Pub Date : 2024-10-20DOI: 10.1080/19427867.2023.2262205
Electric shared mobility is flourishing in urban transportation. However, the problem of uneven vehicle distribution and untimely vehicle charging hampers user trip experience and system operation efficiency. To overcome these challenges, this study proposed a multi-phase vehicle relocation optimization approach for one-way station-based carsharing systems. In phase one, a micro-level shared travel demand forecasting model was developed to capture the number of orders in the short-term future. In phase two, stations were divided into different categories based on the results of user travel demand forecast. In phase three, the minimization of driving mileage and carbon emissions was taken as the optimization objective, and a solution method combining Gurobi solver and charging priority ranking was designed. Finally, the effectiveness and advantages of the proposed model and algorithm were comprehensively validated through a case study using real passenger orders and geographic data from the city of Shanghai, China.
{"title":"Shared travel demand forecasting and multi-phase vehicle relocation optimization for electric carsharing systems","authors":"","doi":"10.1080/19427867.2023.2262205","DOIUrl":"10.1080/19427867.2023.2262205","url":null,"abstract":"<div><div>Electric shared mobility is flourishing in urban transportation. However, the problem of uneven vehicle distribution and untimely vehicle charging hampers user trip experience and system operation efficiency. To overcome these challenges, this study proposed a multi-phase vehicle relocation optimization approach for one-way station-based carsharing systems. In phase one, a micro-level shared travel demand forecasting model was developed to capture the number of orders in the short-term future. In phase two, stations were divided into different categories based on the results of user travel demand forecast. In phase three, the minimization of driving mileage and carbon emissions was taken as the optimization objective, and a solution method combining Gurobi solver and charging priority ranking was designed. Finally, the effectiveness and advantages of the proposed model and algorithm were comprehensively validated through a case study using real passenger orders and geographic data from the city of Shanghai, China.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 9","pages":"Pages 1002-1017"},"PeriodicalIF":3.3,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135967375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-20DOI: 10.1080/19427867.2023.2266184
The global electric vehicle (EV) market overgrew in the previous decade. This paper investigates the factors affecting EV purchase intention in the West Bank, Palestine. This study adopts the exploratory sequential mixed methods approach by conducting unstructured interviews and questionnaires in a developing country context. We obtained 384 survey responses from EV owners and non-EV owners – this study used the partial least squares structural equation modeling (PLS-SEM) tool for empirical analysis. The study results show that environmental concerns, subjective norms, cognitive status, incentive policies, and product perception significantly affect consumers’ intentions to purchase EVs in the West Bank. Environmental concerns indirectly correlate with consumers’ intentions to purchase EVs through attitudes as a mediator. However, perceived behavior control has no significant impact on purchasing intent. These results will help policymakers in improving transportation policies.
{"title":"Psychological antecedents of electric vehicle adoption in the West Bank","authors":"","doi":"10.1080/19427867.2023.2266184","DOIUrl":"10.1080/19427867.2023.2266184","url":null,"abstract":"<div><div>The global electric vehicle (EV) market overgrew in the previous decade. This paper investigates the factors affecting EV purchase intention in the West Bank, Palestine. This study adopts the exploratory sequential mixed methods approach by conducting unstructured interviews and questionnaires in a developing country context. We obtained 384 survey responses from EV owners and non-EV owners – this study used the partial least squares structural equation modeling (PLS-SEM) tool for empirical analysis. The study results show that environmental concerns, subjective norms, cognitive status, incentive policies, and product perception significantly affect consumers’ intentions to purchase EVs in the West Bank. Environmental concerns indirectly correlate with consumers’ intentions to purchase EVs through attitudes as a mediator. However, perceived behavior control has no significant impact on purchasing intent. These results will help policymakers in improving transportation policies.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 9","pages":"Pages 1069-1080"},"PeriodicalIF":3.3,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-20DOI: 10.1080/19427867.2023.2262207
Taxis not only substitute for but also complement bus transit. With the complementary relationship, taxi trips reveal the origin-destination pairs where the level of bus service is low. This study attempts to utilize taxi data to identify potential weak links in the bus network. An evaluation methodology is proposed using taxi trips to evaluate the bus routes by incorporating accessibility measures at the stop level and convenience measures at the route level. With over 52,000 taxi orders collected in Jiading District of Shanghai, China, the corresponding alternative bus trips are simulated and then classified into 16 types of patterns according to the stop-level and route-level measures. The top five types, accounting for 78% of all trips, are selected for visual and quantitative analysis. The findings show that the proposed methodology can well assist bus agencies to improve service efficiency with better planning and design of bus routes.
