The SAGE Handbook of Transport Studies is an authoritative survey of contemporary transportation systems examined in terms of economic, social, and technical issues, as well as environmental challenges. Incorporating an extensive range of approaches - from modes, terminals, planning and policy to more recent developments related to supply chain management, information systems and sustainability/ecology - the work provides a cohesive and extensive overview of transport studies. Authored by international experts in their field, each individual chapter bridges a broad range of conceptual, theoretical and geographical perspectives, and the Handbook is divided into six sections: • Transport in the Global World • Transport in Regions and Localities • Transport, Economy and Society • Transport Policy • Transport Networks and Models • Transport and the Environment This Handbook will be an indispensible resource for academics, planners, and policy-makers.

TRB?s Transportation Research Record: Journal of the Transportation Research Board 1867 examines several algorithms that estimate speed from traffic surveillance cameras in a variety of traffic, weather, and lighting conditions; identify bottleneck locations, the active times, and the delays that are caused; and are applied to the archived loop detector data in the I-4 data warehouse.

This study attempts to estimate post-incident traffic recovery time along a freeway using Monte Carlo simulation techniques. It has been found that there is a linear relationship between post-incident traffic recovery time, and incident time and traffic intensity. For purposes of this paper, the post-incident recovery time is defined as that time beyond the clearing of an incident when pre-incident traffic conditions are achieved and traffic has returned to normalcy or steady state. The research supports Objective 2.1 of the SHA Business Plan, which seeks to develop measures to enhance the Maryland State Highway Administration's (SHA) ability to quantify the impact of congestion and delay on the highway network. In addition, the SHA understands that the capability to reasonably estimate the traffic recovery time for a given duration of incident is crucial in qualifying the cost-effectiveness of current/future traffic management programs involving detection and clearance of incident on freeways. A total of 121 traffic scenarios of traffic intensity (Rho), incident duration, and proportion of lane blockage were simulated resulting in a total of 726 experiments. The VISSIM simulation platform was used to derive values for output flow, density, and speed to determine the post-incident traffic recovery times. The analysis of simulated data showed that for a given incident duration and lane blockage scenario, the recovery time of the traffic increases non-linearly with traffic intensity. The traffic recovery time becomes uniform (stable) for low and moderate traffic intensity values. A set of linear regression models were developed to reasonably estimate the post-incident traffic recovery time using traffic intensity, incident duration, and proportion of lane blockage as exogenous variables.