scholarly journals An Incentive Based Dynamic Ride-Sharing System for Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 532-547
Author(s):  
Abu Saleh Md Bakibillah ◽  
Yi Feng Paw ◽  
Md Abdus Samad Kamal ◽  
Susilawati Susilawati ◽  
Chee Pin Tan
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Smart Cities ◽  
Flow Behavior ◽  
Urban Mobility ◽  
Microscopic Traffic Simulation ◽  
The Road ◽  
Road Capacity ◽  
Ride Sharing ◽  
Traffic Performance

Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both passengers and drivers) that incorporates travelers of similar routes and time schedules on short notice. The objective is to reduce the number of private vehicles on urban roads by utilizing the available seats properly. We develop a mobile-cloud architecture-based system that enables real-time ride-sharing. The effectiveness of the proposed system is evaluated through microscopic traffic simulation using Simulation of Urban Mobility (SUMO) considering the traffic flow behavior of a real smart city. Moreover, we develop a lab-scale experimental prototype in the form of Internet of Things (IoT) network. The simulation results show that the proposed system reduces fuel consumption, CO2 and CO emissions, and average waiting time of vehicles significantly, while increasing the vehicle’s average speed. Remarkably, it is found that only 2–10% ride-sharing can improve the overall traffic performance.

scholarly journals Carpooling as an Immediate Strategy to Post-Lockdown Mobility: A Case Study in University Campuses

2021 ◽  
Vol 13 (10) ◽  
pp. 5512
Author(s):  
Ricardo Tomás ◽  
Paulo Fernandes ◽  
Joaquim Macedo ◽  
Margarida Cabrita Coelho
Keyword(s):  
Public Transportation ◽  
Road Traffic ◽  
Pollutant Emissions ◽  
University Campus ◽  
Microscopic Traffic Simulation ◽  
University Campuses ◽  
The Road ◽  
Traffic Performance ◽  
Campus Networks ◽  
The University

Carpooling is a mobility concept that has been showing promising results in reducing single occupancy use of private cars, which prompted many institutions, namely universities, to implement carpooling platforms to improve their networks sustainability. Nowadays, currently under a pandemic crisis, public transportation must be used with limitations regarding the number of occupants to prevent the spread of the virus and commuters are turning even more to private cars to perform their daily trips. Carpooling under a set of precaution rules is a potential solution to help commuters perform their daily trips while respecting COVID-19 safety recommendations. This research aimed to develop an analysis of the road traffic and emission impacts of implementing carpooling, with social distancing measures, in three university campus networks through microscopic traffic simulation modeling and microscopic vehicular exhaust emissions estimation. Results indicate that employing carpooling for groups of up to three people to safely commute from their residence area to the university campus has the potential to significantly reduce pollutant emissions (reductions of 5% and 7% in carbon dioxide and nitrogen oxides can be obtained, respectively) within the network while significantly improving road traffic performance (average speed increased by 7% and travel time reduced by 8%).

scholarly journals Analisis Kinerja Lalu Lintas Simpang Tak Bersinyal untuk Penentuan Tingkat Pelayanan di Jalan Klampis Jaya Surabaya

2021 ◽  
Vol 1 ◽  
pp. 180-184
Author(s):  
Dwi Prastya Nurcahaya ◽  
R Endro Wibisono
Keyword(s):  
Traffic Flow ◽  
Heavy Traffic ◽  
Working Hours ◽  
Service Level ◽  
Signalized Intersection ◽  
Degree Of Saturation ◽  
The Road ◽  
Road Capacity ◽  
Traffic Performance ◽  
Intersection Analysis

