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Pedestrian behavior prediction is essential to enable safe and efficient driving of intelligent vehicles on urban traffic environment. This article presents a novel framework for pedestrian trajectory prediction, which integrates Dynamic Bayesian network and Sequence-to-Sequence model through an adaptive online weighting method. Dynamic Bayesian network utilizes environmental features and kinematic information to infer the pedestrian's motion intentions through probabilistic reasoning. Sequence-to-Sequence model views trajectory predictions as sequence generation tasks, in which the future trajectories are generated relying on the observed trajectories. A real-world pedestrian motion dataset is employed for model validations and it is also enlarged through data augmentation techniques to enable training of data-driven approaches. We compare our model with several typical baselines methods and results show that our model outperforms those baselines. The average error and the final destination error with one-second prediction are 0.04m and 0.10m in crossing scenarios, and 0.06m and 0.17m in stopping scenarios, respectively. The study expects to provide guidelines for the decision-making of intelligent vehicles in order to protect vulnerable road users.

Cooperative adaptive cruise control (CACC) vehicle string operations have the potential to improve significantly the mobility and energy consumption performance of congested freeway corridors. This study examines the impact of CACC string operations on vehicle speed and fuel economy on the 13-mi SR-99 corridor, near Sacramento, CA. It extends the existing body of knowledge by performing a multi-scenario simulation analysis of the freeway corridor. A simulation study evaluated the performance of the corridor under various CACC market penetration scenarios and traffic demand inputs. The CACC string operation was also analyzed when vehicle awareness device (VAD) and CACC managed lane (ML) strategies were implemented. The case study revealed that the average vehicle speed increased by 70% when the CACC market penetration increased from 0% to 100%. The highest average fuel economy, expressed in miles per gallon (mpg), was achieved under the 50% CACC scenario where mpg was 27. This was 10% higher than the baseline scenario. However, when the CACC market penetration was 50% or higher, the vehicle fuel efficiency only had minor increases. When CACC market penetration reached 100%, the corridor allowed 30% more traffic to enter the network without experiencing reduced average speed. Results also indicate that the VAD strategy increased the speed by 8% when the CACC market penetration was 20% or 40%, while there was a minor decrease in mpg. The ML strategy decreased the corridor performance when implemented alone.

This paper presents quantitative driving performance results for a cooperative adaptive cruise control (CACC) system tested on Class-8 trucks. It focuses on the vehicle following control performance measured on a closed test track and in mixed traffic on public freeways. The speed and distance tracking errors are reported for the string of three trucks driven under CACC control.

Cooperative adaptive cruise control (CACC) is a driver-assist technology that uses vehicle-to-vehicle wireless communication to realize faster braking responses in following vehicles and shorter headways compared with adaptive cruise control. This technology not only enhances road safety, but also offers fuel savings benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore driving preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and throttle actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. “On-the-road” experiments were conducted by recruiting drivers from commercial fleets to operate the second and third trucks in a three-truck CACC string. The driving route spanned 160 miles on freeways in Northern California and five different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions were found to influence the drivers’ opinions about use of CACC. The findings presented in this paper provide insights into the factors that will influence driver reactions to the deployment of CACC in their truck fleets.

Cooperative adaptive cruise control (CACC) systems have the potential to improve traffic flow and fuel efficiency, but these effects are challenging to estimate. This paper reports the development of a micro-simulation model to represent these impacts for heavy trucks using CACC when they share a freeway with manually driven passenger cars. The simulation incorporates automated truck-following models that have been derived from experimental data recorded on heavy trucks driven under CACC, adaptive cruise control (ACC), and conventional cruise control (CC). The simulation includes other behavioral models for lane changing, lane change cooperation and lane use restrictions for trucks to better capture real-world traffic dynamics. The paper explains the calibration of the simulation method for a 15-mile urban freeway corridor with heavy truck traffic and significant congestion. Simulation results for different market penetration rates show that truck CACC improved traffic operations for trucks in terms of vehicle miles traveled, average speed, and flow rate. In addition, truck CACC did not adversely affect passenger car operations and in some locations it even produced considerable improvements in the general traffic conditions.

