International Journal of Transportation Science and Technology最新文献

{"title":"Do existing split failure metrics accurately reflect pedestrian operation at signalized intersections?","authors":"Ferdousy Runa ,&nbsp;S. Ilgin Guler ,&nbsp;Vikash V. Gayah","doi":"10.1016/j.ijtst.2023.02.006","DOIUrl":"10.1016/j.ijtst.2023.02.006","url":null,"abstract":"<div><p>Automated Traffic Signal Performance Measures (ATSPMs) uses high-resolution data to develop operational performance measures for signalized intersections. Split Failure (SFs) is one of the primary metrics to identify intersections with operational issues. These SFs are determined by measuring vehicle occupancy for a given movement during its green time (i.e., Green Occupancy Ratio or GOR) and immediately after the signal turns red (i.e., Red Occupancy Ratio or ROR₅). While the SF metric is a great tool for signal operations and rebalancing green times, it focuses entirely on vehicular measures and ignores the treatment of pedestrians at the intersection. Prioritizing vehicular movements may lead to excess pedestrian delay, which may cause pedestrians to violate traffic signals.</p><p>To address this issue, this paper examines the relationship between pedestrian delay and GOR or ROR₅. The main objective was to identify whether the GOR and ROR₅ could be adequately used as a proxy for pedestrian delays. To achieve this goal, high-resolution data was collected from the ATSPMs database at a signalized intersection in Salt Lake City, Utah. To predict GOR or ROR₅ as a function of pedestrian delay, a linear regression model was developed. The results reveal that there is very weak to no relationship between these metrics. This implies that using only GOR or ROR₅ in quantifying signal performance does not meaningfully capture pedestrian delay and thus might overemphasize vehicle movements. Specific pedestrian delay metrics should be included in a signal operation analysis to identify operational issues.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 270-283"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023000217/pdfft?md5=3a79aba752813d78828e6fd9083e258b&pid=1-s2.0-S2046043023000217-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48367903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does the minimization of the average vehicle delay and the minimization of the average number of stops mean the same at the signalized intersections?","authors":"Ziya Cakici ,&nbsp;Goker Aksoy","doi":"10.1016/j.ijtst.2024.01.003","DOIUrl":"10.1016/j.ijtst.2024.01.003","url":null,"abstract":"<div><p>Signal timings at signalized intersections are frequently optimized by considering commonly used vehicle delay models. It is generally believed that reducing the average number of stops can also decrease the average vehicle delay. Therefore, the aim of this research is to address the question: “Can similar performance outcomes be achieved through the <strong>M</strong>inimization of <strong>A</strong>verage <strong>V</strong>ehicle <strong>D</strong>elay (MAVD) and the <strong>M</strong>inimization of <strong>A</strong>verage <strong>N</strong>umber of <strong>S</strong>tops (MANS)?” The first phase of the study entails the creation of two distinct signal timing optimization models based on the Akcelik average vehicle delay and average number of stops models. Subsequently, scripts were developed in MATLAB to identify the optimal signal timings for both approaches utilizing the Differential Evolution Algorithm. In the third phase, 30 traffic scenarios were generated, each varying in overall traffic volumes at the intersection. Subsequently, the signal timings derived from the MAVD and MANS approaches were applied independently to these scenarios, and performance indicators (average vehicle delay and average number of stops) were compared. The results reveal that the utilization of MANS-based signal timings instead of MAVD may lead to an increase in average vehicle delays of up to 113.55%. Additionally, it is demonstrated that when MAVD-based signal timings are applied instead of MANS, the average number of stops can increase by up to 16.28%. Finally, it is concluded that as the overall traffic volume at the intersection increases, these growth rates tend to decrease.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 213-228"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043024000030/pdfft?md5=64c25295d7b501eb3cdc34cff0283cd8&pid=1-s2.0-S2046043024000030-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139637001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State space model detection of driving fatigue considering individual differences and time cumulative effect","authors":"Xuesong Wang ,&nbsp;Mengjiao Wu ,&nbsp;Chuan Xu ,&nbsp;Xiaohan Yang ,&nbsp;Bowen Cai","doi":"10.1016/j.ijtst.2023.12.004","DOIUrl":"https://doi.org/10.1016/j.ijtst.2023.12.004","url":null,"abstract":"<div><p>Fatigue is an important cause of traffic crashes, and effective fatigue detection models can reduce these crashes. Research has found large differences in fatigued driving performance from driver to driver, as well as a significant cumulative effect of fatigue on a given driver over time. Both sources of variation can decrease the accuracy of detection systems, but previous studies have not done enough to evaluate these differences. The purpose of this study is therefore to develop a fatigue detection model that considers individual differences and the time cumulative effect of fatigue. Data on the lateral position of the car in its lane, steering wheel movement, speed, and eye movement were collected from 22 drivers using a driving simulator with an eye-tracking system. Drivers’ subjective fatigue scores were collected using the Karolinska Sleepiness Scale. State