Klampis Jaya Road, Surabaya City, has a fairly heavy traffic flow, especially during working hours. This resulted in congestion on Klampis Jaya Road and not a few motorists who violated traffic regulations such as turning around Mleto Road. This study aimed to determine the current traffic flow performance and in 2024 at the intersection on Klampis Jaya Road, Surabaya City, predicted the traffic flow performance around the road and intersection on Klampis Jaya Road Surabaya City. The research method used was non-signalized intersection analysis using the Indonesian Road Capacity Manual. The calculation of the traffic performance of the four intersections in Klampis Jaya showed the Degree of Saturation (DS) and Service Level (TP) of each intersection. Traffic performance for the four intersections in 2021 was DS = 0.752 and TP = C (Enough), with the characteristics of stable traffic flow, was restricted movement. The traffic performance for the four intersections in 2024 was DS = 0.95 and TP = D (Less), with the characteristics of traffic flow stable movement being limited.

scholarly journals Effects of Connected and Automated Vehicles in a Cooperative Environment

2020 ◽  
pp. 21-28
Author(s):  
Ondrej Pribyl
Keyword(s):  
Co2 Emissions ◽  
Traffic Control ◽  
Traffic Management ◽  
Automated Vehicles ◽  
Impact Indicator ◽  
Microscopic Traffic Simulation ◽  
Flow Parameters ◽  
Traffic Performance ◽  
Environmental Goals ◽  
The Impact

Cooperative and automated vehicles (CAVs) are often considered a mean to improve quality of life in cities, the traffic flow parameters in particular. This paper provides some evidence based on microscopic traffic simulation on how the effects can really be. Important is that the particular use cases are not built in vehicles only. We focus on so called cooperative environment and advanced traffic control measures.This paper describes the impact of CAVs on a cooperative urban environment, resulting from a European research project - MAVEN. We clearly demonstrate that a proper integration of CAVs into city traffic management can, for example, help with respect to the environmental goals and reduce CO2 emissions by up to 12 % (a combination of GLOSA and signal optimization). On corridors with a green wave, a capacity increase of up to 34% was achieved. Already for lower penetra- tion rates (20% penetration of CAVs), there are significant improvements in traffic performance. For example, platooning leads to a decrease of CO2 emissions of 2,6 % or an impact indicator by 17,7%.

scholarly journals Evaluating Origin–Destination Matrices Obtained from CDR Data

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4470 ◽  
Author(s):  
Marco Mamei ◽  
Nicola Bicocchi ◽  
Marco Lippi ◽  
Stefano Mariani ◽  
Franco Zambonelli
Keyword(s):  
Road Network ◽  
Smart Cities ◽  
Generation Model ◽  
Urban Mobility ◽  
Multiple Perspectives ◽  
Crucial Issue ◽  
The Road ◽  
Transport Studies ◽  
Home Work ◽  
Work Commute

Understanding and correctly modeling urban mobility is a crucial issue for the development of smart cities. The estimation of individual trips from mobile phone positioning data (i.e., call detail records (CDR)) can naturally support urban and transport studies as well as marketing applications. Individual trips are often aggregated in an origin–destination (OD) matrix counting the number of trips from a given origin to a given destination. In the literature dealing with CDR data there are two main approaches to extract OD matrices from such data: (a) in time-based matrices, the analysis focuses on estimating mobility directly from a sequence of CDRs; (b) in routine-based matrices (OD by purpose) the analysis focuses on routine kind of movements, like home-work commute, derived from a trip generation model. In both cases, the OD matrix measured by CDR counts is scaled to match the actual number of people moving in the area, and projected to the road network to estimate actual flows on the streets. In this paper, we describe prototypical approaches to estimate OD matrices, describe an actual implementation, and present a number of experiments to evaluate the results from multiple perspectives.

scholarly journals ANALISIS KINERJA LALU LINTAS DI JALAN SEKITAR HYPERMART JL.VETERAN,PENANGGUNGAN, KLOJEN, MALANG

2019 ◽  
Vol 2 (2) ◽  
pp. 277
Author(s):  
Savira Anggraeni ◽  
Yosef Cahyo Setianto Poernomo ◽  
Sigit Winarto
Keyword(s):  
Direct Observation ◽  
Traffic Volume ◽  
Degree Of Saturation ◽  
Shopping Center ◽  
Real Situation ◽  
The Road ◽  
Road Section ◽  
Road Capacity ◽  
Library Research ◽  
Traffic Performance

