The 12th International Workshop on Computational Transportation Science (IWCTS 2019) is particularly timely given the prominence of connected automated vehicles technologies in the global auto industry's near-term growth strategies, of big data analytics, and unprecedented access to sensing data of mobility, and of integration of this analytics into the optimization of mobility and transport. These developments are deeply computational. We will build upon the success of previous workshops to continue to focus on connectivity, protocols, computation, knowledge discovery, and technology aspects of transportation systems while welcoming research papers in computer science, transportation science, civil engineering, urban and regional planning, urban sensing technologies, V2V and V2I, automotive transformations, connected autonomous vehicles, geography and geo-informatics, and other related disciplines.
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Relative Reachability Analysis as a Tool for Urban Mobility Planning: Position Paper
There is a plethora of user-oriented route planning applications and systems that enable the computation of the fastest journey between two locations using different transportation modes, e.g., car, public transport, walking, bicycle. While useful for ...
Road Map Generation and Feature Extraction from GPS Trajectories Data
Road maps are important in our personal lives and are widely used in many different applications. Therefore, an up-to-date road map is essential. The huge amount of GPS data collected from moving objects provides an opportunity to generate an up-to-date ...
Online Stochastic Prediction of Mid-Flight Aircraft Trajectories
Online trajectory prediction is central to the function of air traffic control of improving the flow of air traffic and preventing collisions, particularly considering the ever-increasing number of air travellers. In this paper, we propose an approach ...
Small Traffic Sign Detection Through Selective Feature Fusion Based Faster R-CNN With Arc-Softmax Loss
- Site Li,
- Yang Gu,
- Zhichao Song,
- Tengfei Xing,
- Yiping Meng,
- Pengfei Xu,
- Runbo Hu,
- Tiancheng Zhang,
- Ge Yu,
- Hua Chai
Traffic signs are basic and important elements in maps. They are related to traffic regulations, profoundly affecting/managing the travel mode of human beings and efficiency of vehicle running. Traffic sign mining technology is applied in many research ...
Quantifying the Impact of Autonomous Vehicles using Microscopic Simulations
- Hairuo Xie,
- Egemen Tanin,
- Shanika Karunasekera,
- Jianzhong Qi,
- Rui Zhang,
- Lars Kulik,
- Kotagiri Ramamohanarao
We use traffic simulations to quantify the impact of autonomous vehicles in various traffic scenarios, where vehicles at higher automation levels behave more opportunistically in car-following and lane-changing and can react to road situations more ...
Alternative Routes for Next Generation Traffic Shaping
Alternative route computations so far have mostly been considered as producing a small set of reasonable routes for a human driver to select from. In the not too distant future most cars will be self-driving, and choosing from a very large set of ...
Map matching when the map is wrong: Efficient on/off road vehicle tracking and map learning
Given a sequence of possibly sparse and noisy GPS traces and a map of the road network, map matching algorithms can infer the most accurate trajectory on the road network. However, if the road network is wrong (for example due to missing or incorrectly ...
Convoy Detection using Sequence Alignment
In this paper, we investigate methods to detect convoys in trajectory data with locations sampled at irregular time intervals. In such cases, convoys that exist may not be detected in some algorithms. We explore three methods, one that involves adding ...
Destination Signs in OpenStreetMap: Quality Assessment and Instrumentation for Routing
In this paper we investigate the mapping quality of destination signs in OpenStreetMap and show how this data can be instrumented for route planning purposes. Our proposed algorithm provides concise driving directions as well as faster query times ...
Shortest-Path Diversification through Network Penalization: A Washington DC Area Case Study
Traditional navigation systems compute the quantitatively shortest or fastest route between two locations in a spatial network. In practice, a problem resulting from all drivers using the shortest path is the congregation of individuals on routes having ...
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