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  • Mobility and traffic research  (4)
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  • Mobility and traffic research  (4)
  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2015
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2488, No. 1 ( 2015-01), p. 10-19
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2488, No. 1 ( 2015-01), p. 10-19
    Abstract: Transit signal priority (TSP) is a vital aspect of the improvement of transit service. However, the effect of bus dwell time on TSP is often neglected, and few researchers have proposed a TSP strategy that predicts the bus dwell time and then implements bus priority. This study focused on the prediction of bus dwell time, which defined the bus arrival time at the intersection, and subsequently established a multiobjective TSP strategy that uses that prediction. The data extracted from the Changzhou, China, bus rapid transit (BRT) Line 2 were used to propose a hybrid model based on the autoregressive integrated moving average and the support vector machine to predict the dwell time. Next, the multiobjective TSP, with the real-time average passenger delay, the maximum queue length, and the exhaust emissions as its optimization objectives, was solved through the use of the fuzzy compromise approach. Finally, the strategy was evaluated with the microscopic simulation software VISSIM. The findings demonstrated that the prediction model produced satisfactory results, and the simulation results suggested that the proposed strategy could significantly reduce the intersection delay, the stop rate, and the exhaust emissions of BRT. Moreover, higher traffic flows corresponded to better benefits being achieved through this strategy. In addition, the delay, the queue length, and the exhaust emissions of general vehicle traffic would be effectively controlled. The findings of this study could be helpful to traffic managers in the development of appropriate signal timing strategies and the enhancement of operating efficiency and environmental quality at intersections.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2403378-9
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  • 2
    Online Resource
    Online Resource
    SAGE Publications ; 2019
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2673, No. 9 ( 2019-09), p. 277-286
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2673, No. 9 ( 2019-09), p. 277-286
    Abstract: At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2403378-9
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  • 3
    Online Resource
    Online Resource
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications
    Abstract: To reveal the complex impact of the road grade on heavy-duty diesel truck (HDDT) emissions, the dynamic coupling relationships among the road grade, vehicle operation, and emissions were quantified based on portable emission measurement system data from 24 HDDTs in Chongqing, China. The results showed that the average emission factors of nitrogen oxides (NO x ) and carbon dioxide (CO 2 ) of China IV HDDTs were the highest among all tested HDDTs, and NO x emissions often exceeded their corresponding standard limit values. Next, the coupling relationships of road grade, speed, and emissions were studied. Graded roads caused a 4%–44% decrease in the average vehicle speed, resulting in a coupling effect on emissions. For all pollutants and vehicle emission standards, the HDDT emissions on uphill roads were much higher, while those on downhill roads did not deteriorate significantly owing to the increased acceleration operation. Overall, ignoring the road grade led to estimation errors of between −99.14% and 291.30% for CO 2 and between −99.21% and 247.73% for NO x . Speed was less correlated with emissions on downhill roads (≤−3%). For uphill roads ( 〉 0%), the joint effect of road grade and speed caused a significant increase in CO 2 and NO x emissions up to 21.26 and 17.29 times compared to idling emissions. A Sigmoid function successfully modeled the coupling relationship (average R 2  = 0.95), and grouped S-shaped mapping curves were revealed for between −8% and 7% road grade and emissions. The model can estimate the influence of road grades on emissions at different speeds, thus providing support for emission reduction control.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2403378-9
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  • 4
    Online Resource
    Online Resource
    SAGE Publications ; 2019
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2673, No. 3 ( 2019-03), p. 51-64
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2673, No. 3 ( 2019-03), p. 51-64
    Abstract: The signaling data of cellular phones, as a passively generated, real-time, wide-coverage, and low-cost data source, have been widely used in recent studies to understand human activity and model urban travel demand. However, in contrast with the Global Positioning System (GPS) data, cellular phone signaling data are sparsely distributed in time and space, which makes travel-mode inference a challenge. Recent studies presented methods of deriving users’ home and work locations, origin-destination trips, and other activities. Very few provided a complete and feasible framework for travel-mode derivation with effective validation methods. This paper provides a real-time travel-mode derivation framework using signaling data and a web-based mapping service. A trip-chain model is proposed to detect individual activity patterns and derive the trips of mobile phone users. Then, the travel mode of each trip is identified by a Fuzzy K-Means model, which is trained and validated by the point-to-point travel time from a web-based mapping service. Finally, the travel-mode shares are aggregated and scaled to the whole population of the study area. The framework is demonstrated using cellular signaling data from 1.9 million users in Shanghai, China for seven days, and citywide point-to-point travel times from a web-based mapping service for three of those seven days. Comparing the modeled travel-mode shares with travel survey data and transportation hub statistics demonstrates the plausibility and efficiency of using a large data source (mobile-trace data and web-based mapping) to accurately assess the travel modes of people in a big city using the proposed framework.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2403378-9
    Location Call Number Limitation Availability
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