2023 Selected Papers in English

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Evolutionary Game Analysis of Port and Shipping System Emission Reduction Under Government Regulation

LI Xiao-dong, KUANG Hai-bo, HE Hong-yua

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (1): 17-29. DOI: 10.16097/j.cnki.1009-6744.2023.01.003

Abstract （593）

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This paper focuses on the emission reduction problem in China's port and shipping system and proposes a game model with environmental regulation evolutions. The model includes the subjects of local governments, ports, and shipping companies. The study analyzes the strategy selection process and overall evolutionary stability of the three subjects and clarifies the driving mechanism of the evolutionary trend for each subject in the port and shipping system. Based on the numerical simulation analysis, the paper discusses the initial strategy of the three subjects and the strategy choice of the port and shipping system under different incentive and punishment mechanisms of local government. The results show that: (1) The active supervision strategy of local governments is related to the low willingness of ports and shipping companies to actively reduce emissions. (2) The evolution rate of active emission reduction strategies of ports and shipping companies corresponds directly to their mitigation intentions. (3) Under the static incentive and punishment mechanism, the penalty intensity of the local government does not affect the positive emission reduction strategies of ports and shipping companies. Still, it leads to their negative emission reduction if local governments adopt low subsidy measures. (4) Local governments have only a single strategy (high subsidies, no penalties) to enable ports and shipping companies to reach an evolutionary equilibrium (active emission reduction, aggressive emission reduction) under the static incentive and punishment mechanism. (5) Under the dynamic incentive and punishment mechanism, local governments adopt a hybrid regulatory strategy (low dynamic subsidy, high static penalty) to achieve the evolutionary equilibrium of active emission reduction strategies for port and shipping systems with low cost.

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Coordination of Signal and Vehicle Trajectory at Intersections for Mixed Traffic Flow

SUN Wei, ZHANG Meng-ya, MA Cheng-yuan, ZHU Ji-chen, YANG Xiao-guang

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (1): 97-105. DOI: 10.16097/j.cnki.1009-6744.2023.01.011

Abstract （787）

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The intersection traffic control under the mixed traffic environment can be realized by the coordination of the signal control and the trajectory control of automated vehicles, which can greatly improve the utilization efficiency of road traffic resources. The centralized control strategies in previous studies with the integrated optimization of signal timing and vehicle trajectory are difficult to be applied to the real operations with self-organized vehicles, and often have high computational complexity. In this paper, a logic-based coordinated control of the signal and vehicle trajectory is proposed within a decentralized framework. Based on the active servo control principle of fast and slow variables in the coordination theory, a coordination framework of the slow variables of intersection signal timing and the fast variables of vehicle trajectory strategy is designed. A logic-based signal timing optimization method and a speed control method are proposed for the connected and automated vehicles (CAV). The signal timing at the intersection can adapt to traffic demand dynamically, and the CAVs can optimize their speed strategy based on the prediction of the traffic states to pass the intersection efficiently and smoothly. Based on the reasonable speed control of the leading vehicle in the approach lanes during the green signal, the "leading effect" of the CAV can be utilized to avoid start-up loss and make the platoon pass the intersection efficiently. The simulation results show that the proposed cooperated control method can significantly reduce the average vehicle delay at intersections compared with the traditional control methods, and the logic-based decision making model can be solved efficiently. Based on the sensitivity analysis of the key parameters of the control strategy for the CAV, the fairness of the mixed traffic flow at intersection is further discussed, and the effectiveness of the control methods are compared for the mixed traffic with different penetration rates of CAVs.