This research was conducted to determine the peak traffic volume, road capacity, degree of saturation, analyze traffic performance, find out the prediction of the next 5 years, and to evaluate the traffic performance around the Hypermart shopping center that occurs in the real situation. The method used is by library research, looking for references from previous research and direct observation. The peak traffic volume is 1469 SMP / hour for the first location and 1104.4 SMP / hour for the second location. The capacity of the road section is 4699.73 SMP / hour. For the analysis of the degree of saturation of the first location of 0.31 SMP / hour and 0.23 SMP / hour in the second location. For the next 5 years prediction in that region, it is predicted to increase by 8.93% so that the volume of vehicles will rise to 2124.76 SMP / hour, and for the degree of saturation of 0.45, which means that the traffic service in this region is included in class C in 2024.Penelitian ini dilaksanakan untuk mengetahui volume puncak lalu lintas, kapasitas jalan,derajat kejenuhan,  menganalisis kinerja lalu lintas, mengetahui prediksi 5 tahun ke depan serta untuk mengevaluasi kinerja lalu lintas di sekitar pusat perbelanjaan Hypermart yang terjadi disituasi rill. Metode yang digunakan adalah dengan cara studi pustaka, mencari referensi dari penelitian terdahulu serta melakukan observasi langsung. Volume puncak lalu lintas didapatkan nilai 1469 smp/jam untuk lokasi pertama dan 1104.4 smp/jam untuk lokasi kedua.Kapasitas ruas jalan sebesar 4699.73 smp/jam.Untuk analisa derajat kejenuhan lokasi pertama sebesar 0.31 smp/jam dan 0.23 smp/jam pada lokasi kedua.Untuk prediksi 5 tahun kedepan pada wilayah tersebut diprediksi akan mengalami kenaikan sebesar 8.93% sehingga volume kendaraan akan naik menjadi 2124.76 smp/jam, dan untuk nilai derajat kejenuhan sebesar 0.45 yang artinya pelayanan lalu lintas wilayah ini termasuk ke dalam kelas C pada tahun 2024.

scholarly journals Pengaruh Pergerakan Putar Balik Arah terhadap Kinerja Ruas Jalan Letjen Hertasning Kota Makassar

2021 ◽  
Vol 6 (2) ◽  
pp. 76
Author(s):  
Rani Bastari Alkam ◽  
Muhammad Ilham Marhabang ◽  
Muhammad Ikhwan
Keyword(s):  
Traffic Congestion ◽  
Research Result ◽  
Degree Of Saturation ◽  
The Road ◽  
Road Section ◽  
Road Capacity ◽  
Traffic Performance ◽  
Road Performance ◽  
Additional Space ◽  
Movement Activities

