kriegel, H.-P., Sander, J., and Xu, X. (1996).
A density-based algorithm for discovering clusters in
large spatial databases with noise. In kdd, pages 226–
231. AAAI Press.
Feng, Y., Hourdos, J., and Davis, G. (2014). Probe vehicle
based real-time traffic monitoring on urban roadways.
Transp. Res. Part C: Emerging Tech., 40:160–178.
Gall, A. and Hall, F. (1989). Distinguishing between inci-
dent congestion and recurrent congestion: a proposed
logic. Transportation Research Record.
Gershenson, C. (2007). Design and Control of Self-
organizing Systems. PhD thesis, Vrije Universiteit
Brussel.
Gokulan, B. and Srinivasan, D. (2010). Distributed geomet-
ric fuzzy multiagent urban traffic signal control. IEEE
Trans. on Int. Transportation Sys., 11(3):714–727.
Helbing, D., L
¨
ammer, S., and Lebacque, J. (2005). Self-
organized control of irregular or perturbed network
traffic. Optimal control and dynamic games, pages
239–274.
Jenelius, E. and Koutsopoulos, H. (2013). Travel time esti-
mation for urban road networks using low frequency
probe vehicle data. Transp. Res. Part B: Methodolog-
ical, 53:64–81.
Kamijo, S., Harada, M., and Sakauchi, M. (2004). An in-
cident detection system based on semantic hierarchy.
In Proc. of 7th Int. Conf. on Int. Trans. Sys. (ITS’04),
pages 853–858. IEEE.
Lin, W. and Daganzo, C. (1997). A simple detection scheme
for delay-inducing freeway incidents. Transp. Res.
Part A: Policy and Practice, 31(2):141–155.
Mauro, V. and Taranto, C. D. (1990). Utopia. Control,
computers, communications in transportation.
M
¨
uller-Schloer, C. and Tomforde, S. (2017). Organic
Computing-Technical Systems for Survival in the Real
World. Springer.
Oliveira, L. D. and Camponogara, E. (2010). Multi-agent
model predictive control of signaling split in urban
traffic networks. Transp. Res. Part C: Emerging Tech.,
18(1):120–139.
Payne, H. and Tignor, S. (1978). Freeway incident-
detection algorithms based on decision trees with
states. Transportation Research Record.
Payne, H. J. (1975). Freeway incident detection based upon
pattern classification. In Proc. of IEEE Conf. on Deci-
sion and Control, volume 14, pages 688–692. IEEE.
Prothmann, H., Branke, J., Schmeck, H., Tomforde, S.,
Rochner, F., H
¨
ahner, J., and M
¨
uller-Schloer, C.
(2009). Organic traffic light control for urban road
networks. Int. J. Auton. Adapt. Commun. Syst., 2(3).
Prothmann, H., Tomforde, S., Lyda, J., Branke, J., H
¨
ahner,
J., M
¨
uller-Schloer, C., and Schmeck, H. (2012).
Self-organised routing for road networks. In Self-
Organizing Systems - 6th IFIP TC 6 International
Workshop, IWSOS 2012, Delft, The Netherlands,
March 15-16, 2012. Proceedings, pages 48–59.
Robertson, D. and Bretherton, D. (1991). Optimizing net-
works of traffic signals in real time – the SCOOT
method. IEEE Trans. on Veh. Tech., 40(1):11–15.
Shehata, M., Cai, J., Badawy, W., Johannesson, R., and
Radmanesh, A. (2008). Video-based automatic inci-
dent detection for smart roads: The outdoor environ-
mental challenges regarding false alarms. IEEE Trans.
on Int. Transp. Sys., 9(2):349–360.
Sims, A. and Dobinson, K. (1980). The Sydney coordinated
adaptive traffic (SCAT) system – Philosophy and ben-
efits. IEEE Trans. on Veh. Tech., 29(2):130–137.
Sommer, M., Tomforde, S., and H
¨
ahner, J. (2013). Using
a neural network for forecasting in an organic traf-
fic control management system. In 2013 Workshop
on Embedded Self-Organizing Systems, ESOS’13, San
Jose, CA, USA, June 25, 2013.
Sommer, M., Tomforde, S., and H
¨
ahner, J. (2016a). An Or-
ganic Computing Approach to Resilient Traffic Man-
agement. In Autonomic Road Transport Support Sys-
tems, pages 113–130. Birkh
¨
auser.
Sommer, M., Tomforde, S., and H
¨
ahner, J. (2016b).
Forecast-augmented route guidance in urban traffic
networks based on infrastructure observations. In
Proc. of VEHITS’16, pages 177–186.
Stephanedes, Y. and Chassiakos, A. (1993). Freeway inci-
dent detection through filtering. Transp. Res. Part C:
Emerging Technologies, 1(3):219–233.
Studer, L., Ketabdari, M., and Marchionni, G. (2015). Anal-
ysis of adaptive traffic control systems design of a de-
cision support system for better choices. J Civil Envi-
ron Eng, 5(195):2.
Takaba, S. and Matsuno, H. (1985). Traffic incident detec-
tion using correlation analysis. In SCS 1985 Summer
Comp. Sim. Conf., pages 529–534.
Thomsen, I. and Tomforde, S. (2022). Intersection-centric
urban traffic flow clustering for incident detection in
organic traffic control. In Proc. of VEHITS’22.
Thomsen, I., Zapfe, Y., and Tomforde, S. (2021). Urban
traffic incident detection for organic traffic control: A
density-based clustering approach. In Proceedings of
the 7th International Conference on Vehicle Technol-
ogy and Intelligent Transport Systems, VEHITS 2021,
Online Streaming, April 28-30, 2021, pages 152–160.
Tomforde, S., Prothmann, H., Branke, J., H
¨
ahner, J., Mnif,
M., M
¨
uller-Schloer, C., Richter, U., and Schmeck, H.
(2011). Observation and control of organic systems.
In Organic Computing—A Paradigm Shift for Com-
plex Systems, pages 325–338. Springer.
Tomforde, S., Prothmann, H., Branke, J., H
¨
ahner, J.,
M
¨
uller-Schloer, C., and Schmeck, H. (2010). Possi-
Incident-Aware Distributed Signal Systems in Self-Organised Traffic Control Systems
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