Braking Characteristics of Chinese Driver in Highway and Urban Road

Zheng

et al. 2015

ICA

The vehicular collision can lead to serious casualties and traffic congestions, especially multiple-vehicle collision. Most recent studies mainly focused on collision warning and avoidance strategies for two consecutive vehicles, but only a few on multiple-vehicle situations. This study proposes a coordinated brake control (CBC) strategy for multiple vehicles to minimize the risk of rear-end collision using model predictive control (MPC) framework. The objective is to minimize total impact energy by determining the desired braking force, where the impact energy is defined as the relative kinetic energy for a consecutive pair of vehicles. Under the MPC framework, this problem is further converted to a quadratic programming at each time step for numerical computations. To compare the performance, three other control strategies, i.e. direct brake control (DBC), driver reaction based brake control (DRBC) and linear quadratic regulator (LQR) control are also considered in this paper. The simulation results, in both a typical scenario and a huge number of scenarios under stochastic situations, show that CBC strategy has the best performance among these four strategies. The proposed CBC strategy has the potential to avoid the collision among a group of vehicles, and to mitigate the impact in cases where the collision is unavoidable.

Section: Simulation Parametersmentioning

confidence: 93%

Section: System Analysis and Modelingmentioning

confidence: 99%

Longitudinal collision mitigation via coordinated braking of multiple vehicles using model predictive control

Zheng

et al. 2015

ICA

“…The maximum deceleration (m/s 2 ) is set according to [10], which follows N(5.5, 0.6). The following distance is set according to [11], which is evenly distributed between 100km/h and 110km/h. The headway (in meters) follows N(2.0.…”

Section: A Initializationmentioning

confidence: 99%

Longitudinal Safety Analysis For Heterogeneous Platoon of Automated And Human Vehicles

Yang

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

Pei

et al. 2018

With the recent advancement in environmental sensing, vehicle control and vehicle-infrastructure cooperation technologies, more and more autonomous driving companies start to put their intelligent cars into road test. But in the near future, we will face a heterogeneous traffic with both intelligent connected vehicles and human vehicles. In this paper, we investigated the impacts of four collision avoidance algorithms under different intelligent connected vehicles market penetration rate. A customized simulation platform is built, in which a platoon can be initiated with many key parameters. For every short time interval, the dynamics of vehicles are updated and input in a kinematics model. If a collision occurs, the energy loss is calculated to represent the crash severity. Four collision avoidance algorithms are chosen and compared in terms of the crash rate and severity at different market penetration rate and different locations of the platoon. The results generate interesting debates on the issues of heterogeneous platoon safety.

“…Intuitively, this can be stated as follows: if any longitudinal maneuver of the subject vehicle would require its follower to take immediate action to ensure safety (to avoid collision), those vehicles are considered coupled. For natural highway driving, the time headway is usually 0.7∼3.8 s [16]. Therefore, most vehicles in the same lane are considered coupled in some group in highway traffic.…”

Section: System Analysis and Modelingmentioning

confidence: 99%

“…Employing time headway (THW) policy, we can get the car following distance distribution in the coupled group. As [16] points out, THW is usually from 0.7 s to 3.8 s in Chinese highway. In this paper, we make the THW distribution follow Gaussian distributions ∼ (1.5, 0.1 2 ).…”

Section: Simulation Developmentmentioning

confidence: 99%

Multiple-Vehicle Longitudinal Collision Mitigation by Coordinated Brake Control

Mathematical Problems in Engineering

et al. 2014

Rear-end collision often leads to serious casualties and traffic congestion. The consequences are even worse for multiple-vehicle collision. Many previous works focused on collision warning and avoidance strategies of two consecutive vehicles based on onboard sensor detection only. This paper proposes a centralized control strategy for multiple vehicles to minimize the impact of multiple-vehicle collision based on vehicle-to-vehicle communication technique. The system is defined as a coupled group of vehicles with wireless communication capability and short following distances. The safety relationship can be represented as lower bound limit on deceleration of the first vehicle and upper bound on maximum deceleration of the last vehicle. The objective is to determine the desired deceleration for each vehicle such that the total impact energy is minimized at each time step. The impact energy is defined as the relative kinetic energy between a consecutive pair of vehicles (approaching only). Model predictive control (MPC) framework is used to formulate the problem to be constrained quadratic programming. Simulations show its effectiveness on collision mitigation. The developed algorithm has the potential to be used for progressive market penetration of connected vehicles in practice.