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Research on HOV Lane Priority Dynamic Control Under Connected Vehicle Environment Hindawi Journal of Advanced Transportation Volume 2020, Article ID 8892859, 12 pages https://doi.org/10.1155/2020/8892859 Research Article Research on HOV Lane Priority Dynamic Control under Connected Vehicle Environment Guiliang Zhou ,1,2 Lina Mao ,1,3 Pengsen Hu,4 Feng Sun,5 and Xu Bao1 1Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China 2School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China 3School of Transportation, Southeast University, Nanjing 210096, China 4Department of Civil and Environmental Engineering, .e Pensylvania State University, University Park, PA 16802, USA 5School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, Shandong 255049, China Correspondence should be addressed to Guiliang Zhou; [email protected] and Lina Mao; [email protected] Received 5 May 2020; Revised 16 July 2020; Accepted 23 July 2020; Published 8 August 2020 Academic Editor: Zhuping Zhou Copyright © 2020 Guiliang Zhou et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -e optimization of high-occupancy vehicle (HOV) lane management can better improve the efficiency of road resources. -is paper first summarized the current research on HOV lane implementation and analyzed and identifies the threshold of setting road HOV lane dynamic control under the connected vehicle environment. -en, the HOV lane priority dynamic control process was determined, and the operating efficiency and energy consumption evaluation method was proposed. Moreover, a case study in Wuxi City, China, was carried out. -e results showed that, after implementing the HOV lane priority dynamic control, the total mileage of road network vehicles was saved by 4.93%, the average travel time per capita was reduced by 4.27%, and the total energy-saving rate of road network travel was 21.96%. 1. Introduction applicable conditions for toll lanes and HOV lanes. Chen [11] discussed the experience and lessons of HOV priority -e setting of the HOV lane can provide more space re- planning and application worldwide in detail and proposed sources for high-occupancy vehicles to improve traffic op- the necessity and feasibility of introducing HOV priority eration efficiency. However, it met with great controversy at into urban transportation planning in China. -e conclusion the beginning [1–3] because when the HOV lane was not shows that the development level and urban residential fully utilized at the time, road space resources were wasted characteristics of intelligent transportation technology in [4]; Pravin and Han [5] made a comprehensive comparison China have provided the necessary conditions for the between the HOV lane and the ordinary lane set in Cal- implementation of HOV lanes. ifornia in the United States. After investigating the HOV Wang [12] put forward conceptual plans for carpooling lane capacity, traffic operating condition, and carpooling priority based on the design experience of HOV schemes percentage, it was believed that, under the appropriate road and pointed out that road, traffic, and urban land use and traffic conditions, HOV lanes can serve to improve the functions are the key influencing factors of HOV lane setting traffic capacity, but when a certain saturation is reached, in large cities. Bi [13] conducted an in-depth study on the frequent lane changes may cause a decline in capacity. carpooling rate model after the HOV lanes were set up and Dahlgren [6] claimed that the HOV lane setting has a sig- clarified the change law of the carpooling rate under the nificant effect on reducing carbon dioxide and other conditions of different passenger numbers for buses and greenhouse gas emissions. Gutierrez et al. [7–10] made a HOV vehicles, thus proving the necessity and feasibility of detailed comparative analysis of the implementation effects setting HOV lanes in urban cities. Wu and Pan [14] analyzed of toll lanes and HOV lanes and concluded different and studied the relationship between the BRT lanes and 2 Journal of Advanced Transportation HOV lanes on urban roads and the implementation strategy; Table 1: Recommended value of free-flow speed for different some scholars also studied aspects such as operating effi- grades of roads (km/h). ciency and traffic conditions. -e feasibility of HOV lane Road grade Expressway Arterial road Collector road setting has been systematically studied [15–21], which Free-flow speed 60∼80 50∼60 40∼50 provides a theoretical basis for the scientific and rational setting of HOV lanes. In summary, most of the previous studies focused on the feasibility of HOV lane setting, road conditions, and HOV lane static management. However, the L V0 � ; (3) dynamic control of HOV lanes based on real-time data is ��L/Vf � + d � ignored. With the rapid development and improvement of information technology and Internet of Vehicles (IoV) where d refers to the average delay at intersections, L is the technology, it is feasible to realize HOV lane dynamic length of road segments, and Vf refers to the free-flow control using real-time data for carpooling priority. speed. 