Effects Of Adaptive Cruise Control Research Articles

The effects of adaptive cruise control (ACC) headway time on young-experienced drivers' overtaking tendency in a driving simulator

The preference to maintain a certain desired speed is perhaps the most prevalent explanation for why a driver of a manually driven car decides to overtake a lead vehicle. Still, the motivation for overtaking is also affected by other factors such as aggressiveness, competitiveness, or sensation-seeking caused by following another vehicle. Whether such motivational factors for overtaking play a role in partially automated driving is yet to be determined. This study had three goals: (i) to investigate whether and how a driver's tendency to overtake a lead vehicle changes when driving a vehicle equipped with an adaptive cruise control (ACC) system. (ii) To study how such tendencies change when the headway time configuration of the ACC system varies. (iii) To examine how the manipulation of the speed and speed variance of the lead vehicle affect drivers' tendencies to overtake a lead vehicle. We conducted two different experiments, where the second experiment followed the first experiment's results. In each experiment, participants drove three 10–12 min simulated drives under light traffic conditions in a driving simulator under manual and level one (L1) automation driving conditions. The automation condition included an ACC with two headway time configurations. In the first experiment, it was 1 sec and 3 secs, and in the second, it was 1 sec and 2 secs. Each drive included six passing opportunities representing three different speeds of the lead vehicle (−3 km/h, +3 km/h, +6 km/h relative to the participant), with or without speed variance. Results show that drivers tended to overtake a lead vehicle more often in manual mode than in automated driving modes. In the first experiment, ACC with a headway time of 1 sec led to more overtaking events than ACC with 3 secs headway time. In addition, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies. In the second experiment, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies only when interacting with each other and with driving configuration. When the speed of the lead vehicle was +3 km/h and included variability, more overtaking events occurred in manual mode than both automation modes. This work has shown that driving with ACC might help reduce overtaking frequencies and more considerable when the headway time is set to 3 secs.

Speeding behavior while using adaptive cruise control and lane centering in free flow traffic

Objective Adaptive cruise control (ACC) and lane centering are usually marketed as convenience features but may also serve a safety purpose. However, given that speeding is associated with increased crash risk and worse crash outcomes, the extent to which driver’s speed using ACC may reduce the maximum safety benefit they can obtain from this system. The current study was conducted to characterize speeding behavior among drivers using adaptive cruise control and a similar system with added lane centering. Methods We recruited 40 licensed adult drivers from the Boston, Massachusetts, metro area. These drivers were given either a 2017 Volvo S90 or a 2016 Range Rover Evoque to use for about 4 weeks. Results Drivers were significantly more likely to speed while they used ACC (95%) relative to periods of manual control (77%). A similar pattern arose for drivers using ACC with added lane centering (96% vs. 77%). Drivers who traveled over the posted limit with these systems engaged also sped slightly faster than drivers controlling their vehicle manually. Finally, we found that these differences were the most pronounced on limited-access roads with a lower speed limit (55 mph). Conclusions These findings point to a possible obstacle to obtaining the full safety potential from this advanced vehicle technology. Any consideration of the net safety effect of ACC and lane centering should account for the effects of more frequent and elevated speeding.

Effect of Adaptive Cruise Control on Mixed Traffic Flow: A Comparison of Constant Time Gap Policy with Variable Time Gap Policy

With the emerging application of low-level driving automation technology, heterogeneous traffic flow mixed with human-driven vehicles and low-level autonomous vehicles is dawning. In this context, it is imperative to investigate its effect on mixed traffic flow. As a key component for adaptive cruise control (ACC) which is a practical low-level application of driving automation, the time gap policy determines the dynamic of ACC-equipped vehicles and plays a crucial role in traffic flow stability and efficiency. There are two main time gap policies used for ACC at present, namely, constant time gap (CTG) policy and variable time gap (VTG) policy. In this study, we carried out a detailed comparison between these time gap policies to investigate their potential effect on mixed traffic flow, where the analytical- and simulation-based approaches are both considered. Analytical results show that VTG policy is superior to CTG policy in stabilizing the mixed traffic flow. In addition, numerical simulations are also conducted and simulation results further support the analytical results. As for throughput, there is no difference between CTG policy and VTG policy in analytical progress when the same time gap is set at the equilibrium. However, simulation results based on an on-ramp scenario show that the throughput of mixed traffic flow with VTG policy is slightly higher than that of CTG policy. Meanwhile, the scatter of mixed traffic flow with VTG policy in the flow-density diagram gradually clusters in the middle range of density (i.e., 20–40 veh/km) with the increase of the penetration rates of ACC vehicles, where the traffic flow operates more efficiently. These results indicate that VTG policy is better than CTG policy when designing controllers for ACC in the context of traffic flow operation and control.