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Signal Phase and Timing Optimization Method for Intersection Based on Hybrid Proximal Policy Optimization

CHEN Xi-qun, ZHU Yi-zhang, LV Chao-feng

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (1): 106-113. DOI: 10.16097/j.cnki.1009-6744.2023.01.012

Abstract （549）

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PDF(English version) （1649KB）（91）

Traffic signal timing is one of the critical measures to alleviate urban traffic congestion from the supply side. With traffic big data technology development, traffic signal control based on deep reinforcement learning has become a key research direction. Most of the existing control frameworks belong to discrete phase selection control, where phase associated duration is obtained by accumulating decision intervals. It may conflict with the agent's exploration for better actions. Therefore, this paper proposes a signal phase and timing optimization method based on hybrid proximal policy optimization for intersection. The study first defines a signal control action as a parameterized action under the constraint of practical application boundary condition of phase duration. Then, the state information is extracted and input into the bi-policy network to adaptively generate the next phase and its associated duration. The reward value of implementing action is evaluated according to the state change of the road network, so as to learn the intrinsic connection between phase and phase associated duration. A simulation platform is built to test the proposed method and compare the algorithms with real traffic flow data. Results show that compared with the discrete control, the proposed method achieves a lower decision frequency and better control effect, and the average travel time of vehicles and average queue length of lanes are reduced by 27.65% and 23.65%, respectively.

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Feeder Bus Route Design and Vehicle Allocation Under Influence of Shared Bikes

LIU Lu-mei, LIU Zheng-ke, MA Chang-xi, TAN Er-long, MA Xiao-lei

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (1): 165-175. DOI: 10.16097/j.cnki.1009-6744.2023.01.018

Abstract （578）

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PDF(English version) （1962KB）（87）

For the "first-and last-mile" of rail transit, feeder buses and shared bikes are two most prevalent modes to provide connection with rail transit for commuters. To understand the impact of bike-sharing on the planning and operation of feeder bus travel demand and route design, this study examines the feeder bus route design and vehicle allocation challenges based on the interaction of demand and supply. From the demand side, the actual travel demand of feeder buses is dynamically estimated depending on the user's mode choice between shared bikes and feeder buses, considering the travel time and travel cost. Comparatively, a mixed-integer non-linear programming model with the objective of minimizing the sum of bus operating cost and user travel cost is developed from the supply perspective to optimize the bus route design and vehicle allocation, including vehicle capacity, vehicle quantity, and flow balance constraints. The Lagrangian relaxation algorithm is used to solve the model. This strategy is applied to the planning of feeder bus routes in the Beijing suburbs surrounding the Huilongguan Metro Station. The actual smart card data and Mobike cycling data are used to obtain the total travel demand. The travel time by various modes between stops is derived from the AutoNavi route planning API (Application Programming Interface). In the case where the total number of vehicles is 10 and the number of lines is 2, the experimental results show that the difference between the assumed bus travel demand and the computed bus ridership can be effectively avoided if the influence of bike-sharing on bus travel demand is considered. The average running time between each bus stop and the station is 15.58 minutes, while the average passenger waiting time is 3.35 minutes. In the case where there are four lines, the average running time from each bus stop to the station is 8.53 minutes, which is almost half of the case with only two lines; the average waiting time for passengers is 3.44 minutes. Nonetheless, the computing time for the model grows exponentially with the increasing of the number of lines. Consequently, from the perspective of model calculation efficiency, both scenarios in which the number of lines is set to 2 or 3 can satisfy the application requirement of updating lines every half hour.

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Research Review of Influence of Social Network Information on Travel Behavior

CHEN Jian, ZHANG Chi, FU Zhi-yan, LIU Ke-liang

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (2): 1-10. DOI: 10.16097/j.cnki.1009-6744.2023.02.001

Abstract （806）

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PDF(English version) （478KB）（119）

To quantitatively review the research results of the influence of social network information on travel behavior, this paper retrieved and screened 133 English and 32 Chinese literatures from 2010 to 2022 based on the database of Web of Science and China National Knowledge Infrastructure. Through the combination of knowledge graph and qualitative literature analysis, the paper quantified and counted three indexes of annual publication volume, research hotspot countries, and keyword graph. The research results were presented in four aspects, including research methodology, social network information behavior, the influence of social network information on travel decisionmaking, and the influence of social network information on travel activities. The results show that: (1) in terms of data sources, the basic data of existing research haven't achieved the integration of feature dimension and decision dimension, and it is necessary to further integrate multi-source data to improve the robustness of research conclusions. (2) In terms of research methods, the existing research lack mutual support among analysis methods, and a variety of research methods can be integrated to analyze the influence of social network information on travel behavior across disciplines. (3) In terms of research content, the existing research results cannot fully reflect the development trend of future travel, and the heterogeneity of travelers can be given more attention. It is necessary to analyze the connection mode between social network information and travel behavior considering traveler heterogeneity in combination with new scenarios such as autonomous driving and shared travel.

