"Robot cars" are cars that allow for automated driving. They can drive closer together than human driven "normal cars" and thereby raise road capacity. Obtaining a robot car instead of a normal car can also be expected to lower the userś value of time losses (VOT), because travel time can be...

This paper presents a dynamic model of road traffic congestion based on simple carfollowing theory, allowing for finite group velocity and discrete vehicles. The model offers a full-fledged dynamic version of the standard static model of road traffic congestion based on the so-called...

Mohring and Harwitz (1962) showed that, under certain conditions, an optimally designed and priced road would generate user toll revenues just sufficient to cover its capital costs. Several scholars subsequently explored the robustness of that finding. This paper briefly summarizes further...

This paper studies the efficiency impacts of private toll roads in initially untolled networks. The analysis allows for capacity and toll choice by private operators, and endogenizes entry and therewith the degree of competition, distinguishing and allowing for both parallel and serial...

This paper discusses a number of issues that will become increasingly important nowthat the concept of marginal external cost pricing becomes more likely to be implementedas a policy strategy in transport in reality. The first part of the paper deals with thelong-run efficiency of marginal...

This paper presents a framework for analysing spatial aspects of environmentalpolicies in the regulation of trans-boundary externalities. A spatial priceequilibrium model for two regions is constructed, where interactions betweenthese regions can occur via trade and transport, via mutual...

There has been wide interest in private supply of roads as a solution to traffic congestion. We study its efficiency under demand uncertainty: we solve for equilibrium and optimum as benchmarks, and evaluate the efficiency of possible regulatory policies for private road operators. We obtain...