The Effects of Vehicle Automation on Driver Engagement: The Case of Adaptive Cruise Control and Mind Wandering.

This field study examined the effects of adaptive cruise control (ACC) on mind wandering prevalence. ACC relieves the driver of the need to regulate vehicle speed and following distance, which may result in safety benefits. However, if ACC reduces the amount of attentional resources drivers must devote to driving, then drivers who use ACC may experience increased periods of mind wandering, which could reduce safety. Participants drove a prescribed route on a public road twice, once using ACC and once driving manually. Mind wandering rates were assessed throughout the drive using auditory probes, which occurred at random intervals and required the participant to indicate whether or not they were mind wandering. Measures of physiological arousal and driving performance were also recorded. No evidence of increased mind wandering was found when drivers used ACC. In fact, female drivers reported reduced rates of mind wandering when driving with ACC relative to manual driving. Driving with ACC also tended to be associated with increased physiological arousal and improved driving behavior. Use of ACC did not encourage increased mind wandering or negatively affect driving performance. In fact, the results indicate that ACC may have positive effects on driver safety among drivers who have limited experience with the technology. Driver characteristics, such as level of experience with in-vehicle technology and gender, should be considered when investigating driver engagement during ACC use. Field research on vehicle automation may provide valuable insights over and above studies conducted in driving simulators.

Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity

Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller’s theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller’s response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity.

The Effect of Secondary Cognitive Task Difficulty on Headway Maintenance and Perceived Workload While Using Lane Keeping Systems

Vehicle automation is developing at a rapid rate worldwide. However, even lower levels of automation, such as SAE Level-1, are expected to reduce drivers’ workload by controlling either speed or lane position. At the same time, however, drivers’ engagement in secondary tasks may make up for this difference in workload displaced by automation. Previous research has investigated the effects of adaptive cruise control on driving performance and workload, but little attention has been devoted to lane keeping systems (LKS). In addition, the influence of secondary cognitive tasks on Level-1 driving performance is also not well understood. The goal of this study was to examine the effects of secondary cognitive tasks on driving performance and perceived workload while using LKS. Nine participants drove a simulated vehicle in manual and LKS modes, while maintaining a specific headway and performing a secondary cognitive (n-back) task with varying levels of difficulty. Results showed that standard deviation of headway and NASA-TLX workload scores were significantly higher during the most difficulty secondary task. Also, LKS was not found to improve driving performance nor reduce perceived workload. This paper highlights potential performance costs and benefits associated with LKS technology and proposes directions for future research.

Effects of ACC and CACC vehicles on traffic flow based on an improved variable time headway spacing strategy

An improved variable time headway (VTH) spacing strategy for the adaptive cruise control (ACC) and cooperative ACC (CACC) system is proposed. On the basis of the novel strategy, the typical two-modes of ACC/CACC upper-level controller are redesigned. Numerical simulations for two traffic scenarios are performed to verify the efficiency of the improved strategy. The results demonstrate the suitability and advantages of the improved VTH strategy in comparison with the constant time headway strategy and the VTH strategy. Furthermore, the authors study the impact of ACC and CACC vehicles on traffic flow by multiple-types mixed scenarios: ACC/manual vehicles, CACC/manual vehicles and ACC/CACC/manual vehicles. The results illustrate that introducing the ACC/CACC vehicles into mixed traffic can improve traffic flow stability, enhance road capacity and alleviate the increasingly serious traffic congestion problem.

A Macroscopic Multi-Lane Traffic Flow Model for ACC/CACC Traffic Dynamics

An extended second-order macroscopic traffic flow model is presented that describes multi-lane traffic dynamics and also incorporates the effects of adaptive cruise control (ACC) or cooperative ACC (CACC). The extended model equations stem from a recently proposed multi-lane gas-kinetic traffic flow (GKT) model that can simulate lane changes due to vehicle interactions as well as spontaneous ones. The proposed extension that models the effects of ACC/CACC satisfies the time-gap principle of such systems on each lane and allows for consideration of mixed traffic comprising both manual and ACC/CACC vehicles. Numerical simulations are performed for a particular three-lane motorway stretch in the United Kingdom, where recurrent traffic congestion is observed during the morning peak hours, so as to compare the effects of ACC/CACC in the traffic flow conditions with those resulting from manual driving.

Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence

Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on drivers’ workload and situation awareness through a meta-analysis and narrative review of simulator and on-road studies. Based on a total of 32 studies, the unweighted mean self-reported workload was 43.5% for manual driving, 38.6% for ACC driving, and 22.7% for HAD (0%=minimum, 100=maximum on the NASA Task Load Index or Rating Scale Mental Effort). Based on 12 studies, the number of tasks completed on an in-vehicle display relative to manual driving (100%) was 112% for ACC and 261% for HAD. Drivers of a highly automated car, and to a lesser extent ACC drivers, are likely to pick up tasks that are unrelated to driving. Both ACC and HAD can result in improved situation awareness compared to manual driving if drivers are motivated or instructed to detect objects in the environment. However, if drivers are engaged in non-driving tasks, situation awareness deteriorates for ACC and HAD compared to manual driving. The results of this review are consistent with the hypothesis that, from a Human Factors perspective, HAD is markedly different from ACC driving, because the driver of a highly automated car has the possibility, for better or worse, to divert attention to secondary tasks, whereas an ACC driver still has to attend to the roadway.

Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow

This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.

Vehicle Trajectory Effects of Adaptive Cruise Control

Adaptive cruise control (ACC) can potentially improve quality-of-service and safety and reduce the environmental effect of the road traffic system. This article uses vehicle trajectories from traffic simulation to study effects of ACC on vehicle acceleration and deceleration rates. The analysis is based on traffic simulations with car-following models including ACC functionality and driver behavior in ACC-equipped as well as standard nonequipped vehicles. The simulation results show that ACC can improve the traffic situation in terms of reduced acceleration and deceleration rates even though macroscopic traffic properties may remain uninfluenced. This supports the hypothesized positive road safety and environmental effects of ACC. It is also established that the results are largely dependent on the assumptions made regarding driver behavior in ACC-equipped and standard vehicles. It is consequently crucial to include appropriate assumptions regarding driver behavior in traffic simulation–based analyses of ACC.

Driver Behavior Analysis During ACC Activation and Deactivation in a Real Traffic Environment

For the development of a traffic-simulation model to estimate the effect of adaptive cruise control (ACC) systems on traffic safety, throughput, and environment, data of a field operational test (FOT) were analyzed, in which vehicles were equipped with ACC and lane-departure warning (LDW) systems. The objective of this paper is to use this FOT to investigate the deactivation or (re)activation of the ACC on driver behavior in a real traffic environment. By taking these results into account in the traffic simulation environment, a more realistic evaluation of the impact of ACC on safety, throughput, and environment can be achieved. Some of the conclusions that were found are that after the participants deactivated the ACC by pressing the brake pedal, the gap with the lead vehicle was decreased. Resuming the ACC by activating the system or by releasing the throttle after overruling the system resulted in a larger gap between participant and lead vehicle than an overruled ACC or the ACC turned off. The participants overruled the ACC by pressing the throttle mainly to overtake the lead vehicle.

Traffic Flow Impacts of Adaptive Cruise Control Deactivation and (Re)Activation with Cooperative Driver Behavior

In 2006 in the Netherlands, a field operational test was carried out to study the effect of adaptive cruise control (ACC) and lane departure warning on driver behavior and traffic flow in real traffic. To estimate the effect for larger penetration rates, simulations were needed. For a reliable impact assessment, the on- and off-switching of the system should be taken into account. Furthermore, because ACC systems are less cooperative than normal drivers, the reference behavior should include this cooperative behavior. In this research, cooperative driver models for normal drivers were developed as well as an ACC model that included on- and off-switching for the microscopic simulation environment known as the intelligent transportation systems modeler. Parameter settings were validated with data from the pilot. The results clearly show that on- and off-switching behavior has a large influence on traffic flow. This effect depends on the degree of congestion. In congestion, the effect of the ACC is larger. Without the possibility of switching it on and off, the ACC has a positive impact on throughput. However, when the ACC can be switched on and off, it has a negative impact on throughput.

The effect of ACC vehicles to mixed traffic flow consisting of manual and ACC vehicles

This paper studies the effect of adaptive cruise control (ACC) system on traffic flow by using simulations. The multiple headway and velocity direrence (MHVD) model is used to depict the motion of ACC vehicles, and the simulation results are compared with the optimal velocity (OV) model which is used to depict the motion of manual vehicles. Compared the cases between the manual and the ACC vehicle flow, the fundamental diagram can be classified into four regions: I, II, III, IV. In low and high density the flux of the two models is the same; in region II the free flow region of the MHVD model is enlarged, and the flux of the MHVD model is larger than that of the OV model; in region III serious jams occur in the OV model while the ACC system suppresses the jams in the MHVD model and the traffic flow is in order, but the flux of the OV model is larger than that of the MHVD model. Similar phenomena also appeared in mixed traffic flow which consists of manual and ACC vehicles. The results indicate that ACC vehicles have significant effect on traffic flow. The improvement induced by ACC vehicles decreases with the increasing proportion of ACC vehicles.