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Airport Taxi Supply and Demand Equilibrium Game Model Considering Ride-hailing Competition

HUANG Ai-ling, LIU Meng-han, LI Ying

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (2): 176-186. DOI: 10.16097/j.cnki.1009-6744.2023.02.019

Abstract （373）

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To balance the supply and demand of taxi at airports, this paper proposes a strategy game model for taxi drivers and passengers decision-making based on the static non cooperative game theory under complete knowledge. The competition influence coefficient (CIC) is introduced in the profit function for taxi driver, and changes in driver's decision-making behavior are analyzed considering the impact of the ride-hailing services. The benefit function of passenger group is proposed to reflect the impact of different decision-making results of passenger group on drivers, and the major factors include queue length, boarding speed, traffic conditions, traffic fare, and comprehensive impact of multiple modes of transportation. Using Beijing Capital International Airport as an example for the empirical analysis, the results show that: when the two groups reach Nash equilibrium (NE) through mutual feedback, the overall supply of airport taxi is slightly higher than the demand under the average competition level of Beijing's ride-hailing services. It also shows a state of oversupply in the morning and evening peak hours, while in the early morning the demand is far greater than the supply with the closure of subway. Taxi drivers' awareness of the effects of online taxi competition can be suitably increased considering the mismatch between the daily supply and demand of airport taxis under the existing level of ride-hailing competition when it reaches NE.

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Scaled Tractive Power Distribution and Emission Model for Heavy-duty Trucks Based on Vehicle Weight

HUANG Yi-ran, SONG Guo-hua, PENG Fei

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (2): 326-334. DOI: 10.16097/j.cnki.1009-6744.2023.02.034

Abstract （449）

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PDF(English version) （752KB）（93）

To quantify the relationship between vehicle weight of Heavy-Duty Trucks(HDT) and Scaled Tractive Power (STP) distribution, and thus improve the accuracy and efficiency of emission estimation, this study develops a model of STP distribution and emission for HDT based on vehicle weight. First, the actual STP distributions are developed based on trajectory data of HDTs with different vehicle weights in Beijing. Then, the STP distributions are fitted by the Gaussian functions, and the relationships between vehicle weight and the parameters of the Gaussian functions are quantified by the polynomial functions to develop the model. Finally, the NOx emission factors are calculated to verify the emission estimation and prediction accuracy of the model, and the impact of vehicle weight on the emission estimation for HDT is elaborated in comparison with the existing emission model MOVES. The results are as follows: (1) The emission estimation accuracy of the model is satisfied. The emission estimation errors of restricted and unrestricted access roads are 4.7% and 7.0% , respectively. (2) The emission can be predicted by the only variable vehicle weight, which reduces the cost of collecting data on the trajectory of HDTs with different vehicle weights and simplifies the traditional emission calculation process, and the emission prediction error of the HDT weighing 6.7 t is 5.3%. (3) Compared with MOVES based on default fixed driving cycles and fixed vehicle weights, the emission error drops by 16.7% according to the developed model.

