The Lord of the Ring Road: A Review and Evaluation of Autonomous Control Policies for Traffic in a Ring Road

This study focuses on the comprehensive investigation of stop-and-go waves appearing in closed-circuit ring road traffic wherein we evaluate various longitudinal dynamical models for vehicles. It is known that the behavior of human-driven vehicles, with other traffic elements such as density held constant, could stimulate stop-and-go waves, which do not dissipate on the circuit ring road. Stop-and-go waves can be dissipated by adding automated vehicles (AVs) to the ring. Thorough investigations of the performance of AV longitudinal control algorithms were carried out in Flow, which is an integrated platform for reinforcement learning on traffic control. Ten AV algorithms presented in the literature are evaluated. For each AV algorithm, experiments are carried out by varying distributions and penetration rates of AVs. Two different distributions of AVs are studied. For the first distribution scenario, AVs are placed consecutively. Penetration rates are varied from 1 AV (5%) to all AVs (100%). For the second distribution scenario, AVs are placed with even distribution of human-driven vehicles in between any two AVs. In this scenario, penetration rates are varied from 2 AVs (10%) to 11 AVs (50%). Multiple runs (10 runs) are simulated to average out the randomness in the results. From more than 3,000 simulation experiments, we investigated how AV algorithms perform differently with varying distributions and penetration rates while all AV algorithms remained fixed under all distributions and penetration rates. Time to stabilize, maximum headway, vehicle miles traveled, and fuel economy are used to evaluate their performance. Using these metrics, we find that the traffic condition improvement is not necessarily dependent on the distribution for most of the AV controllers, particularly when no cooperation among AVs is considered. Traffic condition is generally improved with a higher AV penetration rate with only one of the AV algorithms showing a contrary trend. Among all AV algorithms in this study, the reinforcement learning controller shows the most consistent improvement under all distributions and penetration rates.

Multi-Objective Optimization of Differentiated Urban Ring Road Bus Lines and Fares Based on Travelers’ Interactive Reinforcement Learning

This paper proposes a new multi-objective bi-level programming model for the ring road bus lines and fare design problems. The proposed model consists of two layers: the traffic management operator and travelers. In the upper level, we propose a multi-objective bus lines and fares optimization model in which the operator’s profit and travelers’ utility are set as objective functions. In the lower level, evolutionary multi agent model of travelers’ bounded rational reinforcement learning with social interaction is introduced. A solution algorithm for the multi-objective bi-level programming is developed on the basis of the equalization algorithm of OD matrix. A numerical example based on a real case was conducted to verify the proposed models and solution algorithm. The computational results indicated that travel choice models with different degrees of rationality significantly changed the optimization results of bus lines and the differentiated fares; furthermore, the multi-objective bi-level programming in this paper can generate the solution to reduce the maximum section flow, increase the profit, and reduce travelers’ generalized travel cost.

MODELING THE PLAN OF THE TRANSPORTATION PROCESS DURING THE MORNING RUSH HOUR ON THE CLOSED BOLSHAYA KOLTSEVAYA LINE OF THE MOSCOW METRO

The article analyzes the characteristics of the construction of the Bolshaya Koltsevaya line (Large Circle Line) of the Moscow Metro from the point of view of the transportation process planning. The authors have studied the characteristics of all operating depots of the Moscow Metro that justify the plans for the construction of two new depots (Aminievsky and Nizhegorodsky), as well as the reconstruction of one of the existing depots (Zamoskvoretsky), located within the city limits of Moscow – inside the Moscow Automobile Ring Road (MKAD), in the vicinity of the Third Transport Ring and beyond. For the needs of modeling, the station-to-station length of the closed Bolshaya Koltsevaya line was measured, subject to the transfer of a train traffi c section from the Delovoy Tsentr station to the Khoroshevskaya station of the projected Rublyovo-Arkhangelskaya metro line. Based on the measurement fi ndings, the station-to-station travel times along the closed Bolshaya Koltsevaya line were calculated, which subsequently made it possible to determine the number of electric rolling stock units required to service the Bolshaya Koltsevaya line in the morning rush hour

