Tingkat Kemacetan dan Realita Transportasi di Jalan Letjen Suprapto, Kecamatan Sumbersari, Jember

Pertumbuhan penduduk yang cepat akan menuntut kebutuhan transportasi seperti jumlah kendaraan dan kondisi jalan yang memadai. Kondisi jalan yang tidak sesuai dengan jumlah kendaraan yang semakin meningkat akan menyebabkan permasalahan transportasi. Penelitian ini bertujuan untuk menganalisis penyebab masalah transportasi di jalan Letjen Suprapto, Kabupaten Jember dalam rangka mendukung mobilitas sekuler para pekerja dari wilayah selatan Jember. Metode penelitian yang digunakan adalah metode observasi dengan pengamatan dan perhitungan jumlah kendaraan yang menuju kota pada pagi, siang, dan sore hari saat hari kerja, yaitu pada pukul 06:30-07:30 pagi, 13:00-14:00 siang, dan 16:30-17:30 sore selama 1 bulan. Hasil penelitian menunjukkan bahwa jumlah kendaraan yang masuk ke kota Jember lebih banyak saat pagi hari dibandingkan waktu lainnya. Jenis kendaraan yang paling banyak melintas di Jalan Letjen Suprapto adalah Sepeda motor dengan persentase 90% dari semua jenis kendaraan, dan dalam waktu satu jam rata-rata terdapat 4205 sepeda motor yang berpotensi tinggi terjadi kecelakaan. Pada siang hari jumlah kendaraan kembali stabil dan tidak berpotensi macet. Selanjutnya pada sore hari jumlah kendaraan meningkat kembali dikarenakan mobilitas para pekerja yang kembali ke desa mereka pada sore hari. Tiga pilar aksi penting yang perlu segera diwujudkan untuk mengatasi kemacetan dan permasalahan tranportasi adalah pengembangan fasilitas transportasi umum yang memadai, peningkatan rasio jalan, dan membatasi jumlah kendaraan pribadi pengguna

Ecodriving for Reduction of Bus Transit Emission with Vehicle’s Hybrid Dynamic Model

This paper formulates a global ecodriving optimal control to advise the green driving speed for bus transit to minimize the exhaust emission using Vehicle-to-Infrastructure (V2I) communication. Assuming communication between vehicles and infrastructure (V2I) and knowledge of traffic signal timings and waiting passengers at stations are known, an optimal driving speed is proposed to minimize the total vehicle emissions of the bus route. The dwell time of the bus transit at each station which includes two parts is proposed. A traffic lights timing model is employed as constraints to control the formation of the green wave band. Vehicle specific power (VSP) model is further applied to evaluate the exhaust emission level linked with the speed and acceleration of the bus transit. An approximate sixteen-kilometer traffic network including fourteen intersections and fifteen stations of Beijing bus transit line 1 in Chaoyang District, Beijing, is chosen to investigate the performance of the developed ecodriving approach

There is a Will, There is a Way: A New Mechanism for Traffic Control Based on

Abstract-Traffic light is regarded as one of the most effective ways to alleviate traffic congestion and carbon emission problems. However, traditional traffic light cannot meet the challenges in traffic regulation posed by the fast growing number of vehicles and increasing complexity of road conditions. In this paper, we propose a dynamic traffic regulation method based on virtual traffic light (VTL) for Vehicle Ad Hoc Network (VANET). In our framework, each vehicle can express its "will"-the desire of moving forwardand share among one another its "will"-value and related traffic information at a traffic light controlled intersection. Based on the traffic information collected in real time, the virtual traffic light in our scheme can be adaptive to the changing environment. We conducted a number of simulation experiments with different scenarios using network simulator NS3 combined with traffic simulator SUMO. The results demonstrate the viability of our solution in reducing waiting time and improving the traffic efficiency

STARC: Decentralized Coordination Primitive on Low-Power IoT Devices for Autonomous Intersection Management

Wireless communication is an essential element within Intelligent Transportation Systems and motivates new approaches to intersection management, allowing safer and more efficient road usage. With lives at stake, wireless protocols should be readily available and guarantee safe coordination for all involved traffic participants, even in the presence of radio failures. This work introduces STARC, a coordination primitive for safe, decentralized resource coordination. Using STARC, traffic participants can safely coordinate at intersections despite unreliable radio environments and without a central entity or infrastructure. Unlike other methods that require costly and energy-consuming platforms, STARC utilizes affordable and efficient Internet of Things devices that connect cars, bicycles, electric scooters, pedestrians, and cyclists. For communication, STARC utilizes low-power IEEE 802.15.4 radios and Synchronous Transmissions for multi-hop communication. In addition, the protocol provides distributed transaction, election, and handover mechanisms for decentralized, thus cost-efficient, deployments. While STARC’s coordination remains resource-agnostic, this work presents and evaluates STARC in a roadside scenario. Our simulations have shown that using STARC at intersections leads to safer and more efficient vehicle coordination. We found that average waiting times can be reduced by up to 50% compared to using a fixed traffic light schedule in situations with fewer than 1000 vehicles per hour. Additionally, we design platooning on top of STARC, improving scalability and outperforming static traffic lights even at traffic loads exceeding 1000 vehicles per hour