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Urban Transportation Management from Perspective of General Spatial Equilibrium: Review and Trend

XU Shu-xian, LIU Tian-liang, WANG Ting, XIAN Kai, HUANG Hai-jun, MA Shou-feng

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (3): 6-19. DOI: 10.16097/j.cnki.1009-6744.2023.03.002

Abstract （638）

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PDF(English version) （660KB）（67）

Urban transportation is the foundation of urban social and economic activities. Coordinated development of urban transportation and land use is of great practical significance to reduce traffic congestion, optimize the urban spatial structure, and realize sustainable urban development from the root of problems. With the development of urban society and the advancement of urbanization, as well as the low-carbon, green, and intelligent development trend of the transportation system, traditional urban transportation strategies purely focusing on supply or demand management cannot meet the needs of rapid urban development and the aspirations of the people to live a better life. Urban transportation management needs to focus on comprehensive governance of employment, housing, and transportation and dynamic equilibrium of supply and demand, to realize the coordinated and integrated development with urban spatial layout and land use. Based on the general spatial equilibrium theory, the literature on urban travel behavior analysis, travel demand management, transportation infrastructure supply, and supply-demand coupling strategies are systematically reviewed in this paper. Besides, the theoretical models, methods, and research problems in this area are also reviewed. It is found that the existing models cannot describe the dynamic process of urban development and the reality of China, and the related studies still focused on the traditional transportation management research problems. In the context of urban renewal, new territorial space planning systems, new transportation technologies and travel patterns, and big data, it is suggested that there is great potential for urban transportation management research from the perspective of general spatial equilibrium. It needs urgently a breakthrough in the corresponding theories and methods. Further research directions are proposed: the first is to analyze the influencing factors of residents' utility in the process of urban development, and put forward household utility decision-making theories and models under the integrated transportation and urban development; the second is to do activity/travel behavior analysis and management based on the data-driven and theory-driven methods; the third is to explore the impact of new technologies and modes of the transportation system on urban spatial structure and traffic characteristics, and study urban transport management issues for the era of digitization and intelligence; and the fourth is to explore theories and methods of urban space reshaping guided by transportation under urban renewal.

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Influence Mechanism of Rainfall on Traffic State of Urban Road Network

WANG Dian-hai, HUANG Li-sha, ZENG Jia-qi, CAI Zheng-yi

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (3): 48-55. DOI: 10.16097/j.cnki.1009-6744.2023.03.006

Abstract （549）

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PDF(English version) （1274KB）（67）

It is a common perception that urban roads are prone to experience traffic congestions in rainy days, but is it true that rainfall will inevitably cause traffic congestion? This paper investigates this mechanism from the theoretical view and actual data analysis. It was found that drivers tend to drive conservatively in rainy days, which increases the saturation headway. Based on this hypothesis, a signal-influenced urban road traffic flow model is established, and the changes in average travel speed under different rainfall scenarios are analyzed theoretically. The saturation headway under each rainfall level obtained by using video data statistics verifies the hypothesis that rainfall increases the saturation headway. Simplifying the data of the main road network in Xiaoshan District, Hangzhou, numerical simulations were conducted and the proposed model was verified through VISSIM road network simulation. The results show that the effect of rainfall on the average speed of the road network is negative. When the traffic demand is small, the negative impact of rainfall is almost negligible; as the rainfall level increases, the road network with high traffic demand is more likely to be oversaturated, and the average travel speed of the road network will experience a steep drop and the traffic condition deteriorates rapidly. Taking the maximum demand of the road network as an example, compared with the non-rainfall weather, the average speed of the road network decreases by 8.63% in the light rainfall scenario, 16.51% in the medium rainfall, 23.43% in the heavy rainfall, and 24.94% in the rainstorm. The VISSIM simulation results fit well with the theoretical values of the model, which verifies the effectiveness of the model. Since the traffic demand during the peak hours is much larger than that during the off-peak hours, the rainfall during the peak hours will bring a greater negative impact on the traffic status of the urban road network, which requires more attention from the traffic management.

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Two-layer Model to Distinguish Urban Motorized Travel Mode Based on Mobile Phone Signaling Data

GUO Yu-dong, YANG Fei, ZHOU Tao, YAO Zhen-xing, ZHANG Chu-liang, WEI Yin-cheng

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (3): 101-109. DOI: 10.16097/j.cnki.1009-6744.2023.03.012