2. Threshold Determination for Setting HOV 2.2. Speed-Volume Model Calibration. -e least square Lanes Priority Dynamic Control under method was used to calibrate the speed-volume model under Connected Vehicle Environment the condition of mixed traffic and having HOV lane is as follows: HOV lanes provide the right of way for high-occupancy vehicles. It improves the operating efficiency of highways 31 V(q) � : (4) and attracts more people to carpool, thus reducing the h1 + 1:03(q/c)3:01i number of trips by private cars with low occupancy, and alleviates the urban traffic congestion. At present, the use of 2.3. .reshold for Introducing HOV Lane. For traffic trav- HOV lanes mostly adopts the fixed scheme. With the de- elers, the important indicator for evaluating travel quality velopment of data acquisition methods, it will be feasible to is travel time, which heavily depends on the traffic con- implement dynamic intelligent control over the HOV lanes dition. -e traffic condition could be divided into two under connected vehicle environment, which will realize the states: the ideal state and the actual state. -en, travel time optimal management of infrastructure resources. is divided into ideal travel time and actual travel time as In this section, in order to provide a basis for the dy- well. Actual travel time usually includes two parts: ideal namic control of HOV lanes with carpool priority, the travel time and ideal travel delay. -e ideal travel time is threshold determination of introducing HOV lanes under only related to the travel distance and travel mode; that is, connected vehicle environment was analyzed. when the travel distance and mode are fixed, the ideal travel time is a fixed value, but the ideal travel delay will be determined by the traffic condition and will continue to 2.1. Speed-Volume Model. -e BPR (Bureau of Public increase as the traffic condition changes. -e improve- Roads) model shows the functional relationship between the ment and reduction of the traffic condition can effectively travel time of road segments and the traffic load: reflect the operating efficiency of the road network. -is q β paper takes per capita delay as the evaluation index of road T(q) � T "#1 + α� � ; (1) 0 c network operation efficiency. -e threshold of intro- ducing HOV lanes was investigated by minimizing per where T(q) refers to the travel time at flow q, T0 is the travel capita delay index. time when traffic volume q � 0, C is the traffic capacity, and -e per capita delay index d′ could be calculated by α and β are model parameters. using the following equation: For the same traveler, the travel distance is a constant; q · n · d + q · n · d � therefore, equation (1) can be converted to the following d′ � b b b c c C ; (5) equation: qb · nb + qc · nc� V V(q) � 0 ; where qb refers to the traffic volume of high-occupancy β (2) h1 + α(q/c) i vehicles, nb represents the number of people in each oc- cupancy vehicle, db refers to the delay for each high-oc- where V(q) refers to the traffic speed and V0 refers to the cupancy vehicle, qc refers to the traffic volume of nonhigh- free-flow speed under the condition of mixed traffic of occupancy vehicles, nc represents the number of people in vehicles with different occupancy rates. each nonoccupancy vehicle, and dc refers to the delay for -e free-flow speed can be determined by the road grade, each nonoccupancy vehicle. and its recommended value is shown in Table 1. Per vehicle delay d can be calculated as follows: In terms of the urban roads, V0 is mainly related to intersection spacing, stop time of stations, signal period L L d � (q) − : ( ) duration, and green signal ratio, which can be calculated by � � ! 6 V V0 the following equation: Journal of Advanced Transportation 3 According to the previous survey and data analysis, Step 4: displaying the traffic information and theo- about 2/3 of the people who own private cars are willing retically analyzing the demand for setting HOV lanes to take carpool, and about 1/3 of the people owning based on the carpooling ratio, degree of saturation private cars show reluctance to carpooling, as shown in (v/c), and average traffic speed. Figure 1. Step 5: setting the time scale as the signal cycle of the It can be seen from Figure 2 that most (50.3%) high- downstream intersection. occupancy vehicles have two passengers, followed by one Step 6: determining the number of passengers on high- passenger (24.56%) and three passengers (24.26%).
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