1,720,994 research outputs found
Impact of large-scale activities on macroscopic fundamental diagram: Field data analysis and modeling
Large-scale activities always have serious impacts on regional traffic states. It is necessary for traffic planners to investigate the characteristics of network traffic flow under large-scale activities and apply proper management strategies. In this paper, based on the field data in Tianjin, China, the impact of large-scale activities and the corresponding control strategies on regional Macroscopic Fundamental Diagram (MFD) and regional traffic states are analyzed. The study area is divided into the inner area and the outer area. Based on the work of Haddad (2012) on the traffic perimeter control in two-region, a dynamic model is calibrated by the empirical data in Tianjin to study the influences of activities and control strategies. Based on the calibrated model, different control strategies are simulated to investigate the impacts on regional traffic flow. The results show that decreasing the transfer flow from the outer area will alleviate the congestion in the inner area effectively, and increasing the system outflow will reduce the densities of both two areas effectively. When the traffic states are already congested, the real control strategies cannot alleviate the congestion of the regional network effectively. According to the various impacts of different strategies, combined control strategies are proposed to mitigate the adverse impact of large-scale activities on the surrounding area.This work was partially supported by the National Natural Science Foundation of China (Grant No. 71771012, No. 71961137008, No. 72171018, and No. 71931002). The author would like to thank the anonymous reviewers for their valuable comments on the paper
Estimating freeway travel time and its reliability using radar sensor data
Travel time and its reliability are intuitive system performance measures for freeway traffic operations. This paper proposes a method to estimate travel times based on data collected from roadside radar sensors, considering spatially correlated traffic conditions. Link-level and corridor-level travel time distributions are estimated using these travel time estimates and compared with the ones estimated based on probe vehicle data. The maximum likelihood estimation is used to estimate the parameters of Weibull, gamma, normal, and lognormal distributions. According to the log-likelihood values, lognormal distribution is the best fit among all the tested distributions. Corridor-level travel time reliability measures are extracted from the travel time distributions. The proposed travel time estimation model can well capture the temporal pattern of travel time and its distribution.This is an Accepted Manuscript of an article published by Taylor & Francis as Lu, Chaoru, and Jing Dong. "Estimating freeway travel time and its reliability using radar sensor data." Transportmetrica B: Transport Dynamics 6, no. 2 (2018): 97-114. DOI: 10.1080/21680566.2017.1325785. Posted with permission.</p
Energy-Efficient Adaptive Cruise Control for Electric Connected and Autonomous Vehicles
This paper presented an energy-efficient adaptive cruise control, called Energy-Efficient Electric Driving Model (E3DM), for electric, connected, and autonomous vehicles (e-CAVs) in a mixed traffic stream. E3DM is able to maintain high energy efficiency of regenerative braking by adjusting the spacing between the leading and the following vehicles. Moreover, a power-based energy consumption model is proposed to estimate the on-road energy consumption for battery electric vehicles, considering the impact of ambient temperature on auxiliary load. Using the proposed energy consumption model, the impact of E3DM on vehicle energy consumption is investigated. In particular, single-lane vehicle dynamics in a traffic stream with a mixed of e-CAVs and human-driven vehicles are simulated. The result shows that E3DM outperforms existing adaptive cruise control (i.e. Nissan-ACC) and cooperative adaptive cruise control (i.e. Enhanced-IDM and Van Arem Model) strategies in terms of energy consumption. Moreover, higher market penetration of e-CAVs may not result in better energy efficiency of the entire fleet. The reason is that more e-CAVs in the traffic stream results in faster string stabilization which decreases the regenerative energy. Considering mix traffic streams with battery electric (BEVs) and internal-combustion engine (ICEVs) vehicles, the energy consumption of entire fleet reduces when the market penetration of BEV (contains both e-CAV and human-driven BEV) increases. A higher ratio of e-CAV to human-driven BEV results in higher energy efficiency.This is a manuscript of an article published as Lu, Chaoru, Jing Dong, and Liang Hu. "Energy-efficient adaptive cruise control for electric connected and autonomous vehicles." IEEE Intelligent Transportation Systems Magazine 11, no. 3 (2019): 42-55. DOI: 10.1109/MITS.2019.2919556. Posted with permission.</p
An Ecological Adaptive Cruise Control for Mixed Traffic and Its Stabilization Effect