Phase transition in a mixture of adaptive cruise control vehicles and manual vehicles

In this paper, we have investigated the effects of adaptive cruise control (ACC) vehicles in a mixture with manually-controlled (manual) vehicles. The manual vehicles are simulated by using the modified comfortable driving model, which can describe synchronized traffic flow. The phase transition probabilities from free flow to synchronized flow and from synchronized flow to jams are studied. The impact of ACC vehicles on the flow rates in free flow and synchronized flow and on the propagation velocity of the downstream front of jams are investigated. The dependence of microscopic properties of traffic flow, including the spatiotemporal patterns and the velocity distribution, is explored. Our results are expected to be useful for developing ACC systems.

Effects of Adaptive Cruise Control and Alert Modality on Driver Performance

Adaptive cruise control (ACC) is a rapidly emerging in-vehicle technology that can enhance or degrade driving safety. A critical factor governing the safety benefit of ACC concerns the driver's ability to assume control of the vehicle in situations that exceed ACC capabilities. The effectiveness of various warning modalities for reengaging distracted drivers during severe braking situations that exceed ACC capability was examined. Warnings that paired a visual icon with sound, seat vibration, or brake pulsation or that combined all three cues were compared. A total of 60 participants drove for 35 min in the National Advanced Driving Simulator. Drivers experienced two severe, four moderate, and eight mild braking situations. ACC could accommodate all but the two severe situations without driver intervention. It also provided a substantial benefit during mild events of lead vehicle braking, enabling drivers to maintain a longer, more consistent minimum time to collision. Unlike performance in previous studies, ACC did not decrease safety during severe braking situations. The combination of a visual icon with sound, seat vibration, or brake pulsation led to slower brake reaction time in severe braking situations, but the grouping of all four warning strategies led to a similar minimum time to collision and maximum braking. In contrast to several previous studies, these results suggest that drivers can effectively assume control when warned that ACC braking authority has been exceeded. Additional research is needed to identify the boundary conditions that specify when drivers can successfully intervene and retake control and whether a multimodal combination of cues can be crafted to speed rather than slow driver response.

Effects of Adaptive Cruise Control and Alert Modality on Driver Performance

Adaptive cruise control (ACC) is a rapidly emerging in-vehicle technology that can enhance or degrade driving safety. A critical factor governing the safety benefit of ACC concerns the driver's ability to assume control of the vehicle in situations that exceed ACC capabilities. The effectiveness of various warning modalities for reengaging distracted drivers during severe braking situations that exceed ACC capability was examined. Warnings that paired a visual icon with sound, seat vibration, or brake pulsation or that combined all three cues were compared. A total of 60 participants drove for 35 min in the National Advanced Driving Simulator. Drivers experienced two severe, four moderate, and eight mild braking situations. ACC could accommodate all but the two severe situations without driver intervention. It also provided a substantial benefit during mild events of lead vehicle braking, enabling drivers to maintain a longer, more consistent minimum time to collision. Unlike performance in previous studi...

Taking the load off: investigations of how adaptive cruise control affects mental workload

It has been posited that Adaptive Cruise Control (ACC) represents a new generation of vehicle automation, in that it has the potential to relieve drivers of mental as well as physical workload. The results of previous research however, have raised some confusing issues about the specific effects of Adaptive Cruise Control (ACC) on driver mental workload (MWL)—some studies report reduced MWL compared to manual driving, while others find no effect. Two hypotheses are proposed in an attempt to explain these discrepancies: (a) that any potential MWL reductions due to ACC could be masked by the overriding influence of steering demand; or (b) that the tasks designed in some experiments do not exploit the adaptive nature of the ACC system, therefore precluding any potential benefits. Two related experiments were designed to test these hypotheses. It was found that the main reason for the discrepant findings was the nature of the driving task chosen—constant-speed tasks do not realise the mental workload benefits of ACC. Future researchers using ACC devices are advised to use variable-speed tasks to ensure that all aspects of device functionality are covered.

Effect of adaptive cruise control (ACC) on traffic throughput:: numerical example on actual freeway corridor

This study evaluated the effects of adaptive cruise control (ACC) on traffic flow using a microscopic traffic simulation on an actual freeway corridor, where traffic congestion was observed due to a traffic accident. Four types of ACCs were evaluated to determine their effect on travel time reduction given the low percentage of ACC equipped vehicles. A small numerical example showed that travel times could be significantly reduced only when the ACC is activated for almost all speed ranges and at least 20% of the vehicles are equipped with ACCs.