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Tawhidur Rahman
Department of Civil and Environmental Engineering, West Virginia University, Morgantown, WV

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Research article
Published: 12 July 2021 in Transportation Research Record: Journal of the Transportation Research Board
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Autonomous vehicles (AVs) can dramatically reduce the number of traffic crashes and associated fatalities by eliminating the avoidable human-error-related crash contributing factors. Many companies have been conducting pilot tests on public roads in several states in the U.S. and other countries to accelerate AV mass deployment. AV pilot operations on Californian public roads saw 251 AV-involved crashes (as of February 2020). These AV-involved crashes provide a unique opportunity to investigate AV crash risks in the mixed traffic environment. This study collected the AV crash reports from the California Department of Motor Vehicles and applied the decision tree and association rule methods to extract the pre-crash rules of AV-involved crashes. Extracted rules revealed that the most frequent types of AV crashes were rear-end crashes and predominantly occurred at intersections when AVs were stopped and engaged in the autonomous mode. AV and non-AV manufacturers and transportation agencies can use the findings of this study to minimize AV-related crashes. AV companies could install a distinct signal/display to inform the operational mode of the AVs (i.e., autonomous or non-autonomous) to human drivers around them. Moreover, the automatic emergency braking system in non-AVs could avoid a significant number of rear-end crashes as, often, rear-end crashes occurred as a result of the failure of following non-AVs to slow down in time behind AVs. Transportation agencies can consider separating AVs from non-AVs by assigning “AV Only” lanes to eliminate the excessive rear-end crashes resulting from the mistakes of human drivers in non-AVs at intersections.

ACS Style

Tanvir Ashraf; Kakan Dey; Sabyasachee Mishra; Tawhidur Rahman. Extracting Rules from Autonomous-Vehicle-Involved Crashes by Applying Decision Tree and Association Rule Methods. Transportation Research Record: Journal of the Transportation Research Board 2021, 1 .

AMA Style

Tanvir Ashraf, Kakan Dey, Sabyasachee Mishra, Tawhidur Rahman. Extracting Rules from Autonomous-Vehicle-Involved Crashes by Applying Decision Tree and Association Rule Methods. Transportation Research Record: Journal of the Transportation Research Board. 2021; ():1.

Chicago/Turabian Style

Tanvir Ashraf; Kakan Dey; Sabyasachee Mishra; Tawhidur Rahman. 2021. "Extracting Rules from Autonomous-Vehicle-Involved Crashes by Applying Decision Tree and Association Rule Methods." Transportation Research Record: Journal of the Transportation Research Board , no. : 1.

Original research paper
Published: 31 March 2021 in IET Intelligent Transport Systems
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Matching riders and drivers in ridesharing considering conflicting objectives of diverse stakeholders is challenging. The objective of this research is to formulate and evaluate the performance of four ridesharing matching‐objectives (i.e. system‐wide minimisation of passengers’ wait time, minimisation of VMT, minimisation of detour distance, maximisation of drivers’ profit) considering interests of diverse mobility stakeholders (i.e. drivers, riders, matching agencies, government transportation agencies). A grid roadway network was used to compare the performance of the four matching‐objectives in serving a ridesharing demand scenario. Performance comparison of matching‐objectives revealed that a system‐wide VMT minimisation matching‐objective performed best with least sacrifices on the other three matching‐objectives from their respective best performance level. Also, system‐wide VMT minimisation was the best matching‐objective, when drivers’ and government transportation agencies’ expectations were prioritised. System‐wide drivers’ profit maximisation matching‐objective provided the highest monetary incentives for drivers and riders in terms of maximising profit and travel cost savings, respectively. System‐wide minimisation of detour distance was found to be least flexible in providing shared rides. The findings of this research provide useful insights on ridesharing matching system modelling and performance evaluation based on different matching‐objectives and can be used in developing and implementing ridesharing service considering multiple stakeholders’ concerns.

ACS Style

Tawhidur Rahman; Kakan Dey; David R. Martinelli; Sabya Mishra. Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective. IET Intelligent Transport Systems 2021, 15, 781 -794.