Currently, arterial traffic signals adjacent to freeway on-ramps operate independent of freeway on-ramp metering. During peak periods, the traffic signals employ long signal cycles to maximize intersection capacity. This approach often results in long platoons of freeway-bound traffic advancing toward the on-ramp within a short period, which quickly fills up the on-ramp and causes spillback on the surface streets. Queue override is typically employed to prevent the queue spillback by suspending ramp metering or relaxing the metering rates. Unfortunately, this counteracts the objective of on-ramp metering, which is to prevent capacity drop at freeway merge bottlenecks. Significant benefits can be realized by integrating arterial signal timing with the adjacent ramp-metering system. A signal control strategy was developed and evaluated in this study. The algorithm takes available on-ramp storage and the freeway ramp-metering rate into account and dynamically adjusts the cycle length to prevent on-ramp queue spillback and activation of queue override. The proposed algorithm was tested through simulation and the results show that the proposed strategy reduces the freeway, arterial, and system-wide delay at a modest penalty for on-ramp bound traffic.

Colony-stimulating factor 1 receptor (CSF1R) plays a critical role in promoting tumor progression in various types of tumors. Here, we identified D2923 as a novel and selective inhibitor of CSF1R and explored its antitumor activity both in vitro and in vivo. D2923 potently inhibited CSF1R in vitro kinase activity with an IC50value of 0.3 nM. It exhibited 10- to 300-fold less potency against a panel of kinases tested. D2923 markedly blocked CSF-1-induced activation of CSF1R and its downstream signaling transduction in THP-1 and RAW264.7 macrophages and thus inhibited the in vitro growth of macrophages. Moreover, D2923 dose-dependently attenuated the proliferation of a small panel of myeloid leukemia cells, mainly by arresting the cells at G1 phase as well as inducing apoptosis in the cells. The results of the in vivo experiments further demonstrated that D2923 displayed potent antitumor activity against M-NFS-60 xenografts, with tumor growth inhibition rates of 50% and 88% at doses of 40 and 80 mg/kg, respectively. Additionally, D2923 was well tolerated with no significant body-weight loss observed in the treatment groups compared with the control. Furthermore, a western blot analysis and the immunohistochemistry results confirmed that the phosphorylation of CSF1R in tumor tissue was dramatically reduced after D2923 treatment, and this was accompanied by the depletion of macrophages in the tumor. Meanwhile, the expression of the proliferation marker Ki67 was also markedly decreased in the D2923 treatment group compared with the control group. Taken together, we identified D2923 as a novel and effective CSF1R inhibitor, which deserves further investigation.

Cooperative adaptive cruise control (CACC) has been loosely defined in recent literature to represent a wide variety of vehicle-following control concepts, and when trucks are discussed, CACC is often used synonymously with platooning. This paper discusses the similarities and differences between CACC and platooning and provides a more precise functional description of CACC operations for trucks. CACC operations include not only the steady state cruising mode but also the maneuvers needed to join vehicles together and separate them when a vehicle needs to leave a CACC string or when the string is interrupted by a cut-in maneuver by a noncooperative vehicle. Activity diagrams are used to describe the CACC maneuvers; the diagrams specify the sequence of actions that need to be taken by each driver and each vehicle (and its CACC software) and the information that needs to be exchanged between them. These precise definitions can be used to specify the vehicle-to-vehicle messages that need to be exchanged between vehicles to implement CACC and the driver–vehicle interface displays and controls that are needed. The paper also addresses practical considerations in CACC operation, such as maximum lengths for strings of CACC trucks, strategies for sequencing the trucks in CACC strings, and higher-level strategies for clustering CACC-capable trucks; these strategies range from ad hoc to local and global coordination.

