Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways
Introduction
As traffic has continuously increased on freeways, more congestion has occurred resulting in increased traffic oscillations and higher crash risks (Abdel-Aty and Abdelwahab, 2003, Golob et al., 2004, Kim et al., 2007). Previously, advanced traffic control techniques have been proposed to improve freeway safety. Some techniques have used infrastructure-based control devices at fixed locations to improve traffic operations and safety, including variable speed limits (VSL) (Papageorgiou et al., 1997, Abdel-Aty et al., 2006, Lee et al., 2006, Li et al., 2014b), ramp metering (Papageorgiou et al., 1997, Papageorgiou and Kotsialos, 2000), and lane management (Shewmake and Jarvis, 2014). Recently, some novel in-vehicle driving assistance systems have been developed, such as advanced vehicle-to-vehicle and vehicle-to-infrastructure communication (Van Nunen et al., 2012, Harigovindan et al., 2014), collision warning (Bueno et al., 2014, Aust et al., 2013), and automated driving (De Diego et al., 2013, Zeeb et al., 2015). Automated driving has drawn the attention of both transportation professionals and automobile manufacturers. It consists of several levels depending on how strong the system intervenes in the longitudinal and lateral control of vehicles (Nowakowski et al., 2010, Milanés and Shladover, 2014, Milanés et al., 2014, Shladover et al., 2015).
Although complete automation is not currently applicable, some automated driving techniques, such as vehicle adaptive cruise control (ACC), have already been on the market and are likely to expand their applications in the near future (Marsden et al., 2001, Bose and Ioannou, 2003, Kikuchi et al., 2003, Kesting et al., 2008, Kesting et al., 2010, Tapani, 2012). ACC is an intelligent form of cruise control that controls a vehicle’s acceleration and deceleration to keep pace with the car in front. Current commercial ACC is designed to be a comfortable and convenient driving system. The car will typically slow under ACC, braking at up to half its maximum braking potential to ensure comfort. However, such systems may not prevent the occurrence of crashes in emergency conditions with slow traffic ahead of the ACC-enabled car. Some techniques, such as automatic emergence braking, could be paired with ACC systems, but those techniques only consider the ego-vehicle, and their impact on other vehicles was not fully considered. As the performance of ACC in stop-and-go traffic has not been fully evaluated, users were recommended to deactivate ACC control and use manual driving in congested traffic (Shladover et al., 2015). Those limitations largely affect the future promotion and commercialization of ACC technology.
Previous studies have evaluated the operation of vehicles equipped with ACC in car-following scenarios. Some debates existed regarding the impacts of ACC on traffic flow. In earlier studies, researchers claimed that ACC techniques can reduce the variation of vehicle acceleration (Marsden et al., 2001, Tapani, 2012, Li et al., 2016), increase flow (Bose and Ioannou, 2003, Kesting et al., 2010), and stabilize traffic (Kesting et al., 2008, Kesting et al., 2010). However, some recent field tests of commercial ACC systems currently on the market showed that the strings of ACC vehicles might not be stable; speed oscillation was amplified from the initial vehicle to the following vehicles (Milanés and Shladover, 2014, Milanés et al., 2014). In field experiments, the parameters of the commercial ACC systems were allowed to adjust only within a small range. A larger adjustable range of parameters could be achieved in the future with improvements in the radar detection quality, processing and communication speed, and inherent feedback controllers, which may affect the operation of vehicle strings. However, the impacts of the parameters in ACC systems on traffic operation have not been fully tested.
A literature review suggested that no particular attention has been paid to the safety impact of ACC system parameters in traffic oscillations on congested freeways where crash risks are the highest (Abdel-Aty and Abdelwahab, 2003, Kim et al., 2007). It was assumed by the authors that the safety impact was largely affected by the parameter setting of the ACC system. In addition, as the application of commercial ACC systems is a gradual process, a long period will exist when traffic flow contains mixed ACC and non-ACC vehicles. Thus, studies that consider different market penetration rates of ACC vehicles are necessary. Targeting the above issues, the objective of this study is to evaluate the impacts of the ACC parameters on rear-end collision risks in oscillatory traffic under different market penetration rates. The findings of the study are expected to be useful to policy makers or transport agencies regarding the development, improvement and application of ACC technologies in the future.
The remainder of the paper is organized as follows. In the next section, the occurrence conditions of a rear-end collision are analyzed. In Section 3, a simulation model for simulating vehicle movements equipped with ACC is developed. In Section 4, a surrogate safety measure is proposed to evaluate the collision risks. Section 5 introduces the experimental design. The simulation results are discussed in Section 6. The paper concludes with brief concluding remarks and future research tasks in Section 7.
Section snippets
Rear-end collision risk in stop-and-go traffic
Previous studies have evaluated crashes in different traffic states and have found that collision risks are the highest in stop-and-go traffic (Abdel-Aty and Abdelwahab, 2003, Kim et al., 2007, Oh and Kim, 2010). In stop-and-go traffic, rear-end collisions are the major collision type due to the frequent vehicle deceleration and acceleration caused by the propagation of kinematic waves (Abdel-Aty and Abdelwahab, 2003, Golob et al., 2004, Kim et al., 2007). Thus, in this section, a rear-end
Development of a simulation model
Although some premium vehicles have been equipped with full speed range ACC, currently, commercial ACC systems are usually not recommended for stop-and-go traffic conditions. It is quite difficult to obtain field experimental data for evaluating the safety impacts of ACC in stop-and-go traffic under different market penetration rates. In this study, the simulation technique was adopted. Data from previous small-scale field tests were used to determine the parameters. Previously, both
Surrogate safety measure
To evaluate the safety effects of ACC systems, a relationship mush be established between the risk of collision and traffic conditions. In previous studies, numerous crash prediction models have been developed to predict the risks of traffic collisions. However, most of those models were based on traffic flow data aggregated per 5–10 (Xu et al., 2013, Li et al., 2014a, Li et al., 2014c). Those models are not the first choice for evaluating collision risks from individual vehicle movements.
The
Experiment design
In this study, the Matlab 2014b software was used to build up the simulation platform. The car-following model was coded and embedded into the platform with key parameters allowed to change. After designating the origin and destination in the simulation platform, the location, speed, and acceleration rate of each vehicle at each time step was recorded. Other variables such as time headway, speed difference between two vehicles, collision risk, travel time, etc. were then estimated for further
Results
With the surrogate safety measure and simulation model developed in the previous sections, this section evaluated the safety effects of the ACC system. We first estimated the impacts of the ACC parameter settings on rear-end collision risks. Then, we evaluated the safety performances under different ACC vehicle penetration rates. The effects of the ACC system with the aid of VSL control were finally estimated.
Conclusions and recommendations
This study evaluated the safety impacts of ACC parameters on reducing collision risks on congested freeways. The study analyzed the occurrence conditions of rear-end collisions in stop-and-go traffic. The IDM model was modified to simulate the behaviors of manually driven vehicles and vehicles equipped with ACC systems. Surrogate safety measures based on the time-to-collision index, which were TIT and TET, were used to quantify the safety effects achieved by the application of the ACC
Acknowledgements
This research was sponsored by the Key Project of National Natural Science Foundation of China (51638004), National Natural Science Foundation of China (51508094, 51338003, 51478113), and the Natural Science Foundation of Jiangsu Province (BK20150612). The authors would like to thank the anonymous reviewers for their time to review our article and the constructive comments.
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