Abstract
Using a cellular automaton model, this paper studied the evolution mechanism of traffic incidents affecting the capacity of urban expressway under the mixed traffic environment of manual driving and automatic driving. It showed that the length of the automated-driving early-warning zone could affect the capacity of expressway. Specifically, the early-warning zone is divided into an accelerate lane-changing area, a decelerate lane-changing area, and a forced lane-changing area. The areas vary according to the distance between the vehicle and the location of incident. Based on the study, this paper establishes a codirectional two-lane cellular automaton model. The analysis showed that the capacity of the urban expressway varies under different combinations of early-warning area length and division ratio of early-warning zone. In the case of two-lane reduction caused by traffic incidents, the capacity of the expressway is optimized when the length of early-warning zone is between 450 and 600 m, and the ratio of accelerate zone, decelerate zone, and forced zone to the length of early-warning zone is, respectively, 75%, 10%, and 15%. In addition, this study showed that the capacity will rise with the increase in automated vehicles.
Highlights
Traffic incidents, referred to as “all events which affect the capacity of the road and hinder the smooth flow of traffic” [1], can cause severe congestion in an expressway
Expressways make up only a small part of the urban transportation network, they form the backbone of most urban transportation networks. ese roads carry more than a third of all vehicle travel [3]
connected and automated vehicles (CAVs) can obtain the information of multiple vehicles ahead through vehicle-to-X communication technology, which will play a vital role in improving traffic condition and efficiency [5,6,7,8,9]. us, the driving environment is expected to change with the introduction of automated vehicles
Summary
Traffic incidents, referred to as “all events which affect (or may affect) the capacity of the road and hinder the smooth flow of traffic” [1], can cause severe congestion in an expressway. In a mixed urban traffic flow, which is composed of both regular vehicles and automated vehicles (RAVs), the study of the relationship between the length of the automated-driving early-warning zone and the capacity of the expressway plays a vital role to enhance traffic condition. (i) e impact of length of the early incident warning area on the capacity of the expressway (ii) e impact of the automated-driving behavior on the early incident warning area and on its capacity (iii) e impact of the proportion of automated vehicles in RAV mixed traffic flow on the capacity e contributions of this paper are as follows:. (ii) Based on the CA modeling, the impact of the earlywarning zone length of CAVs on the capacity of an incident affecting expressway of RAV mixed traffic flow is analyzed as well as the two-lane reduction caused by the traffic incident. (iii) e relationship between the proportion of automated vehicles and the capacity of incident affected expressway is discussed
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