Simulating the Response of the Surface Urban Heat Environment to Land Use and Land Cover Changes: A Case Study of Wuhan, China

With the rapid process of urbanization, the urban heat island (UHI), the phenomenon where urban regions become hotter than their surroundings, is increasingly aggravated. The UHI is affected by multiple factors overall. However, it is difficult to dissociate the effect of one aspect by widely used approaches such as the remote-sensing-based method. To qualify the response of surface UHI to the land use and land cover (LULC) changes, this study took the numerical land model named u-HRLDAS (urbanized high-resolution land data assimilation system) as the modeling tool to investigate the effect of LULC changes on the UHI from 1980 to 2013 in Wuhan city, China. Firstly, the simulation accuracy of the model was improved, and the summer urban heat environment was simulated for the summer of 2013. Secondly, taking the simulation in 2013 as the control case (CNTL), the LULC in 1980, 1990, and 2000 were replaced by the LULC while the other conditions kept the same as the CNTL to explore the effect of LULC on UHI. The results indicate that the proper configuration of the modeling setup and accurate surface input data are considered important for the simulated results of the u-HRLDAS. The response intensity of UHI to LULC changes after 2000 was stronger than that of before 2000. From the spatial perspective, the part that had the strongest response intensity of land surface temperature to LULC changes was the region between the third ring road and the inner ring road of Wuhan. This study can provide a reference for cognizing the urban heat environment and guide policy making for urban development.

Integrasi Analisis Spasial dan Statistik untuk Identifikasi Pola dan Faktor Determinan Perkembangan Kota Yogyakarta.

Abstrak Analisis spasial adalah metode analisis yang mempunyai ciri spesifik karenanya banyak digunakan dalam berbagai bidang kajian. Perkembangan kota adalah salah satunya. Penelitian ini bertujuan untuk mengidentifikasi pola perkembangan kota dan faktor determinannya menggunakan integrasi analisis spasial dan statistik. Area di dalam jalan lingkar Yogyakarta dipilih sebagai daerah penelitian. Peta penggunaan lahan tahun 1993 dan 2014 digunakan sebagai data utama. Kombinasi analisis spasial dan statistik digunakan untuk mengidentifikasi faktor determinan perkembangan kota. Pertambahan lahan terbangun digunakan sebagai indikator perkembangan kota. Hasil penelitian menunjukkan, selama periode kajian, lahan terbangun bertambah kurang lebih 766,35 hektar. Secara umum pola perkembangan kota adalah merata namun ada kecenderung lebih intensif di bagian Timur Laut daerah penelitian. Hasil analisis terhadap tujuh variabel yang diduga berhubungan dengan perkembang kota, menunjukkan hanya 2 variabel yang mempunyai signifikan dan dapat disebut sebagai determinan perkembangan kota. Variabel tersebut adalah jarak terhadap jalan lingkar Yogyakarta (ring road) dan jarak terhadap jalan lokal. Abstract : Spatial analysis is often termed as special analysis therefore widely used in various studies. The study of urban growth is one among them. Identifying the pattern of urban growth and its determinant factors was the objective of this research. The study was located in the inner area of the ring road of Yogyakarta. Multitemporal land use data i.e. 1993 and 2014 were used as main data in this study. Spatial analysis was utilized to identify the distribution as well as the pattern of urban growth. A combination of spatial and statistical analysis was used to identify the determinant factor of urban growth. This study shows that during 199 and 2014, about 766,4 hectares of non-built-up land in the study area had been converted into built-up land. The pattern of urban growth was dispersed in general but the direction tends to the northeast of the study area. Transportation network, particularly the ring road and local roads were considered as the main determinants of urban growth.