space models (SSMs) were built to detect fatigue in each driver, considering his or her individual features. As a time series model, the SSM can also address the time cumulative effect of fatigue, and it does not require a large dataset to achieve high levels of accuracy. The differences in SSM results confirm that diversity does exist among drivers’ fatigued driving performance, so the ability of the SSM to take into account driver-specific information from each individual driver suggests that it is more suitable for fatigue detection than models that use aggregated driver data. Results show that the fatigue detection accuracy of the SSM (77.73%) is higher than that of artificial neural network models (61.37%). The advantages of accuracy, high interpretability, and flexibility make the SSM a comprehensive and valuable individualized fatigue detection model for commercial use.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 200-212"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001090/pdfft?md5=114507ba641c1cea886f31b52501ac52&pid=1-s2.0-S2046043023001090-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139549215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factoring in temporal variations of public transit-based healthcare accessibility and equity","authors":"Xinghua Li ,&nbsp;Ziqi Yang ,&nbsp;Yuntao Guo ,&nbsp;Wei Xu ,&nbsp;Xinwu Qian","doi":"10.1016/j.ijtst.2024.01.001","DOIUrl":"10.1016/j.ijtst.2024.01.001","url":null,"abstract":"<div><p>Access to healthcare services using public transportation (PT-based healthcare accessibility) is a crucial aspect in achieving healthcare equity as it affects individuals’ ability to receive healthcare. Previous research has focused on the spatial features of healthcare accessibility. However, less attention has been given to its temporal characteristics, which can be influenced by transit schedules, multimodal connectivity, congestion, and other factors. This study proposes a framework to better understand the impacts of temporally varying PT-based healthcare accessibility on healthcare equity. A case study of Shanghai, China is used to illustrate the temporal variation of healthcare accessibility, with a focus on hourly inter- and intra-regional disparities. These disparities are captured using the Gini coefficient and Theil index. Additionally, the study introduces bivariate local Moran’s I to identify healthcare shortage areas and evaluate the spatial autocorrelation between population density and healthcare accessibility. The findings of this study reveal that the accessibility to healthcare services experiences significant fluctuations throughout the day, leading to temporal variations in healthcare equity. Subway service quality contributes more to temporal variations than bus service quality. The lowest point of such equity is reached when PT operates at its full capacity. On a spatial level, individuals residing in newly developed regions, which surround the historical urban core or recently planned city subcenters, tend to experience decreased accessibility to healthcare via public transportation. Consequently, it results in a heightened reliance on motorized transportation in these areas. These findings provide insights that can inform the design of PT accessibility-based strategies, healthcare improvement plans and inclusive housing policies, to address healthcare equity issues in metropolitan areas. By considering both spatial and temporal factors, we can better understand the complex relationships between transportation and healthcare accessibility to promote equitable access to healthcare services and foster social equity.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 186-199"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043024000017/pdfft?md5=381860e1ed91d1b3d8e4a87b41fcaa56&pid=1-s2.0-S2046043024000017-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139457630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive agent-based approach for instant delivery order dispatching: Incorporating task buffering and dynamic batching strategies","authors":"Miaojia Lu ,&nbsp;Xinyu Yan ,&nbsp;Shadi Sharif Azadeh ,&nbsp;Pengling Wang","doi":"10.1016/j.ijtst.2023.12.006","DOIUrl":"https://doi.org/10.1016/j.ijtst.2023.12.006","url":null,"abstract":"<div><p>The volume of instant delivery has witnessed a significant growth in recent years. Given the involvement of numerous heterogeneous stakeholders, instant delivery operations are inherently characterized by dynamics and uncertainties. This study introduces two order dispatching strategies, namely task buffering and dynamic batching, as potential solutions to address these challenges. The task buffering strategy aims to optimize the assignment timing of orders to couriers, thereby mitigating demand uncertainties. On the other hand, the dynamic batching strategy focuses on alleviating delivery pressure by assigning orders to couriers based on their residual capacity and extra delivery distances. To model the instant delivery problem and evaluate the performances of order dispatching strategies, Adaptive Agent-Based Order Dispatching (ABOD) approach is developed, which combines agent-based modelling, deep reinforcement learning, and the Kuhn-Munkres algorithm. The ABOD effectively captures the system's uncertainties and heterogeneity, facilitating stakeholders learning in novel scenarios and enabling adaptive task buffering and dynamic batching decision-makings. The efficacy of the ABOD approach is verified through both synthetic and real-world case studies. Experimental results demonstrate that implementing the ABOD approach can lead to a significant increase in customer satisfaction, up to 275.42%, while simultaneously reducing the delivery distance by 11.38% compared to baseline policies. Additionally, the ABOD approach exhibits the ability to adaptively adjust buffering times to maintain high levels of customer satisfaction across various demand scenarios. As a result, this approach offers valuable support to logistics providers in making informed decisions regarding order dispatching in instant delivery operations.