Driver　workload　(DWL)　is　an　important　factor　that　needs　to　be　considered　in　the　study　of　traffic　safety.　The　research　focus　on　DWL　has　undergone　certain　shifts　with　the　rapid　development　of　scientific　and　technological　advancements　in　the　field　of　transportation　in　recent　years.　This　study　aims　to　grasp　the　state　of　research　on　DWL　by　both　bibliometric　analysis　and　individual　critical　literature　review.　The　knowledge　structure　and　development　trend　are　described　using　bibliometric　analysis.　The　knowledge　mapping　method　is　applied　to　mine　the　available　literature　in　depth.　It　is　discovered　that　one　of　the　current　research　focus　on　DWL　has　shifted　towards　investigating　its　application　in　the　field　of　autonomous　driving.　Subjective　questionnaires　and　experimental　tests　(including　both　simulation　technology　and　field　study)　are　the　main　approaches　to　analyze　DWL.　An　individual　critical　literature　review　of　the　influencing　factors,　measurement,　and　performance　of　DWL　is　provided.　Research　findings　have　shown　that　DWL　was　highly　impacted　by　both　intrinsic　(e.g.,　age,　temperament,　driving　experience)　and　external　factors　(e.g.,　vehicles,　roads,　tasks,　environments).　Scholars　are　actively　exploring　the　combined　effects　of　various　factors　and　the　level　of　vehicle　automation　on　DWL.　In　addition　to　assess　DWL　by　using　subjective　measures　or　physiological　parameter　measures　separately,　studies　have　started　to　improve　classification　accuracy　by　combining　multiple　measurement　methods.　Safety　thresholds　of　DWL　are　not　sufficiently　studied　due　to　the　various　interference　items　corresponding　to　different　scenarios,　but　it　is　expected　to　quantify　the　DWL　and　find　the　threshold　by　establishing　assessment　models　considering　these　intrinsic　and　external　multiple-factors　simultaneously.　Driver　or　vehicle　performance　indicators　are　controversial　to　measure　DWL　directly,　but　they　were　suitable　to　reflect　the　impact　of　DWL　in　different　driving　conditions.　Copyright　©　2023　Elsevier　Ltd.　All　rights　reserved.