The emergence of connected and automated vehicle (CAV) technology has the potential to bring a number of benefits to our existing transportation systems. Specifically, when CAVs travel along an ...arterial corridor with signalized intersections, they can not only be driven automatically using pre-designed control models but can also communicate with other CAVs and the roadside infrastructure. In this paper, we describe a cooperative eco-driving (CED) system targeted for signalized corridors, focusing on how the penetration rate of CAVs affects the energy efficiency of the traffic network. In particular, we propose a role transition protocol for CAVs to switch between a leader and following vehicles in a string. Longitudinal control models are developed for conventional vehicles in the network and for different CAVs based on their roles and distances to intersections. A microscopic traffic simulation evaluation has been conducted using PTV VISSIM with realistic traffic data collected for the City of Riverside, CA, USA. The effects on traffic mobility are evaluated, and the environmental benefits are analyzed by the U.S. Environmental Protection Agency's MOtor Vehicle Emission Simulator (MOVES) model. The simulation results indicate that the energy consumption and pollutant emissions of the proposed system decrease, as the penetration rate of CAVs increases. Specifically, more than 7% reduction on energy consumption and up to 59% reduction on pollutant emission can be achieved when all vehicles in the proposed system are CAVs.
•NKE is defined and used as a variable for capturing the regenerative braking effect in EV energy consumption estimation.•A systematic data-driven EV energy consumption decomposition analysis is ...conducted.•A novel link-level EV energy consumption estimation model is built upon the decomposition analysis.•A “W”-shaped relationship between link-level EV energy consumption rate and average speed is discovered and explained.
Electric vehicles (EVs) have great potential to reduce transportation-related fossil fuel consumption as well as pollutant and greenhouse gas (GHG) emissions, due to their use of renewable electricity as the sole energy source. Therefore, the wide-spread deployment of EVs is regarded asan attractive means to mitigate the environmental problems (e.g., air pollution and climate change) resulting from transportation activities. Government agencies are trying to promote EV deployment by allocating considerable funding as well as promulgating supportive policies. However, the mass adoption of EVs is still impeded by the limited charging infrastructure and all-electric-range (AER). All these lead to a critical research topic: the EV energy consumption analysis and estimation under real-world traffic conditions, which is fundamental to various types of EV-centred applications that aim at improving the EV energy efficiency and extending the AER. For example, eco-routing systems for EVs rely on accurate link-level energy consumption estimation to calculate the EV energy consumption costs of the different route options. In this work, to obtain an accurate link-level energy consumption estimation model for EVs, the energy consumption under real-world traffic congestion is decomposed based on two proposed impact factors: positive kinetic energy (PKE) and negative kinetic energy (NKE). Upon this decomposition, a data-driven model is built to estimate EV energy consumption on each roadway link considering real-world traffic conditions. Finally, the model performance is evaluated by comparing with the performance of baseline model adapted from existing models. The results show that the proposed EV link-level energy consumption estimation model outperforms the existing models in terms of accuracy, implying that it is quite promising in various on-board EV applications.
The connected vehicle eco-approach and departure (EAD) application for signalized intersections has been widely studied and is deemed to be effective in terms of reducing energy consumption and both ...greenhouse gas and other criteria pollutant emissions. Prior studies have shown that tangible environmental benefits can be gained by communicating the driver with the signal phase and timing (SPaT) information of the upcoming traffic signals with fixed time control to the driver. However, similar applications to actuated signals pose a significant challenge due to their randomness to some extent caused by vehicle actuation. Based on the framework previously developed by the authors, a real-world testing has been conducted along the El Camino Real corridor in Palo Alto, CA, USA, to evaluate the system performance in terms of energy savings and emissions reduction. Strategies and algorithms are designed to be adaptive to the dynamic uncertainty for actuated signal and real-world traffic. It turns out that the proposed EAD system can save 6% energy for the trip segments when activated within DSRC ranges and 2% energy for all trips. The proposed system can also reduce 7% of CO, 18% of HC, and 13% of NOx for all trips. Those results are compatible with the simulation results and validate the previously developed EAD framework.