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 137-154"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001119/pdfft?md5=a5659ce7203aa86c5e895c4feb9f4c9a&pid=1-s2.0-S2046043023001119-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of machine learning models to predict driver left turn destination lane choice behavior at urban intersections","authors":"Mohammed Moinuddin ,&nbsp;Logan Proffer ,&nbsp;Matthew Vechione ,&nbsp;Aaditya Khanal","doi":"10.1016/j.ijtst.2023.12.005","DOIUrl":"10.1016/j.ijtst.2023.12.005","url":null,"abstract":"<div><p>When there are multiple lanes to choose from downstream of a turning movement, drivers should choose the innermost lane so that drivers at other approaches of the intersection may make concurrent turning movements in the outermost lane(s). However, human drivers do not always choose the innermost lane, which could lead to crashes with other vehicles. Therefore, predicting human driver behaviors is vital in reducing crashes, as the need to share the roadways with automated vehicles (AVs) continues to grow. In this research, various machine learning models have been used to predict the left turn destination lane choice of human-driven vehicles (HDVs) at urban intersections based on several quantifiable parameters. A total of 174 subject vehicles were extracted and analyzed in Los Angeles, California, and Atlanta, Georgia, using HDV trajectory data from the Next Generation SIMulation (NGSIM) database. Five machine learning techniques, namely binary logistic regression, k nearest neighbors, support vector machines, random forest, and adaptive neuro-fuzzy inference system, were applied to the extracted data to predict the lane choice behavior of drivers. The k nearest neighbors model showed the most promising results for the evaluated data with a correct decision score of over 93% for the unseen test data. This model may be programmed into: (i) AVs, in conjunction with sensors, to predict if an HDV is about to turn into the incorrect destination lane; and (ii) microscopic traffic simulation tools so that modelers can identify potential conflicts when HDVs do not select the appropriate destination lane.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 155-170"},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001107/pdfft?md5=0d67cf0b5af9b82ee5f3b3e948aa0a90&pid=1-s2.0-S2046043023001107-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139014239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of optimal locations of adaptive traffic signal control using heuristic methods","authors":"Tanveer Ahmed,&nbsp;Hao Liu,&nbsp;Vikash V. Gayah","doi":"10.1016/j.ijtst.2023.12.003","DOIUrl":"10.1016/j.ijtst.2023.12.003","url":null,"abstract":"<div><p>Adaptive Traffic Signal Control (ATSC) adjusts signal timings to real-time traffic measurements, increasing operational efficiency within a network. However, ATSC is both expensive to install and operate making it infeasible to deploy at all signalized intersections within a network. This study presents a bi-level optimization framework that applies heuristic methods to identify a limited set of locations for ATSC deployment within an urban network. At the upper-level, the Population Based Incremental Learning (PBIL) algorithm is employed to generate, evaluate, learn, and update different ATSC configurations. The lower-level uses the delay-based Max-Pressure algorithm to simulate the ATSC configuration within a microsimulation platform. The study proposes improvements to the PBIL algorithm by considering constraints on the maximum number of intersections for ATSC deployment and incorporates prior information about the intersection performance (i.e., informed search). Simulation results on the traffic network of State College, PA reveal that the proposed PBIL algorithm consistently outperforms baseline methods that select locations only based on queue-lengths or delays in terms of reducing overall network travel times. The study also reveals that intersections experiencing the highest delays or longest queues are not always the best candidates for ATSC. Moreover, applying ATSC at all intersections does not always provide the best performance; in fact, ATSC applied to some locations could increase travel times by contributing additional congestion downstream. Additionally, the modified PBIL algorithm with the informed search strategy is more efficient at identifying promising solutions suggesting it can be readily applied to more generalized optimization problems.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 122-136"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001089/pdfft?md5=3af154f13b0b2154ae09b9d12f55dac9&pid=1-s2.0-S2046043023001089-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139015009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the influential factors for customized bus service reopening from naturalistic observations in Shanghai","authors":"Yu Shen ,&nbsp;Chenlong Xu ,&nbsp;Shengchuan Jiang ,&nbsp;Zhikang Zhai ,&nbsp;Yuxiong Ji ,&nbsp;Yuchuan Du","doi":"10.1016/j.ijtst.2023.12.002","DOIUrl":"10.1016/j.ijtst.2023.12.002","url":null,"abstract":"<div><p>This work attempts to understand how a customized bus (CB) operator decides to open or close a CB line. We look into the changes in the operation status of CB lines (<em>i.e.