Flexibility Versus Certainty in Planning: A Critical Review of Cross-Boundary Spatial Planning Systems and Practices

This research has critically argued that a vigilant combination of flexibility and certainty in spatial planning can bring about the most optimum planning outcomes. Therefore, to reproachfully evaluate the core argument, this research has tried to empirically respond to the research question of which balance of government intervention and market freedom produces the optimal economic, social and spatial outcomes. This research question has been further translated into an associated central hypothesis i.e., a hybrid planning system with an optimal balance between discretionary and regulatory planning approach can bring about the desired economic, social, and spatial outcomes.

Regression models for predicting physical and EQD2 plan parameters of two methods of hybrid planning for stage III NSCLC

Background/purpose To establish regression models of physical and equivalent dose in 2 Gy per fraction (EQD2) plan parameters of two kinds of hybrid planning for stage III NSCLC. Methods Two kinds of hybrid plans named conventional fraction radiotherapy & stereotactic body radiotherapy (C&S) and conventional fraction radiotherapy & simultaneous integrated boost (C&SIB) were retrospectively made for 20 patients with stage III NSCLC. Prescription dose of C&S plans was 2 Gy × 30f for planning target volume of lymph node (PTVLN) and 12.5 Gy × 4f for planning target volume of primary tumor (PTVPT), while prescription dose of C&SIB plans was 2 Gy × 26f for PTVLN and sequential 2 Gy × 4f for PTVLN combined with 12.5 Gy × 4f for PTVPT. Regression models of physical and EQD2 plan parameters were established based on anatomical geometry features for two kinds of hybrid plans. The features were mainly characterized by volume ratio, min distance and overlapping slices thickness of two structures. The possibilities of regression models of EQD2 plan parameters were verified by spearman’s correlation coefficients between physical and EQD2 plan parameters, and the influence on the consistence of fitting goodness between physical and EQD2 models was investigated by the correlations between physical and EQD2 plan parameters. Finally, physical and EQD2 models predictions were compared with plan parameters for two new patients. Results Physical and EQD2 plan parameters of PTVLN CI60Gy have shown strong positive correlations with PTVLN volume and min distance(PT to LN), and strong negative correlations with PTVPT volume for two kinds of hybrid plans. PTV(PT+LN) CI60Gy is not only correlated with above three geometry features, but also negatively correlated with overlapping slices thickness(PT and LN). When neck lymph node metastasis was excluded from PTVLN volume, physical and EQD2 total lung V20 showed a high linear correlation with corrected volume ratio(LN to total lung). Meanwhile, physical total lung mean dose (MLD) had a high linear correlation with corrected volume ratio(LN to total lung), while EQD2 total lung MLD was not only affected by corrected volume ratio(LN to total lung) but also volume ratio(PT to total lung). Heart D5, D30 and mean dose (MHD) would be more susceptible to overlapping structure(heart and LN). Min distance(PT to ESO) may be an important feature for predicting EQD2 esophageal max dose for hybrid plans. It’s feasible for regression models of EQD2 plan parameters, and the consistence of the fitting goodness of physical and EQD2 models had a positive correlation with spearman’s correlation coefficients between physical and EQD2 plan parameters. For total lung V20, ipsilateral lung V20, and ipsilateral lung MLD, the models could predict that C&SIB plans were higher than C&S plans for two new patients. Conclusion The regression models of physical and EQD2 plan parameters were established with at least moderate fitting goodness in this work, and the models have a potential to predict physical and EQD2 plan parameters for two kinds of hybrid planning.

A Hybrid Planning Approach Based on MPC and Parametric Curves for Overtaking Maneuvers

Automated Driving Systems (ADS) have received a considerable amount of attention in the last few decades, as part of the Intelligent Transportation Systems (ITS) field. However, this technology still lacks total automation capacities while keeping driving comfort and safety under risky scenarios, for example, overtaking, obstacle avoidance, or lane changing. Consequently, this work presents a novel method to resolve the obstacle avoidance and overtaking problems named Hybrid Planning. This solution combines the passenger’s comfort associated with the smoothness of Bézier curves and the reliable capacities of Model Predictive Control (MPC) to react against unexpected conditions, such as obstacles on the lane, overtaking and lane-change based maneuvers. A decoupled linear-model was used for the MPC formulation to ensure short computation times. The obstacles and other vehicles’ information are obtained via V2X (vehicle communications). The tests were performed in an automated Renault Twizy vehicle and they have shown good performance under complex scenarios involving static and moving obstacles at a maximum speed of 60 kph.