Cooperative adaptive cruise control (CACC) has been loosely defined in recent literature to represent a wide variety of vehicle-following control concepts, and when trucks are discussed, CACC is often used synonymously with platooning. This paper discusses the similarities and differences between CACC and platooning and provides a more precise functional description of CACC operations for trucks. CACC operations include not only the steady state cruising mode but also the maneuvers needed to join vehicles together and separate them when a vehicle needs to leave a CACC string or when the string is interrupted by a cut-in maneuver by a noncooperative vehicle. Activity diagrams are used to describe the CACC maneuvers; the diagrams specify the sequence of actions that need to be taken by each driver and each vehicle (and its CACC software) and the information that needs to be exchanged between them. These precise definitions can be used to specify the vehicle-to-vehicle messages that need to be exchanged between vehicles to implement CACC and the driver–vehicle interface displays and controls that are needed. The paper also addresses practical considerations in CACC operation, such as maximum lengths for strings of CACC trucks, strategies for sequencing the trucks in CACC strings, and higher-level strategies for clustering CACC-capable trucks; these strategies range from ad hoc to local and global coordination.

In this paper, we present an overview and background on speed harmonization (SH). This paper reviews a number of representative studies that designed traffic control algorithms based on variable speed limits, ramp metering, connected vehicle, or automated vehicle for SH. We summarize fundamental mechanisms, control algorithms, and evaluation results of these studies. We investigate the opportunities brought by a portion of the vehicles communicating with each other using new technologies. We also investigate opportunities due to some vehicles having automated speed control. We discuss experiments undertaken and underline a new experiment performed in real traffic. Finally, we discuss other new SH experiments that can be undertaken as market penetration makes communication ubiquitous.

Most previous algorithms for variable speed limit and variable speed advisory (VSL-VSA) for bottleneck flow maximization are local and occupancy measurement–based. Some algorithms for freeway networks with multiple bottlenecks were proposed on the basis of the second-order METANET model, but these were rather complicated. This paper proposes (a) a novel simple VSL-VSA control algorithm for bottleneck flow improvement based on speed measurements and (b) a strategy to expand to a freeway network with multiple bottlenecks by using a distance-based interpolation. The algorithm was validated with a well-calibrated traffic network model for I-66 inside the Capital Beltway around Washington, D.C. Simulation results showed that overall system performance was improved even with a 10% compliance rate, and the improvement was not sensitive to the compliance rate if the latter was greater than 10%. The performance parameters included total travel time, total travel distance, total number of stops, average speed variation, total delays, and flow at the bottlenecks. The VSL-VSA algorithm can be implemented by using infrastructure-to-vehicle communication to a display or to determine the set speed for an adaptive cruise control system or variable message signs on the roadside. The algorithm was conceptually tested with three vehicles that used the VSL as a set speed for their infrastructure-to-vehicle cooperative adaptive cruise control systems.

Cooperative adaptive cruise control (CACC) includes multiple concepts of communication-enabled vehicle following and speed control. Definitions and classifications are presented to help clarify the distinctions between types of automated vehicle-following control that are often conflated with each other. A distinction is made between vehicle-to-vehicle (V2V) CACC, based on vehicle–vehicle cooperation, and infrastructure-to-vehicle CACC, in which the infrastructure provides information or guidance to the CACC system (such as the target set speed value). In V2V CACC, communication provides enhanced information so that vehicles can follow their predecessors with higher accuracy, faster response, and shorter gaps; the result would be enhanced traffic flow stability and possibly improved safety. A further distinction is made between CACC, which uses constant-time-gap vehicle following (forming CACC strings), and automated platooning, which uses tightly coupled, constant-clearance, vehicle-following strategies. Although adaptive cruise control (ACC) and CACC are examples of Level 1 automation as defined by both SAE and NHTSA, the vehicle-following performance that can be achieved under each scenario is representative of the performance that should be expected at higher levels of automation. Implementation of CACC in practice will also require consideration of more than the lowest level of vehicle-following and speed regulation performance. Because CACC requires interactions between adjacent equipped vehicles, strategies are needed such as ad hoc, local, or global coordination to cluster CACC vehicles. Some of the challenges that must be overcome to implement the clustering strategies are discussed as well as strategies for separating CACC clusters as they approach their destinations, as potential traffic improvements from CACC will be negated if the vehicles cannot disperse effectively.