Using connected vehicle technology, a number of eco-approach and departure (EAD) strategies have been designed to guide vehicles through signalized intersections in an eco-friendly way. Most of the ...existing EAD applications have been developed and tested in traffic-free scenarios or in a fully connected environment, where the presence and behavior of all surrounding vehicles are detectable. In this paper, we describe a prediction-based EAD strategy that can be applied toward more realistic scenarios, where the surrounding vehicles can be either a connected or non-connected. Unlike highway scenarios, predicting speed trajectories along signalized corridors is much more challenging due to disturbances from signals, traffic queues, and pedestrians. Based on vehicle activity data available via inter-vehicle communication or onboard sensing (e.g., by radar), we evaluate three state-of-the-art nonlinear regression models to perform short-term speed forecasting of the preceding vehicle. It turns out radial basis function neural network outperformed both Gaussian process and multi-layer perceptron network in terms of prediction accuracy and computational efficiency. Using signal phase and timing information and the predicted state of the preceding vehicle, our prediction-based EAD algorithm achieved better fuel economy and emissions reduction in urban traffic and queues at intersections. Results from the numerical simulation using the next generation simulation data set show that the proposed prediction-based EAD system achieve 4.0% energy savings and 4.0% - 41.7% pollutant emission reduction compared with a conventional car following strategy. Prediction-based EAD saves 1.9% energy and reduces criteria pollutant emissions by 1.9% - 33.4% compared with an existing EAD algorithm without prediction in urban traffic.
Due to increased public awareness on global climate change and other energy and environmental problems, a variety of strategies are being developed and used to reduce the energy consumption and ...environmental impact of roadway travel. In advanced traveler information systems, recent efforts have been made in developing a new navigation concept called "eco-routing," which finds a route that requires the least amount of fuel and/or produces the least amount of emissions. This paper presents an eco-routing navigation system that determines the most eco-friendly route between a trip origin and a destination. It consists of the following four components: 1) a Dynamic Roadway Network database, which is a digital map of a roadway network that integrates historical and real-time traffic information from multiple data sources through an embedded data fusion algorithm; 2) an energy/emissions operational parameter set, which is a compilation of energy/emission factors for a variety of vehicle types under various roadway characteristics and traffic conditions; 3) a routing engine, which contains shortest path algorithms used for optimal route calculation; and 4) user interfaces that receive origin-destination inputs from users and display route maps to the users. Each of the system components and the system architecture are described. Example results are also presented to prove the validity of the eco-routing concept and to demonstrate the operability of the developed eco-routing navigation system. In addition, current limitations of the system and areas for future improvements are discussed.
Plug-in hybrid electric vehicles (PHEVs) have been regarded as one of several promising countermeasures to transportation-related energy use and air quality issues. Compared with conventional hybrid ...electric vehicles, developing an energy management system (EMS) for PHEVs is more challenging due to their more complex powertrain. In this paper, we propose a generic framework of online EMS for PHEVs that is based on an evolutionary algorithm. It includes several control strategies for managing battery state-of-charge (SOC). Extensive simulation testing and evaluation using real-world traffic data indicates that the different SOC control strategies of the proposed online EMS all outperform the conventional control strategy. Out of all the SOC control strategies, the self-adaptive one is the most adaptive to real-time traffic conditions and the most robust to the uncertainties in recharging opportunity. A comparison to the existing models also employing short-term prediction shows that the proposed model can achieve the best fuel economy improvement but requiring less trip information.
Abstract Background and Aims The optimal type of stent for the palliation of malignant biliary obstruction in patients with pancreatic adenocarcinoma undergoing neoadjuvant chemoradiotherapy with ...curative intent is not known. We performed a prospective trial comparing 3 types of biliary stents—fully covered self-expandable metal stents (fcSEMSs), uncovered self-expandable metal stents (uSEMSs), and plastic stents—to determine which best optimized cost effectiveness and important clinical outcomes. Methods In this prospective, randomized trial, consecutive patients with malignant biliary obstruction from newly diagnosed pancreatic adenocarcinoma who were to start neoadjuvant chemoradiotherapy were randomized to receive fcSEMSs, uSEMSs, or plastic stents during index ERCP. The primary outcomes were time to stent occlusion, attempted surgical resection, or death after the initiation of neoadjuvant therapy and the secondary outcomes were total patient costs associated with the stent, including the index ERCP cost, downstream hospitalization cost due to stent occlusion, and the cost associated with procedural adverse event. Results A total of 54 patients were randomized and reached the primary endpoint; 16 patients in the fcSEMS group, 17 in the uSEMS group, and 21 in the plastic group. No baseline demographic or tumor characteristic differences were noted between groups. fcSEMSs had a longer time to stent occlusion