With the rapid development of technologies, the ecological control strategies of connected and autonomous vehicle (CAV) technologies are gaining more and more attention. In this paper, a rule-based ecological cruise control, called the ecological smart driver model (EcoSDM), is proposed to improve the fuel efficiency of an individual vehicle and the traffic flow. By adjusting the spacing between the leading and the following vehicles, EcoSDM provides smoother deceleration and acceleration than the enhanced intelligent driver model (Enhanced-IDM) and the smart driver model (SDM). The linear stability of EcoSDM is analyzed both theoretically and numerically. The numerical results validate the results of theoretical analysis. Moreover, the simulations results show that EcoSDM outperforms the Enhanced-IDM and SDM in terms of stabilization effect on homogeneous traffic flow. In addition, the calibrated VT-Micro model is used to estimate the fuel consumption of CAVs and manually driven vehicles. The result shows that CAVs have better fuel economy than the human-driven vehicles, which is consistent with existing studies. The EcoSDM outperforms Enhanced-IDM and SDM in terms of fuel consumption. For the EcoSDM-equipped CAVs, the fuel saving benefit is greatest when a CAV is at the front of the platoon.This article is published as Lu, Chaoru, Jing Dong, Liang Hu, and Chenhui Liu. "An Ecological Adaptive Cruise Control for Mixed Traffic and Its Stabilization Effect." IEEE Access 7 (2019): 81246-81256. DOI: 10.1109/ACCESS.2019.2923741.</p
Incorporating the standstill distance and time headway distributions into freeway car-following models and an application to estimating freeway travel time reliability
Standstill distances and following time headways are two important microsimulation model parameters associated with driver aggression. This paper investigates the distributions of standstill distances and time headways and incorporates these distributions into car-following models to estimate travel time reliability. By incorporating standstill distance and following headway into car-following models as stochastic parameters, a speed-density region can be generated, based on which various travel-time-reliability measures can be calculated. Key findings of this study are as follows: (1) Both standstill distances and time headways follow fairly dispersed distributions. Therefore, it is suggested that microsimulation models should include the option of allowing standstill distances and time headways to follow distributions as well as to be specified separately for different vehicle classes. (2) By incorporating stochastic standstill distance and time headway parameters in car-following models, travel-time-reliability measures can be estimated more precisely and faster compared with using VISSIM.This article is published as Lu, Chaoru, Jing Dong, Andrew Houchin, and Chenhui Liu. "Incorporating the standstill distance and time headway distributions into freeway car-following models and an application to estimating freeway travel time reliability." Journal of Intelligent Transportation Systems 25, no. 1 (2021): 21-40. DOI: 10.1080/15472450.2019.1683450.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Estimate freeway travel time reliability under recurring and nonrecurring congestion
Travel time and its reliability are considered as intuitive measure of service quality by transportation agencies. Moreover, highly reliable travel times allow for arriving at work or other destinations on time in the context of personal travel and facilitate just-in-time logistics services in freight operations. Travel times are the result of the traffic congestion. By considering different impact factors and shortcoming of the sensing technologies, this dissertation proposed methods for travel time and its reliability estimation.
First of all, this dissertation presented a method to estimate corridor-level travel times based on data collected from roadside radar sensors, considering spatially correlated traffic conditions. Link-level and corridor-level travel time distributions are estimated using these travel time estimates and compared with the ones estimated based on probe vehicle data. The maximum likelihood estimation is used to estimate the parameters of Weibull, gamma, normal, and lognormal distributions. According to the log likelihood values, lognormal distribution is the best fit among all the tested distributions. Corridor-level travel time reliability measures are extracted from the travel time distributions. The proposed travel time estimation model can well capture the temporal pattern of travel time and its distribution.
Second, a travel time reliability measure estimation method is proposed by incorporating standstill distance and time headway distributions in car-following models. The method is based on simplified two-component travel time distribution. By using Monte Carlo simulation, the speed-density region under congested condition and the travel time reliability measures can be generated. The results shows that the speed-density region derived from the steady-state Pipes model encloses most of the field data. Moreover, the proposed method estimate travel time reliability measures more precisely and faster, compared with using VISSIM simulation.
Finally, a work zone travel time estimation approach is proposed in this dissertation. First, the impact of work zone on capacity is investigated. For the work zone capacity prediction framework, the predicted upper bound of capacity is close to the maximum 15-min flow rate. Moreover, based on the predicted capacity, density at capacity and free flow speed, work zone travel times are estimated by using the modified segment speed estimation model from the study of Newman. The estimated travel times roughly followed the pattern of the INRIX travel times. Moreover, the travel time reliability indices are estimated directly from the estimated travel times. The result shows that the travel time reliability indices based on estimated travel times are close to the indices based on INRIX travel times.</p
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