Cooperative adaptive cruise control (CACC) includes multiple concepts of communication-enabled vehicle following and speed control. Definitions and classifications are presented to help clarify the distinctions between types of automated vehicle-following control that are often conflated with each other. A distinction is made between vehicle-to-vehicle (V2V) CACC, based on vehicle–vehicle cooperation, and infrastructure-to-vehicle CACC, in which the infrastructure provides information or guidance to the CACC system (such as the target set speed value). In V2V CACC, communication provides enhanced information so that vehicles can follow their predecessors with higher accuracy, faster response, and shorter gaps; the result would be enhanced traffic flow stability and possibly improved safety. A further distinction is made between CACC, which uses constant-time-gap vehicle following (forming CACC strings), and automated platooning, which uses tightly coupled, constant-clearance, vehicle-following strategies. Although adaptive cruise control (ACC) and CACC are examples of Level 1 automation as defined by both SAE and NHTSA, the vehicle-following performance that can be achieved under each scenario is representative of the performance that should be expected at higher levels of automation. Implementation of CACC in practice will also require consideration of more than the lowest level of vehicle-following and speed regulation performance. Because CACC requires interactions between adjacent equipped vehicles, strategies are needed such as ad hoc, local, or global coordination to cluster CACC vehicles. Some of the challenges that must be overcome to implement the clustering strategies are discussed as well as strategies for separating CACC clusters as they approach their destinations, as potential traffic improvements from CACC will be negated if the vehicles cannot disperse effectively.

Most previous algorithms for variable speed limit and variable speed advisory (VSL-VSA) for bottleneck flow maximization are local and occupancy measurement–based. Some algorithms for freeway networks with multiple bottlenecks were proposed on the basis of the second-order METANET model, but these were rather complicated. This paper proposes (a) a novel simple VSL-VSA control algorithm for bottleneck flow improvement based on speed measurements and (b) a strategy to expand to a freeway network with multiple bottlenecks by using a distance-based interpolation. The algorithm was validated with a well-calibrated traffic network model for I-66 inside the Capital Beltway around Washington, D.C. Simulation results showed that overall system performance was improved even with a 10% compliance rate, and the improvement was not sensitive to the compliance rate if the latter was greater than 10%. The performance parameters included total travel time, total travel distance, total number of stops, average speed variation, total delays, and flow at the bottlenecks. The VSL-VSA algorithm can be implemented by using infrastructure-to-vehicle communication to a display or to determine the set speed for an adaptive cruise control system or variable message signs on the roadside. The algorithm was conceptually tested with three vehicles that used the VSL as a set speed for their infrastructure-to-vehicle cooperative adaptive cruise control systems.

Previous studies on variable speed limits (VSLs) were reviewed. These studies were classified as three types: simulations for algorithm development and evaluations, VSL implementation and field testing, and a combination of VSLs with ramp metering. The review considered strategies and algorithms, targeted traffic improvements (safety, throughput, etc.), applicable traffic conditions, performance evaluations, and simulation or test results and their implications. Most practices in Europe indicated that the use of VSLs was effective in both traffic safety and flow improvement, although the former was more significant. Practices in the United States indicated that safety improvement was significant but the impact on traffic flow was controversial. Practices are summarized, and some new viewpoints and future research directions are presented.

Previous studies on variable speed limits (VSLs) were reviewed. These studies were classified as three types: simulations for algorithm development and evaluations, VSL implementation and field testing, and a combination of VSLs with ramp metering. The review considered strategies and algorithms, targeted traffic improvements (safety, throughput, etc.), applicable traffic conditions, performance evaluations, and simulation or test results and their implications. Most practices in Europe indicated that the use of VSLs was effective in both traffic safety and flow improvement, although the former was more significant. Practices in the United States indicated that safety improvement was significant but the impact on traffic flow was controversial. Practices are summarized, and some new viewpoints and future research directions are presented.

