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Assad Al Alam

dblp:59/10704 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0002-0998-6756ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Smart cities and intelligent transportation · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Smart cities and intelligent transportation › logistics
fleet management
0.212016
Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016
Smart cities and intelligent transportation › connected autonomous vehicles
vehicle platooning
0.212016
Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016
Embedded and real-time systems
cyber-physical systems
0.212016
Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016

Methods — techniques the papers use, named apart from their topics

vehicle-to-vehicle communication · 0.5simulation · 0.5
YearPublicationVenuePosition
2016 Cyber-Physical Control of Road Freight Transport
abstract
Freight transportation is of outmost importance in our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of the total energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network.
Bart Besselink, Valerio Turri, Sebastian van de Hoef, Kuo-Yun Liang, Assad Al Alam, Jonas Mårtensson 0001, Karl Henrik Johansson
Proc. IEEE5
2012 Optimal Distributed Controller Synthesis for Chain Structures - Applications to Vehicle Formations
Omid Khorsand, Assad Al Alam, Ather Gattami
ICINCO (1)2
2012 The Development of a Cooperative Heavy-Duty Vehicle for the GCDC 2011: Team Scoop
abstract
The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Södertälje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios.
Jonas Mårtensson 0001, Assad Al Alam, Sagar Behere, Altamash Khan, Joakim Kjellberg, Kuo-Yun Liang, Henrik Pettersson, Dennis Sundman
IEEE Trans. Intell. Transp. Syst.2