{"title":"Can taxi data inform bus route improvement? A case study in Shanghai","authors":"","doi":"10.1080/19427867.2023.2262207","DOIUrl":"10.1080/19427867.2023.2262207","url":null,"abstract":"<div><div>Taxis not only substitute for but also complement bus transit. With the complementary relationship, taxi trips reveal the origin-destination pairs where the level of bus service is low. This study attempts to utilize taxi data to identify potential weak links in the bus network. An evaluation methodology is proposed using taxi trips to evaluate the bus routes by incorporating accessibility measures at the stop level and convenience measures at the route level. With over 52,000 taxi orders collected in Jiading District of Shanghai, China, the corresponding alternative bus trips are simulated and then classified into 16 types of patterns according to the stop-level and route-level measures. The top five types, accounting for 78% of all trips, are selected for visual and quantitative analysis. The findings show that the proposed methodology can well assist bus agencies to improve service efficiency with better planning and design of bus routes.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 9","pages":"Pages 1018-1038"},"PeriodicalIF":3.3,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-20DOI: 10.1080/19427867.2023.2264046
Providing effective Through Train Services (TTSs) faces challenges due to complex infrastructure conditions, train performances and passenger demands. To enhance TTSs between two different classes of urban rail transit lines with variations in train speed and capacity, we propose a multi-objective Integer Non-Linear Programming (INLP) model. This model maximizes passenger travel time savings and average train load utilization, and develops an integrated approach to simultaneously optimize the frequencies of through express trains and local trains, as well as the operation zones, stopping patterns and type selection of through trains. Additionally, a Non-Dominated Sorting Genetic Algorithm II is designed to solve the INLP model based on a simple test network and a real-world case from the Nanjing Subway. The unique benefits of our proposed method are demonstrated by a comprehensive compared with the Single Line Operation Mode and the all-stop plans under Through Operation Mode.
由于复杂的基础设施条件、列车性能和乘客需求,提供有效的直通车服务(TTS)面临着挑战。为了在列车速度和运力不同的两类城市轨道交通线路之间加强直通车服务,我们提出了一个多目标整数非线性编程(INLP)模型。该模型最大限度地节省了乘客的旅行时间,提高了列车平均载荷利用率,并开发了一种综合方法,可同时优化直通特快列车和本地列车的班次,以及直通列车的运行区域、停靠模式和类型选择。此外,基于一个简单的测试网络和南京地铁的实际案例,设计了一种非支配排序遗传算法 II 来求解 INLP 模型。通过与单线运行模式和直通运行模式下的全停方案进行综合比较,证明了我们提出的方法的独特优势。
{"title":"Multi-objective optimization for through train service integrating train operation plan and type selection","authors":"","doi":"10.1080/19427867.2023.2264046","DOIUrl":"10.1080/19427867.2023.2264046","url":null,"abstract":"<div><div>Providing effective Through Train Services (TTSs) faces challenges due to complex infrastructure conditions, train performances and passenger demands. To enhance TTSs between two different classes of urban rail transit lines with variations in train speed and capacity, we propose a multi-objective Integer Non-Linear Programming (INLP) model. This model maximizes passenger travel time savings and average train load utilization, and develops an integrated approach to simultaneously optimize the frequencies of through express trains and local trains, as well as the operation zones, stopping patterns and type selection of through trains. Additionally, a Non-Dominated Sorting Genetic Algorithm II is designed to solve the INLP model based on a simple test network and a real-world case from the Nanjing Subway. The unique benefits of our proposed method are demonstrated by a comprehensive compared with the Single Line Operation Mode and the all-stop plans under Through Operation Mode.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 9","pages":"Pages 1039-1058"},"PeriodicalIF":3.3,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-20DOI: 10.1080/19427867.2023.2259143
This paper presents an experimental study on the departure time choice behavior during the morning rush hours under different road capacity conditions. Experimental data are analyzed from the aspects of the equilibrium state of a traffic system and the choice behavior of subjects. The experimental results showed that the user equilibrium is easy to achieve in the medium-capacity scenario; however, it is difficult in the low- and high-capacity scenario. This implies that the user equilibrium cannot predict the aggregate behavior well when the bottleneck capacity is too low or too high. A reinforcement learning model is constructed to reproduce experimental results and uncover subjects’ learning mechanism. Simulation results are in good agreement with the experimental results. The results presented in this study could provide the theoretical support for developing measures for transportation management and control during the morning rush hours.