Cyclic adenosine 3′,5′-monophosphate (cAMP)–elevating agents, such as β2-adrenergic receptor (β2-AR) agonists and phosphodiesterase (PDE) inhibitors, remain a mainstay in the treatment of obstructive respiratory diseases, conditions characterized by airway constriction, inflammation, and mucus hypersecretion. However, their clinical use is limited by unwanted side effects because of unrestricted cAMP elevation in the airways and in distant organs. Here, we identified the A-kinase anchoring protein phosphoinositide 3-kinase γ (PI3Kγ) as a critical regulator of a discrete cAMP signaling microdomain activated by β2-ARs in airway structural and inflammatory cells. Displacement of the PI3Kγ-anchored pool of protein kinase A (PKA) by an inhaled, cell-permeable, PI3Kγ mimetic peptide (PI3Kγ MP) inhibited a pool of subcortical PDE4B and PDE4D and safely increased cAMP in the lungs, leading to airway smooth muscle relaxation and reduced neutrophil infiltration in a murine model of asthma. In human bronchial epithelial cells, PI3Kγ MP induced unexpected cAMP and PKA elevations restricted to the vicinity of the cystic fibrosis transmembrane conductance regulator (CFTR), the ion channel controlling mucus hydration that is mutated in cystic fibrosis (CF). PI3Kγ MP promoted the phosphorylation of wild-type CFTR on serine-737, triggering channel gating, and rescued the function of F508del-CFTR, the most prevalent CF mutant, by enhancing the effects of existing CFTR modulators. These results unveil PI3Kγ as the regulator of a β2-AR/cAMP microdomain central to smooth muscle contraction, immune cell activation, and epithelial fluid secretion in the airways, suggesting the use of a PI3Kγ MP for compartment-restricted, therapeutic cAMP elevation in chronic obstructive respiratory diseases.

This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.

The estimation of traffic speed based on loop detector occupancy is a long-standing problem that is critical to traffic management and control. Single-loop detector stations are still popular in highway traffic systems in practice. Although dual loop stations could generate more accurate speed estimation with event data, updating single loops to dual loops is costly. Most previous work, such as the g-factor method on speed estimation with a single-loop system, used aggregated data and assumed a known effective vehicle length. However, those methods did not always produce good results, particularly in traffic transition phases. This paper proposes a new approach using event data and mode occupancy within a moving window of variable length to estimate the effective vehicle length, or g-factor. Berkeley Highway Laboratory dual loop data with a 1-Hz update rate and 60-Hz information were used for algorithm validation and reliability tests. The speed estimated from the corrected dual loop data was used as the ground truth for comparison. Root mean square error was used to quantify the discrepancy. Results showed that the proposed approach generates very satisfactory speed estimations compared with estimations from dual loop stations. This algorithm can be run at the control-cabinet level, in which event data of an individual loop from a 170 or 2070 controller are available without the need of any hardware modification. These controllers have the processor capabilities to handle data in real time.

The estimation of traffic speed based on loop detector occupancy is a long-standing problem that is critical to traffic management and control. Single-loop detector stations are still popular in highway traffic systems in practice. Although dual loop stations could generate more accurate speed estimation with event data, updating single loops to dual loops is costly. Most previous work, such as the g-factor method on speed estimation with a single-loop system, used aggregated data and assumed a known effective vehicle length. However, those methods did not always produce good results, particularly in traffic transition phases. This paper proposes a new approach using event data and mode occupancy within a moving window of variable length to estimate the effective vehicle length, or g-factor. Berkeley Highway Laboratory dual loop data with a 1-Hz update rate and 60-Hz information were used for algorithm validation and reliability tests. The speed estimated from the corrected dual loop data was used as the ground truth for comparison. Root mean square error was used to quantify the discrepancy. Results showed that the proposed approach generates very satisfactory speed estimations compared with estimations from dual loop stations. This algorithm can be run at the control-cabinet level, in which event data of an individual loop from a 170 or 2070 controller are available without the need of any hardware modification. These controllers have the processor capabilities to handle data in real time.

