scholarly journals Cooperative Adaptive Cruise Control of Vehicle Platoons with Fading Signals and Heterogeneous Communication Delays

2020 ◽  
Vol 53 (2) ◽  
pp. 15319-15324
Author(s):  
Xiulan Song ◽  
Feng Xiao ◽  
Hong Peng ◽  
Defeng He
Author(s):  
Stacy A. Balk ◽  
Steven Jackson ◽  
Brian Philips

This study explored human factors issues associated with cooperative adaptive cruise control (CACC); specifically entering and exiting vehicle platoons. Participants were asked to complete one of three different types of merges in a driving simulator: (1) manual left entrance merge, (2) merge into the middle of a CACC platoon vehicles without speed assistance, and (3) merge into the middle of a CACC platoon vehicles with speed assistance. Drivers’ perceived workload was significantly less for both groups that drove with the CACC system engaged than for the group that manually maintained speed. Perhaps surprisingly, participant condition did not significantly affect physiological arousal as assessed by galvanic skin response (GSR). However, across all groups, GSR was significantly greater during the merges than during cruising/straight highway driving time periods. The two groups that had to manually adjust speed during the merge experienced collisions in 24 (18 percent) of the merges. A possible explanation, supported by participant feedback, is that drivers expect others to act in a courteous manner and to create larger gaps for entrance on to a freeway – something that may not be possible in real world CACC deployment.


Author(s):  
Yuwei Bie ◽  
Tony Z. Qiu

The cooperative adaptive cruise control (CACC) algorithm is a simple and effective way to form small-headway platoons so that road capacity and traffic throughput can be improved. The CACC algorithm has been broadly discussed in relation to the highway driving environment where frequent stopping and merging are uncommon. This paper proposes that CACC can also benefit urban arterials, using the appropriate algorithm to predict platoon behavior with optimized trajectories to divide and reform platoons before and after signalized intersections, thus maintaining small, safe headways. Connected vehicle (CV) technology is the key to adapting and improving the CACC algorithm, as it enables the signal phasing plan to be sent to a target CACC platoon and allows vehicles to acquire real-time information from other vehicles in the platoon. In this research, a CV-CACC algorithm is proposed consisting of two functions: platoon division and platoon reforming. The new algorithm is also equipped with acceleration as a new control variable instead of speed, so that the platoon is able to accommodate sharp speed changes around intersections, something the baseline CACC is unable to accommodate. In this study, computer simulations have been conducted to test the reliability of the CV-CACC algorithm and compare its performance against the baseline CACC algorithm.


2020 ◽  
Vol 53 (2) ◽  
pp. 15217-15222
Author(s):  
Erjen Lefeber ◽  
Jeroen Ploeg ◽  
Henk Nijmeijer

Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.


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