Abstract （385）

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It is always difficult to apply the mobile phone signaling data in the actual urban complex travel environment and also challenging to distinguish the motorized travel mode under dense road networks. This paper proposes a twolayer model considering accurate path fitting and multidimensional spatio-temporal characteristics. At the level of travel path identification, S- G filtering can effectively smooth signaling data fluctuation relative to the actual travel path. The linear interpolation algorithm can fill in the time and space gaps. At the level of travel mode recognition, the key factors are mined, including the similarity of the recognized travel path, travel time similarity, acceleration, and wavelet velocity. The K-nearest neighbor algorithm is used to identify the travel modes (by car or bus). The results show that the proposed method can effectively identify the bus and car in the dense urban road network, and the accuracy rates can reach 88.29% and 82.28% , respectively. Under different travel distances, travel time, congestion conditions, road classes, road types, and path similarity, the proposed method is better than the existing algorithms, such as random forest, in the accuracy rate. The research supports the accurate recognition of travel characteristics based on mobile phone signaling data. It also provides an essential basis for road planning, construction, and public transit network planning.

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A Rescheduling Optimization Method for Metro Trains Under Cross-line Operation

ZHANG Xi-ran, CHEN Shao-kuan, ZHAO Xing-dong, WANG Zhuo

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (4): 164-174. DOI: 10.16097/j.cnki.1009-6744.2023.04.017

Abstract （696）

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PDF(English version) （1827KB）（35）

The cross-line operation makes emergency train timetable rescheduling complex. In order to handle a reduction of passing capacity in a line section, train timetables of metro lines are rescheduled by integrating five strategies including short-turning, service cancellation/insertion, and cross-line cancellation/restoration. A train timetable rescheduling optimization model is proposed to minimize the delay of trains and the traveling time of passengers, in which operational safety, occupation of sidings, circulation of rolling stocks, and dynamic passenger flow are considered. A solution algorithm incorporating the non-dominated sorting genetic algorithm Ⅱ and timetable recalculation algorithm under cross-line operation is addressed to solve the proposed model, and the effectiveness of the proposed model and algorithm are verified by a case study. The results from the case study show that: compared with rescheduled timetables in which the original cross-line operation scheme is completely maintained or changed to an independent operation, the proposed method is able to effectively reduce the passenger traveling time by 3.86% and reduce the train delay by 21.07%. The stability of train rescheduling will be increased if the buffer time of cross-line operation is long, and the average passenger transfer waiting time and train delay are further reduced by 4.06% and 3.77% respectively.

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China Railway Express Network Flow Assignment in Blockchain Background

HONG Zhi-chao, ZHANG Jin, SUN Wen-jie, SHEN Hao, ZHAO Gang, LIANG Hong-bin

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (4): 270-281. DOI: 10.16097/j.cnki.1009-6744.2023.04.027

Abstract （328）

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PDF(English version) （881KB）（28）

Network traffic analysis is the basis of traffic network optimization. This paper focuses on the China Railway Express, and constructs a two-objective network assignment model with the minimum total transportation cost and the shortest transportation time. For the transportation costs, considering the competition between China Railway Express liner and international liner and international air transport, the two-stage game is used to depict the change in the freight rate of the liner before and after the application of blockchain technology. For the transportation time, the proportion of customs clearance time before and after the application of blockchain technology is considered to affect the total time. The analysis results based on the one-week operation data of the China Railway Express in 2020 show that the application of blockchain technology has a significant impact on network traffic. After the application of blockchain technology, the traffic of the East and Middle Passages will decrease by 2.76% and 5.12% respectively, and the traffic of the West Passage will increase by 7.88%. A part of the cargo transportation tasks of the East and Middle Passages will be transferred to the West Passage. At the same time, the total transportation cost of the network was reduced by 17.08% , the total time was reduced by 8.27% , and the comprehensive transportation cost was reduced by 13.08% , which is beneficial to improving the economic benefits and attractiveness of the China Railway Express to customers. This analysis of the changes in the network traffic of the China Railway Express before and after the application of blockchain technology in this paper can provide an important reference for the adjustment of the train operation plan and the optimization of network facilities.