This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.

Freeway corridor traffic flow is limited by bottleneck flow. If the section upstream of a bottleneck is congested, the bottleneck flow will drop well below its capacity. A logical approach to maximizing recurrent bottleneck flow is to create a discharge section immediately upstream of the bottleneck. This paper proposes a control strategy for combining variable speed limits (VSL) and coordinated ramp metering (CRM) design to achieve this objective when the bottleneck can be represented as a lane (or virtual lane) reduction. At each time step, VSL is designed first, with mainline flow, on-ramp demand and length, and driver acceptance taken into account. VSL values are determined for three locations: (a) the critical VSL to regulate the discharge section flow to match bottleneck capacity, (b) the VSL for the potentially congested section (mainline storage), and (c) the VSL upstream of the congestion tail. With the selected VSL, the first-order mainline flow model is linearized and then used for CRM design with model predictive control to minimize the difference between scaled total travel time (or vehicle hours traveled) and the total travel distance (equivalent to vehicle miles traveled). Microscopic simulation shows that this control strategy should improve bottleneck throughput significantly.

Freeway corridor traffic flow is limited by bottleneck flow. If the section upstream of a bottleneck is congested, the bottleneck flow will drop well below its capacity. A logical approach to maximizing recurrent bottleneck flow is to create a discharge section immediately upstream of the bottleneck. This paper proposes a control strategy for combining variable speed limits (VSL) and coordinated ramp metering (CRM) design to achieve this objective when the bottleneck can be represented as a lane (or virtual lane) reduction. At each time step, VSL is designed first, with mainline flow, on-ramp demand and length, and driver acceptance taken into account. VSL values are determined for three locations: (a) the critical VSL to regulate the discharge section flow to match bottleneck capacity, (b) the VSL for the potentially congested section (mainline storage), and (c) the VSL upstream of the congestion tail. With the selected VSL, the first-order mainline flow model is linearized and then used for CRM design with model predictive control to minimize the difference between scaled total travel time (or vehicle hours traveled) and the total travel distance (equivalent to vehicle miles traveled). Microscopic simulation shows that this control strategy should improve bottleneck throughput significantly.

Density, speed, and flow are the three critical parameters for traffic analysis. High-performance traffic management and control require the estimation-prediction of space mean speed and density for large spatial and temporal coverage. Speed, including spot mean speed and space mean speed, and flow estimation are relatively easy to measure and estimate, while less attention has been devoted to measuring and estimating density. Because IntelliDrive (previously known as vehicle infrastructure integration) is a promising technology for providing a new type of real-time traffic data, and loop detector systems have already been widely deployed, this paper proposes a method to estimate freeway traffic density with both loop detector data and IntelliDrive-based probe vehicle data. The proposed method has been validated with Berkeley Highway Laboratory loop detector data combined with field-collected probe vehicle data in the first validation study and next-generation simulation video trajectory data in the second validation test. The algorithm can be used offline and in real time.

Density, speed, and flow are the three critical parameters for traffic analysis. High-performance traffic management and control require the estimation–prediction of space mean speed and density for large spatial and temporal coverage. Speed, including spot mean speed and space mean speed, and flow estimation are relatively easy to measure and estimate, while less attention has been devoted to measuring and estimating density. Because IntelliDrive (previously known as vehicle infrastructure integration) is a promising technology for providing a new type of real-time traffic data, and loop detector systems have already been widely deployed, this paper proposes a method to estimate freeway traffic density with both loop detector data and IntelliDrive-based probe vehicle data. The proposed method has been validated with Berkeley Highway Laboratory loop detector data combined with field-collected probe vehicle data in the first validation study and next-generation simulation video trajectory data in the second validation test. The algorithm can be used offline and in real time.