</em> reopening and closure) from one of the largest CB operators in Shanghai, China, with a 22-month consecutive observation ranging from January 2019 to October 2020. As all CB services were totally suspended at the beginning of 2020 due to the COVID-19 travel restriction and then gradually recovered in March 2020, we utilize this study period as a naturalistic observation experiment to investigate the changes in the operation status of each CB line before and after the travel restriction. Using the operation status at each month as the binary alternatives, the mixed logit models and the tree-based models with explainable machine learning techniques are respectively adopted to explore the factors that influence the decision-making process. The findings from both types of models are in general consistent. The results show that the characteristics of each CB line including the ridership, the length of the line, the closeness to charging stations, and the overlap of CB lines significantly impact the decisions. In addition, the land-use types around the CB stops and the market competition from alternative travel modes also play a key role in making the decisions.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 106-121"},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001077/pdfft?md5=adbd19c4ef845e1dfafd0157b461da80&pid=1-s2.0-S2046043023001077-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139020932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating e-grocery shopping behavior and its travel effect","authors":"Ibukun Titiloye ,&nbsp;Md Al Adib Sarker ,&nbsp;Xia Jin ,&nbsp;Brian Watts","doi":"10.1016/j.ijtst.2023.12.001","DOIUrl":"10.1016/j.ijtst.2023.12.001","url":null,"abstract":"<div><p>Since the adoption rate of e-grocery skyrocketed in the wake of the Covid-19 pandemic due to the influx of first-time e-grocery shoppers, grocery shopping behavior has been evolving and the travel effects of e-grocery are largely unknown. Thus, this study sought to examine the relationship between consumers’ grocery shopping behavior online and in-store, and the influencing factors (i.e., socio-demographic characteristics, household attributes, and personal attitudes). To achieve this, information relating to online and in-store grocery purchase frequencies, personal and household characteristics, and attitudes of more than 2,000 Florida residents were collected through an online survey. Using a bi-directional structural equation modeling (SEM) approach, our results show that online grocery shopping exhibited no significant effect on in-store grocery shopping frequency (i.e., neutrality), but in-store grocery shopping reduced the frequency of online grocery shopping (i.e., substitution). Also, a positive attitude toward some positive aspects of online shopping, preference for alternative travel modes, and tech savviness were associated with more frequent online grocery shopping, while cost consciousness and the joy of shopping encouraged more in-store shopping. Several socio-demographic and household attributes were also found to have direct and indirect effects mediated via attitudes on the shopping frequencies. Overall, this study provides insights into the demand and travel effects of e-grocery and highlights the need for retailers and transport planners to collaborate in order to mitigate the potential travel effects of e-grocery.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 91-105"},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001065/pdfft?md5=ec6fe6f935d14f76f40cfa6dc83e1199&pid=1-s2.0-S2046043023001065-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138616413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of connected and automated vehicles on the travel time reliability of an urban network","authors":"Shehani Samaranayake ,&nbsp;Sai Chand ,&nbsp;Amolika Sinha ,&nbsp;Vinayak Dixit","doi":"10.1016/j.ijtst.2023.11.008","DOIUrl":"10.1016/j.ijtst.2023.11.008","url":null,"abstract":"<div><p>Connected and automated vehicles (CAVs) have the potential to revolutionise the transportation industry, with a plethora of research already revealing considerable gains in safety, travel time and mobility, as well as reduced congestion and pollution. As the number of CAVs on the road grows, rigorous testing for various market penetration rates (MPRs) of CAVS is essential to determine under what conditions the benefits can be realised. For the studies investigating the impact of CAVs on travel time reliability specifically, the MPRs in which the network most thrives have been inconsistent. The majority of the research is concerned with highway networks with only a few travel time reliability studies that focus on urban networks. In this simulation study, the impact of varying MPRs of CAVs on travel time reliability is evaluated in an urban network for different traffic demands. Travel time reliability metrics are assessed, including the standard deviation, buffer time index and misery index. The study demonstrated that from 0% to 100% MPR, the overall weighted average travel time decreased by 28%, and the standard deviation of the weighted average travel time declined by 35%, highlighting the significant increase in travel time reliability. Travel time improvements were visible from the MPR of 10%; however, the reliability metrics highlighted the greatest benefits occurred at higher MPRs. This study presents valuable results about the reliability that CAVs can bring to urban networks during the fleet transition to CAVs.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"13 ","pages":"Pages 171-185"},"PeriodicalIF":0.0,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023001053/pdfft?md5=c667e1af217c06e45acdce863a0db84d&pid=1-s2.0-S2046043023001053-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138617912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}