{"title":"Experimental study on the departure time choice behavior during the morning rush hours under different road capacity conditions","authors":"","doi":"10.1080/19427867.2023.2259143","DOIUrl":"10.1080/19427867.2023.2259143","url":null,"abstract":"<div><div>This paper presents an experimental study on the departure time choice behavior during the morning rush hours under different road capacity conditions. Experimental data are analyzed from the aspects of the equilibrium state of a traffic system and the choice behavior of subjects. The experimental results showed that the user equilibrium is easy to achieve in the medium-capacity scenario; however, it is difficult in the low- and high-capacity scenario. This implies that the user equilibrium cannot predict the aggregate behavior well when the bottleneck capacity is too low or too high. A reinforcement learning model is constructed to reproduce experimental results and uncover subjects’ learning mechanism. Simulation results are in good agreement with the experimental results. The results presented in this study could provide the theoretical support for developing measures for transportation management and control during the morning rush hours.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 9","pages":"Pages 943-958"},"PeriodicalIF":3.3,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136236223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/19427867.2023.2252222
This study analyzed the impact of driving environments (real-world and simulated world) and driving conditions (no time pressure and time pressure) on speed compliance and speed adaptation. Professional car drivers were recruited, and the data was collected in real-world and simulated world under no time pressure and time pressure driving conditions. The comparison results using Wilcoxon-signed rank test showed that speed compliance and speed adaptation were not consistently significant and were not in the same direction highlighting the influence of various factors like road features and driver characteristics. The generalized linear mixed model results showed that speed compliance was relatively better in simulated world (by 3.98 kmph) than real-world. Further, speed adaptation under time pressure was about 5.86 kmph lower during real-world as compared to simulated world. The findings from this study can provide new insights on road safety strategies and policy implications for limiting speeding-related crash risks.
{"title":"Impact assessment of professional drivers’ speed compliance and speed adaptation with posted speed limits in different driving environments and driving conditions","authors":"","doi":"10.1080/19427867.2023.2252222","DOIUrl":"10.1080/19427867.2023.2252222","url":null,"abstract":"<div><div>This study analyzed the impact of driving environments (real-world and simulated world) and driving conditions (no time pressure and time pressure) on speed compliance and speed adaptation. Professional car drivers were recruited, and the data was collected in real-world and simulated world under no time pressure and time pressure driving conditions. The comparison results using Wilcoxon-signed rank test showed that speed compliance and speed adaptation were not consistently significant and were not in the same direction highlighting the influence of various factors like road features and driver characteristics. The generalized linear mixed model results showed that speed compliance was relatively better in simulated world (by 3.98 kmph) than real-world. Further, speed adaptation under time pressure was about 5.86 kmph lower during real-world as compared to simulated world. The findings from this study can provide new insights on road safety strategies and policy implications for limiting speeding-related crash risks.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 8","pages":"Pages 872-882"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42001120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/19427867.2023.2250622
Nowadays, deploying an intelligent vehicle detection system (IVDS) in diverse traffic is a work priority. It provides real-time traffic information with vehicle counts and types of vehicles. IVDS deployment in diverse traffic is challenging because different vehicle classes occlude each other on the road. In recent years, convolutional neural network (CNN) based deep learning (DL) methods have attained incredible progress in implementing IVDS. However, most CNN-based DL methods do not include diverse traffic conditions in Asian countries. Also, due to existing feature extraction backbones, they cannot accurately detect multi-scale vehicles. This work proposes an advanced visual computing deep learning (AVCDL) method with a vast labeled vehicle dataset to detect vehicles in diverse traffic. It includes an ensemble backbone and an improved multi-stage vehicle detection head (MSVDH). An ensemble CNN backbone extracts the vehicle features and combines them on a single channel via a feature concatenation. The final detection is carried out by an improved MSVDH that classifies the target vehicles. The proposed method is examined, tested, and evaluated using traffic statistics. It is contrasted with current cutting-edge vehicle detection techniques. It achieves 86.32% mean average precision (mAP) on self-collected diverse traffic labeled dataset (DTLD) and 86.17% mAP on KITTI. Moreover, the real-time performance is validated with NVIDIA Jetson Tx2 and Nano boards. It achieves 15 frames per second (FPS) on Jetson Tx2 and 7 FPS on Jetson Nano.
