China
Africa
Explore chapters and articles related to this topic
Design of Platoon Controller with V2V Communication for Highways
Published in Nishu Gupta, Joel J. P. C. Rodrigues, Justin Dauwels, Augmented Intelligence Toward Smart Vehicular Applications, 2020
Anuj Abraham, Nagacharan Teja Tangirala, Pranjal Vyas, Apratim Choudhury, Justin Dauwels
The challenge in platooning is to develop a capable controller that can keep the vehicles at a close-range, track the abrupt speed changes of the first vehicle, and avoid collisions among the platoon members [3]. Most of the earlier work on the platoon controller design entails the use and development of an adaptive cruise control (ACC) strategy [4]. In the ACC system, a controlled vehicle obtains the speed and position of the immediate neighboring vehicles to calculate its control input. Radar communication is used for communication between the platoon members. Due to the inherent time-delays in radar communication, it is unreliable in emergencies [5]. To overcome the shortcomings of the ACC strategy, researchers proposed an advanced version of ACC, called cooperative adaptive cruise control (CACC). CACC strategy uses wireless communication, such as 5.9 GHz dedicated short-range communications (DSRC) or 5G to exchange data among the platoon members. The use of wireless communication allows low latency and high-frequency data exchange of a wide range of data such as GPS position, inertial measurement unit data, and the control actions like throttle or brake. Access to more data helps in implementing advanced control strategies. In this chapter, the development of a CACC strategy using a proportional integral derivative (PID) and model predictive control (MPC) is described.
A vehicle following controller for highly-actuated vehicles
Published in Johannes Edelmann, Manfred Plöchl, Peter E. Pfeffer, Advanced Vehicle Control AVEC’16, 2017
R. de Castro, A. Schaub, C. Satzger, J. Brembeck
Cooperative driving, where two or more vehicles perform cooperative sensing and maneuvering, is currently envisaged as a promising building block for addressing the growing challenges in transportation systems. For instance, the increase in traffic efficiency, safety and driving comfort offered by cooperative longitudinal control, such as cooperative adaptive cruise control (CACC), are well-known benefits of this technology (Naus et al. 2010). Within this context, the present article focuses on the development of a vehicle-following controller (VFC) for highly actuated electric vehicles (EVs). Our aim is to determine appropriate control actions such that the motion of a partner/target vehicle is followed.
Localization for Vehicular Ad Hoc Network and Autonomous Vehicles, Are We Done Yet?
Published in Hussein T. Mouftah, Melike Erol-Kantarci, Sameh Sorour, Connected and Autonomous Vehicles in Smart Cities, 2020
Abdellah Chehri, Hussein T. Mouftah
The cooperative automation of CAVs can introduce benefits to current transportation systems concerning safety, mobility, and environmental sustainability [83]. The Cooperative Adaptive Cruise Control (CACC) is a developed version of the Adaptive Cruise Control (ACC) that uses motion sensors to detect obstacles, like other vehicles. Once a car is detected, the ACC adjusts the speed to keep the same inter-car distance. The driver sets this distance.
Intersection capacity adjustments considering different market penetration rates of connected and automated vehicles
Published in Transportation Planning and Technology, 2023
To better model the car-following behaviors of CAVs, the framework of advanced intelligent driving assistance systems (ADAS) for cruising control is proposed (Mintsis 2018). The primary function of the cruising control system is to maintain the desired speed set by a driver. After that, adaptive cruise control (ACC), which is a benchmark ADAS, has been widely implemented for commercial AVs (Shladover, Su, and Lu 2012). Based on the speed and gap distance to the preceding vehicle collected by the Lidar sensor, the ACC system changes the acceleration/deceleration rate to maintain a safe following gap. The cooperative adaptive cruise control (CACC) is a functional extension of the ACC system, and it enables cooperative platoon driving by sharing the current and target acceleration, deceleration, and vehicle positions by V2V communications (Shladover 2018). Amoozadeh et al. (2015) tested the impact of message falsification disturbances and radio jamming attacks on the acceleration and following distance of CACC-controlled vehicles. Results indicated that security attacks could reduce traffic safety and result in traffic flow instability and rear-end collisions. In this case, the CACC system could work properly only when the preceding vehicle is also a CAV. The additional information collected from surroundings enables CAVs with a CACC system to follow the front CAV with a shorter response time, shorter distance gap, and higher accuracy compared to ACC-controlled vehicles (Shladover, Su, and Lu 2012).
Human-centred design of next generation transportation infrastructure with connected and automated vehicles: a system-of-systems perspective
Published in Theoretical Issues in Ergonomics Science, 2023
Yiheng Feng, Yunfeng Chen, Jiansong Zhang, Chi Tian, Ran Ren, Tianfang Han, Robert W. Proctor
It is reasonable to expect that roadway design will be changed when CAVs become prevailing. If all vehicles on the road can be controlled precisely based on planned trajectories and cooperate with each other, tremendous infrastructure improvements and adaptations are possible and necessary. For example, due to closer spacing and shorter headway of platooning through cooperative adaptive cruise control (CACC), dedicated CAV lanes can greatly improve the road capacity on the highway. Ye and Yamamoto (2019) studied the impact of CAV dedicated lanes on the traffic flow throughput. Furthermore, Ghiasi et al. (2017) built an analytical lane management model using Markov chain to determine the optimal CAV lane number under different demand levels, market penetration rates, platooning intensities, and technology scenarios (i.e. time headway).
A Bayesian regression analysis of truck drivers’ use of cooperative adaptive cruise control (CACC) for platooning on California highways
Published in Journal of Intelligent Transportation Systems, 2023
Shiyan Yang, Steven E. Shladover, Xiao-Yun Lu, Hani Ramezani, Aravind Kailas, Osman D. Altan
Cooperative adaptive cruise control (CACC) is an extension of adaptive cruise control (ACC) by incorporating dedicated short-range communications (DSRC) to enable wireless vehicle-to-vehicle (V2V) communications. The CACC at SAE Level 1 can automate the longitudinal control of the following vehicle(s) based on other vehicle’s information (e.g., velocity, acceleration) transmitted through V2V wireless communications and remote sensors (e.g., radar and lidar). It can maintain a desired time gap between the vehicles in a string to avoid human delays in speed control, therefore enabling safe but smaller time gaps between these vehicles (Shladover et al., 2015). Due to the smaller following time gaps, increase in CACC market penetration rate is expected to generate macro-level benefits on transportation corridors, such as reducing fuel consumption and emissions (Browand et al., 2004; McAuliffe et al., 2018), improving traffic flow stability (Liu et al., 2018; van Arem et al., 2006), and relieving traffic congestion (Arnaout & Arnaout, 2014; Lunge & Borkar, 2015; Ramezani et al., 2018).