Aktivitas putar balik arah pada beberapa bukaan median yang tersedia di sepanjang ruas Jalan Letjen Hertasning disinyalir sebagai pemicu kemacetan lalu lintas sebab pergerakan ini dapat menghambat pergerakan kendaraan pada kedua arah lalu lintas saat kendaraan memerlukan ruang manuver tambahan untuk menyelesaikan gerakan putar balik arah secara penuh. Penelitian ini bertujuan untuk menganalisis pengaruh pergerakan putar balik arah terhadap kinerja ruas jalan pada Jalan Letjen Hertasning Kota Makassar. Survei lalu lintas dilakukan pada lima pos pengamatan yang dipilih pada lima bukaan median pertama Jalan Letjen Hertasning yang berbatasan langsung dengan Jl. AP Pettarani selama tiga hari untuk segmen jam puncak pagi, siang, dan sore hari. Kinerja ruas jalan dianalisis mengikuti prosedur pada Manual Kapasitas Jalan Indonesia. Hasil penelitian menunjukkan bahwa antrian kendaraan saat bermanuver untuk memutar arah khususnya pada jam puncak setara dengan panjang 9 kendaraan atau sepanjang 36 m. Antrian ini menyebabkan kapasitas ruas jalan berkurang sebesar 2,5-10% dari kapasitas sesungguhnya yang menyebabkan terjadinya penurunan kecepatan, peningkatan derajat kejenuhan, dan penurunan tingkat pelayanan ruas jalan Letjen Hertasning. The U-turn movement activities at several median openings available along the Letjen Hertasning road arguably is one of the triggering factors for the occurrence of traffic congestion on that road section because this movement creates hindrances to traffic flow in the same lane and the contra flow when the vehicle requires additional space to complete the movement. The purpose of this study is to reveal the consequence caused by the U-turn movement to the traffic performance of Letjen Hertasning road in Makassar City. The traffic surveys were conducted at five selected observation points at the first five median openings of Jalan Letjen Hertasning which is directly adjacent to Jl. AP Pettarani for three days at three peak hours segment which are in the morning, afternoon, and evening. The analysis of road performance follows the procedures in the Indonesian Road Capacity Manual. Research result shown that the length of vehicles queuing to finish the U-turn movement during the peak hours reached 9 vehicles with a queue length of 36 m. This queue causes the capacity of the road to decrease by 2.5-10% of the actual capacity which causes a decrease in speed, an increase in the degree of saturation, and a reduction in the level of service of the road.

scholarly journals Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248764
Author(s):  
Angelo Furno ◽  
Nour-Eddin El Faouzi ◽  
Rajesh Sharma ◽  
Eugenio Zimeo
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Large Scale ◽  
Transportation Networks ◽  
Smart Cities ◽  
Dynamic Networks ◽  
Computation Time ◽  
Weighted Graphs ◽  
Dynamic Graphs ◽  
Physical Infrastructure

Betweenness Centrality (BC) has proven to be a fundamental metric in many domains to identify the components (nodes) of a system modelled as a graph that are mostly traversed by information flows thus being critical to the proper functioning of the system itself. In the transportation domain, the metric has been mainly adopted to discover topological bottlenecks of the physical infrastructure composed of roads or railways. The adoption of this metric to study the evolution of transportation networks that take into account also the dynamic conditions of traffic is in its infancy mainly due to the high computation time needed to compute BC in large dynamic graphs. This paper explores the adoption of dynamic BC, i.e., BC computed on dynamic large-scale graphs, modeling road networks and the related vehicular traffic, and proposes the adoption of a fast algorithm for ahead monitoring of transportation networks by computing approximated BC values under time constraints. The experimental analysis proves that, with a bounded and tolerable approximation, the algorithm computes BC on very large dynamically weighted graphs in a significantly shorter time if compared with exact computation. Moreover, since the proposed algorithm can be tuned for an ideal trade-off between performance and accuracy, our solution paves the way to quasi real-time monitoring of highly dynamic networks providing anticipated information about possible congested or vulnerable areas. Such knowledge can be exploited by travel assistance services or intelligent traffic control systems to perform informed re-routing and therefore enhance network resilience in smart cities.

scholarly journals Simulation network-level relationships of traffic flow

2021 ◽  
Vol 334 ◽  
pp. 01005
Author(s):  
Vladimir Zyryanov
Keyword(s):  
Traffic Flow ◽  
Urban Areas ◽  
Central Area ◽  
Fundamental Diagram ◽  
Microscopic Traffic Simulation ◽  
The Road ◽  
Flow Parameters ◽  
Macroscopic Fundamental Diagram ◽  
Trip Time ◽  
Road Capacity

This paper describes possibilities of the macroscopic fundamental diagram (MFD) of traffic flow to predict the conditions of operation of the road network in urban areas. This study examines relationships between traffic flow parameters on the network level. Microscopic traffic simulation has provided important data on the estimation of road capacity, velocity, trip time, and detection of congestions reasons. Data of spatial distribution density in network useful for implementing approach based on gating policy on subnetwork using MFD. It presents the results of a simulation using the example of central area of Rostov-on-Don

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