{"title":"Vehicle detection in diverse traffic using an ensemble convolutional neural backbone via feature concatenation","authors":"","doi":"10.1080/19427867.2023.2250622","DOIUrl":"10.1080/19427867.2023.2250622","url":null,"abstract":"<div><div>Nowadays, deploying an intelligent vehicle detection system (IVDS) in diverse traffic is a work priority. It provides real-time traffic information with vehicle counts and types of vehicles. IVDS deployment in diverse traffic is challenging because different vehicle classes occlude each other on the road. In recent years, convolutional neural network (CNN) based deep learning (DL) methods have attained incredible progress in implementing IVDS. However, most CNN-based DL methods do not include diverse traffic conditions in Asian countries. Also, due to existing feature extraction backbones, they cannot accurately detect multi-scale vehicles. This work proposes an advanced visual computing deep learning (AVCDL) method with a vast labeled vehicle dataset to detect vehicles in diverse traffic. It includes an ensemble backbone and an improved multi-stage vehicle detection head (MSVDH). An ensemble CNN backbone extracts the vehicle features and combines them on a single channel via a feature concatenation. The final detection is carried out by an improved MSVDH that classifies the target vehicles. The proposed method is examined, tested, and evaluated using traffic statistics. It is contrasted with current cutting-edge vehicle detection techniques. It achieves 86.32% mean average precision (mAP) on self-collected diverse traffic labeled dataset (DTLD) and 86.17% mAP on KITTI. Moreover, the real-time performance is validated with NVIDIA Jetson Tx2 and Nano boards. It achieves 15 frames per second (FPS) on Jetson Tx2 and 7 FPS on Jetson Nano.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 8","pages":"Pages 838-856"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45326643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/19427867.2023.2254527
In this paper, we explore the regulation of one-way station-based vehicle-sharing system (OSVS) through dynamic-hybrid parking reservation policies. We first propose a dynamic-hybrid parking reservation policy. This policy only requires trips with expected travel distances shorter than a specific threshold to make a parking reservation. The distance threshold varies with time. We develop a discrete event simulation model based on the O2DES (object-oriented discrete event simulation) framework to compare the dynamic-hybrid parking reservation (DHPR) strategy with the no-reservation (NR), static-hybrid parking reservation (SHPR) and complete parking reservation (CPR) strategies. Furthermore, we propose a simulation-optimization model and an Elitism-based Genetic algorithm with the optimal computation budget allocation to determine the fleet size, station capacity, and dynamic reservation distance threshold. The analysis of case studies of a real-world system indicates that DHPR is always superior to NR, SHPR and CPR.