A novel peer-to-peer congestion pricing marketplace enabled by vehicle-automation

This paper proposes a novel concept of congestion pricing based on voluntary peer-to-peer exchange of money between motorists in exchange for one ceding priority to another in a traffic stream. While in the classical congestion charging paradigm payments are compulsory and flow only towards the system operator, in the proposed marketplace participation is voluntary and motorists directly compensate each other. A particular motorist may find that he/she is a ‘payer’ at certain points in a given journey and a ‘payee’ at others. Humans would not be expected to successfully seek, negotiate and execute a continuous series of peer-to-peer trades involving micro-payments while also handling the cognitively-demanding task of driving; real-world implementation will therefore require vehicles operating under fully-automated control in both the longitudinal and lateral dimensions during the time periods that they seek and engage in trades. The automated vehicle control algorithms must be sufficiently intelligent and adaptable to enable alternative maneuvers on short timescales, given the inherent uncertainty of whether or not a potential trade will in fact be executed. The peer-to-peer trading would be executed algorithmically, subject to strategic-level guidance given by a vehicle’s occupant(s) regarding the occupant’s relative valuation of money and priority in the traffic stream. In this paper we detail the prospective marketplace and present a simple simulation model to expose its properties. We show that the proposed peer-to-peer marketplace could lead to both desirable and undesirable outcomes; which of these would be predominant is a matter requiring empirical study. The paper concludes with a discussion of further research needs to refine and develop these concepts into practice

Vehicle automation and freeway 'pipeline' capacity in the context of legal standards of care

The study evaluates, in the context of freeway segments, the interaction between automated cars’ kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the ‘Assured Clear Distance Ahead’ criterion). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDA-compliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral ‘cut-ins’ by vehicles making lane changes. The paper concludes with a brief discussion of policy questions and research needs

Urban Navigation Handling Openstreetmap Data for an Easy to Drive Route

Atualmente, os cidadãos podem escolher as suas opções de viagem com base no tempo, distância, emissões, consumo, entre outros parâmetros. Não obstante, a literatura indica que os sistemas de planeamento de rotas atuais têm, maioritariamente, por base a distância e o tempo. Com efeito, verificou-se uma falta de sistemas de planeamento de rotas que se preocupem com as preferências dos utilizadores num ponto de vista mais qualitativo. Este projeto de investigação desenvolve um framework de planeamento de rotas com a integração de diferentes atributos da rede rodoviária como semáforos, passadeiras e paragens de autocarro, com o objetivo de providenciar aos utilizadores a opção de evitar estes mesmos atributos, oferecendo uma opção easy drive, nomeadamente em ambiente urbano. O estudo foi conduzido através de dados georreferenciados da cidade de Lisboa, Portugal. No entanto, é transferível para qualquer outra cidade. O algoritmo providencia alternativas para a rota mais curta, easy drive e rota balanceada, considerando apenas um modo de viagem: carro/mota. O modelo foi desenvolvido no PostgreSQL com a extensão PostGIS e PgRouting, e os resultados foram visualizados no software QGIS. O software permite customizar pesos para cada uma das restrições para a escolha das rotas e estes pesos são modificados com o objetivo de encontrar o caminho ótimo consoante as preferências de cada utilizador.Currently, citizens can choose their travel options based on time, distance, consumption, emission, among other parameters. Nevertheless, the literature indicates that current route planning systems are based on distance and time. In fact, there is a lack of route planning systems which are concerned with users' preferences from a more qualitative point of view. This research project develops a route planning framework with the integration of different road network features like traffic lights, pedestrian crossings, and bus stops, to provide users with the option to avoid these features, offering an easy drive option, namely in an urban environment. The study was conducted using georeferenced data from the city of Lisbon, Portugal. However, it is transferable to any other city. The algorithm provides alternatives for the shortest route, easy drive, and balanced route, considering only one travel mode: car/motorbike. The model was developed in PostgreSQL with the PostGIS extension and PgRouting, and the results were visualized in QGIS software. The software allows to custom weights for each of the constraints for route choices, and these weights are modified to find the optimal route according to the preferences of each user