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The goal of this study is to explore the effect of two-sided lateral gap with uncertain velocity on the stability of traffic flow on a curved road.

In this paper, an extended car-following model considering the effect of two-sided lateral gap with uncertain velocity on a curved road is proposed. The effects of different lateral positions and radius of different sizes can be considered as control signals. The stability condition of the new model is obtained by the control theory. The numerical simulations are carried out to analyze how the control signal and lateral positions and radius of curved road affect traffic flow stability. The results show that driving between two lanes and inaccurate speed estimates both have a negative effect on traffic flow stability, and the stability also decreases with the increase in the radius of curved road.

(1) Simulation of influencing factors of vehicle lateral position indicates that if the driver drives between two lanes, it would have a negative impact on traffic flow. (2) When the speed is fixed, the traffic flow becomes more and more unstable with the increase in the radius of the curve. (3) The stability of traffic flow will be affected when the driver estimates the speed of the vehicle ahead. Therefore, whether it is manual driving or future intelligent vehicle driving, it is necessary to accurately judge the speed of the front vehicle.

There is little research on two-sided lateral gap with uncertain velocity for the stability of traffic flow on a curved road. The enhanced model constructed in this study can better reflect the real traffic, which can also give some theoretical reference for the development of connected and autonomous vehicles (CAVs).

The purpose of this paper is to propose a seamless autonomous navigation method based on the motion constraint of the mobile robot, which is able to meet the practical need of maintaining the navigation accuracy during global positioning system (GPS) outages.

The seamless method uses the motion constraint of the mobile robot to establish the filter model of the system, in which the virtual observation about the speed is used to overcome the shortage of the navigation accuracy during GPS outages. The corresponding motion constraint model of the mobile robot is established. The proposed seamless navigation scheme includes two parts: the micro inertial navigation system (MINS)/GPS-integrated filter model and the motion constraint filter model. When the satellite signals are good, the system works on the MINS/GPS-integrated mode. If some obstacles block the GPS signals, the motion constraint measurement equation will be effective so as to improve the navigation accuracy of the mobile robot.

Three different vehicle tests of the mobile robot show that the seamless navigation method can overcome the shortage of the navigation accuracy during GPS outages, so as to improve the navigation performance in practical applications.

A seamless navigation system based on the motion constraint of the mobile robot is proposed to overcome the shortage of the navigation accuracy during GPS outages, thus improving the adaptability of the robot navigation.