{"title":"Simulation and optimization of dynamic-hybrid parking reservation strategies for one-way vehicle-sharing systems","authors":"","doi":"10.1080/19427867.2023.2254527","DOIUrl":"10.1080/19427867.2023.2254527","url":null,"abstract":"<div><div>In this paper, we explore the regulation of one-way station-based vehicle-sharing system (OSVS) through dynamic-hybrid parking reservation policies. We first propose a dynamic-hybrid parking reservation policy. This policy only requires trips with expected travel distances shorter than a specific threshold to make a parking reservation. The distance threshold varies with time. We develop a discrete event simulation model based on the O2DES (object-oriented discrete event simulation) framework to compare the dynamic-hybrid parking reservation (DHPR) strategy with the no-reservation (NR), static-hybrid parking reservation (SHPR) and complete parking reservation (CPR) strategies. Furthermore, we propose a simulation-optimization model and an Elitism-based Genetic algorithm with the optimal computation budget allocation to determine the fleet size, station capacity, and dynamic reservation distance threshold. The analysis of case studies of a real-world system indicates that DHPR is always superior to NR, SHPR and CPR.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 8","pages":"Pages 894-910"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48674392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/19427867.2023.2252220
The platoon size is a critical parameter in connected and automated vehicle (CAV) platoon configuration. However, the optimal platoon size configuration for the mixed human-driven vehicles (HVs) and CAVs traffic has not been well-studied, especially in merging areas. This paper aims to determine the optimal platoon size in the merge area through numerical analysis. Specifically, the existing merge probability calculation model is improved considering the impact of mainline random platoon size on on-ramp vehicles. In the improved model, the CAV platoon is treated as a vehicle with different lengths, and the headway between the platoon and single vehicle and the headway between the platoons are related to the maximum platoon size and CAV penetration rate. Three key parameters, namely the CAV penetration rate, acceleration lane length, and mainline traffic volume, were combined at various values. Based on this input, the relationship between the success rate and the platoon size was analyzed. The numerical analysis results indicate that: (1) when the CAV penetration rate is 10% ~30%, the merge success rate increases and stabilizes as the platoon size increases, and the optimal platoon size is 4 ~ 6. (2) When the CAV penetration rate is 40% ~70%, the trend of merge success rate varies with increasing platoon size under different mainline traffic volumes and acceleration lane lengths. Under the situation with lower traffic and longer acceleration length, the merge success rate tends to decline easier with larger platoon sizes, with 3 ~ 8 being the optimal platoon size. (3) When the CAV penetration rate is 80% ~90%, as the platoon size increases, the merging success rate tends to increase to the highest point and decrease. The optimal platoon size is 3 ~ 5. Finally, the validity of the theoretical model is confirmed through simulation experiments, and its limitations are discussed.
{"title":"Determination of the optimal connected and automated vehicles platoon size based on the merging success rate","authors":"","doi":"10.1080/19427867.2023.2252220","DOIUrl":"10.1080/19427867.2023.2252220","url":null,"abstract":"<div><div>The platoon size is a critical parameter in connected and automated vehicle (CAV) platoon configuration. However, the optimal platoon size configuration for the mixed human-driven vehicles (HVs) and CAVs traffic has not been well-studied, especially in merging areas. This paper aims to determine the optimal platoon size in the merge area through numerical analysis. Specifically, the existing merge probability calculation model is improved considering the impact of mainline random platoon size on on-ramp vehicles. In the improved model, the CAV platoon is treated as a vehicle with different lengths, and the headway between the platoon and single vehicle and the headway between the platoons are related to the maximum platoon size and CAV penetration rate. Three key parameters, namely the CAV penetration rate, acceleration lane length, and mainline traffic volume, were combined at various values. Based on this input, the relationship between the success rate and the platoon size was analyzed. The numerical analysis results indicate that: (1) when the CAV penetration rate is 10% ~30%, the merge success rate increases and stabilizes as the platoon size increases, and the optimal platoon size is 4 ~ 6. (2) When the CAV penetration rate is 40% ~70%, the trend of merge success rate varies with increasing platoon size under different mainline traffic volumes and acceleration lane lengths. Under the situation with lower traffic and longer acceleration length, the merge success rate tends to decline easier with larger platoon sizes, with 3 ~ 8 being the optimal platoon size. (3) When the CAV penetration rate is 80% ~90%, as the platoon size increases, the merging success rate tends to increase to the highest point and decrease. The optimal platoon size is 3 ~ 5. Finally, the validity of the theoretical model is confirmed through simulation experiments, and its limitations are discussed.