compared with uSEMSs and plastic stents (219 vs. 88 and 75 days, p<0.01), although the groups had equivalent rates of stent occlusion, attempted surgical resection, and death. Although SEMS placement cost more during index ERCP (uSEMS = $24,874 and fcSEMS = $22,729 vs plastic = $18,701, p <0.01), they resulted in higher procedural adverse event costs per patient (uSEMS $5521 and fcSEMS=$12,701 vs plastic = $0, p<0.01). Conversely, plastic stents resulted in a $11,458 hospitalization cost per patient due to stent occlusion, compared with $2301 for uSEMSs and $0 for fcSEMSs (p<0.01). The total cost of the index ERCP, procedural adverse events associated with the index ERCP and adverse events from stent occlusion were similar between stent types (fcSEMSs = $41,112; uSEMSs = $41,475; and plastic = $39,955; p=1.00). There was no difference between groups in terms of number of days hospitalized for index ERCP adverse event and/or stent occlusion, although fcSEMSs resulted in fewer total days (3) of neoadjuvant treatment delay than uSEMSs (39) or plastic stents (79) (p<0.01). Conclusions In a prospective trial comparing fcSEMSs, uSEMSs, and plastic stents for malignant biliary obstruction in patients undergoing neoadjuvant therapy with curative intent for pancreatic adenocarcinoma, no stent type was superior in optimizing cost effectiveness, although fcSEMS resulted in fewer days of neoadjuvant treatment delay and a longer time to stent occlusion. (ClincialTrials.gov, number NCT01038713)
Automatic longitudinal control of vehicles is an automobile technology that has been implemented for many years. Connected eco-driving has the potential to extend the capability of an automatic ...longitudinal control by minimizing the energy consumption and emissions of the vehicle. In this paper, we propose a power-based longitudinal control algorithm for a connected eco-driving system, which takes into account the vehicle's brake specific fuel consumption or BSFC map, roadway grade, and other constraints (e.g., traffic condition ahead and traffic signal status of the upcoming intersection) in the calculation of an optimal speed profile in terms of energy savings and emissions reduction. The performance of the proposed algorithm was evaluated through extensive numerical analyses of driving along a signalized arterial, and the results validated the effectiveness of the proposed algorithm as compared with baseline and an existing eco-driving algorithm.
California has set a goal for all drayage trucks operating in the state to be zero-emitting by 2035. In order to achieve this goal, drayage operators would need to transition 100% of their fleets to ...zero-emission vehicles such as battery electric trucks (BETs). This article presents an intelligently controlled charging model for BETs that minimizes charging costs while optimizing subsequent tour completion. To develop this model, real-world activity data from a drayage truck fleet operating in Southern California was combined with a two-stage clustering technique to identify trip and tour patterns. The energy consumption for each trip and tour was then simulated for BETs with a battery capacity of 565 kWh using a 150 kW charging power level. Home base charging load profiles were generated using the proposed charging model, subject to constraints of the energy needed to complete the next subsequent tour and Time-of-Use energy cost rates. A sensitivity analysis evaluated three scenarios: a passive scenario with a 5% state-of-charge (SOC) constraint after completing the subsequent tour, an average scenario with a 50% SOC constraint, and an aggressive scenario with an 80% SOC constraint. Results indicated that the 80% SOC constraint scenario achieved the lowest charging cost. However, it also yielded the lowest tour completion rate (51%). In contrast, the 5% SOC constraint scenario registered the highest tour completion rate. These results revealed that 96% of the tours could be successfully completed using the intelligently controlled charging model. The remaining tours were infeasible, indicating that the available time at the home base was inadequate for charging the necessary energy for the next tour. In terms of total costs, the scenario with a 5% SOC constraint resulted in an annual cost of approximately 40,000, whereas the 80% SOC scenario nearly doubled that amount.
Summary
Treatment with dose‐adjusted EPOCH (etoposide, doxorubicin, cyclophosphamide, vincristine, prednisone) chemotherapy and rituximab (DA‐EPOCH‐R) has become the standard of care for primary ...mediastinal B‐cell lymphoma (PMBCL) at many institutions despite limited data in the multi‐centre setting. We report a large, multi‐centre retrospective analysis of children and adults with PMBCL treated with DA‐EPOCH‐R to characterize outcomes and evaluate prognostic factors. We assessed 156 patients with PMBCL treated with DA‐EPOCH‐R across 24 academic centres, including 38 children and 118 adults. All patients received at least one cycle of DA‐EPOCH‐R. Radiation therapy was administered in 14·9% of patients. With median follow‐up of 22·6 months, the estimated 3‐year event‐free survival (EFS) was 85·9% 95% confidence interval (CI) 80·3–91·5 and overall survival was 95·4% (95% CI 91·8–99·0). Outcomes were not statistically different between paediatric and adult patients. Thrombotic complications were reported in 28·2% of patients and were more common in paediatric patients (45·9% vs. 22·9%, P = 0·011). Seventy‐five per cent of patients had a negative fluorodeoxyglucose positron emission tomography (FDG‐PET) scan at the completion of DA‐EPOCH‐R, defined as Deauville score 1–3. Negative FDG‐PET at end‐of‐therapy was associated with improved EFS (95·4% vs. 54·9%, P < 0·001). Our data support the use of DA‐EPOCH‐R for the treatment of PMBCL in children and adults. Patients with a positive end‐of‐therapy FDG‐PET scan have an inferior outcome.
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