Characteristics of lateral vehicular interactions in heterogeneous traffic with weak lane discipline

Heterogeneous traffic conditions prevail in developing countries. Vehicles maintain weak lane discipline which increases lateral interactions of vehicles significantly. It is necessary to study these interactions in the form of maintained lateral gaps for modeling this traffic scenario. This paper aims at determining lateral clearances maintained by different vehicle types while moving in a heterogeneous traffic stream during overtaking. These data were collected using an instrumented vehicle which runs as a part of the stream. Variation of obtained clearance with average speed of interacting vehicles is studied and modeled. Different instrumented vehicles of various types are developed using （1） ultrasonic sensors fixed on both sides of vehicle, which provide inter-vehicular lateral distance and relative speed; and （2） GPS device with cameras, which provides vehicle type and speed of interacting vehicles. They are driven on different roads in six cities of India, to measure lateral gaps maintained with different interacting vehicles at different speeds. Relationships between lateral gaps and speed are modeled as regression lines with positive slopes and beta-distributed residuals. Nature of these graphs （i.e., slopes, intercepts, residuals） are also evaluated and compared for different interacting vehicle-type pairs. It is observed that similar vehicle pairs maintain less lateral clearance than dissimilar vehicle pairs. If a vehicle interacts with two vehicles （one on each side） simultaneously, lateral clearance is reduced and safety of the vehicles is compromised. The obtained relationships can be used for simulating lateral clearance maintaining behavior of vehicles in heterogeneous traffic.

Multi-Gradient Routing Protocol for Wireless Sensor Networks

Sensor networks tend to support different traffic patterns since more and more emerging applications have diverse needs. We present MGRP, a Multi-Gradient Routing Protocol for wireless sensor networks, which is fully distributed and efficiently supports endto-end, one-to-many and many-to-one traffic patterns by effectively construct and maintain a gradient vector for each node. We further combine neighbor link estimation with routing information to reduce packet exchange on network dynamics and node failures. We have implemented MGRP on Tiny OS and evaluated its performance on real-world testbeds. The result shows MGRP achieves lower end-to-end packet delay in different traffic patterns compared to the state of the art routing protocols while still remains high packet delivery ratio.

Field Investigation of Vehicle Acceleration at the Stop Line with a Dynamic Vision Sensor

This article presents a study of vehicle acceleration distribution at a traffic signal stop line in an urban environment. Accurate representation of vehicle acceleration behavior provides important inputs to traffic simulation models especially when traffic related emissions need to be estimated. A smart eye TDS （traffic data sensor） system was used to record vehicle trajectories, which were extracted to calculate vehicle acceleration profiles. This paper presents the acceleration distributions obtained from over 300 passenger-car acceleration cycles observed on site from the stop line up to a maximum speed of 40 km/h. These distributions are compared with the outputs from a traffic micro simulation tool modeling a similar stop line scenario. The comparison shows that measured accelerations present wider distribution and lower values than the micro simulation. This result highlights the importance of using acceleration distribution calibrated with real-world measured data rather than default values in order to estimate accurate emission levels.

Topology Optimization for Urban Traffic Sensor Network

This paper presents an optimized topology for urban traffic sensor networks. Small world theory is used to improve the performance of the wireless communication system with a heterogeneous transmission model and an optimal transmission radius. Furthermore, a series of simulations based on the actual road network around the 2nd Ring Road in Beijing demonstrate the practicability of constructing artificial ＂small worlds＂. Moreover, the particle swarm optimization method is used to calculate the globally best distribution of the nodes with the large radius. The methods proposed in this paper will be helpful to the sensor nodes deployment of the new urban traffic sensor networks.