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 8","pages":"Pages 857-871"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42014197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/19427867.2023.2250161
Traffic conflict is frequently utilized as a stand-in for crashes for analyzing traffic safety from a broader perspective for varying roadways and traffic conditions. In Indian heterogeneous traffic conditions, vehicles with various static and dynamic properties interact simultaneously in longitudinal and lateral directions, forming traffic conflicts. To this end, the present study develops crossing conflict-based safety performance functions (C-SPFs) for eight urban un-signalized T-intersections. The video-graphic survey approach was used to gather the necessary traffic data with different intersection and traffic flow characteristics. After that, from the recorded video, traffic conflicts were identified using the Post encroachment time (PET) for the selected eight study intersections. Based on the PET values, crossing conflicts were initially divided into critical conflicts (CC) and non-critical conflicts (NCC). Then, using the Poisson-Tweedie regression technique, crossing conflicts were modeled as a function of traffic flow and intersection-related parameters. The findings showed that the most important factors defining the number of CC and NCC are intersection geometry (with or without Central Island), time of day, traffic volume, and composition (offending and conflicting approach). Based on the study’s findings, city planners and traffic engineers estimate the number of CC and NCC; as a result, they may project the necessary laws, rules, and regulations to enhance traffic safety operations.
交通冲突经常被用来代替碰撞事故,以便从更广阔的角度分析不同道路和交通状况下的交通安全。在印度的异构交通条件下,具有各种静态和动态特性的车辆在纵向和横向同时发生相互作用,形成交通冲突。为此,本研究为八个城市非信号灯 T 型交叉路口开发了基于交叉冲突的安全性能函数(C-SPF)。本研究采用视频图形调查方法,收集不同交叉口和交通流特征的必要交通数据。然后,根据录制的视频,使用后侵占时间(PET)对选定的八个研究交叉口的交通冲突进行识别。根据 PET 值,交叉口冲突被初步分为关键冲突(CC)和非关键冲突(NCC)。然后,利用泊松-特威迪回归技术,将交叉口冲突模拟为交通流量和交叉口相关参数的函数。研究结果表明,决定交叉口冲突和非关键冲突数量的最重要因素是交叉口的几何形状(有无中央岛)、一天中的时间、交通流量和组成(违规和冲突方向)。根据研究结果,城市规划者和交通工程师可估算出 CC 和 NCC 的数量,并据此制定必要的法律、规则和法规,以加强交通安全运行。
{"title":"Crossing conflict models for urban un-signalized T-intersections in India","authors":"","doi":"10.1080/19427867.2023.2250161","DOIUrl":"10.1080/19427867.2023.2250161","url":null,"abstract":"<div><div>Traffic conflict is frequently utilized as a stand-in for crashes for analyzing traffic safety from a broader perspective for varying roadways and traffic conditions. In Indian heterogeneous traffic conditions, vehicles with various static and dynamic properties interact simultaneously in longitudinal and lateral directions, forming traffic conflicts. To this end, the present study develops crossing conflict-based safety performance functions (C-SPFs) for eight urban un-signalized T-intersections. The video-graphic survey approach was used to gather the necessary traffic data with different intersection and traffic flow characteristics. After that, from the recorded video, traffic conflicts were identified using the Post encroachment time (PET) for the selected eight study intersections. Based on the PET values, crossing conflicts were initially divided into critical conflicts (CC) and non-critical conflicts (NCC). Then, using the Poisson-Tweedie regression technique, crossing conflicts were modeled as a function of traffic flow and intersection-related parameters. The findings showed that the most important factors defining the number of CC and NCC are intersection geometry (with or without Central Island), time of day, traffic volume, and composition (offending and conflicting approach). Based on the study’s findings, city planners and traffic engineers estimate the number of CC and NCC; as a result, they may project the necessary laws, rules, and regulations to enhance traffic safety operations.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"16 8","pages":"Pages 829-837"},"PeriodicalIF":3.3,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42586026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}