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Calculation for Carbon Emission Reduction Effect of Urban Rail Transit Based on Carbon Recovery Period Theory

YANG Yang, WANG Xue-chun, YUAN Zhen-zhou, CHEN Jin-jie, NA Yan-ling

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (5): 1-11. DOI: 10.16097/j.cnki.1009-6744.2023.05.001

Abstract （642）

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Reasonable quantification of the carbon emission reduction effect of urban rail transit has theoretical and practical significance to calculate the external cost of urban rail transit, enrich the theoretical system of carbon trading in the field of transportation, and even formulate subsidy policies for urban rail transit. This paper considered the passengers' travel behavior difference after the construction of urban rail transit, and established the carbon emission model of urban rail transit datum line and project activity from the perspective of life cycle. Furthermore, a theoretical model of carbon recovery period was established as a quantitative indicator of carbon emission reduction effect of urban rail transit. Carbon recovery period refers to the duration of carbon emission recovery toward the construction period through carbon emission reduction during the operation period, which is the time when the cumulative carbon footprint changes from positive to negative for the first time. Then, the urban rail transit data collection was completed in the datum line, project construction and activity period, and the model is calibrated. The Shijiazhuang Subway Line 3 was taken as a case study, the carbon emissions of its datum line, the project construction period and the project activity period were analyzed, and the carbon recovery period was calculated under the two models of future development. The results show that the carbon recovery period is respectively 27 years, 22 years and 29 years under normal, rapid, and slow growth scenarios. Under the scenario of normal development of energy structure and energy efficiency level, rapid development and slow development, the carbon recovery period is respectively 25 years, 24 years and 29 years. The conclusions indicate that large-scale passenger volume and efficient passenger transportation intensity are important elements for the positive impact of carbon emission reduction in urban rail transit. The systematic changes brought about by the adjustment of energy structure and the energy efficiency improvement can have a great positive impact on the carbon emission reduction of urban rail transit.

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Impact of Mountain Urban Roads on Vehicle Carbon Emissions Driven by Big Data

ZHOU Tao, LI Yi-jun, SUN Qin-mei, REN Han-kun, LIU Yi, ZHANG Zhen-hao

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (5): 172-183. DOI: 10.16097/j.cnki.1009-6744.2023.05.019

Abstract （337）

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PDF(English version) （1653KB）（33）

Understanding the relationship between urban roads and vehicle carbon emissions is of great significance for the calculation of urban traffic carbon emissions, urban traffic construction, and urban traffic planning, design. Based on the OBD big data, this paper takes Chongqing as an example to analyze the influence of road type and road slope on vehicle carbon emissions, and explore the localized road carbon emission factors in Chongqing. First, introduce the OBD data and processing method, combine the gasoline fuel carbon emission factor to convert vehicle fuel consumption into vehicle carbon emissions. The characteristics divide the vehicles into three categories: non-operating, operating, and freight. Finally, the LM method is used to iteratively fit the relationship between the average vehicle speed and the carbon emission factor. The research shows that increasing the average speed of urban roads to over 25 km· h ^-1 has a significant effect on reducing vehicle carbon emissions; the order of road carbon emission factors is that secondary roads are greater than arterial roads than expressways, which is related to serious interchanges and openings. The vehicle carbon emission factor is most sensitive to steep slope roads, and the order of influence is that the road slope is greater than the vehicle type than the road type.

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Critical Transportation Distance Analysis for Express Goods Transportation Modes Considering Low Carbon Emissions

SUN Zong-sheng, SHUAI Bin, XU Min-hao

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (6): 11-21. DOI: 10.16097/j.cnki.1009-6744.2023.06.002

Abstract （388）

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PDF(English version) （808KB）（47）