Src family of protein tyrosine kinases (SFKs) play key roles in regulating signal transduction in cellular processes. However, hyper-activated SFKs lead to uncontrolled cell proliferation and cancers. Many SFKs inhibitors were designed and synthesized as anticancer agents in the past several years and great progress has been made. Herein, some predominant examples of SFKs inhibitors recently developed are reviewed and special attentions are paid to the most important ATP binding site inhibitors.

Previous work on asymptotic stabilization of MIMO non‐linear systems using dynamic sliding mode control to produce dynamic state feedback has been generalized to dynamic output feedback. All the states in the feedback controller are replaced with estimated states which come from a semi‐high‐gain observer. The bound on the observer gain is explicitly given, which depends on some previously chosen design parameters. If the given differential input–output (I–O) system is minimum phase and proper, local uniform asymptotic output feedback stabilization can be achieved. In addition, the restriction on the stability of the zero dynamics has been relaxed to weakly minimum phase and semi‐global results are obtained under some mild conditions. The stability of the closed‐loop system is based on some stability results of triangular systems when continuous or discontinuous controllers are adopted. Two pertinent examples are given to illustrate the design method. Copyright © 1999 John Wiley & Sons, Ltd.

Previous work on asymptotic stabilization of MIMO non-linear systems using dynamic sliding mode control to produce dynamic state feedback has been generalized to dynamic output feedback. All the states in the feedback controller are replaced with estimated states which come from a semi-high-gain observer. The bound on the observer gain is explicitly given, which depends on some previously chosen design parameters. If the given differential input–output (I–O) system is minimum phase and proper, local uniform asymptotic output feedback stabilization can be achieved. In addition, the restriction on the stability of the zero dynamics has been relaxed to weakly minimum phase and semi-global results are obtained under some mild conditions. The stability of the closed-loop system is based on some stability results of triangular systems when continuous or discontinuous controllers are adopted. Two pertinent examples are given to illustrate the design method. Copyright © 1999 John Wiley & Sons, Ltd.

This paper considers the development of tracking controllers for a multi-input nonlinear non-minimum phase Planar Vertical Take-off and Landing (PVTOL)aircraft. The system is considered to be subject to bounded/sector additive external uncertainties. A dynamic sliding mode control philosophy is employed. The stability and robustness of the resulting closed-loop system is analysed. It is demonstrated that ultimate bounded tracking may be achieved with bounded inputs despite the presence of uncertainty.

A newly developed dynamic sliding mode control technique for multiple input systems which may be not dynamic feedback linearisable is extended to the control of nonlinear nonminimum phase systems (corresponding zero dynamics have no finite escape time). A thin layer is introdued around the sliding surface. Outside the layer, the sliding mode controller is used; inside the layer, the controller is designed to asymptotically (exponentially) stabilise the dynamic compensator. The method is illustrated by the control of the Inverted Double Pendulum.

A dynamic sliding mode controller design method is proposed for multiple input systems. The method uses a novel choice of sliding surface to effect asymptotic linearization of nonlinear differential input output systems. The stability of the overall system, i.e. a canonical state space form with a dynamic feedback, is analyzed. This method is shown to be able to control a fairly general class of systems which is not linearizable by dynamic feedback using chatter free control. The theoretical results are applied to Gas Jet Actuators with both one and two inputs. It is known to be not feedback linearizable when only one input is utilised.

Although the very important concept of relative order is defined in differential geometric control with respect to an affine input-state-output (I-S-O) system, it is rather the difference between the highest orders of the derivative of output and that of input in the corresponding input-output (I-O) systems. This is a direct generalization of the result in the case of the transfer function in linear control theory. The relative order is proved to be an invariant of realization, and applications in realization and minimal equivalence are discussed..

Previous work on dynamic state feedback asymptotic stabilisation of nonlinear systems using sliding mode control has been generalised to dynamic output feedback. A semi-high-gain observer is used to estimate the states. The lower bound for the observer gain is explicitly given. Stability analysis is Lyapunov approach.