AMA Style

Tawhidur Rahman, Kakan Dey, David R. Martinelli, Sabya Mishra. Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective. IET Intelligent Transport Systems. 2021; 15 (6):781-794.

Chicago/Turabian Style

Tawhidur Rahman; Kakan Dey; David R. Martinelli; Sabya Mishra. 2021. "Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective." IET Intelligent Transport Systems 15, no. 6: 781-794.

Journal article
Published: 29 March 2021 in Transportation Research Part F: Traffic Psychology and Behaviour
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Public perception assessment is important for gaining a better understanding of the acceptance of autonomous vehicles (AVs) and identifying potential ways to resolve public concerns. This study investigated how pedestrians and bicyclists perceived AVs based on their knowledge and road sharing experiences, applying a combined inductive and deductive data analysis approach. Survey responses of pedestrians and bicyclists in Pittsburgh, Pennsylvania, USA collected by Bike Pittsburgh (BikePGH) in 2019, were analyzed in this research. AVs following traffic rules appropriately and AVs driving safer than the human drivers were the most notable positive perceptions towards AVs. Pedestrians and bicyclists showed comparatively fewer negative perceptions towards AVs than positive perceptions. Negative perceptions mostly included a lack of perceived safety and comfort around AVs and trust in the AV technology. Respondents also concerned about AV technology issues (e.g., slow and defensive driving, disruptive maneuver), while sharing the road with AVs. Perceptions of the respondents were significantly influenced by their views on AV safety, familiarity with the technology, the extent respondents followed AV on the news, and household automobile ownership. Regulating AV movement on roadways, developing safety assessment guidelines, and controlling oversights of improper practices by AV companies were the major suggestions from the survey participants. Findings of this study might help AV companies to identify potential improvement needed in AV technology to increase pedestrians and bicyclists acceptance, and policymakers to develop policy guidelines to ensure safe road sharing among pedestrians, bicyclists, and AVs.

ACS Style

Tawhidur Rahman; Kakan Dey; Subasish Das; Melissa Sherfinski. Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour 2021, 78, 433 -445.

AMA Style

Tawhidur Rahman, Kakan Dey, Subasish Das, Melissa Sherfinski. Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour. 2021; 78 ():433-445.

Chicago/Turabian Style

Tawhidur Rahman; Kakan Dey; Subasish Das; Melissa Sherfinski. 2021. "Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists." Transportation Research Part F: Traffic Psychology and Behaviour 78, no. : 433-445.

Journal article
Published: 22 June 2020 in Sustainability
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Accurate and real-time traffic and road weather information acquired using connected vehicle (CV) technologies can help commuters perform safe and reliable trips. A nationwide survey of transit operation managers/supervisors was conducted to assess the suitability for CV transit applications in improving the safety and mobility during winter weather. Almost all respondents expressed positive attitudes towards the potential of CV applications in improving winter transit travel and voiced their concerns over the safety consequences of CV equipment failure, potential of increased driver distraction, and reliability of system performance in poor weather. A concept of operations of CV applications for multimodal winter travel was developed. In the conceptual framework, route-specific road weather and traffic flow data will be used by the transit managers/supervisors to obtain real-time operational status, forecast operational routes and schedules, and assess operational performance. Subsequently, multimodal commuters can receive the road-weather and traffic-flow information as well as transit routes and schedule information.

ACS Style

Yaqin He; Tawhidur Rahman; Michelle Akin; Yinhai Wang; Kakan Dey; Xianming Shi. Connected Vehicle Technology for Improved Multimodal Winter Travel: Agency Perspective and a Conceptual Exploration. Sustainability 2020, 12, 5071 .

AMA Style

Yaqin He, Tawhidur Rahman, Michelle Akin, Yinhai Wang, Kakan Dey, Xianming Shi. Connected Vehicle Technology for Improved Multimodal Winter Travel: Agency Perspective and a Conceptual Exploration. Sustainability. 2020; 12 (12):5071.

Chicago/Turabian Style

Yaqin He; Tawhidur Rahman; Michelle Akin; Yinhai Wang; Kakan Dey; Xianming Shi. 2020. "Connected Vehicle Technology for Improved Multimodal Winter Travel: Agency Perspective and a Conceptual Exploration." Sustainability 12, no. 12: 5071.