Latest revision as of 12:11, 5 April 2017

Abstract

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles (AV) are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about the driving environment. Studies have proved that automated driving have the potential to decrease traffic congestion by reducing the time headway (THW), enhancing the traffic capacity and improving the safety margins in car following. Despite different encouraging factors, automated driving raise some concerns such as possible loss of situation awareness, overreliance on automation and system failure. This paper aims to investigate the effects of AV on driver’s behavior and traffic performance. A literature review was conducted to examine the AV effects on driver’s behavior. Findings from the literature survey reveal that conventional vehicles (CV), i.e. human driven, which are driving close to a platoon of AV with short THW, tend to reduce their THW and spend more time under their critical THW. Additionally, driving highly AV reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of AV on traffic performance, a simulation case study consisting of a 100% AV scenario and a 100% CV scenario was performed using microscopic traffic simulation. Outputs of this simulation study reveal that the positive effects of AV on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably improved by 8.09% during p.m. peak hours in the AV scenario, while the average travel speed enhanced relatively by 8.48%. As a consequent, the average travel time improved by 9.00% in the AV scenario. The outcome of this study jointly with the previous driving simulator studies illustrates a successful practice of microscopic traffic simulation to investigate the effects of AV. However, further development of the microscopic traffic simulation models are required and further investigations of mixed traffic situation with AV and CV need to be conducted.

Keywords

Automated driving ; Automated vehicles ; Microscopic traffic simulation ; Driver behavior ; Traffic performance ; capacity

References

1. Amditis, 2015 Amditis, A. (2015). From advanced active safety systems to automated systems. VRA webinar. [Online]. Available: http://vra-net.eu/wp-content/uploads/2015/02/2015-02-06_VRA_From-Advanced-Active-Safety-Systems-to-Automated-Systems.pdf [Apr. 16, 2015].
2. Chiang and Chan, 2013 C. Chiang, Y. Chan; Autonomous safety group behavior of vehicle simulation; 8th International Conference on Computer Science & Education (2013), pp. 310–315
3. Carsten et al., 2012 O. Carsten, F.C.H. Lai, Y. Barnard, A.H. Jamson, N. Merat; Control Task Substitution in Semi-automated Driving: Does It Matter What Aspects Are Automated?; Human Factors: The Journal of the Human Factors and Ergonomics Society, 54 (5) (2012), pp. 747–761
4. Fagnant and Kockelman, 2013 Fagnant, D. and Kockelman, K. (2013). Preparing a Nation for Autonomous Vehicles. 1st ed. Texas: Eno Center for Transportation , pp. 7-9.
5. Gouy, 2013 Gouy, M. (2013). Behavioural adaption of drivers of unequipped vehicles to short time headways observed in a vehicle platoon. PhD thesis, The Open University .
6. Gouy et al., 2014 Gouy, M., Wiedemann, K., Stevens, A., Brunett, G. and Reed, N. (2014). Driving next to automated vehicle platoons: How do short time headways influence non-platoon drivers’ longitudinal control?. Transportation Research Part F: Traffic Psychology and Behaviour , vol. 27, pp. 264-273.
7. Jamson et al., 2013 A.H. Jamson, N. Merat, O.M.J. Carsten, F.C.H. Lai; Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions; Transportation Research Part C: Emerging Technologies, 30 (2013), pp. 116–125
8. Johansson, 2014 Johansson, E. (2014). Human Factors in Vehicle Automation - Activities in the European Project Adaptive. VRA webinar. [Online]. Available: http://vra-net.eu/wp-content/uploads/2014/10/AdaptIVe_SP3_ERTICOWebinar_oct14_v4.pdf [May. 10, 2015].
9. Kesting et al., 2008 A. Kesting, M. Treiber, M. Schönhof, D. Helbing; Adaptive cruise control design for active congestion avoidance; Transportation Research Part C: Emerging Technologies, 16 (6) (2008), pp. 668–683
10. Laquai et al., 2011 F. Laquai, M. Duschl, G. Rigoll; Impact and Modeling of Driver Behavior Due to Cooperative Assistance Systems. Springer-Verlag, 6777 (2011), pp. 473–482
11. Leyn and Vortisch, 2014 U. Leyn, P. Vortisch; Calibrating Vissim for the German Highway Capacity Manual; Karlsruhe Institute of Technology: Institute for Transport Studies (2014), pp. 1–11
12. Merat et al., 2014 Merat, N., Jamson, A., Lai, F., Daly, M. and Carsten, O. (2014). Transition to manual: Driver behaviour when resuming control from a highly automated vehicle. Transportation Research Part F: Traffic Psychology and Behaviour , vol. 27, pp. 274-282.
13. Ntousakis et al., 2015 I. Ntousakis, I. Nikolos, M. Papageorgiou; On Microscopic Modelling of Adaptive Cruise Control Systems; Transportation Research Procedia, 6 (2015), pp. 111–127
14. Rotfuchs, 2015 Rotfuchs, K. (2015). Wir dürfen nicht wieder eine Chance verpassen, heute die Stadt von morgen zu sichern. Straßen-Verkehrstechnik 2 , (in German), pp. 118-119.
15. Sabey and Taylor, 1980 B.E. Sabey, H. Taylor; The known risks we run: the highway; Plenum Press, New York (1980)
16. Treat et al., 1979 Treat, J., Tumbas, N., McDonald, S., Shinar, D., Hume, R., Mayer, R. et al. (1979). Tri-level study of the causes of traffic accidents. Indiana, Bloomington: Institute for Research in Public Safety , Indiana University.
17. Automotive, 2015 TU Automotive. (2015). Levelling up to driverless cars [Online]. Available: http://img03.en25.com/Web/FCBusinessIntelligenceLtd/%7B10b01428-b6d8-477a-9bf1-49c4edb33e05%7D_2693_10MAR15_Content.pdf [Jun. 12, 2015].
18. USA Today, 2013 USA Today journal. (2013). GM to offer nearly self-driving car by 2020 [Online]. Available: http://www.usatoday.com/story/money/cars/2013/08/30/gm-general-motors-self-driving autonomous-car/2725091/[Jun. 8, 2015].
19. Nachrichten, 2015 VDI Nachrichten. (2015). Hände weg vom Lenkrad. (in German), Nr. 8, p. 12.
20. Convention, 1968 Convention on Road Traffic. (1968). Part I , pp. 10-16.
21. Wei et al., 2013 Wei, J., Dolan, J. and Litkouhi, B. (2013). Autonomous vehicle social behavior for highway entrance ramp management. 2013 IEEE Intelligent Vehicles Symposium (IV) , vol. 1, pp. 201-207.