The left hard shoulder plays an important role in the event of an emergency on the inside of a multi-lane highway, but past studies have not been able to clarify the criteria for its installation or quantify the safety impact of its installation on the left side. In order to study the influence of the left hard shoulder on the safety of vehicles traveling on multi-lane highways, based on past studies that only studied the situation of four-lane highways, this paper firstly constructs a multi-lane highway simulation model under different numbers of lanes based on the VISSIM traffic simulation and uses Surrogate Safety Assessment Model (SSAM) to study the conflict characteristics of multi-lane highway vehicles under different numbers of lanes. Based on the above findings, this paper introduces the Safety Performance Function (SPF) to construct a multi-lane freeway accident prediction model, calibrates the model by adding the indexes affected by the left side hard shoulder to the basic prediction mode, and uses the historical accident data of the Badou-Shihu section of the Guangdong Northern Second Ring Highway as the basis to study the differences in accident rates of the investigated section before and after setting the left hard shoulder. The study showed that the average Time to Collision (TTC) increased by 57.2%, Maximum Deceleration (MaxD) increased by 19.2%, and Delta Speed (DeltaS) increased by 15.3% after setting hard shoulders on the left side of multi-lane freeways, and traffic conflicts on multi-lane freeways were significantly reduced, and safety was improved considerably. In addition, the rear-end conflict rate decreased by 0.17%, 0.75%, and 4.6% after setting hard shoulders on the left side of one-way three, four, and five lanes, respectively, indicating that hard shoulders on the left side are the most effective in improving the safety of one-way five-lane freeways. The accident prediction results show that within the reasonable setting range of the left hard shoulder width (0~4 m), the accident rate decreases by about 1.5% for every 0.5 m increase if only the influence of the left hard shoulder width is considered. Without considering other factors, increasing the width of the hard shoulder on the left side can reduce the number of accidents. This indicates a significant safety improvement for a one-way five-lane highway after setting the hard shoulder on the left side, and the conclusion is consistent with the simulation results. In this paper, based on past research, the research object is extended to one-way three-, four-, and five-lane highways. The findings of this paper can help the road authorities develop specifications for installing hard shoulders on the left side of multi-lane freeways and adopt strategies to improve the traffic safety level of multi-lane freeways. In addition, the models and methods used in this paper can also help build a framework for future intelligent networked vehicle avoidance systems and promote the development of intelligent networked technologies.

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This study aims to assess the traffic risk of the lane-changing (LC) process in the urban inter-tunnel weaving (UIW) segment. Time to collision (TTC) and extended time to collision (ETTC) are selected as indices for traffic risk assessment. An instantaneous traffic risk level classification method integrating Pareto’s law and the K-means clustering algorithm is proposed. Based on the classification results, the study also proposes an overall LC risk assessment method. Field-collected trajectory data are used to evaluate and characterize the traffic risk associated with the LC process. The instantaneous traffic risk analysis shows that the high-risk state accounts for a high percentage of the LC process in the UIW segment, and the front vehicle on the starting lane has the highest potential for conflict with the target vehicle. The overall risk index analysis shows that the risk distribution of the LC process is significantly clustered in the weaving segment and that the safety level of the UIW segment needs to be improved. This study quantifies the safety level and analyzes the characteristics of traffic risks of the LC process in the UIW segment to provide a decision basis for the development of assisted driving schemes and improvement of traffic safety management in the UIW segment.

Urban intertunnel weaving (UIW) section is a special type of weaving section, where various lane-changing behaviours occur. To gain insight into the lane-changing behaviour in the UIW section, in this paper we attempt to analyse the decision feature and model the behaviour from the lane-changing point selection perspective. Based on field-collected lane-changing trajectory data, the lane-changing behaviours are divided into four types. Random forest method is applied to analyse the influencing factors of choice of lane-changing point. Moreover, a support vector machine model is adopted to perform decision behaviour modelling. Results reveal that there are significant differences in the influencing factors for different lane-changing types and different positions in the UIW segment. The three most important factor types are object vehicle status, current-lane rear vehicle status and target-lane rear vehicle status. The precision of the choice of lane-changing point models is at least 82%. The proposed method could reveal the detailed features of the lane-changing point selection behaviour in the UIW section and also provide a feasible choice of lane-changing point model.