The increasing demand of express goods transportation has also brought a surge in carbon emissions. Adjustment of transportation structure and technological progress are the main approaches to reduce carbon emissions in the field of transportation. This paper proposes a market share rate model based on the Logit model, which includes service attributes such as economy, timeliness, stability, safety, convenience and environmental sustainability. The purpose is to analyze the competitive relationships and transportation distance among the array of express goods transportation modes. Based on the share rate model, the interaction relationship between the critical transportation distance and the speed changes of high-speed railway is analyzed, and the feasibility of the model is verified by examples. The results indicate that the absolute advantage of high-speed railway express transportation at 250 km·h ^-1 is 700 km to 1500 km, and the advantageous transportation time is 2.8 hours to 6.0 hours. When considering carbon emissions, the transportation distance of 600 km and above is the absolute dominant range of high-speed railway express transportation, with a dominant transportation time of 2.4 hours. The absolute advantage distance of high-speed railway over highways will expand by 100 kilometers on the left boundary of the interval for every 0.1 increase in carbon emission weight coefficient. Under the speeds of 200 km · h ^{- 1} , 250 km · h ^{- 1} , 300 km · h ^{- 1}, and 350 km · h ^{- 1} , the maximum increase in critical distance between highways and high-speed railway is achieved at 250 km · h ^{- 1} , which is 50% higher than the critical distance under 200 km·h ^-1 . When the carbon emission factor of air express transportation is reduced by half, the left boundary of its advantageous distance range will expand by 23%.

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Bus Operation Optimization Control Strategy Considering Speed Regulation and Boarding Guidance

WENG Jian-cheng, LI Wen-jie, LIN Peng-fei, DI Xiao-jian, XU Li-quan

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (6): 165-175. DOI: 10.16097/j.cnki.1009-6744.2023.06.017

Abstract （347）

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Improving the uniformity of bus arrival intervals and operational service reliability through effective control strategies is an important way to enhance the quality of bus services and the satisfaction of passengers. First, a bus operation model was developed in consideration of the fluctuation of passenger boarding demand at stops. Second, a bus interval speed regulation strategy was proposed based on travel time deviation feedback mechanism, and then a station passenger information guidance strategy was designed based on the boarding choice behavior model. To minimize passenger travel costs and bus headway deviations, this paper proposed a combination optimization control strategy integrating speed regulation and boarding guidance for bus operation and the solution method. Taking the bus Route No. 57 in Beijing as an example, this paper performed the numerical simulation comparison experiments for four scenarios. The results show that the combination control strategy has the best optimization effect. Compared with the no control strategy, the stability of bus operation has been improved by 47.7% through the proposed method, and the bus bunching on the route was avoided. The comprehensive cost considering travel time and congestion has been reduced by 18.71%. The study also compared the optimization effects of strategies under different passenger income levels and passenger guidance information compliance rates. The results show that the effect of information guidance strategies on reducing total travel costs reduce as income levels increase. When the passenger guidance information compliance rate is 0.7. The combination control strategy has the most significant improvement effect on bus operation and passenger travel. This study can provide important support for the bus operation reliability and service quality improvement.

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Prediction Model for Residents Travelling OD in Urban Areas Based on Mobile Phone Signaling Data

HU Bao-yu, LIU Xue

Journal of Transportation Systems Engineering and Information Technology 2023, 23 (6): 296-306. DOI: 10.16097/j.cnki.1009-6744.2023.06.029

Abstract （700）

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PDF(English version) （1242KB）（30）

To reveal the travel pattern and OD generation principle of urban area residents, the destination selection mechanism of urban area residents is explored based on mobile phone signaling data. The position opportunity selection (POS) model was developed by considering the population and the number of POI. The mobile phone signaling travel data of Harbin residents, obtained from the Unicom Smart Footprint Platform, is used to validate the model. The analysis is conducted at both the traffic cell and traffic mid-zone levels, focusing on Harbin's second, third, and fourth ring roads. The results show that the POS model predictions were generally consistent with the actual data patterns in the traffic attraction capacity and travel distance distributions. At both the traffic cells and mid-zones scales, the model achieves a prediction accuracy of 67% ~72% and 75% ~83% , respectively. These results indicate an improvement of 13%~18% and 9%~20% over the opportunity priority selection model and a superiority of 57%~60% and 55%~60% over the radiation model, respectively. The advantage of the proposed model lies in its simplicity and lack of parameters. The input data are easily obtainable, and the model offers high prediction accuracy. The findings provide a theoretical reference for urban traffic planning.

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